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Manual Participation Deception | RECRUITMENT | In total, 4.3% (294/6818) of randomized participants were identified as having engaged in manual participant deception during the entire recruitment period. As illustrated in Manual participant deception, bots, and actual recruitment throughout the study. CAPTCHA: Completely Automated Public Turing Test to Tell Computers and Humans Apart.Updating the advertising helped reduce the number of false responses but also reduced the number of genuine participants enrolling. Because of the impact on the recruitment of genuine participants, a third version of the advertisement was used, where compensation was mentioned but not given prominence (Figure S3 in The rate of manual participant deception was reduced as a result of further screening questions, diligent checks by the research team, and excluding false participants from the study. This fluctuated throughout the study (CONSORT (Consolidated Standards of Reporting Trials) diagram of participant numbers and reasons excluded. | PMC10540014 | |
Discussion | PMC10540014 | |||
Overview | RECRUITMENT | This paper presents a case study on participant deception experienced throughout a remotely conducted large randomized controlled trial. Two types of participant deception were detected: automated bots and manual participant deception. Automated bots were identified based on clusters of enrollments very early in the morning with non–United Kingdom–based addresses. A CAPTCHA was added that resolved the issue, and no additional bots were identified. Manual participant deception was discovered due to incorrect or repetitive information provided, including restaurant and hotel contact details instead of home addresses. Monthly data checks to identify any unexpectedly high recruitment periods, suspicious entries, and contacting participants swiftly helped to mitigate the problem, although it required close monitoring throughout recruitment.Considering the circumstances under which recruitment took place, some of our experiences and recommendations may not be applicable when conducting research outside of a pandemic; this is an empirical question. While it is likely the pandemic meant some people were more engaged with web-based research, the highest recruiting day with the most suspicious entries occurred with 312 enrollments on July 29, 2020, when no active recruitment or social media advertising was taking place. Such automated bots have the potential to seriously disrupt recruitment and bias the final results. In our trial, we forecast that the target (n=5562) would have been reached within 3 months rather than the 21 months planned. Without rapid identification, this would have meant that the research budget was being spent compensating bots, with 81.9% (4556/5562) of the final sample estimated to be bots. This would likely have resulted in an underestimation of the effectiveness of the intervention due to the noise from the bot responses.We recommend using a CAPTCHA when setting up a remote trial to deter automated responses. We did not initially use one to ensure the trial was as accessible as possible and so as not to deter “real” participants. However, it is worth noting that a CAPTCHA does not render a survey invulnerable and could still be passed by a manual fraudulent entry [Participant deception occurred on a smaller scale than the bots, accounting for 5% (298/5955) of participants enrolled, and as such, appears to be less of an issue. However, it is also less likely to be detected, and it is also more time intensive for researchers to try to identify suspicious responses based on the contact information provided. Establishing a strict procedure for identification and management meant the research team could act swiftly and deter future attempts. We suspect most of the participant deception was perpetrated by a relatively small number of individuals at different time points attempting to enroll on multiple occasions, as once several of their entries were removed with emails explaining why, the numbers engaging in deception decreased considerably. Without identification and management of this issue, individuals may have continued to submit false entries throughout the study.There were 3 elements of the trial that helped the team to identify manual participant deception. First, participants were followed up 3 times over the course of 6 months, which presented several opportunities for researchers to contact participants and potentially identify any anomalies in contact details. With fewer resources and time spent on follow-up, some of the manual participant deception may have gone undetected. Second, there was no financial incentive offered for enrolling in the study initially, but only for completed follow-ups, so the incentive was delayed, making it less attractive for people seeking an immediate reward. Finally, the vouchers were sent manually by a member of the research team rather than being sent automatically, so there was a time lapse between follow-up completion and compensation being sent and a further opportunity to detect any discrepancies with the information given or similar or duplicate email addresses used before the vouchers were sent.It is worth noting the potential issues with inequalities when creating data management procedures to detect participant deception and the need to strike a balance [ | PMC10540014 | |
Recommendations | Based on our experiences, we have made 6 recommendations for other researchers for limiting bots and manual participant deception:Use CAPTCHAS.Use attention checks.Rigorous data management plan.Be cautious with mentioning financial compensation in web-based advertising.Consider the risk of introducing bias.Plan for the additional resources required. | PMC10540014 | ||
Use CAPTCHAs (and Other Available Automated Security Protections) | Ensure there are safeguards against automated bots when creating a web-based survey, particularly if financial compensation is involved. We used a CAPTCHA, also recommended by other studies [ | PMC10540014 | ||
Use Attention Checks | Consider adding attention-check questions to the survey, which we found helpful. Examples include requiring participants to select a particular response option to a question, or use duplicate questions with absolute answers such as date of birth, and programming the survey to automatically flag respondents not providing matching responses [ | PMC10540014 | ||
Rigorous Data Management Plan | A detailed data management plan and data checking methods are important to protect the validity of data. It is a challenge for researchers to stay ahead of bots and manual participant deception and prevent them from completing surveys [ | PMC10540014 | ||
Be Cautious With Mentioning Financial Compensation in Web-Based Advertising | Web-based advertising is often used in remote research to direct potential participants to surveys [However, advertising that financial compensation is available can invite participant deception, as in our case. A previous study investigated participation rates with and without financial incentives and reported that participation from nonunique IP addresses (so suspected duplication) was 6 times higher when an incentive was advertised compared to when it was not [Response rate can be impacted by the amount of incentive, with an increase of US $5 resulting in a higher screener response rate recorded (29.9% vs 22.7%) [Other studies have reported no additional impact of the inclusion of an incentive compared to participants without an incentive [ | PMC10540014 | ||
Consider the Risk of Introducing Bias | Compromises are required to protect against participant deception while trying to avoid deterring genuine participants [ | PMC10540014 | ||
Plan for the Additional Resources Required | RECRUITMENT | Consider the time and resources required for appropriate data management and the associated costs within project plans and funding applications, depending on the recruitment target and study length, as continuous monitoring and verification while data collection is ongoing is essential [ | PMC10540014 | |
Conclusions | Conducting research remotely has many advantages, but it is vulnerable to manual participant deception and automated bots posing as genuine participants, which can disrupt research and lead to low-quality data. At the outset of planning a remote study, we recommend using CAPTCHAs, using at least one attention check question in a screening or baseline survey, writing a rigorous data management plan, including dynamic protocols that can adapt in response to changes in deceit [This study is funded by the National Institute for Health and Care Research (NIHR; Public Health Research Program, #127651). The views expressed are those of the authors and not necessarily those of the NIHR or the Department of Health and Social Care. The authors would like to acknowledge the support of the members of the iDEAS research team and coapplicants of NIHR127651: Dr Colin Angus, Dr Emma Beard, Dr Robyn Burton, Prof Matthew Hickman, Prof Eileen Kaner, Prof Marcus Munafo, and Dr Elena Pizzo.Conflicts of Interest: GL, LD, MF, and SM declare no conflicts of interest. JB received unrestricted funding related to smoking cessation research and sits on the scientific advisory board for the SmokeFree app. CG and MO are paid scientific consultants for the behavior change and lifestyle organization “One Year No Beer” and provide fact checking for blog posts. MO and CG are also partially funded by the Medical Research Council (MR/W026430/1). FG is employed by both NICE and Imperial; he has no other conflicts of interest.S1: Social media advert on Facebook and Twitter (1) (September-November 2020).
