title stringlengths 1 1.19k | keywords stringlengths 0 668 | concept stringlengths 0 909 | paragraph stringlengths 0 61.8k | PMID stringlengths 10 11 |
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Missing data | The amounts of missing data for the outcome variables and most baseline variables assessed were negligible except for lactate levels; | PMC9874464 | ||
Software | Analyses were conducted using R (R Core Team, R Foundation for Statistical Computing, Vienna, Austria) v. 4.1.0 with the | PMC9874464 | ||
Additional analyses added during peer review | During the peer review process, additional descriptive baseline data and analyses not outlined in the statistical analysis plan | PMC9874464 | ||
RESULTS | Descriptive baseline and outcome data for the 982 patients in the ITT population are presented in Table Descriptive baseline and outcome data
Abbreviations: CPAP, continuous positive airway pressure; NIV, non‐invasive ventilation.A total of 13 patients on closed systems (1.3% of the full intention‐to‐treat population; ... | PMC9874464 | ||
Internal prediction model and | The performance of the internal prediction model (full model presented in the supplement) was adequate regarding both discrimination (AUROC 0.73, 95% CI 0.68–0.77) and calibration (Figure The median predicted risks of mortality were 35.5% (12 mg) versus 34.6% (6 mg) with mean predicted probabilities of 38.5% (12 mg) ve... | PMC9874464 | ||
Treatment effect differences | Estimated treatment effects for both outcomes according to the variables assessed are presented in Figure Between‐group differences in outcomes according to various baseline characteristics. Differences in days alive without life support (DAWOLS) and mortality at Day 90 with 95% confidence intervals according to the va... | PMC9874464 | ||
Additional analyses added during peer review | Additional descriptive data and results from analyses added during peer review are presented in the supplement (Table | PMC9874464 | ||
DISCUSSION | hypoxaemia | In this post hoc exploratory sub‐study of the COVID STEROID 2 trial, we found no strong evidence for substantial HTE with higher (12 mg) versus lower (6 mg) doses of dexamethasone on days alive without life support or mortality at Day 90 in patients with COVID‐19 and severe hypoxaemia. All We previously hypothesised th... | PMC9874464 | |
Strengths and limitations | This study comes with several strengths, including the overall strengths of the COVID STEROID 2 trial, that is, a relatively large, international pragmatic trial with blinding and limited missing data.The study also has limitations, including those general to the COVID STEROID 2 trial, that is, the evolving pandemic an... | PMC9874464 | ||
CONCLUSIONS | respiratory failure, hypoxaemia | RESPIRATORY FAILURE | In conclusion, we found no convincingly strong evidence for substantial HTE with higher (12 mg) versus lower (6 mg) doses of dexamethasone on days alive without life support or mortality at Day 90 in patients with COVID‐19 and severe hypoxaemia according to age, weight, number of comorbidities, category of respiratory ... | PMC9874464 |
AUTHOR CONTRIBUTIONS | This exploratory, post hoc study was conceived and planned by Anders Granholm, Marie Warrer Munch and Anders Perner. Anders Granholm conducted all analyses presented in this manuscript and wrote the first draft, which was critically revised by all authors. Marie Warrer Munch was the coordinating investigator of the COV... | PMC9874464 | ||
FUNDING INFORMATION | SECONDARY | The COVID STEROID 2 trial was funded by Novo Nordisk Foundation and the Research Council of Rigshospitalet. The funders had no role in the design, conduct, analyses or reporting of the trial or this secondary study. | PMC9874464 | |
CONFLICT OF INTEREST | EDWARDS | Anders Granholm, Marie Warrer Munch, Morten Hylander Møller and Anders Perner are affiliated with the Department of Intensive Care at Rigshospitalet—Copenhagen University Hospital, which has received funding for other projects from the Novo Nordisk Foundation, Sygeforsikringen ‘danmark’, Pfizer and Fresenius Kabi, and ... | PMC9874464 | |
Supporting information |
Click here for additional data file. | PMC9874464 | ||
ACKNOWLEDGMENTS | We thank everyone involved in the COVID STEROID 2 | PMC9874464 | ||
