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Results | Completed FLU-PRO Plus questionnaires were available from 84% of participants in the sotrovimab arm (n = 446) and 83% of participants in the placebo arm (n = 437) on Day 1. By Day 21, completed questionnaires were available for 50% of participants in the sotrovimab arm (n = 262) and 48% of participants in the placebo arm (n = 250). Full details of questionnaire availability and proportions of electronic PROs versus paper questionnaires are shown in Table S1 in Additional file | PMC10499766 | ||
FLU-PRO Plus total and domain score subgroup analyses | Results of the FLU-PRO Plus subgroup analyses of mean change from baseline in total score (AUC) were generally consistent with those for the overall population (Table S3 in Additional file | PMC10499766 | ||
Other PRO measurements | All domain scores of the WPAI decreased over time in both arms (Fig. S10 in Additional file There was also little difference observed between the treatment arms in any of the eight domains of the SF-12, plus the Physical and Mental Component Summary score (Fig. S11 in Additional file | PMC10499766 | ||
Discussion | infection, illness | INFECTION, DISEASE, INFLUENZA | A previous report from the COMET-ICE study has demonstrated the efficacy of sotrovimab for improving rates of hospitalization and survival in high-risk COVID-19 patients [Based on AUC, sotrovimab provides statistically significant improvements through Day 21 in patient-reported symptoms compared with placebo. Based on the observed mean daily FLU-PRO Plus total and individual domain scores, improvements with sotrovimab occurred rapidly (within a week of treatment administration) compared to placebo, and the observed mean daily score for the individual domains of the FLU-PRO Plus followed a similar pattern. The clinical relevance of the PRO findings was further supported by estimates towards shorter time to symptom resolution in the sotrovimab arm compared to placebo. As COVID-19 vaccination and prior infection become increasingly widespread, further improvements in time to symptom resolution may occur. As seen previously in influenza, duration of illness is shortened among immune participants [Sub-group analyses were generally consistent with results for the overall population, although interpretation of the data for some categories is limited due to the small numbers of participants completing the questionnaires. Results obtained with other PRO tools were less conclusive. Minimal difference between the sotrovimab and placebo arms was observed for any of the WPAI domains, and little difference was observed for any of the SF-12 domains or summary scores. It should be noted that these instruments are generic, and therefore may be less sensitive to change overall in a specific disease.Although the COMET-ICE trial, as well as analyses of the content validity and psychometric properties of the FLU-PRO Plus [The main limitation of the current analysis is the potential for bias due to missing questionnaire data. This was primarily due to operational challenges surrounding rapid initiation of the study which resulted from urgent medical need during the early stages of the pandemic. This led to a lack of time to sufficiently execute electronic PRO set-up and implement a back-up paper plan. However, despite these challenges, completion rates were similar between both treatment arms, with more than 80% of participants completing the questionnaire on Day 1 and approximately 50% at Day 21. In addition, no single minimal clinically important difference for FLU-PRO in COVID-19 has been established, and was not developed as part of this study. | PMC10499766 |
Conclusions | death | The COMET-ICE trial was designed to test pandemic-relevant serious clinical outcomes (hospitalization or death) and demonstrated a clinical benefit of sotrovimab treatment. The current study adds to these findings by demonstrating significant and rapid improvements in patient-reported COVID-19 symptoms, as measured by the FLU-PRO Plus questionnaire in both total and individual domain scores, with patients noticing a benefit within a week of treatment administration. | PMC10499766 | |
Acknowledgements | Editorial support (in the form of writing assistance, including preparation of the draft manuscript under the direction and guidance of the authors, collating and incorporating authors’ comments for each draft, assembling tables and figures, grammatical editing, and referencing) was provided by Tony Reardon and Kathryn Wardle of Apollo, OPEN Health Communications, and was funded by GSK and Vir Biotechnology, Inc. | PMC10499766 | ||
Author contributions | Concept and design: SS, PG, CMR, TJHK, HJB, DB, MA, EA, EHS, JHP III; Acquisition, analysis, or interpretation of data: SS, PG, CMR, TJHK, HJB, DB, MA, EA, AL; Drafting of the manuscript: SS, PG, CMR, TJHK, HJB, DB, MA, EA, AL, EHS, AG, AES, JHP III; Critical revision of the manuscript for important intellectual content: SS, PG, CMR, TJHK, HJB, DB, MA, EA, AL, EHS, AG, AES, JHP III; Statistical analysis: AG, DB; Supervision: EHS, EA, MA, AES. All authors read and approved the final manuscript. | PMC10499766 | ||
Funding | This study was sponsored by Vir Biotechnology, Inc. in collaboration with GSK. The study sponsors were involved in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication. | PMC10499766 | ||
Availability of data and materials | The datasets generated and/or analyzed during the current study are not publicly available but are available from the corresponding author on reasonable request. | PMC10499766 | ||
Declarations | PMC10499766 | |||
Ethics approval and consent to participate | The COMET-ICE study was conducted in accordance with the principles of the Declaration of Helsinki and Council for International Organizations of Medical Sciences International Ethical Guidelines, applicable International Council for Harmonisation Good Clinical Practice guidelines, and applicable laws and regulations. Written informed consent was provided by all patients prior to study entry. | PMC10499766 | ||
Consent for publication | Not applicable. | PMC10499766 | ||
Competing interests | PG, TJHK, HJB, DB, and AL are employees of, and/or hold stocks/shares in, GSK. SS, MA, and EA are employees of, and/or hold stocks/shares in, Vir Biotechnology, Inc. CMR was an employee of Vir Biotechnology, Inc. at the time of study. JHP III has consulted for Arrevus, Eicos, Eli Lilly, Evofem, Eyecheck, Fuji, Gilead, Johnson & Johnson, Microbion, OPKO, Otsuka, Resolve, Romark, Shinogi, SpineBioPharma, and UTIlity, outside the submitted work, and for GSK and Vir Biotechnology, Inc. for the submitted work. AG and AES have acted as trial investigators for Vir Biotechnology, Inc. and received non-financial support from Vir Biotechnology, Inc. during the conduct of the study. EHS has acted as a trial investigator for Vir Biotechnology, Inc. and received non-financial support from Vir Biotechnology, Inc. during the conduct of the study; has received research support from AbbVie, Eisai, Eli Lilly, GSK, Ironshore, Otsuka, and Vir Biotechnology, Inc.; and served on speaker bureaus for AbbVie, Janssen, and Teva. | PMC10499766 | ||
References | PMC10499766 | |||
Background | ADVERSE EVENTS, MALARIA | Malaria morbidity and mortality increase in the Democratic Republic of the Congo (DRC) may be the consequence of the low utilization rate of long-lasting insecticidal nets (LLINs) resulting from poor compliance due to adverse events (AEs). This study aimed at determining the prevalence and predictors of AEs following the mass distribution of LLINs in the Kisantu Health Zone (KHZ), a high malaria-endemic region in the DRC. | PMC9893672 | |
Methods | ADVERSE EVENTS, REGRESSION | A community-based cross-sectional study embedded was conducted within a randomized controlled trial (RCT) after the mass distribution of LLINs in 30 villages located in DRC KHZ. A three-stage sampling method was used without replacement to select 1790 children. Data was collected on adverse events (AEs) using a reporting form and information on demographics, nutritional status, and house characteristics. This was done using a structured questionnaire administered to household heads. Logistic regression models were used to identify predictors of AEs following the mass distribution of LLINs. | PMC9893672 | |
Result | In a total of 1790 children enrolled, 17.8% (95% CI 16.1–19.7) experienced AEs. The most common AEs were respiratory-related (61%). Around 60% of AEs occurred within 24 h of use, and 51% were resolved without treatment. Sleeping under deltamethrin LLINs (Adjusted OR, 95% CI 5.5 [3.8–8.0]) and zinc roofing (Adjusted OR, 95% CI 1.98 [1.1–3.57]) were associated with the risk of reporting an AE following the mass distribution of LLINs. | PMC9893672 | ||
Conclusion | ADVERSE EVENTS | Approximately 1 out of 5 children had an AE within 24 h following LLIN use. These adverse events were often respiratory-related. LLINs and roofing types were associated with a higher risk of reporting AEs. However, further research using a robust study design is needed to confirm these findings. Future studies should design and implement interventions aiming to reduce AEs and improve compliance with LLINs. | PMC9893672 | |
Background | deaths, Malaria | MALARIA | Malaria is a major public health problem in Sub-Saharan Africa. In 2020, the World Health Organization (WHO) reported 627,000 malaria-related deaths, mainly in children under 5 years of age [These insecticides can, in some cases, be responsible for some inconvenience both in humans and in the environment [According to the Democratic Republic of the Congo (DRC) National Malaria Control Programme (NMCP) activity reports for 2015 and 2016, a considerable increase in the distribution of LLINs was observed during the previous three years [ | PMC9893672 |
Methods | PMC9893672 | |||
Study setting | malaria | MALARIA | This study was conducted in Kisantu Health Zone (KHZ), located in Kongo Central Province, DRC, where malaria is highly endemic and with vector populations resistant to pyrethroids. In 2017, the prevalence of malaria was estimated at 36% [ | PMC9893672 |
Study design | A community based cross-sectional study was conducted to analyse safety data collected in the context of an open randomized controlled trial (RCT) evaluating the effectiveness of bed nets treated with deltamethrin + PBO LLINs The intervention brand was PermaNet 3.0, which contained two active ingredients with the following specification: (1) Deltamethrin had a concentration of 4 g/kg for the roof and 2.8 g/kg and 2.1 g/kg for the side, respectively [The control brand was DawaPlusAfter the mass distribution of the LLIN within the 30 villages included in the trial, the households were contacted to determine the prevalence of AEs following exposure to any type of LLIN. Eligible households were those having one or more children below the age of 10, where the household head demonstrated ability and willingness to participate in the trial by signing an informed consent (or fingerprint) and with the assistance of an impartial witness (if the head of the household is illiterate). | PMC9893672 | ||