S2: Social media advert on Facebook and Twitter (2) (financial compensation not mentioned) (December 2020 – March 2021).
S3: Social media advert on Facebook and Twitter (3), financial compensation mentioned, amount unspecified (March-June 2021, and during other advertising periods).Advert placed on NHS webpage.Primary Care Poster advert.Radio advert transcript.Email to suspected bots.Textbox S1. Email to suspected false participants, sent between October 7 and November 10, 2020
Textbox S2. Email to suspected false participants from November 11, 2020
Textbox S3. Email following spot checks where phone number was invalid or participant was not known.CONSORT checklist. | PMC10540014 | ||
Abbreviations | Completely Automated Public Turing Test to Tell Computers and Humans ApartConsolidated Standards of Reporting TrialsNational Health Service | PMC10540014 | ||
Summary | PMC10754264 | |||
What is already known about this topic? | Nirmatrelvir/ritonavir (Paxlovid) is recommended for treatment of mild-to-moderate COVID-19 in adults at high risk for progression to severe COVID-19. Rebound in SARS-CoV-2 shedding or COVID-19 signs and symptoms has been described after nirmatrelvir/ritonavir treatment, although the drug’s direct contribution to rebound remains unclear. | PMC10754264 | ||
What is added by this report? | death | Similar SARS-CoV-2 RNA rebound rates were observed in nirmatrelvir/ritonavir and placebo recipients in two randomized, double-blind, clinical trials. Virologic rebound after nirmatrelvir/ritonavir treatment was not associated with COVID-19–related hospitalization or death. | PMC10754264 | |
What are the implications for public health practice? | SARS-CoV-2 RNA rebound can occur with or without nirmatrelvir/ritonavir treatment, supporting the Food and Drug Administration’s determination of safety and efficacy of nirmatrelvir/ritonavir in eligible patients at high risk for severe COVID-19. | PMC10754264 | ||
Abstract | death | COVID-19 REBOUND | Rebound of SARS-CoV-2 shedding or COVID-19 signs and symptoms has been described after treatment with nirmatrelvir/ritonavir (Paxlovid). The direct association of nirmatrelvir/ritonavir to COVID-19 rebound remains unclear because most reports are based on individual cases or nonrandomized studies. Viral RNA shedding data from two phase 2/3, randomized, double-blind, placebo-controlled clinical trials of nirmatrelvir/ritonavir (Evaluation of Protease Inhibition for COVID-19 in High-Risk Patients [EPIC-HR] and Evaluation of Protease Inhibition for COVID-19 in Standard-Risk Patients [EPIC-SR]) were analyzed to investigate the role of nirmatrelvir/ritonavir treatment in COVID-19 rebound. Rates of rebound of SARS-CoV-2 RNA shedding, identified based on an increase in nasopharyngeal viral RNA levels from day 5 (end-of-treatment) to day 10 or day 14, were similar between nirmatrelvir/ritonavir and placebo recipients. Among subjects with a virologic response through day 5, viral RNA rebound occurred in 6.4%–8.4% of nirmatrelvir/ritonavir recipients and 5.9%–6.5% of placebo recipients across EPIC-HR and the 2021/pre-Omicron and 2022/Omicron enrollment periods of EPIC-SR. Viral RNA rebound after nirmatrelvir/ritonavir treatment was not associated with COVID-19–related hospitalization or death. Data from randomized trials demonstrated that SARS-CoV-2 rebound can occur with or without antiviral treatment, supporting the Food and Drug Administration’s determination of safety and efficacy of nirmatrelvir/ritonavir in eligible patients at high risk for severe COVID-19. | PMC10754264 |
Introduction | Nirmatrelvir/ritonavir (Paxlovid) | PMC10754264 | ||
Methods | PMC10754264 | |||
Data Sources | The authors conducted retrospective analyses of viral RNA shedding levels in nasopharyngeal samples from phase 2/3 clinical trials EPIC-HR and Evaluation of Protease Inhibition for COVID-19 in Standard-Risk Patients (EPIC-SR).Viral RNA levels were measured in nasopharyngeal swab samples collected by health care providers at prespecified study visits on days 1 (baseline), 3, 5 (end-of-treatment), 10, and 14 ( | PMC10754264 | ||
Data Analyses | Subjects with posttreatment viral RNA rebound were identified based on an increase in viral RNA levels from day 5 to day 10 or day 14 (Exploratory statistical analyses were conducted using two-sided Fisher’s exact tests to provide nominal p-values, without multiplicity adjustments; p<0.05 was considered statistically significant. Analyses were conducted using JMP (version 16; SAS Institute). This study was reviewed by the FDA Institutional Review Board and deemed not to constitute research involving human subjects as defined in 45 CFR part 46. | PMC10754264 | ||
Results | PMC10754264 | |||
SARS-CoV-2 RNA Rebound Rates | Demographic characteristics and predominant SARS-CoV-2 variants were similar between nirmatrelvir/ritonavir and placebo recipients within clinical trial EPIC-HR and within the 2021/pre-Omicron and 2022/Omicron periods of EPIC-SR (Supplementary Table, | PMC10754264 | ||
SARS-CoV-2 RNA Levels at Individual Timepoints | Across both trials, for all subjects irrespective of viral RNA rebound by any definition, a similar or higher percentage of nirmatrelvir/ritonavir recipients than placebo recipients had viral RNA below the lower limit of quantification (LLOQ) at all postbaseline visits, indicating nirmatrelvir/ritonavir treatment was not associated with delayed viral clearance overall ( | PMC10754264 | ||
Discussion | nirmatrelvir resistance-associated substitutions | VIRUS | Analyses of nasopharyngeal SARS-CoV-2 RNA levels from two randomized, double-blind, placebo-controlled trials that collectively enrolled approximately 3,000 subjects did not identify a consistent association between virologic rebound and nirmatrelvir/ritonavir treatment. One analysis from EPIC-HR indicated a statistically significantly higher rate of viral RNA rebound overall in nirmatrelvir/ritonavir recipients compared with that in placebo recipients (8.3% versus 5.7%, respectively; p = 0.036), but this analysis did not account for differences in viral RNA declines while on treatment. Other analyses from EPIC-HR and EPIC-SR did not show significant differences but did show modestly (nonsignificant) higher viral RNA rebound rates in nirmatrelvir/ritonavir recipients. Collectively, these data indicate that viral RNA rebound might be more common with nirmatrelvir/ritonavir treatment. However, viral RNA rebound was not restricted to nirmatrelvir/ritonavir recipients, and rebound rates were generally similar to those in placebo recipients across all analyses. Further, regardless of virologic rebound, nirmatrelvir/ritonavir treatment did not appear to contribute to delayed viral clearance overall, as nirmatrelvir/ritonavir recipients were more likely than were placebo recipients to have viral RNA levels below the LLOQ at all study visits. Viral RNA rebound during the treatment period between day 3 and day 5 was frequently observed, indicating that viral RNA rebound after treatment cannot definitively be attributed to virologic relapse caused by drug clearance and loss of antiviral activity. Rather, at least some cases of posttreatment rebound likely reflect natural variability in virus production, periods of shedding of viral components related to host factors, or technical variability in sampling via topical swab, any of which might also explain the occurrence of rebound in placebo recipients. Although nirmatrelvir drug resistance was not typically associated with viral RNA rebound, consistent with previous studies, two nirmatrelvir/ritonavir-treated subjects in EPIC-HR had virus with nirmatrelvir resistance-associated substitutions at the time of rebound. Genomic databases should continue to be monitored for the emergence or spread of nirmatrelvir-resistant SARS-CoV-2 variants. | PMC10754264 |