REFERENCES | PMC9874464 | |||
Context | PCOS | POLYCYSTIC OVARY SYNDROME 1 | Edited by: Lisa Owens, St. James’s Hospital, IrelandReviewed by: Stephen Franks, Imperial College London, United Kingdom; Daniel Ninello Polesel, Federal University of São Paulo, BrazilThis article was submitted to Reproduction, a section of the journal Frontiers in EndocrinologySleep duration and sleep quality have im... | PMC9950253 |
Objective | PCOS | To compare sleep variables assessed by actigraphy in over-weight/obese women with PCOS and controls, and to assess sleep variables after behavioral modification intervention in comparison with minimal intervention in a randomized trial. | PMC9950253 | |
Design | Randomized controlled trial, and a control group. | PMC9950253 | ||
Setting | Outpatient gynecological clinic at a university hospital in Sweden. | PMC9950253 | ||
Participants | PCOS | OTHER METABOLIC DISEASE | 39 women fulfilling all Rotterdam PCOS criteria, randomized to behavioral modification intervention or minimal intervention and 21 controls with no other metabolic disease, all aged 18‐40 years with a BMI ≥ 27 kg/m | PMC9950253 |
Intervention | A four-month behavioral modification intervention including weekly group meetings focusing on behavioral and healthy lifestyle aspects. Minimal intervention reflecting standard care. | PMC9950253 | ||
Main outcome measure | Sleep durations and sleep efficiency assessed by actigraphy. | PMC9950253 | ||
Results | PCOS | Compared to the control group, women with PCOS had significantly shorter time in bed (501 vs 548 min, p= 0.049), sleep time over 24 hours (448 vs 567 min, p=0.005) and sleep time at night (434 vs 511 min, p=0.002), poorer sleep efficiency (87 vs 93%, p<0.001), and longer wakefulness after sleep onset (64 vs 38 min, p<0... | PMC9950253 | |
Conclusions | sleep behavior, PCOS | We found over-weight/obese women with PCOS to have normal sleep duration, but worse sleep efficiency than controls. Behavioral modification intervention seems to reduce the amount of daytime sleep, suggesting improved sleep behavior. | PMC9950253 | |
Clinical trials registration | PMC9950253 | |||
Introduction | obesity, endocrine disorder, sleep disturbances, non-PCOS, OSA, PCOS | OBESITY, ENDOCRINE DISORDER, OBSTRUCTIVE SLEEP APNEA, POLYCYSTIC OVARY SYNDROME, INSULIN SENSITIVITY | Polycystic ovary syndrome (PCOS) is the most common endocrine disorder in fertile women with a prevalence of 8-13% (In addition, sleep disturbances have been reported as common among women with PCOS, and the occurrence of obstructive sleep apnea (OSA) is higher than for controls (Studies on non-PCOS, including female o... | PMC9950253 |
Materials and methods | PMC9950253 | |||
Study design | PCOS | SECONDARY | This is a secondary analysis of data from a Randomized Controlled Trial (RCT) (ISRCTN48947168), previously described in Oberg et al. (In this study, we have focused on objectively measured sleep variables in the same population of over-weight/obese women with PCOS and measured the treatment effects of the four-month in... | PMC9950253 |
Women with PCOS | Study participants were recruited through adverts in a local newspaper as well as on a website for clinical studies. Inclusion criteria were BMI ≥ 27 kg/m | PMC9950253 | ||
Controls | The women used as controls were recruited | PMC9950253 | ||
Study intervention | PMC9950253 | |||
Behavioral modification intervention | We used a behavioral modification intervention, developed as a training course with focus on achieving long-term weight control ( | PMC9950253 | ||
Minimal intervention | The minimal intervention group received standard care comprising oral and written information on healthy living including advice on diet and exercise delivered by a research midwife. | PMC9950253 | ||
Procedures | PMC9950253 | |||
Women with PCOS | bleeding, PCOS, amenorrhea | BLEEDING | Before and after the 4-month intervention, the women with PCOS underwent a physical examination on menstrual cycle day 6-8. In women with oligo- or amenorrhea, a bleeding was induced by taking 10 mg medroxyprogesterone for seven days. A thorough medical history was taken, anthropometric measurements were obtained, a gy... | PMC9950253 |