Data collection | wasting, SD | WASTING, ADVERSE EVENTS, MALNOURISHED, ADVERSE REACTION, WASTED | Data on adverse events (AEs) was actively collected using a reporting form that a team member completed during a household visit 60 days after the mass distribution of the LLINs. The reporting form contained information regarding (1) the type and the outcome of AEs (date and place of adverse reaction, circumstances of occurrence/description of facts, clinical consequences found, and preventive measures and actions taken) and (2) the medical device used (model, type, impregnation, trade name).AEs were defined as any harmful and unwanted reaction in any part of the body and were coded using the Medical Dictionary for Regulatory Activities (MedDRA). Blinded physicians trained in pharmacovigilance assessed the causality of AEs according to the following toxicovigilance process [Data on potential predictors of AE, including demographics, children, and household characteristics, were also collected using a structured study questionnaire during the household visit. These variables were collected during the baseline study (bed net distribution), this choice is justified by the facts that the populations which received the different kind of bed net were statistically different with regards to household and children characteristics. To control the potential confounding factors; these variables have been included in the study. The following variables were included from the base line:For household characteristics: type of floor, type of wall, type of roofing.For children characteristics and nutritional status: gender, age, weight, height. Three nutritional status indices were calculated, using Anthroplus application, notably stunting (height/age), wasting (weight/height) and underweight (weight/age) were defined as per WHO child growth standards. Children with Z scores less than two standard deviations (≤ 2 SD) below the median of the WHO child growth standards were classified as malnourished (stunted, wasted or underweight), minus 3 SD indicates severe stunting, wasting, and underweight. Z scores of less than − 2 SD were considered indicative of stunting. Anthroplus application was used to estimate these nutritional indicators.From the twenty samples stored at NIRB, five pieces per mosquito net was cut off of each mosquito net. This implies that there were 50 pieces per type of mosquito net giving a total of 100 pieces sent to CDC/Atlanta for residual insecticide assay by X-ray Fluorescence Analysis (XRF). | PMC9893672 |
Statistical analysis | After the survey, a database was created with Epi-info version 7. The data was previously cleaned to identify outliers, and corrections were made when possible. The analyses was performed using Epi-info7 and STATA 13.0 softwares. Descriptive analyses were performed to compare the proportions using the | PMC9893672 | ||
Results | ADVERSE EVENTS | From March 15 to April 15, 2018, among a total of 1790 children residing in 30 villages in KZH, 48.6% (870/1790) were female, 51.4% (920/1790) were less than five years old, and 49.8%(862/1790) were sleeping under deltamethrin + PBO LLINs. Baseline characteristics are presented in Table Socioeconomic characteristic of children according to type of LLINs in Kisantu Health ZoneOf 1790 children included in the study, 319 (17.8%) experienced at least one AE (Table Characteristic of children according to the reporting of adverse events post use of the LLIN in Kisantu Health ZoneReport of adverse events after the use of mosquito nets in Kisantu Health ZoneDistribution of adverse events types according to the model of mosquito nets in Kisantu Health ZoneUndesirable effects number of post-use LLINs to the children in Kisantu Health ZoneSleeping under deltamethrin LLINs (Adjusted OR, 95% CI 5.5 [3.8–8.0]) and zinc roofing (Adjusted OR, 95% CI 1.98 [1.1–3.57]) emerged as independent predictors of reporting of AEs following the mass distribution of the LLINs (Table Predictors of adverse events post use of LLINs in Kisantu Health ZoneValues in bold, means that the p is significant | PMC9893672 | |
Discussion | malaria, adverse drug reactions | ADVERSE EVENTS, ADVERSE DRUG REACTIONS, MALARIA | This study showed that approximately 1 in 5 children had an AE within 24 h following LLINs use. This result was consistent with studies done in Mali demonstrating adverse events after using the LLINs [Sleeping under deltamethrin LLINs was associated with a five-fold higher risk of experiencing AEs after the mass distribution of LLINs. However, residual confounding factors may partly explain these findings. Deltamethrin LLINs may be less effective at preventing malaria than deltamethrin + PBO. As such, the higher proportion of AEs observed in children sleeping under deltamethrin LLINs may be due to untreated malaria. Several factors could explain this difference in the occurrence of adverse events, including the quality of mosquito nets. In this study, some nets had an incorrect residual dosage, either above or below the manufacturer's declared threshold. Although this study was descriptive and was not designed to compare the risk of reporting adverse events between the two types of mosquito nets, these results warrant further consideration in future studies. Zinc roofing was associated with almost a two-fold higher risk of AEs. These results were unexpected but may warrant further consideration in future studies.The present study has several strengths. First, this is the first community-based cross-sectional study to determine the prevalence and predictors of AEs after exposure to LLINs in the DRC. Second, this is the first study that captures AEs following exposure to LLINs using active pharmacovigilance surveillance. Third, findings from this study will help design and implement knowledge-based intervention to reduce AEs and improve compliance to malaria prevention strategies in the DRC. Finally, these findings provide hypothesis-generating research to be tested in future studies using robust design. For example, future research should compare the two LLINs safety to determine which option is associated with fewer AEs.This study has several limitations. First, misclassification of the outcome in this study cannot be ruled out since the AEs were subjectively assessed in a recent survey after the occurrence of the outcome. Second, underreporting is a concern inherent to pharmacovigilance studies. For example, several studies have suggested that less than 10% of detected adverse drug reactions are effectively reported to medicine regulatory authorities [ | PMC9893672 |
Conclusion | ADVERSE EVENTS | Approximately 1 in 5 children had an AE within 24 h following LLIN use. These adverse events are often respiratory-related. AEs were associated with LLINs and roofing types. In view of the results, delthamethrin in combination with PBO would be the best indicated. However, further research using a robust study design is needed to confirm these findings. Future studies should design and implement interventions aiming to reduce AEs and improve compliance with LLIN. | PMC9893672 | |
Acknowledgements | The authors would like to thank all responsible of the study participants for their cooperation in providing the necessary information, as well as in providing the blood sample. | PMC9893672 | ||
Author contributions | AML | AML | PL, JPV and GI participated in the conception and design of the study. GI, TM, GM and BM performed the fieldwork and wrote the first draft manuscript. AML, VM, JRM, SL participated in the development of the computer software, the analysis, interpretation of data and revision of manuscript. JRM, NMM and AML analysed, interpreted the data and revised the manuscript. FTM, JPVand PL participated in the revision of manuscript. All authors read and approved the final manuscript. | PMC9893672 |
Funding | This study was funded by the RIPSEC Project DR Congo «Institutional Capacity Building in evidence-based research in DRC», financing by Europa.EU. The Outbreak Research Team of the Institute of Tropical Medicine is financially supported by the Department of Economy, Science and Innovation of the Flemish government. | PMC9893672 | ||
Availability of data and materials | All relevant data supporting the findings of this study are included within the paper and their additional files. | PMC9893672 | ||
Declarations | PMC9893672 | |||
Ethics approval and consent to participate | febrile | The study received the approval (ESP/CE/061/2016) from the ethics committee of the School of Public Health of the University of Kinshasa, DRC. After a detailed explanation of the purpose of the study, written informed consent was obtained from parents or guardian and mosquito collectors. All febrile participants received an antipyretic and those with a positive RDT were treated according to national treatment guidelines. | PMC9893672 | |
Consent for publication | Not applicable. | PMC9893672 | ||
Competing interests | All authors declare that they have no competing interests. | PMC9893672 | ||
References | PMC9893672 | |||
Background | Principal investigatorsAnaesthetic-induced unresponsiveness and non-rapid eye movement (NREM) sleep share common neural pathways and neurophysiological features. We hypothesised that these states bear resemblance also at the experiential level. | PMC10375502 | ||
Methods | We compared, in a within-subject design, the prevalence and content of experiences in reports obtained after anaesthetic-induced unresponsiveness and NREM sleep. Healthy males ( | PMC10375502 | ||
Results | Most subjects were rousable, with no difference between anaesthetic agents ( | PMC10375502 | ||
Conclusions | Anaesthetic-induced unresponsiveness and NREM sleep are characterised by disconnected conscious experiences with corresponding recall frequencies and content. | PMC10375502 | ||
Clinical trial registration | Clinical trial registration. This study was part of a larger study registered at | PMC10375502 | ||
Keywords | Handling editor: Hugh C Hemmings Jr
| PMC10375502 | ||
Editor's key points |