Limitations | The findings in this report are subject to at least four limitations. First, rebound rates are highly dependent on analysis definitions and the types, frequency, and timing of sample collection. The described analyses used sensitive parameters (within limitations of available sampling timepoints) to identify viral RNA rebound, and unlike a previous analysis from EPIC-HR ( | PMC10754264 | ||
Implications for Public Health Practice | Data from randomized, double-blind clinical trials demonstrated similar rates of SARS-CoV-2 RNA rebound in nirmatrelvir/ritonavir and placebo recipients. These findings support FDA’s determination of safety and efficacy of nirmatrelvir/ritonavir in eligible patients at high risk for severe COVID-19. | PMC10754264 | ||
Acknowledgments | EMERGENCY | The nirmatrelvir/ritonavir sponsor (Pfizer) and the EPIC-HR and EPIC-SR study investigators and study volunteers; Glen Huang, Cristina Miglis, Barbara Styrt, and the Food and Drug Administration nirmatrelvir/ritonavir New Drug Application review team.Nirmatrelvir/ritonavir (Paxlovid) first became available in the United States for the treatment of mild-to-moderate COVID-19 through Emergency Use Authorization from the Food and Drug Administration (FDA) on December 22, 2021, (Data from clinical trials EPIC-HR and EPIC-SR were submitted to FDA by the applicant (Pfizer) in support of the review and approval of New Drug Application (NDA) 217188 (Paxlovid). Analyses of viral RNA and symptom rebound for this report were conducted for all randomized subjects in these trials who took ≥1 dose of nirmatrelvir/ritonavir or placebo and were randomized ≤5 days of symptom onset. Viral RNA levels in nasopharyngeal samples were measured in a central laboratory (University of Washington) using the Abbott RealTime Quantitative SARS-CoV-2 assay, which had a lower limit of quantification (LLOQ) and limit of detection of 2 logAnalysis of selected samples from EPIC-HR for cell culture infectious SARS-CoV-2 demonstrated a trend of positive infectivity for samples with viral RNA ≥5 logIn the EPIC-HR modified intent-to-treat-2 population, which included all randomized subjects who took ≥1 dose of study intervention and were dosed ≤5 days of symptom onset, 1.0% (10 of 1,038) of nirmatrelvir/ritonavir recipients and 6.2% (65 of 1,053) of placebo recipients experienced COVID-19–related hospitalization through day 28 (per FDA Integrated Review of NDA 217188). All authors have completed and submitted the International Committee of Medical Journal Editors form for disclosure of potential conflicts of interest. No potential conflicts of interest were disclosed. | PMC10754264 | |
References | PMC10754264 | |||
Subject terms | neuropsychiatric disorders, psychiatric, cognitive disorders | Selective serotonin reuptake inhibitors (SSRIs) are widely used for treating neuropsychiatric disorders. However, the exact mechanism of action and why effects can take several weeks to manifest is not clear. The hypothesis of neuroplasticity is supported by preclinical studies, but the evidence in humans is limited. Here, we investigate the effects of the SSRI escitalopram on presynaptic density as a proxy for synaptic plasticity. In a double-blind placebo-controlled study (NCT04239339), 32 healthy participants with no history of psychiatric or cognitive disorders were randomized to receive daily oral dosing of either 20 mg escitalopram ( | PMC10827655 | |
Introduction | affective and anxiety-related disorders, heterogeneous syndrome, depressive disorder, MDD, depression, neuropsychiatric disorders | DYSFUNCTION | Drugs targeting the serotonin system, specifically the serotonin transporter, have long been the primary pharmacological treatment for affective and anxiety-related disorders [Despite years of research, the question of how inhibition of the serotonin transporter leads to symptom relief in neuropsychiatric conditions, remains unresolved. Major depressive disorder (MDD) is a vastly heterogeneous syndrome [One hypothesis for the mechanism of action in neuropsychiatric disorders is that strengthened serotonergic neurotransmission induces neuroplasticity and, in turn, improves cognitive and emotion processing [PET studies on several neuropsychiatric disorders linked to synaptic dysfunction, including depression, have found lower cerebral SV2A density in patients compared to healthy individuals [Given the limited knowledge of SSRIs’ neurobiological effects in humans, such as their capacity to induce neuroplasticity, we here aim to investigate if SSRI administration over several weeks can alter synaptic density in the healthy human brain, specifically in the hippocampus and the neocortex. The hippocampus is often the target of research on neuroplasticity as it is a key region in learning and memory, and patients with severe depression have been found to have lower SV2A in the hippocampus and several neocortical regions [Here, we used a double-blind, semi-randomized, placebo-controlled design to test the hypothesis that healthy participants receiving daily SSRI administration would have higher SV2A binding in the hippocampus and the neocortex than those receiving a placebo. We further hypothesized that SV2A binding would be positively associated with the duration of escitalopram intervention. | PMC10827655 |
Methods | PMC10827655 | |||
Study design | psychiatric | EVENTS, EPILEPSY, DISORDERS | The study was conducted in conjunction with a cross-sectional (i.e., single-scan), double-blinded, semi-randomized, placebo-controlled study (see Supplementary Fig SAll participants were recruited from a database of individuals who had expressed interest in participating in brain imaging studies. Following information about the study, including potential side effects of escitalopram, participants gave their written consent. Next, participants underwent a screening procedure, including medical history, physical and neurological examination, and screening for current or previous psychiatric disorders according to in- and exclusion criteria (see Supplementary file for complete list). Following the screening procedure and neuropsychological testing of IQ (assessed using the Reynolds Intellectual Screening Test (RIST) [Randomization balanced with regards to age, sex, and IQ was done by a research administrator not otherwise involved in data collection or analysis. Participants were instructed to take one capsule daily by mouth for three days and then increase to two capsules daily (i.e., full dose). The aim was an intervention period of a minimum 3 weeks, and for logistical purposes and to allow room for unforeseen events (e.g., illness or technical issues), participants could continue the intervention for up to 5 weeks. After the intervention period, all participants came in for extensive neuropsychological testing and MRI examination. On intervention day 10 and the day of neuropsychological testing and MRI, a blood sample was collected to measure s-escitalopram steady-state levels as confirmation of drug adherence. Participants were instructed only to take their daily dose of medication after the blood sample had been drawn. S-escitalopram was measured with an ultra-performance liquid chromatography-tandem mass spectrometer (UPLC-MS/MS; Filadelfia Epilepsy Hospital, Dianalund, Denmark).The main study included 66 healthy participants, for which we have reported the neuropsychological outcomes [ | PMC10827655 |