Controls | A medical history was taken from the controls to ensure they fulfilled the entry criteria and no exclusion criteria. Fasting blood sampling was carried out on cycle day 6-8 to allow for analysis of hormones and binding proteins and anthropometric measurements were obtained. The controls did not receive any intervention... | PMC9950253 | ||
Actigraph assessment of sleep | PCOS | Both the women with PCOS and the controls wore an actigraph, ActiSleep+ (ActiGraph) device on their non-dominant wrist or in some cases where this was not possible, around their ankle. They were encouraged to wear the device for 7 consecutive days, the whole time apart from when showering/taking a bath or undertaking o... | PMC9950253 | |
Biochemical measurements | The sex steroids were analyzed by liquid chromatography tandem-mass spectrometry ( | PMC9950253 | ||
Assessment of psychological general well-being | The non-disease specific questionnaire PGWBI was used to assess the psychological well-being. The PGWBI contains 22 questions with 6 answers to choose from and it assesses the well-being during the previous month ( | PMC9950253 | ||
Statistics | ±, PCOS | Statistical analysis was carried out using SPSS software version 26 (IBM; Stockholm, Sweden). In Baseline characteristics of the PCOS population as well as the control group.• Baseline categorical data is presented as a proportion/percentage, and continuous data as means ± standard deviation.• To determine the differen... | PMC9950253 | |
Results | PMC9950253 | |||
Baseline characteristics | PMC9950253 | |||
Sleep in women with PCOS compared to controls | PCOS | When looking at all days of the week, the women with PCOS had significantly shorter mean total sleep time over 24 hours (TST 24h, min), time in bed at night (TIB, min), total sleep time at night (TST night, min), total sleep time during the day (TST day, min), poorer sleep efficiency (%), and longer periods of wakefuln... | PMC9950253 | |
Sleep following behavioral modification intervention in women with PCOS | PCOS | For the women with PCOS, the TST 24h and the TST daytime decreased in the behavioral modification intervention group albeit not significantly, following the 4-months behavioral intervention program, and increased in the PCOS minimal intervention group during the same period, as shown in | PMC9950253 | |
Correlations between sleep variables and baseline characteristics | PCOS | For the women with PCOS at baseline, there were no correlations between the objective sleep variables and the hormonal and anthropometric measurements respectively, nor were there any correlations between the changes in these variables following intervention. In the same study, we have previously shown that psychologic... | PMC9950253 | |
Discussion | napping, non-PCOS, sleep behavior, PCOS, co-morbidity, psychiatric | OBSTRUCTIVE SLEEP APNEA, INCREASED SLEEP | To our knowledge, this is the first study investigating objectively measured sleep health variables in overweight women with PCOS both compared to controls, as well as after lifestyle intervention. We found that women with PCOS had poorer sleep efficiency and longer wakefulness after sleep onset than controls. Furtherm... | PMC9950253 |
Data availability statement | The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation. | PMC9950253 | ||
Ethics statement | The studies involving human participants were reviewed and approved by Regionala etikprövningsnämnden Stockholm, Avdelning 3. The patients/participants provided their written informed consent to participate in this study. | PMC9950253 | ||
Author contributions | ALH | All authors contributed to the study conception and design. Data collection and analysis were performed by EO and ALH. The first draft of the manuscript was written by EO and all authors commented on previous versions of the manuscript. All authors contributed to the article and approved the submitted version. | PMC9950253 | |
Acknowledgments | We would like to thank Elisabeth Berg at Karolinska Institutet for advice regarding the statistical analysis as well as the research midwives Anna Cockin, Berit Legerstam and Siv Rödin Andersson at the Women’s Health Research Unit at the Karolinska University Hospital for their logistical support. | PMC9950253 | ||
Conflict of interest | The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. | PMC9950253 | ||