Anaesthetic-induced unresponsiveness and non-rapid eye movement (NREM) sleep share common neurophysiological features which might be reflected also at the experiential level.This study compared the prevalence and content of experiences in reports obtained from healthy male volunteers after dexmedetomidine- or propofol-induced unresponsiveness and NREM sleep.Disconnected dream-like experiences and experiences related to research setting were often present in both anaesthesia and sleep interviews, whilst awareness signifying connected consciousness was rarely reported for either.Anaesthetic-induced unresponsiveness and NREM sleep are both characterized by disconnected conscious experiences with similar recall frequencies and content.Anaesthetic-induced unresponsiveness and non-rapid eye movement (NREM) sleep share similarities on mechanistic, neurophysiological, and subjective levels. Relevant for the current study, both the αAt the subjective level, anaesthetic-induced unresponsiveness and NREM sleep are associated with reports of disconnected conscious experiences, that is, both states seem to support purely internally generated experiences that are not induced by external sensory stimuli. In interviews performed immediately after recovery from general anaesthesia conducted with a broad range of agents (excluding ketamine), 21.7–27.7% of patients indicate remembering dreams.In systematic sleep laboratory awakenings from NREM sleep, dream recall averages around 43.0% but has varied significantly between studies depending on how dreaming is defined and the timing of the awakenings.Given the many similarities between anaesthetic-induced unresponsiveness and NREM sleep, we investigated the prevalence and content of subjective experiences in interviews obtained after arousals from dexmedetomidine-induced or propofol-induced unresponsiveness and NREM sleep in the same participants. Direct comparison between the states in a within-subject design was used to account for individual trait differences in recall. We hypothesised that anaesthetic-induced unresponsiveness and NREM sleep are characterised by highly similar rates of recall of subjective experiences and that the contents of the experiences are not systematically different in most respects. | PMC10375502 | ||
Methods | This study was part of a larger research project registered in | PMC10375502 | ||
Participants | This open-label parallel-group study consisted of two separate experiments conducted with the same participants. We recruited 40 non-smoking, 20-30-yr-old right-handed healthy males (ASA physical status 1) with normal hearing. The participants were randomised with a permuted block design to receive either dexmedetomidine or propofol. The sample size was based on our previous experience with similar study designs, and no formal statistical power calculation regarding the required number of participants was conducted before the study. | PMC10375502 | ||
Experiments | RECRUITMENT | The recruitment, anaesthetic protocol, and experimental details have been published | PMC10375502 | |
Experiment 1: the anaesthesia experiment | Participants were randomised to receive either dexmedetomidine (Design of Experiments 1 and 2. (a) Anaesthesia experiment. R1, first regaining of responsiveness; R2, second regaining of responsiveness; R3, recovery to responsiveness; UR1, first period of unresponsiveness; UR2, second period of unresponsiveness; UR3, third period of unresponsiveness with higher drug concentration level. (b) Sleep experiment. N1, NREM sleep stage N1; N2, NREM sleep stage N2; N3, NREM sleep stage N3. NREM, non-rapid eye movement; PET, positron emission tomography.Participant responsiveness was tested using an auditory responsiveness test (Interview questions and content analysis scale.Participants were then left unstimulated, and if they achieved a second unresponsive (UR2) period with the same drug concentration as in UR1/R1, the procedure was repeated. Finally, the drug concentration was increased by 50% to achieve a third period of unresponsiveness with a higher drug concentration level (UR3). The mean targeted doses for UR3 were 2.38 (1.05) ng mlBlood samples for drug concentration measurements were drawn at baseline, at the end of each drug target infusion step, and when the responsiveness of the participant changed during the steady infusion or after the infusion was terminated. Dexmedetomidine concentrations in plasma were measured by high-performance liquid chromatography (HPLC) with tandem mass spectrometry, and propofol concentrations were measured by HPLC with fluorescence detection. | PMC10375502 | ||
Experiment 2: the sleep experiment | Two additional participants withdrew before Experiment 2 (Sleep stages were identified online by an experienced sleep technician according to the American Academy of Sleep Medicine criteria. | PMC10375502 | ||
Data analysis | All brief dream questions and full interviews were digitally recorded and transcribed for systematic content analysis conducted by two independent judges. Modified versions of the Subjective Experiences During Anesthesia (SEDA) and Orlinsky scales | PMC10375502 | ||
Statistical methods | Statistical analyses were performed using SAS System version 9.4 for Windows (SAS Institute Inc., Cary, NC, USA). Inter-rater agreement of vigilance state scoring and content analysis were assessed with per cent agreement and Cohen's kappa ( | PMC10375502 | ||
Results | PMC10375502 | |||
Awakenings and interviews | There were 76 successful awakenings and interviews obtained in Experiment 1 (Experiment 1: awakenings and interviews, and achieved states, with mean measured drug plasma concentrations for those participants who achieved the state. ∗Four dexmedetomidine and four propofol experiments were terminated before UR3. R, responsiveness; In Experiment 1, we noted discrepancies between the participants' answers to the brief dream question and the full interview, but we used only the full interviews (with detailed content reports) in the analyses. Of note, five times (6.6%) the participants answered ‘yes’ to the brief dream question but in the full interview no longer recalled any content. Further, nine times (11.8%) the participants stated in the brief dream question that they were ‘unsure’ but reported dreaming in the full interview. Relatedly, 15 times (19.7%) the participants answered ‘no’ to the brief dream question but in the full interview reported experiences categorised as memory incorporation.In Experiment 2, 36 out of the 37 participants fell asleep at least once but successful PET scans, and subsequent interviews were achieved with 32 participants. Notably, in Experiment 2, the same participant could be interviewed more than once from the same sleep stage. | PMC10375502 | ||
Experiences during anaesthetic-induced unresponsiveness and NREM sleep stages | In Experiment 1, 80.0% of dexmedetomidine-receiving and 73.7% of propofol-receiving participants recalled experiences (i.e. produced content reports) at least once (difference 6.3%; 95% CI −20.1% – 32.8%). Of the 76 interviews, 69.7% included content from the unresponsive period (for details, see Prevalence of recalling experiences from anaesthetic-induced unresponsiveness (Experiment 1) and non-rapid eye movement sleep (Experiment 2). ∗Differences were not observed in drug plasma concentrations measured immediately before the interview (UR1, UR2, and R3 states combined) between those who reported no recall or content reports in either dexmedetomidine (Differences in recalling experiences were not observed between drugs in different unresponsiveness periods (UR1 FET | PMC10375502 | ||
Disconnected and connected experiences during anaesthetic-induced unresponsiveness and NREM sleep stages | Disconnected experiences (i.e. dreaming and memory incorporation of the research setting) were frequently reported, whilst recall of connected experiences (i.e. awareness) was rare (Disconnected and connected experiences during anaesthetic-induced unresponsiveness (Experiment 1) and non-rapid eye movement sleep (Experiment 2). ∗Differences were not observed in drug plasma concentrations measured immediately before the interview (UR1, UR2, and R3 states combined) in the dexmedetomidine group between those who reported or did not report dreaming or memory incorporation (dreaming | PMC10375502 | ||
Complexity and modality of experiences during anaesthetic-induced unresponsiveness and NREM sleep stages | In Experiment 1, there were no differences between drugs (UR1 FET Complexity and modality of experiences in reports from anaesthetic-induced unresponsiveness (Experiment 1) and non-rapid eye movement (NREM) sleep (Experiment 2). ∗Negative emotions were more often present during anaesthetic-induced unresponsiveness than during NREM sleep in reports that included dreaming ( | PMC10375502 | ||
Discussion | hallucinatory, amnesic | We compared recall and content of subjective experiences reported after awakenings from anaesthetic-induced unresponsiveness and NREM sleep in the same male participants. As hypothesised, we found no significant differences in the recall rate or main content of experiences between anaesthesia and natural sleep, although disconnected experiences during anaesthesia tended to be more often dynamic than experiences during sleep. Our results are, in general, in line with previous findings regarding experiences in experimental anaesthesia and NREM sleep.Rousability did not differ between dexmedetomidine and propofol, but lower drug plasma concentrations were related to rousability with both drugs, as expected. Experiences with specific remembered content were reported in about two-thirds of the awakenings, and the reported experiences almost always reflected disconnected contents of consciousness. The recall of experiences after unresponsive periods (no recall, white report, or content report) or the type of recalled content (dreaming or memory incorporation) did not differ between anaesthetic agents or sleep stages N1, N2, and N3, but in the propofol group those who reported dreaming after waking up from the first unresponsive period had higher measured drug plasma concentrations than those who did not report dreaming. Memory incorporation, that is, contents that reflected some remembered aspects of the research environment but not direct awareness of it, was present in more than 80% of the reports in all awakenings (except for the N1 sleep stage). Interestingly, memory incorporation experiences were not related to drug plasma concentrations with either dexmedetomidine or propofol, even though a higher probability of sensory intrusions from the research environment could have been expected to be related to lower concentrations.Notably, in 50.9% of anaesthesia reports and 29.8% of sleep reports, dream-like content was present in the same report as memory incorporation content, that is, content related and unrelated to the research setting co-existed in the same report. Similarly, all six reports that included awareness aslo included memory incorporation and all but one dreaming. These findings not only add evidence that disconnected conscious experiences persist and are prevalent in unresponsive states, but they show that when probed with a detailed interview, experiences reflecting different degrees of connectedness can interweave. Experiences during both anaesthesia and sleep often superimposed Given that we cannot exclude the possibility that connected phenomenal consciousness was present in some of those occasions when memory incorporation was reported, our findings might bear some relevance for clinical practices. Administration of anaesthetics in the current study corresponds to mild-to-moderate sedation rather than surgical anaesthesia and both responsive and unresponsive sedation are widely used in clinical contexts. When unresponsive sedation