MRI acquisition and preprocessing | All participants underwent MRI scans in a Siemens Magnetom Prisma 3 T scanner (Siemens AG, Erlangen, Germany) using a Siemens 32-channel head coil. Structural T1- and T2-weighted images were acquired (T1 protocol: Isotropic 0.9 × 0.9 × 0.9 mm | PMC10827655 | ||
PET acquisition | Radiosynthesis of [ | PMC10827655 | ||
Arterial blood acquisition and analysis | For determination of the arterial input function, arterial blood samples were collected from a 20 G catheter which had been placed in the radial artery under local anesthesia. For the first 15 min of each scan, whole blood radioactivity was continuously measured (2-s intervals, flow = 8 mL/min) using an Allogg ABSS autosampler (Allogg Technology, Mariefred, Sweden). In addition, manual blood samples were drawn at 2.5, 5, 10, 25, 40, 60, 90, and 120 min for measuring radioactivity in blood and plasma using a gamma counter (Cobra II auto-gamma, Packard, Packard Instrument Company, Meriden, CT, USA) that was cross-calibrated to the PET scanner biweekly. Plasma was extracted after centrifugation of arterial blood at 2246xg for 7 min at 4 °C. To measure intact tracer and radiolabeled metabolites, plasma samples up until 90 min were analyzed using radio-HPLC (see the Supplementary file for full detail).The plasma free fraction ( | PMC10827655 | ||
PET image processing | All PET images were motion corrected using the AIR software with the reconcile command (Automated Image Registration, v. 5.2.5, LONI, UCLA, | PMC10827655 | ||
Kinetic modeling | Kinetic modelling of [In addition, as a complementary analysis, time-activity curves from the hippocampus and neocortex were fitted to the simplified reference tissue model 2 (SRTM2) to estimate the non-displaceable binding potential ( | PMC10827655 | ||
Statistical analyses | SECONDARY, CORTEX, REGRESSIONS | The distributions of demographic variables and PET scan parameters were visually compared between the groups and formally tested with a Welch two-sample As a secondary analysis, we investigated if there was an effect on [Group means for [As exploratory analyses, we investigated the effects of escitalopram versus placebo, intervention duration, and s-escitalopram concentration on hippocampus volume adjusted for age, sex, and intracranial volume (ICV). Lastly, for the neocortical subregions frontal, parietal, temporal, occipital, and insular cortex, we examined if there was a group and intervention duration effect on cortical thickness using linear regressions, as described for [All tests were performed as two-sided tests. Secondary and exploratory analyses were corrected for multiple comparisons according to the number of regions investigated, using the Bonferroni-Holm method. Statistical analyses were performed in R (v. 4.2.2). | PMC10827655 | |
Results | PMC10827655 | |||
Primary analyses | There was no statistically significant difference in [ | PMC10827655 | ||
Effects of escitalopram on SV2A density. | Comparison of [Including age, sex, and IQ as covariates did not reveal any significant group differences in the neocortex or the hippocampus (Supplementary Table Neocortical subregions and subcortical regions were not included in our a priori hypothesis; none of these regions showed significant differences in [ | PMC10827655 | ||
Secondary analyses | PMC10827655 | |||
Effect of intervention duration on [ | As the length of the intervention period ranged from 24 to 35 days for the escitalopram group, we investigated if longer exposure to escitalopram was associated with higher [ | PMC10827655 | ||
Time-dependent effects of escitalopram on SV2A density. | Relationship between [When including age, sex, and IQ in the models, the effects of intervention duration in the escitalopram group were further strengthened: in the neocortex, the effect of intervention duration on [ | PMC10827655 | ||
Effect s-escitalopram concentration on [ | We also investigated the effect of participants’ s-escitalopram level on [ | PMC10827655 | ||
Exploratory analyses | PMC10827655 | |||
Effects of escitalopram on hippocampus volume | The mean (SD) hippocampus volume was 4572 (389) mm | PMC10827655 | ||
Effects of escitalopram on cortical thickness | REGRESSION | Linear regression models with age and sex as covariates showed no difference in cortical thickness between the escitalopram group compared to the placebo group for the neocortical subregions (minimum | PMC10827655 | |
Discussion | depression, psychiatric, neurodegenerative and, cocaine-use disorder | SECONDARY, DISORDERS | In this study, we examine the effects of the SSRI escitalopram on brain synaptic density in SSRI-naïve healthy volunteers, as indexed by SV2A density measured with [This positive association with escitalopram intervention duration suggests that a reason why we do not find a group difference in the primary analysis could be that an average of 28 days of escitalopram intervention is too short for synaptic effects to fully emerge. Delayed effects of the escitalopram intervention align with the clinical observations that when SSRIs are used for treating, e.g., depression, at least 2–4 weeks of treatment is required before effects on symptoms can be expected [The reason for the delay in symptom relief following the initiation of SSRI treatment is unclear, although both biological and neuropsychological hypotheses have been proposed, e.g., affective bias and reward sensitivity [Aside from the intervention duration, the drug dose is also an important aspect to consider. Despite substantial variation in drug concentration, we saw no association between [Few other studies have investigated the effect of drug interventions on SV2A quantified with radioligand techniques. Using [So far, most other SV2A PET imaging studies have been cross-sectional case-control studies of neurodegenerative and psychiatric disorders for which causal relationships cannot be determined. Yet, indications of how modifiable SV2A is in the human brain may potentially be derived indirectly: A study on SV2A binding in cocaine-use disorder by Angarita et al. [Some methodological aspects of the current study