Publisher’s note | All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or ... | PMC9950253 | ||
References | PMC9950253 | |||
Key Points | PMC10692866 | |||
Question | TYPE 2 DIABETES | Can a voice-based conversational artificial intelligence (AI) application help patients with type 2 diabetes titrate basal insulin at home to achieve rapid glycemic control? | PMC10692866 | |
Findings | type 2 diabetes | TYPE 2 DIABETES | In this randomized clinical trial that included 32 adults with type 2 diabetes requiring initiation or adjustment of basal insulin, participants who used a voice-based conversational AI application had a significantly improved time to optimal insulin dose (median, 15 days vs >56 days) and insulin adherence (83% vs 50%)... | PMC10692866 |
Meaning | TYPE 2 DIABETES | Patient-facing, voice-based conversational AI applications can help patients with type 2 diabetes quickly achieve basal insulin dose optimization. | PMC10692866 | |
Importance | TYPE 2 DIABETES | Optimizing insulin therapy for patients with type 2 diabetes can be challenging given the need for frequent dose adjustments. Most patients receive suboptimal doses and do not achieve glycemic control. | PMC10692866 | |
Objective | TYPE 2 DIABETES | To examine whether a voice-based conversational artificial intelligence (AI) application can help patients with type 2 diabetes titrate basal insulin at home to achieve rapid glycemic control. | PMC10692866 | |
Design, Setting, and Participants | type 2 diabetes | TYPE 2 DIABETES | In this randomized clinical trial conducted at 4 primary care clinics at an academic medical center from March 1, 2021, to December 31, 2022, 32 adults with type 2 diabetes requiring initiation or adjustment of once-daily basal insulin were followed up for 8 weeks. Statistical analysis was performed from January to Feb... | PMC10692866 |
Interventions | Participants were randomized in a 1:1 ratio to receive basal insulin management with a voice-based conversational AI application or standard of care. | PMC10692866 | ||
Main Outcomes and Measures | diabetes-related emotional distress | Primary outcomes were time to optimal insulin dose (number of days needed to achieve glycemic control), insulin adherence, and change in composite survey scores measuring diabetes-related emotional distress and attitudes toward health technology and medication adherence. Secondary outcomes were glycemic control and gly... | PMC10692866 | |
Results | The study population included 32 patients (mean [SD] age, 55.1 [12.7] years; 19 women [59.4%]). Participants in the voice-based conversational AI group more quickly achieved optimal insulin dosing compared with the standard of care group (median, 15 days [IQR, 6-27 days] vs >56 days [IQR, >29.5 to >56 days]; a signific... | PMC10692866 | ||
Conclusions and Relevance | diabetes-related emotional distress | TYPE 2 DIABETES | In this randomized clinical trial of a voice-based conversational AI application that provided autonomous basal insulin management for adults with type 2 diabetes, participants in the AI group had significantly improved time to optimal insulin dose, insulin adherence, glycemic control, and diabetes-related emotional di... | PMC10692866 |
Trial Registration | TYPE 2 DIABETES | ClinicalTrials.gov Identifier: This randomized clinical trial examines whether a voice-based conversational artificial intelligence (AI) application can help patients with type 2 diabetes titrate basal insulin at home to achieve rapid glycemic control. | PMC10692866 | |
Introduction | diabetes | TYPE 2 DIABETES, DIABETES | Nearly one-fourth of the 33 million US adults with type 2 diabetes have poor glycemic control with a hemoglobin ASelf-titration of insulin by patients is a potential solution to overcome these barriers. Several studies have shown self-titration to be safe and effective.In this study, we developed a voice-based conversa... | PMC10692866 |
Methods | PMC10692866 | |||
Trial Design | The Managing Insulin with Voice AI (MIVA) trial was a remote (decentralized), randomized, open-label, parallel-group clinical trial investigating a novel VBAI application for basal insulin titration compared with standard of care. The trial was conducted at 4 primary care clinics at Stanford University from March 1, 20... | PMC10692866 | ||