is used with the hope of abolishing connectedness, it might be important to address retrospective recall to assess whether this goal was successfully achieved. In previous studies on dreaming during surgical anaesthesia, the contents of dreams have mostly been related to everyday life or the surgical setting and operating room.Although the amnesic effects of anaesthetics are well documented,The strengths of the present study lie in the direct comparison of experiences in two different unresponsive states utilising the same methods in a within-subject design, thus mitigating the effect of individual trait differences (such as retrospective memory for subjective experiences) on outcomes.The current study also suffers from several limitations. First, sample size was limited. However, the reported 95% CIs exclude large differences between the drug groups or between anaesthesia and sleep and suggest that our sample size was adequate to test our hypotheses. Second, our sample included only males because of the potential risks of exposing fertile females to radioactive tracers. We are unable to exclude potential sex differences on the outcomes, and future investigations on this topic are needed.As to other weaknesses in design, in Experiment 1 the full interviews were slightly delayed because of intervening PET scans. Delays might have accentuated the amnesic effects of anaesthetics and distorted the reports. To reduce memory bias, we presented the brief dream question immediately after arousal and conducted the full interview on average 7.5 min later. This, however, led to discrepancies in participants' answers. On a few occasions, participants answered ‘yes’ to the brief dream question (i.e. they recalled a dream) but in the full interview no longer recalled any content, which likely reflects the amnesic effects of the anaesthetics. On other occasions, participants were ‘unsure’ in the brief dream question but then reported dreaming in the full interview. Possibly, when participants had time to think about the experience during the PET scan, they recalled details that could not be immediately reported, that is, an immediate white report transformed into a content report. Another explanation might be that despite responsiveness tests that verified responsiveness before and after the PET scan, participants' state of consciousness fluctuated, and between the brief dream question and the full interview their contents of consciousness alternated between disconnected and connected experiences. Participants might have had brief episodes of internally generated thoughts and imagery during this responsive period, similar to mind wandering or sleep onset hypnagogia, and thus in the full interview they reported hallucinatory dream-like experiences that they had during the scan just before the full interview.The largest discrepancy was observed between answering ‘no’ to the brief dream question and reporting memory incorporation in the full interview. This discordance could point to the possibility that some memory incorporations occurred during the responsive period, between the brief dream question and full interview. Yet, memory incorporation experiences were not related to drug plasma concentrations, that is, lower concentrations did not lead to higher levels of connectedness and incorporation from the responsive period. Another possibility is that directly inquiring about the incorporation of the research environment in the interview might have led to over-representation of such content. However, memory incorporation rate in the present study is not substantially higher than in our previous study utilising immediate interviews,For future studies, we stress the importance of clarifying concepts to participants, asking unambiguous questions, and conducting immediate interviews to diminish the time lag between the experience and the report, and to mitigate amnesic effects, memory bias, and filling in the gaps by confabulation. We support use of thorough and transparently reported interview and classification procedures and clearly defined categories in research of anaesthesia-related experiences. | PMC10375502 | |
Conclusions | Our findings support the hypothesis that anaesthetic-induced unresponsiveness and NREM sleep are both characterised by disconnected conscious experiences with highly similar recall frequencies and content. These findings align with the mechanistic and neurophysiological similarities between anaesthetic-induced unresponsiveness and NREM sleep. Although anaesthetic-induced unresponsiveness in an experimental setting is not comparable with surgical anaesthesia and rather corresponds to moderate sedation, our results have relevance for clinical practices, both for sedation and surgical anaesthesia. We speculate that in some cases surgical anaesthesia does not represent a state of unconsciousness, but that patients disconnected from the environment might experience internally generated experiences similar to those experienced under NREM sleep. This poses no problem for successful surgical anaesthesia as long as patients remain disconnected from and unaware of external and bodily stimuli. | PMC10375502 | ||
Authors’ contributions | Principal investigators: KV, HSStudy conception/design: KV, REK, AS, JL, KK, AR, HSStudy conduct: KV, LR, REK, AS, JL, KK, JKData analysis: KV, LR, REK, JKStatistical analyses: TV, KVWriting of paper: KV, LR, REKRevising of paper: all authors | PMC10375502 | ||
Declaration of interest | The authors declare no conflicting interests. | PMC10375502 | ||
References | PMC10375502 | |||
Acknowledgements | sleep stage | The authors are grateful to Irmeli Dahlblom and Leena Vierikko (Turku PET Centre, University of Turku, and the Hospital District of Southwest Finland) and Milla Karvonen (Department of Psychology and Speech-Language Pathology, University of Turku) for assistance during the experimental sessions. The authors also thank the staff in Turku PET Centre, especially radiographers Minna Aatsinki, Anne-Mari Jokinen, and Hannele Lehtinen, and medical laboratory technologists Sanna Suominen and Heidi Partanen for assistance during the imaging sessions. The authors further wish to express their gratitude to sleep technician Kati Lahtinen (Sleep Research Centre at the University of Turku) for offline sleep stage scoring, and Maria Ek and Teemu Laine (Department of Psychology and Speech-Language Pathology, University of Turku) for the background support. Finally, the authors thank all participants for contributing to the experiments. | PMC10375502 | |
Summary | Joint first authorsJoint last authors | PMC10126227 | ||
Background | tuberculosis | DRUG-SENSITIVE TUBERCULOSIS, TUBERCULOSIS | Drug-sensitive tuberculosis treatment requires 6 months of therapy, so adherence problems are common. Digital adherence technologies might improve tuberculosis treatment outcomes. We aimed to evaluate the effect of a daily reminder medication monitor, monthly review of adherence data by the health-care provider, and differentiated care for patients with adherence issues, on tuberculosis treatment adherence and outcomes. | PMC10126227 |
Methods | death, tuberculosis | PULMONARY TUBERCULOSIS, RECURRENCE, TUBERCULOSIS, MULTIDRUG-RESISTANT TUBERCULOSIS | We did a cluster-randomised superiority trial across four prefectures in China. 24 counties or districts (clusters) were randomly assigned (1:1) to intervention or control groups. We enrolled patients aged 18 years or older with GeneXpert-positive, rifampicin-sensitive pulmonary tuberculosis, who were receiving daily fixed-dose combination treatment. Patients in the intervention group received a medication monitor for daily drug-dosing reminders, monthly review of adherence data by health-care provider, and management of poor adherence; and patients in the control group received routine care (silent-mode monitor-measured adherence). Only the independent endpoints review committee who assessed endpoint data for some participants were masked to study group assignment. Patients were followed up (with sputum solid culture) at 12 and 18 months. The primary outcome was a composite of death, loss to follow-up, treatment failure, switch to multidrug-resistant tuberculosis treatment, or tuberculosis recurrence by 18 months from treatment start, analysed in the intention-to-treat population. Analysis accounted for study design with multiple imputation for the primary outcome. This trial is now complete and is registered with ISRCTN, 35812455. | PMC10126227 |
Findings | tuberculosis | EVENTS, EVENT, RECURRENCE, TUBERCULOSIS | Between Jan 26, 2017, and April 3, 2019, 15 257 patients were assessed for eligibility and 3074 were enrolled, 2686 (87%) of whom were included in the intention-to-treat population. 1909 (71%) of 2686 patients were male, 777 (29%) were female, and the median age was 44 years (IQR 29–58). By 18 months from treatment start, using multiple imputation for missing outcomes, 239 (16% [geometric mean of cluster-level proportion]) of 1388 patients in the control group and 224 (16%) of 1298 in the intervention group had a primary composite outcome event (289 [62%] of 463 events were loss to follow-up during treatment and 42 [9%] were tuberculosis recurrence). The intervention had no effect on risk of the primary composite outcome (adjusted risk ratio 1·01, 95% CI 0·73–1·40). | PMC10126227 |
Interpretation | death, tuberculosis | RECURRENCE, TUBERCULOSIS | Our digital medication monitor intervention had no effect on unfavourable outcomes, which included loss to follow-up during treatment, tuberculosis recurrence, death, and treatment failure. There was a failure to change patient management following identification of treatment non-adherence at monthly reviews. A better understanding of adherence patterns and how they relate to poor outcomes, coupled with a more timely review of adherence data and improved implementation of differentiated care, may be required. | PMC10126227 |
Funding | Bill & Melinda Gates Foundation. | PMC10126227 | ||
Introduction | tuberculosis | DRUG-SENSITIVE TUBERCULOSIS, RECURRENCE, TUBERCULOSIS | There were an estimated 10·6 million new cases of tuberculosis globally in 2021.National guidelines recommend daily fixed-dose combination therapy to treat drug-sensitive tuberculosis, consisting of 2 months of isoniazid, rifampicin, pyrazinamide, and ethambutol, followed by 4 months of isoniazid and rifampicin. Treatment adherence is considered important for cure and reducing recurrence of tuberculosis.A major component of the directly observed treatment short-course strategy, introduced in China in 1992 and with national coverage by 2005, is directly observed therapy, defined as direct observation of treatment usually by a health-care worker or treatment supporter, to help improve medication adherence. However, a systematic review of treatment support using studies from China showed that only 20% of patients had directly observed therapy by a health professional and more than 50% of patients were self-administering treatment.