should be considered. First, the use of SV2A as a proxy for pre-synaptic density. Although SV2A is ubiquitously expressed throughout the brain, it cannot be excluded that SSRI induced changes (or lack thereof) in SV2A binding estimates could have several different causes, such as a number of vesicles per synapse or differential effects on excitatory and inhibitory synapses. Preclinical studies comparing in vivo SV2A PET imaging with in vitro methods will help advance our understanding and interpretations of SV2A imaging studies.Second, we chose Third, as our study did not include baseline [Finally, the sample size was targeted to detect larger effect sizes, which limits us in detecting subtler differences and subgroup differences (e.g., sex). As such, the study should be replicated in an independent sample, ideally with a longer range in the intervention period and in more subjects, to confirm the results and map the temporal dynamics more closely.In summary, this is the first study to investigate the effect of an SSRI intervention, using clinically relevant doses and duration (i.e., 3–5 weeks), on pre-synaptic density in the human brain. Whereas we find no statistically significant group difference in SV2A, our secondary analyses suggest that escitalopram has a time-dependent effect on cerebral SV2A, i.e., that over 3–5 weeks, escitalopram induces synaptic neuroplasticity in the human brain. This offers a biological explanation for the delayed response commonly observed in patients treated with SSRIs. While replication of the findings is warranted, these results have important implications for future studies investigating the effects of SSRIs, especially concerning the duration of intervention studies. As such, our study adds a novel perspective to the growing literature on synaptic alterations in neuropsychiatric conditions. | PMC10827655 |
Supplementary information | The online version contains supplementary material available at 10.1038/s41380-023-02285-8. | PMC10827655 | ||
Acknowledgements | Freddy | LARSEN, JENSEN | Assistance from Lone Freyr, Anna Søndergaard, Elisabeth Pedersen, Dorthe Givard, Peter Steen Jensen, Lucas Andreasen, Oliver Overgaard-Hansen, Caroline Lund, Ida Likaj, Anton Lund, Ida Møller Larsen, Christina Schulze, and Vibeke Jensen, is greatly acknowledged. The John and Birthe Meyer Foundation is gratefully acknowledged for donating the Cyclotron and PET scanner. The Kirsten and Freddy Johansen Foundation is gratefully acknowledged for donating the MRI scanner. The Toyota Foundation is gratefully acknowledged for the donation of the HPLC equipment. | PMC10827655 |
Author contributions | DSS | RECRUITMENT | GMK and BJS conceptualized the study and designed the main study together with CL and DSS. BJS and GMK acquired funding for the study. AJ designed the PET experiments and data processing pipeline with input from CS, PPS, GMK, and SHK. SA was responsible for recruitment and MRI acquisition. AJ acquired the PET data with assistance from AN, KM, and AV. INP and JM were responsible for radiochemistry. VB was responsible for the processing of volumetric MRI data. AJ analyzed the data with assistance from PPS, GMK, BO, CS, SHK, and VB. AJ drafted the manuscript in consultation with GMK. All authors critically reviewed the manuscript. | PMC10827655 |
Funding | Funding support was provided by the Danish Council for Independent Research (AJ, GMK), the Lundbeck Foundation (AJ, GMK, BJS, SA, CL), Rigshospitalet (AJ, GMK), and the Swedish Research Council (PPS). Open access funding provided by Royal Library, Copenhagen University Library. | PMC10827655 | ||
Data availability | Upon completion of the study, all data will be uploaded to the existing CIMBI Database [ | PMC10827655 | ||
Code availability | The code generated and used in the production of this manuscript is available from the corresponding authors upon request. | PMC10827655 | ||
Competing interests | GMK has received honoraria as a speaker for Sage Biogen and H. Lundbeck, and is a consultant for Onsero, Pangea, and Gilgamesh, Abbvie, PureTechHealth. BJS consults for Cambridge Cognition and receives technology transfer fees from PopReach via Cambridge Enterprise. All other authors declare no competing interests. Funding agencies did not impact the study and played no role in manuscript preparation and submission. | PMC10827655 | ||
References | PMC10827655 | |||
Methods | Low active adults (n = 47) were randomly assigned to a home-based HIIT intervention or wait-list control lasting 12 weeks. Participants in the HIIT intervention received motivational phone sessions based on Self-Determination Theory and accessed a website that included workout instructions and videos demonstrating proper form. | PMC9942957 | ||
Results | RECRUITMENT | The HIIT intervention appears feasible based on retention, recruitment, adherence to the counseling sessions, follow-up rates, and the consumer satisfaction survey. HIIT participants reported more minutes of vigorous intensity PA at six weeks relative to control (no differences at 12 weeks). HIIT participants reported higher levels of self-efficacy for PA, enjoyment of PA, outcome expectations related to PA, and positive engagement with PA than the control. | PMC9942957 | |
Conclusions | This study provides evidence for feasibility and possible efficacy of a home-based HIIT intervention for vigorous intensity PA; however, additional studies are needed with larger samples sizes to confirm efficacy of home-based HIIT interventions. | PMC9942957 | ||
Trial registration | Clinical Trials Number: | PMC9942957 | ||
Data Availability | All relevant data are within the paper and its | PMC9942957 | ||
Introduction | stroke, depression, anxiety, sleep problems | STROKE, TYPE 2 DIABETES, CARDIOVASCULAR DISEASE, CHRONIC DISEASES | Physical activity (PA) is associated with numerous health benefits including the reduced risk of cardiovascular disease, type 2 diabetes, stroke, depression, anxiety, and sleep problems [Research indicates that vigorous intensity PA may be superior to moderate intensity PA for reducing the risk of chronic diseases such as type 2 diabetes and cardiovascular disease [Behavioral interventions are efficacious for increasing PA among low-active and sedentary adults [Recent research has examined the efficacy of High Intensity Interval Training (HIIT) as a strategy to address the limitations of previous traditional PA studies [A majority of HIIT studies have been conducted in a laboratory, which does not address long-term adherence to PA nor do lab-based studies generalize to real world settings [The purpose of this pilot study was to examine the feasibility and efficacy of a 12-week home-based High Intensity Interval Training (HIIT) program among low-active individuals relative to a wait-list control arm. Self-Determination Theory informed the intervention for this study, which addressed limitations of the previous home-based studies by including muscle strengthening exercises and a motivational component. As outlined by Bowen et al., [Regarding preliminary efficacy, we hypothesized that participants randomized to the HIIT intervention would exhibit more moderate to vigorous intensity (MVPA) and vigorous intensity PA minutes per week at 6 and 12 weeks than those randomized to the wait-list control. We also hypothesized that the HIIT intervention group would report greater increases in PA-related psychosocial variables including social support, self-efficacy, enjoyment, and outcome expectations than the wait-list control arm. Affective responses to the exercise sessions were also examined. | PMC9942957 |