Recruitment, Enrollment, and Randomization | VBAI | TYPE 2 DIABETES | We recruited English-speaking adults with type 2 diabetes who required initiation or adjustment of once-daily basal insulin. Exclusion criteria were the use of insulin pumps or the inability to independently carry out the intervention (ie, technical barriers in the home).Participants were randomly assigned in a 1:1 rat... | PMC10692866 |
Interventions | diabetes-related emotional distress, Diabetes | DIABETES | All participants completed a demographics intake form recording age, gender, race, and ethnicity. They also filled out 3 surveys: the 5-item Problem Areas in Diabetes Scale (PAID-5), a survey on diabetes-related emotional distress; a 5-question survey on attitudes toward medication adherence; and a 2-question survey on... | PMC10692866 |
Voice-Based Conversational AI | primary diabetes | We developed custom voice AI software for this trial powered by Alexa, a Health Insurance Portability and Accountability Act–compliant conversational AI platform by Amazon.Participants received an Amazon smart speaker loaded with the custom VBAI. Prior to activation, the participant’s primary diabetes clinician (primar... | PMC10692866 | |
Standard of Care | Participants randomized to the standard of care group had basal insulin titrated by their clinician per usual care. They received an online blood glucose and insulin log, which they were instructed to fill out daily for the duration of the trial (eAppendix 4 in | PMC10692866 | ||
Outcomes | diabetes | DIABETES | The key primary outcome was time to optimal insulin dose, measured as the number of days between the study start date and the date that the goal 3-day mean FBG level was achieved. Other primary outcomes were mean insulin adherence based on logged data and change in the composite scores of the 3 surveys measuring attitu... | PMC10692866 |
Sample Size | Based on a similar study, sample size was determined to be 32 participants. | PMC10692866 | ||
Statistical Analysis | VBAI | EVENT | Analysis was performed on an intent-to-treat basis. The primary outcome of the time to optimal insulin dose was assessed using the log-rank test to compare time to event for the VBAI group vs standard of care. Standard methods for mean values and proportions were used to construct 95% CIs and to conduct tests. Specific... | PMC10692866 |
Results | PMC10692866 | |||
Study Participants | Between March 1, 2021, and October 31, 2022, 330 individuals were screened for eligibility, 39 participants were randomized, and 32 participants completed the enrollment process ( | PMC10692866 | ||
Patient Flow Diagram | HbA | PMC10692866 | ||
Baseline Characteristics of Enrolled Participants | Abbreviations: HbASI conversion factor: To convert HbARace and ethnicity were self-reported by the participant.Survey items were scored from 0 to 4, and composite scores were calculated as the sum across all items. | PMC10692866 | ||
Outcomes | The time to optimal insulin dose was different for participants in the VBAI group compared with the standard of care group; the median time to optimal insulin dose was 15 days (IQR, 6-27 days) for the VBAI group and exceeded 56 days (IQR, >29.5 to >56 days; significant difference in time-to-event curves; | PMC10692866 | ||
Primary and Secondary Outcomes | fasting blood glucose, Diabetes | DIABETES | Abbreviations: FBG, fasting blood glucose; PAID-5, 5-item Problem Areas in Diabetes Questionnaire; VBAI, voice-based conversational artificial intelligence.SI conversion factor: To convert glucose to millimoles per liter, multiply by 0.0555.Survey items were scored from 0 to 4, and composite scores were calculated as t... | PMC10692866 |
Discussion | diabetes, hypertension, VBAI, diabetes-related emotional distress | HEART FAILURE, DISEASE, HYPERTENSION, DIABETES | In this randomized clinical trial, we demonstrated the effectiveness of a VBAI in managing basal insulin titration compared with standard of care. Participants in the VBAI group had significantly faster insulin dose optimization, improved insulin adherence and glycemic control, and decreased diabetes-related emotional ... | PMC10692866 |
Limitations | This study has many limitations. First, because participants were followed up for 8 weeks, glycemic control was measured by mean FBG level, rather than HbA | PMC10692866 | ||