| PMC10126227 |
Research in context | TB, death, tuberculosis | DRUG-SENSITIVE TUBERCULOSIS, EVENT, RECURRENCE, TUBERCULOSIS |
We searched Medline and Embase in December, 2015, for papers published from Jan 1, 2000, to Dec 1, 2015, with no language restrictions, using the terms (“digital pill box*” OR “smart pill box*” OR “SMS” OR “text messag*”) AND “TB” OR “tuberculosis”. We found one systematic review assessing the effect of mobile phone text messaging on treatment adherence used as a proxy for treatment outcomes and development of drug resistance. Four studies (three observational cohort studies and one randomised trial) were included in the review, meta-analysis was not conducted, and the authors concluded that there were mixed findings for the effectiveness of text messaging to promote adherence to tuberculosis treatment. Our previous study in China, published in 2015, reported improved adherence to tuberculosis treatment in patients who received text messaging or smart pill box reminders compared with those who did not. The study was not powered to evaluate treatment outcomes. Since 2019, three studies have reported improved tuberculosis outcomes using digital treatment adherence technologies. A study in Kenya assessed weekly motivational messages, daily text message reminders, an unstructured supplementary service data platform for patients to confirm daily adherence followed by text message and calls from the research team for patients who had not confirmed adherence, and clinic notification of patients with no confirmation for more than 2 days. The intervention reduced the risk of poor treatment outcomes (on-treatment death, loss to follow-up, or treatment failure) by 68%, entirely through reducing loss to follow-up. A stepped-wedge trial in Uganda assessed a text-message-based intervention, where patients received daily text message dosing reminders and were asked to confirm a dose taken using a toll-free phone number. Adherence data were reviewed at clinics visits every 2 weeks or monthly and resulted in differentiated management. The authors showed improved successful treatment outcomes (defined as cured or completed treatment) with the intervention, although only among a per-protocol population (which included 97% of patients in the control phase and 52% in the intervention phase) who enrolled within the first 2 months of treatment. In Peru, a per-protocol analysis of an individually randomised trial showed higher treatment success (cured or completed treatment) among patients who had a real-time medication event reminder monitor versus those who received standard of care. A systematic review in 2022 reported variable effects of digital adherence technologies on tuberculosis treatment outcomes.
To our knowledge, this is the first trial to evaluate the effect of a digital adherence technology intervention (smart pill box reminder, monthly review of adherence data, and differentiated care for patients with adherence issues) on a composite outcome of death, loss to follow-up, treatment failure, or subsequent retreatment including culture-confirmed recurrence, among patients with drug-sensitive tuberculosis. We found that the intervention was not adequate to influence poor treatment outcomes, in particular loss to follow-up or tuberculosis recurrence. There was a failure to change patient management following identification of non-adherence at the monthly reviews. We did, however, show a reduction in treatment non-adherence in the intervention group compared with the standard of care group, similar to in our previous study, indicating that the smart pill box intervention improved treatment adherence.
There is no strong evidence that digital adherence technology interventions improve treatment outcomes, including incidence of tuberculosis recurrence, among patients with drug-sensitive tuberculosis. More frequent review of adherence data, with a streamlined approach for identifying patients with adherence issues and escalating supportive management of these patients, might be key to improving tuberculosis treatment outcomes.Digital adherence technologies, including SMS and electronic pill boxes, which support patients in their adherence to treatment, have the potential to enhance patient care through improving interactions between patients and health-care providers, and improving treatment adherence and outcomes.Three studies have shown improved tuberculosis treatment outcomes with digital adherence technologies. An individually randomised trial in Kenya showed a reduction in poor outcomes (on-treatment death, loss to follow-up, or treatment failure), mainly through reducing loss to follow-up, when using SMS reminders and an unstructured supplementary service data intervention.We aimed to evaluate the effect of a daily reminder medication monitor, monthly review of adherence data by the health-care provider, and differentiated care for patients with adherence issues, on tuberculosis treatment adherence and outcomes. | PMC10126227 |
Methods | PMC10126227 | |||
Study design | tuberculosis | TUBERCULOSIS | We did a cluster-randomised superiority trial in four prefectures (administrative subdivisions of provinces) in China. Geographical areas served by a tuberculosis dispensary or designated hospital were the unit of randomisation (clusters). | PMC10126227 |
Participants | pulmonary tuberculosis, tuberculosis | PULMONARY TUBERCULOSIS, TUBERCULOSIS | Prefectures were initially screened to identify at least five counties or districts with more than 300 patients with pulmonary tuberculosis in 2014 (to achieve our sample size), access to GeneXpert testing and culture diagnosis, tuberculosis services supplied by a designated hospital or dispensary, and use of a daily tuberculosis treatment regimen. Consent was obtained at the provincial and prefecture-level CDC and from the local health authority of each cluster. We enrolled consecutive patients aged 18 years or older with GeneXpert-positive and rifampicin-sensitive pulmonary tuberculosis, who were receiving daily fixed-dose combination treatment and were able to attend follow-up visits at 12 and 18 months after treatment start. Patients provided written informed consent to participate. | PMC10126227 |
Randomisation and masking | tuberculosis | TUBERCULOSIS | Constrained randomisation was used to randomly assign 24 clusters (1:1) to intervention or control groups, balanced for prefecture (difference by group was at most one prefecture), health setting type (hospital or dispensary; seven hospitals and five dispensaries in each group), area (urban or rural; difference in number per group was at most one), and sputum smear-positive tuberculosis notifications in 2015 (difference in average notifications by group was at most ten cases). Randomisation was done by the trial statistician using Stata (version 14). After randomisation, it was identified that two clusters in the intervention group used the same dispensary, so these were combined into one cluster.Cluster randomisation was justified to reduce contamination between groups and for logistical convenience: the intervention required changes to the delivery of care, so there were concerns that individual randomisation would lead to staff changing their behaviour towards patients in the control group and patients discussing care with one another.Only the independent endpoints review committee who assessed endpoint data for some participants were masked to study group assignment. | PMC10126227 |
Procedures | tuberculosis | EVENT, TUBERCULOSIS | In all clusters, the tuberculosis doctors and relevant staff from the county-level CDC received a 3-day training on enrolment of patients, data collection, and the medication event reminder monitor. In both groups, patients were given a daily tuberculosis treatment regimen of 2 months of isoniazid, rifampicin, pyrazinamide, and ethambutol, followed by 4 months of isoniazid and rifampicin, and a medication event reminder monitor to store medication. The medication event reminder monitor recorded the dates and times that it was opened for more than 2 s for patients to take their medication, and recorded a daily output to indicate that it was working. Further training was conducted after the start of the study on quality control of data and follow-up of participants after the end of treatment.In clusters in the intervention group, the tuberculosis doctors at the county level received a 1·5-day training on delivering the intervention and doctors at the township and village level received a half-day training on the intervention. The medication event reminder monitor was set up to give an audio and visual reminder to take medication (daily, three times within 5 min) and attend monthly clinic visits. The default time for the daily dosing reminder was 0800 h but could be changed to an alternative time in the morning according to patient preferences. At clinic visits, the doctor could display monitor openings in the previous month on their computer, to discuss adherence with the patient. Intensive management was initiated at the first instance of non-adherence of 20–50% of treatment days when monitor was not opened as a proxy for doses missed in the previous month; township doctors would be asked to visit patients every 2 weeks and village doctors every week. At the second instance of non-adherence of 20–50% or the first instance of non-adherence of greater than 50% in the previous month, patients were switched to directly observed therapy, with medical staff observing therapy administration. Every month, staff from China CDC or the county-level CDC visited each intervention cluster to check the intervention was being implemented as planned.Patients in control clusters had the reminder functions on the medication event reminder monitor disabled. Managing doctors could not review monitor openings at clinic visits, but data were collected for the trial. In consultation with the doctor, patients chose whether to take medication under direct observation by a health-care worker, family member, or through self-administration.Patients attended monthly routine clinic visits for the 6 months of treatment. Patients had routine sputum collection for smear microscopy at 2 months, 5 months, and end of treatment. At end of treatment, an additional sputum sample was collected for solid culture (using routine laboratories) and a chest radiograph was done to help define treatment failure. Patients were telephoned at 9 and 15 months after the start of treatment and self-reported retreatment for tuberculosis. At 12 and 18 months after the start of treatment, patients attended the clinic to provide sputum for culture, have a chest radiograph, and self-report tuberculosis retreatment.Missed doses were measured by days with no opening recorded on the medication event reminder monitor, excluding days when patients reported not using the monitor because of travel or hospitalisation or when there was no medication event reminder monitor daily output to show it was working. | PMC10126227 |