Methods | PMC9942957 | |||
Overview of study | BLIND | This study was a randomized controlled single blind pilot study in which participant were recruited from August, 2018 to January, 2019 (assessments were completed by April, 2019). Participants (n = 47) were randomized 1:1 to either a home-based High Intensity Interval Training program (HIIT) or a wait-list control arm each lasting 12 weeks. Participants also completed a moderate intensity session one time per week in order to compare affective responses to the HIIT sessions. The primary dependent variable was PA minutes per week at six and 12 weeks based on a modified version of the 7-Day Physical Activity Recall. Secondary dependent variables included social support, self-efficacy, enjoyment, outcome expectancies, and affective responses to PA. Participants completed an online written informed consent form prior to participating. This study was approved by the University of Minnesota’s Institutional Review Board, which reports to the Office of the Vice President for Research. The wait-list condition was given the opportunity to complete the HIIT intervention following their 12-week assessment. | PMC9942957 | |
Participants | ideation, angina, stroke, psychosis, psychiatric, diabetes | MYOCARDIAL INFARCTION, STROKE, OSTEOARTHRITIS, CORONARY HEART DISEASE, DIABETES | Low active participants ages 18 years of age or older were recruited from the northern region of the United States through worksite emails. Eligibility criteria were assessed using a telephone-based interview. Exclusion criteria included the following: (1) Engaging in PA for more than 90 minutes each week; (2) lack of access to the Internet; (3) history of coronary heart disease (history of myocardial infarction, symptoms of angina); (4) orthopedic problems that would limit physical activity participation; (5) diabetes, stroke, osteoarthritis, and any other medical condition that may make physical activity unsafe or unwise; (6) current or planned pregnancy; (7) psychiatric hospitalization within the last six months; (8) psychosis or current suicidal ideation; and (9) unwilling to be randomized to either of the study conditions. | PMC9942957 |
Measures | PMC9942957 | |||
Primary aim: Feasibility | RECRUITMENT | Feasibility will be assessed by examining acceptability and implementation. Level of acceptability will be based on attendance at the motivational phone sessions and the consumer satisfaction questionnaire (items were on a seven point Likert scale). Implementation will be based on recruitment and retention rates. Additionally, as recommended by Eldridge et al. [ | PMC9942957 | |
Secondary dependent variables: PA minutes per week and psychosocial variables | PA minutes per week was assessed at baseline, six and 12 weeks based on a modified version of the 7-Day Physical Activity Recall Interview (PAR). The PAR is considered the gold standard for assessing PA via self-report [Social support for engaging in PA was measured using the 13-item Social Support for Physical Activity Scale [The Feeling Scale (FS) was administered to the HIIT intervention participants to assess affective responses to the HIIT and moderate intensity sessions [ | PMC9942957 | ||
Procedure | In response to the worksite emails, potential participants called, emailed, or texted a study line. A telephone screening interview, which was adapted from the 10-item Physical Activity Readiness Questionnaire [ | PMC9942957 | ||
HIIT intervention | The HIIT intervention was a 12-week high intensity interval training workout that consisted of home-based HIIT sessions prescribed by the telephone counselor. The content of the HIIT sessions were determined based on exercises the participant could confidently engage in (e.g., regular push-ups vs. knee push-ups vs. wall push-ups). Participants in the HIIT condition were told when PA should be stopped for safety reasons in order to minimize risk to the participant. The goal was to engage in four PA sessions per week including three HIIT sessions and one moderate intensity continuous session. The moderate intensity session was included to allow for a comparison of affective responses during the HIIT and moderate intensity sessions. Ten percent of the HIIT sessions were audiotaped and reviewed by the PhD-level project director to ensure fidelity to the telephone sessions. The project director completed protocol checklists when listening to the sessions.The HIIT intervention included telephone calls delivered by a master’s level health coach who is a trained personal trainer and holds an American College of Sports Medicine Certified Exercise Physiologists | PMC9942957 | ||
Summary of intervention component targeting psychosocial variables. | Note: Behavior Change Techniques from Abraham & Michie [Sessions were approximately 30 minutes total including a five minute warm-up, 20 minutes of HIIT, and a five minute cool-down. The sessions were progressively overloaded using bodyweight. For example, a participant may have started with pushups on their knees, which progressed to pushups on their toes, overall repetitions of burpees were increased, and/or sprints improved from 45 to 40 seconds. Resistance training included bodyweight exercises such as squats, push-ups, lunges, and planks. Aerobic exercise included exercises such as jumping jacks, sprints, jump rope, high knees, and mountain climbers. Resistance exercises aimed to increase strength and stability along with increasing heart rate and aerobic exercise aimed to increase heart rate. The session intensity was determined by RPE.Participants also accessed a study website that included descriptions of several different HIIT sessions. The website also included videos that demonstrated the HIIT exercises. Examples of exercises included push-ups, squat jumps, walking lunges, mountain climbers, hill sprints, plank, and jumping rope. Participants chose the type of moderate intensity PA they participated in each week. The goal was for participants to reach 70–85% of their maximum heart rate for the HIIT session with the high intensity components reaching 80–90%. The goal for the moderate sessions were 55–70% of maximum heart rate. | PMC9942957 | ||
Data analysis | SECONDARY | Descriptive statistics were used to summarize baseline variables in the aggregate sample and t-tests and chi-squared tests were used to compare groups at baseline (as appropriate). Unadjusted means were reported over time by condition for each of the primary and secondary study outcomes.A series of generalized linear models were used to examine intervention effects on absolute scores at follow-up (six and 12 weeks in a single model) controlling for baseline. Models included effects of time, condition, time* condition, and baseline value of the outcome. Fixed effects were estimated in each model. Repeated measures ANOVA was used to examine within subject differences on affective responses between the HIIT and moderate intensity PA sessions. All analyses were run in SAS 9.3 based on the intent to treat sample (all randomized participants included in the analysis). | PMC9942957 | |