Conclusions | type 2 diabetes | TYPE 2 DIABETES | This randomized clinical trial found that a VBAI that provided autonomous basal insulin titration improved time to optimal insulin dosing, insulin adherence, and glycemic control among adults with type 2 diabetes compared with standard of care. | PMC10692866 |
Subject terms | heterogeneous cognitive impairment, cognitive impairment | NEUROLOGICAL DISORDERS | Deficits in spatial memory are often early signs of neurological disorders. Here, we analyzed the geometrical shape configuration of 2D-projections of pointing performances to a memorized array of spatially distributed targets in order to assess the feasibility of this new holistic analysis method. The influence of gen... | PMC10665407 |
Introduction | inceptive mild cognitive impairment, Acquired deficits | Acquired deficits in spatial memory and orientation often indicate inceptive mild cognitive impairment or sensory deficitsIn this pilot study we compared the thus analyzed | PMC10665407 | |
Methods | PMC10665407 | |||
Subjects | Two groups of participants were enrolled. The first group consisted of 56 healthy participants (28 female, mean age 48.89 ± 19.35 years) with scores higher than 26 points in the screening by the Montreal Cognitive Assessment (MoCA)-testThe Patient Health Questionnaire subsection 9 (PHQ-9, Ref.The data protection cleara... | PMC10665407 | ||
3D real world pointing test | The clinical pointing task was performed using a pointing device attached at the participants forearm and testing setup from previous work and consisted of two calibration and five testing paradigmsDepiction of the pointing task and | PMC10665407 | ||
Single point data analysis and figure frame creation | The pointing vectors from the 3D-RWPT can be used to calculate mean angular deviations in azimuth (≘horizontal) and polar (≘ vertical) plane between the two sets of calibrations and the five tasks, respectively as described in previous studies | PMC10665407 | ||
Statistical analyses | In further shape analysis, for every participant seven paradigm-wise After data collection, all data was irreversibly anonymized for data analyses and processed using Microsoft | PMC10665407 | ||
Results | cognitive impairment, cognitive deficits | No participants had to be excluded because they were unable to complete the calibration or testing paradigm. Sex differences were clearly visible with male Groupwise mean The data of the 22 patients with suspected cognitive impairment in the screening test were pooled for females and males because of the small total nu... | PMC10665407 | |
Acknowledgements | TB | The present study was supported by the Hertie Foundation to TB, and the Deutsche Stiftung Neurologie (DSN) to MD (project 80766113). This work was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany‘s Excellence Strategy (Munich Cluster for Systems Neurology: EXC 2145 SyNergy).... | PMC10665407 | |
Author contributions | J.G.: study concept and design, data collection, data curation, statistical analysis, interpretation of data, drafting the manuscript, figure creation; T.B.: study design, drafting and revising the manuscript. M.D.: providing funding, study design, drafting and revising the manuscript. All authors contributed to the ar... | PMC10665407 | ||
Funding | Open Access funding enabled and organized by Projekt DEAL. | PMC10665407 | ||
Data availability | The data that support the findings of this study are not publicly available due to patient and participant privacy, but anonymized group- or paradigm-wise datasets are available on reasonable request from the corresponding author [JG]. | PMC10665407 | ||
Competing interests | The authors declare no competing interests. | PMC10665407 | ||
References | PMC10665407 | |||
Background | T2D | HEART, TYPE 2 DIABETES | I have read the journal’s policy and the authors of this manuscript have the following competing interests: Authors declare support from the UK Medical Research Council, British Heart Foundation, Wellcome Trust, European Research Council, Swedish Research Council and National Institute for Health Research Cambridge Bio... | PMC10138823 |
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