Outcomes | death, tuberculosis | RECURRENCE, MULTIDRUG-RESISTANT TUBERCULOSIS, EVENT, TUBERCULOSIS, ADVERSE REACTION | The primary outcome was a composite of death, loss to follow-up (or stopping treatment due to an adverse reaction or refusal of treatment), treatment failure, switch to multidrug-resistant tuberculosis treatment, or tuberculosis recurrence by 18 months from treatment start. Treatment outcomes were based on standard national tuberculosis programme outcomes documented on the tuberculosis register (Secondary outcomes were poor treatment outcome (death, treatment failure, loss to follow-up during treatment, and switch to multidrug-resistant tuberculosis treatment), loss to follow-up during treatment, poor treatment outcome or recurrence within 12 months of treatment start, time to recurrence in those who had been cured or completed treatment, and 2-month smear conversion to negative among those with a positive smear at the start of treatment. Secondary outcomes for adherence were percentage of months in which patients missed at least 20% of doses, percentage of overall doses missed, and visits attended on schedule. Process measures included inability to use the fixed dose combination treatment, number of visits by township and village doctor, medication event reminder monitor malfunctions, and withdrawal from using the medication event reminder monitor. In the intervention group, we also summarised the number of times the alarm sounded each day, and change of management due to non-adherence.Visits were defined as being attended on schedule if the number of days between visits was the same or fewer than the number of days’ worth of medication given to patients at their previous visit. | PMC10126227 |
Statistical analysis | TUBERCULOSIS PLEURISY, EVENT, RECRUITMENT, TUBERCULOSIS, ADVERSE REACTION | In our original sample size calculations, 12 clusters per group and a harmonic mean of 125 patients per cluster gave 85% power to detect a 40% risk reduction in the primary composite outcome at the 5% level, assuming an 18% risk of the primary composite outcome in the control group, 5% loss to follow-up, and a coefficient of variation of outcome of 0·3. In recalculation after two clusters were combined, a harmonic mean of 108 patients per cluster (due to slower than expected recruitment), allowing for 10% loss to follow-up, gave 83% power to detect a 40% risk reduction in the primary composite outcome. Sample size calculations were conducted using the Stata command clustersampsi.The intention-to-treat population was defined as participants enrolled into the trial, excluding those who met a post-enrolment exclusion criterion (participants who stopped taking the fixed-dose combination treatment within the first month due to an adverse reaction; permanently stopped their treatment within the first month because of travel or hospitalisation; had their treatment extended due to updated diagnosis of tuberculosis pleurisy, or tracheal or bronchial tuberculosis; or had diagnosis of drug resistance due to non-rifampicin drug resistance), and participants with a change of diagnosis confirmed by the endpoint review committee. The per-protocol population further excluded participants who withdrew early from use of the medication event reminder monitor, regardless of the reason given.All analyses were done in Stata (version 15), using the clan command. Our primary estimand was a risk ratio (RR), calculated using the logarithm of the cluster proportions: this estimates the ratio of geometric means of the cluster-level risks in each group, so all percentages reported are geometric means. The primary analysis was adjusted for age, sex, occupation, migrant status, distance to clinic, education level, household expenditure, and smear result at treatment initiation, using the two stage approach.For the primary outcome, the primary analysis was based on multiple imputation in the intention-to-treat population. Multiple imputation due to missing composite outcome was applied with 25 imputations (This trial is registered with ISRCTN, 35812455. | PMC10126227 | |
Role of the funding source | SH is employed by the funder of the study and contributed to the design and conduct of the trial and the writing of this manuscript. The funder of the study had no role in the decision to submit the results for publication. | PMC10126227 | ||
Results | tuberculosis, death, silicosis, diabetes | MULTIDRUG-RESISTANT TUBERCULOSIS, EVENT, TUBERCULOSIS, SECONDARY, SILICOSIS, EVENTS, EXTRAPULMONARY TUBERCULOSIS, DIABETES | Between Jan 26, 2017, and April 3, 2019, 15 257 patients were assessed for eligibility and 3074 were enrolled (Trial profileParticipants could have met more than one exclusion criterion. *Extrapulmonary tuberculosis, diabetes, or silicosis.Baseline characteristicsData are n, n (%), n/N (%), or median (IQR). Percentages are overall, ignoring clustering. CNY=Chinese yuan renminbi. NA=not applicable.By health-care worker.1909 (71%) of 2686 patients were male, 777 (29%) were female, the median age was 44 years (IQR 29–58), and 1675 (62%) had sputum smear-positive tuberculosis (Using multiple imputation for missing outcomes, 239 (16%; geometric mean of cluster-level event rate based on mean of 25 imputations) of 1388 patients in the control group and 224 (16%) of 1298 in the intervention group had a primary composite outcome event. There was no evidence of a difference in the risk of the primary composite outcome between groups (adjusted RR 1·01, 95% CI 0·73 to 1·40, p=0·95; adjusted risk difference 0·7%, 95% CI –4·5 to 5·9%). Results were similar in unadjusted, complete case, and per-protocol analyses (Primary and secondary outcomes, excluding adherenceData are n/N (%) or RR (95% CI); p value unless otherwise stated. All analyses were in the intention-to-treat population. All comparisons are intervention group versus control group. RR=risk ratio.Number of events in number of participants, ignoring cluster; percentages are the geometric mean of the cluster-level risk or rate of an event.Calculated using multiple imputation; values shown by group are the imputation-mean of total number of events and geometric mean of cluster-level proportion of events; all other outcomes used complete cases.Rate difference reported between the groups in those with a successful treatment outcome; adjusted analysis not completed because of the small number of events.In those with a positive smear at the start of treatment.Prespecified subgroup analysis did not show significant differences in the risk of the primary composite outcome between groups by clinic type, patient age, education level, sex, or household expenditure (Subgroup analyses of primary composite outcome in the intention-to-treat populationCNY=Chinese yuan renminbi. RR=risk ratio.Most primary composite outcome events were due to death, loss to follow-up, treatment failure, or switch to multidrug-resistant tuberculosis treatment, which had similar percentages between the groups (203 events [14%; geometric mean] in 1350 patients in the control group Patients in the intervention group were 64% less likely to miss more than 20% of treatment doses in a month (geometric mean 0·9 months [16%] of 6·0 months per person in the intervention group Secondary outcomes of medication adherence and process measuresData are n/N (%) unless otherwise stated. All comparisons are intervention group versus control group.Adherence outcomes summarised by patient, taking the arithmetic mean within cluster, then the geometric mean between clusters (1306 in the control group and 1261 in the intervention group contributed to the analysis of adherence outcomes).Before any change in management in the intervention group.Post-hoc sensitivity analyses for the primary outcome and secondary adherence outcomes were consistent with the primary analyses (Most patients in the control group reported self-administering treatment (943 [68%] of 1388 patients), and only 10% (138) were supervised by a health-care worker, although this differed widely by cluster (Before any change in patient management in the intervention group, patients in both groups had similar contact with the township and village doctor between clinic visits (mean 2·5 visits [SD 0·8] per month in the control group | PMC10126227 |
Discussion | death, tuberculosis, Tuberculosis | RECURRENCES, RECURRENCE, DRUG-SENSITIVE TUBERCULOSIS, EVENT, TUBERCULOSIS, TUBERCULOSIS, SECONDARY, EVENTS | In this large, cluster-randomised trial of 2686 patients with drug-sensitive tuberculosis from four prefectures in China, a digital adherence technology intervention had no effect on the risk of the primary composite outcome, and secondary outcomes of death, treatment failure, or loss to follow-up during treatment. Tuberculosis recurrence was uncommon, with a 12-month risk of 1·9% after the end of treatment among patients who had a successful treatment outcome. Non-adherence was reduced by 57–64% in the intervention group compared with the control group, depending on the metric used, which was a greater reduction than in our previous study.The intervention had no effect on loss to follow-up, which accounted for most of the primary composite outcome events (289 [67%] of 433 events); this might have been because there was a paucity of timely adherence data, and because of failure to change management following identification of non-adherence at monthly reviews. Rather than monthly adherence assessment, a more frequent review of adherence data by health-care workers and initiation of intensive management to assist patients who have issues with adherence are likely to be needed to reduce loss to follow-up. The Keheala intervention, evaluated in a study in Kenya, assessed weekly motivational messages, daily text message reminders, an unstructured supplementary service data platform for patients to confirm daily adherence with follow-up by the research team for patients who had not confirmed adherence, and clinic notification of patients with no confirmation for more than 2 days. The intervention was associated with a 68% (95% CI 50–79) reduced risk of poor treatment outcome (composite outcome of on-treatment death, treatment failure, or loss to follow-up), entirely through reducing loss to follow-up.In our trial, despite non-adherence being higher in the control group than in the intervention group, there was no apparent intervention effect on treatment outcomes or tuberculosis recurrence, which contradicts the findings from some other studies. An analysis of the fluoroquinolone treatment trials, albeit a non-randomised comparison, showed a strong relationship between lower adherence and increased risk of unfavourable tuberculosis treatment outcomes.Alternatively, we might have underestimated tuberculosis recurrence, although underestimation was unlikely to be differential by study group. We followed up patients for 12 months after the end of treatment, which would be likely to capture the vast majority of recurrences.This trial did show a reduction in non-adherence, measured by box-opening, in the intervention group compared with the control group, similar to in our previous study,Other digital adherence technologies have been assessed in upper-middle-income and high-income settings, including video-supported therapy, to improve treatment outcomes. These studies have