Results | Demographic information is summarized in | PMC9942957 | ||
Baseline characteristics by study arms. | Note: Age is reported as means with standard deviations in parentheses. | PMC9942957 | ||
Feasibility | RECRUITMENT | Recruitment is summarized in | PMC9942957 | |
HIIT flow chart. | PMC9942957 | |||
Consumer satisfaction survey. | Note: Items were on a seven point Likert scale. | PMC9942957 | ||
Physical activity | Unadjusted PA minutes per week by study arm are reported in | PMC9942957 | ||
The effect of the HIIT on physical activity: Unadjusted effects. | Abbreviations: MVPA = Moderate to Vigorous Intensity Physical Activity. The above values are means. Standard deviations are in parentheses. | PMC9942957 | ||
Psychosocial variables | The effect of the HIIT intervention on several psychosocial variables is summarized in | PMC9942957 | ||
The effect of HIIT on psychosocial variables: Unadjusted effects. | Note: EFI = Exercise Feeling Inventory. The above values are means (standard deviations in parentheses). | PMC9942957 | ||
Affective responses to moderate vs. HIIT sessions | Sixty-five percent of the participants completed at least one moderate intensity session affect log and 83% completed at least one HIIT log during the intervention. Participants completed a mean number of 4.26 (SD = 4.65) moderate intensity logs and 6.09 (SD = 6.84) HIIT logs. Among the participants randomly assigned to the HIIT intervention, there were no differences between the moderate and HIIT sessions regarding affective responses (i.e., pleasure and enjoyment; p’s > .05). | PMC9942957 | ||
Discussion | RECRUITMENT | The home-based HIIT intervention appears feasible based on meeting the acceptability and implementation parameters. Specifically, we met our recruitment goal within the intended timeframe, which was to recruit 40 participants in six months. Our retention rate (98%) was higher than our 90% retention goal. We randomized two-thirds of the eligible participants. Additionally, participants attended a mean number of 90% of the motivational sessions, which exceeded our 75% goal. The mean rating across the seven consumer satisfaction items was 5.07, which exceed our goal of five. Participants rated the information from the exercise counselor and the exercise sessions as the highest and the online exercise logs the lowest.Regarding efficacy, contrary to our hypotheses and previous studies [The study was not powered to examine which psychosocial variables mediated the effect of the intervention on PA. Therefore, in order to inform future trials examining mediation, only the effect of the intervention on the psychosocial variables was examined. Self-efficacy of physical activity, enjoyment, outcome expectations (i.e., expected outcomes and value of those outcomes as a result of PA), and positive engagement (i.e., upbeat, enthusiastic, happy) increased from baseline to 12 weeks for the intervention relative to the control. This is consistent with previous studies indicating that these psychosocial variables are related to physical activity behavior change [Among the participants randomized to the HIIT sessions, there were no differences between the moderate and HIIT sessions regarding affective responses (i.e., ratings of pleasure and enjoyment). This is inconsistent with previous HIIT studies [There were several strengths to this study. First, the examination of a home-based HIIT intervention is novel given a majority of HIIT studies have been lab-based. Second, the study was strong methodologically in that participants were randomized to the conditions, there was quality control for the counseling sessions, an experienced health coach delivered the intervention, and validated measures were used. Finally, the study sample was relatively diverse when compared to the overall population of the recruitment area. Despite these strengths, there were some limitations. First, data from the objective measure of PA was not included given the lack of validity for using accelerometers to assess HIIT sessions [The HIIT intervention appears feasible based on retention, recruitment, adherence to the counseling sessions, follow-up rates, and the consumer satisfaction survey. Participants indicated they were the least satisfied with the online exercise logs suggesting that additional research is needed to improve upon the usability and acceptability of online exercise logs. Participants were the most satisfied with the exercise counseling sessions indicating that personal motivational sessions may be important for adherence to HIIT. Based on the feasibility data and the preliminary efficacy data indicating higher rates for vigorous intensity PA among the HIIT intervention relative to control, it appears that the HIIT intervention should be examined in a large trial. It will be important to examine affective responses to better understand how these responses influence adherence. Studies should explore integrating HIIT interventions within existing opportunities (e.g., physical education) and increase physical literacy [In summary, this small pilot study indicates that home-based HIIT is acceptable and feasible for low active adults. However, selection bias may have played a role in the acceptability of vigorous intensity PA. It is possible that participants who enrolled in the study were more open to vigorous intensity PA than those not interested in the study. HIIT may be advantageous to traditional PA given it takes less time to meet the PA recommendation and it may be more enjoyable than moderate intensity activity. Future studies with larger sample sizes and objective measures of PA are needed to better understand if this study is viable for dissemination to low active adults. | PMC9942957 | |
Supporting information | PMC9942957 | |||
CONSORT 2010 checklist of information to include when reporting a randomised trial*. | (DOC)Click here for additional data file.(XLSX)Click here for additional data file.(DOCX)Click here for additional data file. | PMC9942957 | ||
References | PMC9942957 | |||
Keywords | Open access funding provided by Karolinska Institute. | PMC10435650 | ||