shown similar or increased rates of favourable treatment outcomes with video supported therapy compared with control groups (often directly observed therapy); although, individually, all 95% CIs for the ratio effect estimate overlap 1, so are not significant.This trial has many strengths, including a large sample size and an intervention that was implemented by the national tuberculosis programme rather than a research team in parallel, it was conducted across varied settings, and follow-up continued for 12 months after the end of treatment. The study does, however, have several limitations: more intensive management activities, such as home visits to patients identified as having adherence problems, did not always happen as planned; after randomisation, two intervention clusters were combined, although this had minimal impact on power; solid culture rather than the more sensitive liquid culture was used to measure recurrence; and adherence outcomes were defined using a box-opening as a proxy for doses taken.In conclusion, the digital adherence technology intervention, involving a daily reminder medication monitor, monthly review of adherence data, and differentiated care for patients with adherence issues, was inadequate to influence unfavourable outcomes, which included loss to follow-up during treatment, tuberculosis recurrence, death, and treatment failure. Poor implementation of targeted adherence support might have contributed to no effect of the intervention on outcomes. Other trials have shown that digital adherence technologies (SMS-based and those based on medication event reminder monitors), implemented in real-time, can improve successful treatment outcomes. It is important, though, to understand the cost of delivering such interventions and also how these can be implemented in routine practice. Programmatically, treatment adherence might be substandard and clinicians do not have adequate methods to measure dose-taking. WHO uses treatment success (cured or completed treatment) as an indicator for performance of tuberculosis programmes, although it is a poor indicator of care as treatment completion is often not based on robust measures of adherence. For evaluating digital adherence technologies, rather than relying solely on outcomes at the end of treatment, a combined endpoint of adherence and treatment outcome could be used, with adherence measured in all trial participants using digital technologies with excellent accuracy characteristics. It is important that future trials do measure end of treatment outcomes, ideally incorporating quality treatment completion and possibly recurrence, if measured robustly, to generate strong evidence to influence policy. | PMC10126227 |
Data sharing | The individual deidentified participant data that underlie the results reported in this article, data dictionary, study protocol, statistical analysis plan, and Stata code will be made available on London School of Hygiene & Tropical Medicine Data Compass, without restriction, immediately following publication. | PMC10126227 | ||
Declaration of interests | We declare no competing interests. | PMC10126227 | ||
References | PMC10126227 | |||
Supplementary Material | PMC10126227 | |||
Supplementary appendix | PMC10126227 | |||
Acknowledgments | TB, Tuberculosis | DISEASE, THORACIC TUMOR, TUBERCULOSIS | This work was supported, in whole, by the Bill & Melinda Gates Foundation (INV-006543). Under the grant conditions of the Foundation, a Creative Commons Attribution 4.0 Generic License has already been assigned to the Author Accepted Manuscript version that might arise from this submission. We would like to acknowledge the support of Yongxin Gao, Lili Cheng, Fanfan Zheng, and Fei Huang (China National Health Commission, Gates Foundation TB Project National Program Management Office, Beijing, China); James J Lewis (London School of Hygiene & Tropical Medicine, London, UK); the Trial Steering Committee—Daniel Chin (Gates Foundation), Lixia Wang (Chinese Center for Disease Control and Prevention, Beijing, China), and Xiexiu Wang (Chinese Anti-tuberculosis Association, Beijing, China); and the Endpoint Review Committee—Mengqiu Gao, Liqun Zhang, and Liping Ma (Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing, China). | PMC10126227 |
Contributors | The study was conceptualised and designed by XiL, BT, SH, SJ, AV, KF, and YZ. XiL, HD, XuL, YY, XW, WH, CX, DH, HZ, SJ, and YZ were responsible for data collection. JT, HD, and KF were responsible for the data analysis. All authors contributed to data interpretation, writing of the manuscript, and have approved the final submitted version of the manuscript. The corresponding author attests that all listed authors meet authorship criteria and that no others meeting the criteria have been omitted. All authors had full access to the data in this study and had final responsibility for the decision to submit for publication. JT and HD accessed and verified the underlying data reported in this study. | PMC10126227 | ||
Subject terms | hypertrophy | HYPERTROPHY | The objective of this study was to compare the effects of progressive bodyweight training and barbell back squat on muscle strength, muscluar hypertrophy, and body fat percentage in sedentary young women. Thirteen sedentary young women (aged 19.77 ± 0.83 years, height 164.91 ± 6.01) were randomly assigned to either the progressive bodyweight group (n = 6, consisting of 10 levels of movements progressing from bilateral to unilateral) or the barbell squat group (n = 7, 60–80% 1RM). Both groups underwent two training sessions per week for 6 weeks. Measurements of muscle strength (isokinetic knee extensor and flexor muscle peak torque of each leg), muscle thickness (gluteus maximus, rectus femoris, and gastrocnemius muscles), and body fat percentage were taken at baseline and post-testing. Both groups showed a significant increase in isometric peak torque of the knee extensor and flexor (p < 0.05), but there were no significant between-group differences in isometric peak torque of the knee extensor and flexor (p > 0.05) or in the mean concentric peak torque of the knee H/Q ratio (p > 0.05). Both groups also showed significant increases in muscle thickness (p < 0.05), with no significant differences in Gastrocnemius, Rectus femoris and Gluteus maximus (p > 0.05). The percentage of body fat significantly decreased in the barbell group (pre: 28.66 ± 4.58% vs post: 24.96 ± 5.91%, p = 0.044), but not in the bodyweight group (pre: 24.18 ± 4.63% vs post: 24.02 ± 4.48%, p = 0.679). Our findings indicate that while both training methods increased maximum strength and muscle mass, barbell back squat training may be more effective in reducing body fat percentage. | PMC10439966 |
Introduction | muscle hypertrophy, lower limb muscle hypertrophy, muscular hypertrophy, diabetes | CARDIOVASCULAR DISEASE, CHRONIC DISEASES, DIABETES | Sedentary behavior has become increasingly common due to lifestyle changes. Long time of sedentary behavior not only can lead to high risks of chronic diseases such as cardiovascular disease, diabetes, and cancerThe squat exercise is a kind of multiple-joint exercise mainly to increase the muscle strength and muscular hypertrophy of lower body muscles that descent and ascent the body center of gravity by flexing and extending the hip, knee and ankleOn the other hand, bodyweight squats, which promote lower limb muscle strength by working against the gravity of the body's own weight, have also been widely used by increasing repetitions, shortening the rest-interval time, changing the squat angle, or increasing the difficulty of movement under constant load (weight)The present study aimed to compare the effects of 6-week progressive barbell-back and bodyweight squat training programs on muscle strength, thickness, and body composition in sedentary young women. This will provide scientific evidence for designment of effective training programs for females. We hypothesized that bodyweight squats would significantly improve knee joint strength, lower limb muscle hypertrophy, and body fat and that barbell-back squats and barbell squats would have similar effects on strength and muscle hypertrophy. | PMC10439966 |
Method | PMC10439966 | |||
Study design | The study utilized a parallel, single-blind, randomized controlled trial design (RCT). To divide the participants into two groups, a simple randomization system was employed, namely the in-college course selection system, which required the participants to choose one of the two groups. The participants were given the option to randomly and voluntarily join either group via the system. 13 participants were selected from two supervised programs and followed the same progressive resistance training principles for the entire 8-week period. Each program consisted of two weekly training sessions for eight weeks, with two weeks allocated for familiarization and six weeks for formal intervention. | PMC10439966 | ||
Subjects | motion-limiting osteoarthritis, muscle injuries, depression, patellar injury | FIBROMYALGIA, CARDIOVASCULAR DISEASE | Thirteen young women, with an average age of 19.77 ± 0.83 years, were conveniently recruited from Beijing Normal University for this study. The participants were required to meet specific criteria, including being between 18 and 30 years old, weight stable (with a weight change of < 3% of body weight) for at least 6 months (with a BMI < 30), inactive (< 150-min of moderate to vigorous physical activity per week), not taking any nutritional supplements, and free of medical problems that could be excluded by the study protocol. A validated medical screening questionnaire was used to screen for physical or mental health problems such as cardiovascular disease, patellar injury, muscle injuries, orthopedic problems, motion-limiting osteoarthritis, fibromyalgia, and depression. Thirty-six sedentary young women were recruited, ultimately, thirteen sedentary young women were able to complete the study (Fig. Flow chart of the present study.The study protocol and experimental procedures were explained to each participant, who then provided informed consent. The testing and training sessions took place at the College of P.E. and Sports at the Beijing Normal University and the Institute of Sports Medicine at the Third Hospital of Peking University, and followed the ethical guidelines of the Declaration of Helsinki for the study of humans. The Experiment of Sports and Health Promotion Research Center, College of P.E and Sports, Beijing Normal University of Ethics Committee reviewed and approved the studies involving human participants. Written informed consent was obtained from all participants to participate in the study, and to publish any potentially identifiable images or data included in the article. | PMC10439966 |
Procedures | Each session lasted 60 min and was separated by at least 48 h. The sessions comprised of a 15-min warm-up consisting of 10 activities, followed by a 30-min activity segment of squat exercises, with each group performing 6 sets of either bodyweight or barbell squats. Finally, there was a 15-min cool-down consisting of 8 activities. The warm-up and cool-down exercises were the same for both experimental groups. All sixteen training sessions were supervised by two experienced exercise instructors, who paid special attention to the consistency of the movement pace | PMC10439966 | ||