Background and Aims | arterial stiffness, bleeding, thrombus, airway inflammation | BLEEDING, THROMBUS, ARTERIAL STIFFNESS, OXIDATIVE STRESS, ENDOTHELIAL DYSFUNCTION | The electronic cigarette (EC) was introduced in 2003 as an alternative to traditional cigarette smoking. Over the years, the use of ECs has steadily increased across the world, especially among adolescents. This is partially due to major marketing efforts by the EC industry and e-liquid flavours especially targeting youth [Studies targeting EC-related health effects have demonstrated increased airway inflammation and obstruction, endothelial dysfunction, increased arterial stiffness and oxidative stress following EC use with e-liquids containing nicotine [The aim of the present study was to further investigate the impact of EC aerosol on vascular health applying well-established methods for assessing vascular function and haemostasis. Haemostasis was investigated by the Total-Thrombus-formation analysis system (T-TAS), which has been used for bedside assessment of thrombus formation in whole blood, evaluate anti-platelet therapies, anticoagulants and risk of bleeding during catheter interventions [ | PMC10435650 |
Materials and Methods | PMC10435650 | |||
Study Design and Sample | infection | STASIS, INFECTION, BLOOD, CHRONIC DISEASE | Twenty-two healthy male and female occasional smokers or Swedish snus users (maximum 10 cigarettes or 10 pouches of snus per month) between 18 and 45 years of age were included in the study. Written informed consent was obtained at inclusion. The study design adhered to the 1975 Helsinki declaration and was approved by the Swedish Ethical Review Authority. The study was performed with a randomised, double-blind crossover design (Fig. 3, supplements). No significant carry-over effects were expected with a wash-out period of one week to allow for elimination of any inhaled nicotine. EC exposures, with and without nicotine, were performed on two occasions separated by a wash-out period of at least one week. Volunteers had to refrain from all sorts of nicotine products, water-pipe, drugs including marijuana, anti-inflammatory medications, and strenuous physical activity one week prior to exposures. Volunteers also had to abstain from caffeine and alcohol 24 h prior to exposure. Exclusion criteria were any chronic disease, infection, pregnancy, or inflammatory symptoms within the last 7 days prior to participation, and BMI below 18 kg/mAll exposures were supervised and performed in a well-ventilated and temperature-controlled room. On each occasion, subjects inhaled one puff of EC aerosol per minute for 30 min. Each puff lasted 2–3 s. A third-generation EC (eVic Primo SE, Joyetech Electronics Co.,Ltd, China) was used, with a proC1-S atomizer with a resistance of 0.25Ω. Exposure settings were standardised (effect 32W, temperature 230 °C). Two commercially available e-liquids were used (Valeo laboratories GmbH, Germany), composed of propylene glycol (49%), glycerine (44%) and ethanol (5%) with no added flavourings; one contained 19 mg/ml of nicotine, the other without nicotine.Venous blood was sampled from the antecubital vein with no or minimal stasis. At inclusion routine blood tests were taken including blood cell count, serum-creatinine, electrolytes and glucose. Blood pressure and pulse were measured at baseline, as well as at 30 and 60 minutes post exposure. Blood pressure equipment was a semi-automatic oscillometric sphygmomanometer (Omron M7, Omron Healthcare Europe B.V., Hoofddorp, NL). | PMC10435650 |
T-TAS | thrombus | THROMBUS | Total-Thrombus-formation analysis system (T-TAS®. Fujimoro Kogyo Co., Ltd., Japan) evaluates thrombus formation in whole blood using a microchip flow chamber system that can simulate various venous or arterial blood flow conditions [Different shear rates simulate different flow conditions. For the PL chip, a flow rate of 18μL/min was chosen, corresponding to a shear rate of 1500 s | PMC10435650 |
Laser Speckle Contrast Imaging and Iontophoresis | SKIN | Skin microvascular function was evaluated through investigation of changes in skin perfusion, assessed by laser speckle contrast imaging (LSCI) in response to iontophoresis of vasoactive drugs at baseline and 30 min after exposure [ | PMC10435650 | |
Skin Temperature | SKIN | Skin temperature of the volar side of left forearm and distal phalange of the left fourth digit was recorded with an electronic thermistor (Exacon, Copenhagen, Denmark) at baseline and 30 min following exposure. | PMC10435650 | |
Statistical Analysis | It was planned to include 22 subjects due to the risk of drop-out and technical problems. Statistical analysis was performed in SPSS 27.0.0.0 64-bit edition (IBM Corporation, NY, US) and GraphPad Prism 8.4.2. (GraphPaSoftware Inc., CA, US). All data sets were tested for normality with Shapiro–Wilk test. Normally distributed data were expressed as means with standard deviations, while significantly skewed data were reported as medians and interquartile range. For normally distributed data, repeated measures ANOVAs and post hoc analysis with pairwise comparisons with Bonferroni correction were used to detect differences between groups. For skewed data, Friedman’s test together with post hoc analysis through Dunn’s pairwise comparisons and Wilcoxon signed-rank test were applied. P-values of < 0.05 were considered statistically significant. Any missing data point at any measurement point excluded that participant from the specific data analysis. | PMC10435650 | ||
Results | Twenty-two healthy individuals, 15 females and 7 males, were included in the study and analysis. Data collection took place between September 2019 and January 2020. Mean age was 27 ± 7, BMI was 24 kg/m | PMC10435650 | ||
Skin Temperature, Heart Rate and Blood Pressure | Forearm skin temperature decreased significantly after exposure in both groups (Table Temperature and circulatory results before and after exposure to electronic cigarette aerosol with and without nicotineNicotineNon-nicotine30.1 ± 1.430.2 ± 1.129.2 ± 1.229.4 ± 1.2NicotineNon-nicotine28.0 (5.8)29.1 (5.0)24.4 (2.8)25.2 (2.9)NicotineNon-nicotine66 ± 1068 ± 1073 ± 1363 ± 971 ± 1364 ± 11NicotineNon-nicotine108 ± 14110 ± 11117 ± 14113 ± 13112 ± 10114 ± 13NicotineNon-nicotine70 ± 1270 ± 974 ± 873 ± 874 ± 775 ± 9Effects of exposure to electronic cigarette aerosol with and without nicotine on forearm skin temperature, finger temperature, heart rate, systolic and diastolic blood pressureParametric data are presented as mean values ± standard deviations. Non-parametric data presented as median (interquartile range). P-values are repeated measures ANOVAs or Friedman’s test, Exposure x TimeBold values indicates the P-values below 0.05 was considered statistically significant | PMC10435650 | ||
T-TAS | fibrin-rich thrombus | T-TAS measurement data are presented in Fig. Platelet and fibrin-rich thrombus formation following exposure to electronic cigarette aerosol with and without nicotine. Graphs show individual values and bars median values. P-values for Friedman’s test (exposure and time) are shown on the right side. P-values above the brackets represent post hoc analysis with pairwise comparisons baseline vs post exposureAR-AUC increased significantly following EC exposure with nicotine (Fig. | PMC10435650 | |
LSCI | LSCI data showing changes in skin microvascular reactivity following EC exposure are presented in Fig. Endothelial-dependent and independent skin microcirculation following exposure to electronic cigarette aerosol with and without nicotine. Basal skin flux before iontophoresis of ACh and SNP | PMC10435650 |
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