Familiarization session | During the first 2 weeks (Weeks 1–2), the participants attended four familiarization sessions at the gym to get acquainted with the exercise equipment and protocol in their respective groups, including key points of attention in each activity.In the first week, the participants in the barbell group completed six sets of ten repetitions of barbell squats without disks, while the participants in the bodyweight squat group followed the progressive bodyweight training protocol and performed six sets of bodyweight squats. In the second week, the participants were required to attend baseline assessments twice, with intervals of 48 h based on their groups, to determine the starting level of bodyweight squat movement in the bodyweight group and the one-repetition maximum of the barbell squat in the barbell squat group. After the baseline assessments, the lowest values (one repetition maximum and initial squat level) of participants in the two groups were used as the evaluation results to determine the load in the formal intervention. The evaluation approach of bodyweight squat movement level is based on the progressive push-up level assessment used in the research by Kotarsky et al.Forty-eight hours after the 2 weeks of familiarization visits, another baseline assessment of height, weight, body fat, and muscle strength and thickness were conducted in the laboratory of the Beijing Normal University and the Third Hospital at Peking University. The evidence strongly suggests that the 2-week short-term training would not have a significant impact on the physiological indicators of subjectsFrom week 3 (weeks 3–8), all participants started the formal intervention in each experimental condition. The intervention included 60-min sessions separated by at least 48 h, comprising of 15-min warm-up activities (10 activities, 15-min), 30-min squat exercises (6 sets of bodyweight or barbell-squat for each group), and 15-min cool-down exercises (8 activities, 15-min). Both the warming and cool-down exercises were the same in the two experimental groups. All 16 training sessions were supervised by two experienced exercise instructors, and special attention was given to the consistency of the movement pace | PMC10439966 | ||
The progressive bodyweight squat program | The progressive bodyweight squat protocol consisted of 10 levels of squats from A to J, as described in supplementary During the familiarization sessions, all participants began with level C for the first set. If they could correctly complete 10 repetitions for double leg squat on four sets at level C in two consecutive training sessions, they could advance to level D. For single leg squat, participants had to perform 5 repetitions per side for single leg squat on four sets at level F in two consecutive training sessions to advance to level G. For example, participants who began with level C were required to perform six sets of bodyweight squats, including 12 repetitions for double leg squats at level A, 10 repetitions for double leg squats at level B, and four sets of double leg squats at level C (8 repetitions per set). In total, during an exercise session, they were required to complete the following: 12 (A)/10 (B)/8 (C)/8 (C)/8 (C)/8 (C)/8 (C). From the first training session in the formal intervention (week 3), participants gradually increased to 12 (E)/10 (F)/8 (G)/8 (G)/8 (G)/8 (G) after achieving 12 repetitions of level E, 10 repetitions of level F, and 4 sets of 8 repetitions of level G in that session (4 repetitions per side). In the next session, they aimed to finish 12 (E)/10 (F)/10 (G)/10 (G)/10 (G)/10 (G) (5 repetitions per side). If participants could perform 12 (E)/10 (F)/10 (G)/10 (G)/10 (G)/10 (G) in two consecutive sessions, they could progress to level H. Participants who began with 12 (F)/10 (G)/8 (H)/8 (H)/8 (H)/8 (H) followed the same pattern to progress throughout the 6-week training. When participants could not complete 8 repetitions for double leg squats or 4 repetitions on each side for single leg squats at each level, the progression ended, and they began again at the previous level. An example is shown in Table Bodyweight squat progression.Note: Repetitions × Sets = R × S; 1–6 represents each participant; E: Lunge, F: Bulgarian single leg squat, G: Skating squat; the table shows the training volume and movement level (A–J) completed by the 6 participants in the bodyweight squat group in the first four training sessions; | PMC10439966 | ||
The progressive barbell-back squat program | During the familiarization session, participants performed exercises under the guidance of two trained instructors. All subjects attended two training sessions in the first week to get familiarized with the equipment and squat techniques, and to ensure they understood the proper form. The instructors used a barbell (20 kg) and weight plates with different loads to measure each participant's one-repetition maximum (1RM) in the second week. Using a multiple-repetitions testing procedure, participants were required to perform 5 sets of 5 repetitions of their maximum load of squats to estimate their 1RM. A jump box was placed behind participants to ensure proper squat form, with their hips and thighs close to the box and their thighs parallel to the ground, while their knees did not extend beyond their toes. The barbell squat movement adopted a high-bar back squat action Before the test, participants had their barbell-back squat technique critiqued and corrected during the first and second familiar sessions in the first week, and became familiar with the equipment. The test was preceded by a warm-up set of 8 repetitions of barbell squats without plates. Participants then performed sets at progressively increasing loads until they failed to complete a valid repetition, judged by their inability to complete the full range of motion. Ideally, subjects failed within 3–5 repetitions during the last and heaviest setAfter the initial familiarization period, each exercise session from the third week onward consisted of six sets of barbell-back squats. Prior to the first set, participants performed a warm-up set of 12 repetitions, starting at 60% of their predicted 1RM, progressing to 10 repetitions at 70% of predicted 1RM in the second set, and finally 8 repetitions at 80% of 1RM in the last four sets. We encouraged participants to aim for one extra repetition in each of the last four sets, and the number of repetitions per set was based on the quality and intensity of their performance as well as their perceived exertion. The total training volume was calculated by multiplying the number of repetitions by the sets performed in 12 training sessions over 6 weeks. A rest period of 2 min was allowed between subsequent sets. For example, in the first formal intervention session (session 1), participant A used barbell weights of 10/12/14/14/14/14 kg, and the repetitions performed under each weight were 12/10/8 + 1/8 + 1/8 + 1/8 + 1. If she completed an extra repetition in each of the last four sets, her next training session would involve using weights of 12/10/10/10/10/10 kg and performing 12/10/10/10/10/10 repetitions. If she was able to achieve this for two consecutive sessions, the weights were increased by 2.5 kg for each set, resulting in weights of 12.5/14.5/16.5/16.5/16.5/16.5 kg and 12/10/8/8/8/8 repetitions per set. All participants’ progression loads were determined according to the progressive resistance training for healthy adults, with the content of the first to fourth sessions in six weeks shown in Table Barbell back squat progression.Note: Repetitions × Sets = R × S, weight unite (kilogram); 1–7 represents each participant; The table shows the training volume (intensity, number of sets and times) completed by 7 participants in the barbell squat group in the first four training sessions. | PMC10439966 | ||
Measurements | The measurements were taken at baseline and 48 h after the final training session of the formal intervention. All individuals responsible for taking the measurements were unaware of the participants’ treatment status. | PMC10439966 | ||
Anthropometrics | Body height, weight, and body composition (including body fat percentage, lean body mass, minerals, and body water) were measured using InBody 770 (InBody Co, Ltd, Seoul, Korea) at baseline and 24 h after completing the last exercise session. Participants were instructed to wear light clothing and no shoes. They stood barefoot on the test platform with their feet in contact with the electrodes and their hands holding the test handle until the machine successfully measured their body composition. All personnel involved in the measurements were blinded to the participants’ treatment status. | PMC10439966 | ||
Strength measurement | Isokinetic knee extensor and flexor muscle peak torque of each leg were assessed using a dynamometer (PHYSIOMED CON-TREX-MJ, Schnaittach, Germany) both concentrically and eccentrically. Before the test, the subjects warmed up by riding a stationary bike (PRO2® SPORT TOTAL BODY, Tulsa, USA) at its easiest setting while seated. The seat and pedals were adjusted to ensure that the subjects were positioned properly to produce efficient power during the warm-up, which lasted 10 min. After a rest of three minutes, the participants were seated and secured to the dynamometer using torso and inactive thigh straps. Both legs were secured to the machine arm by two soft pads allowing comfortable knee movement. The testing protocol involved five successful trials for eccentric and concentric knee flexion and extension, where the participants produced a constant maximal effort. Concentric and eccentric peak torque was measured at an angular velocity of 60° per second between 0° and 90° of knee flexion. The trials were performed at 60°/s with self-determined maximum effort. Prior to the testing procedure, the participants were given instructions and two practice trials to familiarize themselves with the tasks. Verbal encouragement was given throughout each trial to ensure maximal effort. | PMC10439966 | ||
Measurement of muscle thickness | Muscle thickness was assessed using a B-mode ultrasound device (SONIMAGEHS1 musculoskeletal ultrasonic diagnostic system, Tokyo, Japan) at three anatomical sites: (a) gluteus maximus (the first third between the posterior superior iliac spine and the greater trochanter of the femur); (b) rectus femoris (a point two-thirds of the distance between the anterior–superior iliac spine and the superior tip of the patella on the anterior aspect of the thigh); and (c) gastrocnemius muscles (30% proximal between the lateral malleolus of the fibula and the lateral condyle of the tibia), as previously describedMuscle thickness images. | PMC10439966 | ||
Covariates | To reduce the influence of other factors, we utilized a set of questionnaires to assess daily physical activity | PMC10439966 |
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