Chauhan, Mohit

ABSTRACT Consumer‐grade wearables, including smartwatches, fitness trackers, and smart rings, are accessible tools for studying pharmacologic responses in real‐time, monitoring participant health in decentralized clinical trials, optimizing outcome measures, and delivering digital interventions that promote behavior change. However, incorporating consumer wearables into clinical studies is not as straightforward as simply purchasing devices and providing them to participants. It requires engaging with a complex engineering ecosystem with multiple investigator decisions on device selection, associated data management practices, and patient/participant engagement and technical support. This tutorial, based on experience running large clinical trials using consumer wearables, outlines the wearables market landscape across varying form factors and manufacturers as well as the data management software products supporting wearable use. It delineates the major decision processes involved in designing studies that incorporate wearables and presents a structured framework to guide the selection of devices and supporting data tools according to study objectives.

Abstract Unsupervised molecular clustering is fundamental to precision medicine, yet most published subtyping studies lack standardized validation criteria, making it impossible to distinguish biological signal from statistical artifact. We present the Pathway Subtyping Framework, which enforces four mandatory validation gates—label shuffle, random gene set, bootstrap stability with adaptive thresholds, and ancestry independence—before any clustering result is reported. On TCGA-COAD (n=452), the framework independently recovered CMS4 (Mesenchymal) with 75.9% CMS4 enrichment (Fisher OR=16.71, p=1.4×10⁻²⁵), outperforming PCA+k-means (67%), gene-level k-means (50%), and NMF (32%) on the same data. Applied to autism (n=56) and schizophrenia (n=281) as pilot demonstrations, the framework produced replicable subtypes across platforms (ARI=0.870) and achieved the strongest gate performance across all datasets (bootstrap ARI=0.923). Cross-disease analysis reveals that molecular subtypes are independent of DSM diagnosis (Cramér's V=0.036) but strongly dependent on brain region (V=0.528); within-region concordance is 84% (ARI=0.862), decomposing the 87% global concordance into disease-agnostic and anatomical components. The adaptive bootstrap threshold model, calibrated on 47 independent benchmarks (R²=0.889, LOOCV RMSE=0.051), replaces arbitrary fixed thresholds with data-driven, silhouette-calibrated gates. The framework is open-source (PyPI, Docker, Codeberg; 1,054 tests; DOI:10.5281/zenodo.18867165).

Introduction Sleep is routinely assessed in the management of mental health conditions. Wearable technologies like smartwatches offer a non-intrusive method to quantitatively measure sleep. However, there are limited empirical benchmarks for sleep duration and sleep quality measured by wearables against user reports. This study aims to evaluate the concordance between user-reported and smartwatch-measured hours of sleep and sleep quality. Methods Participants were recruited from two decentralized digital health well-being studies and completed a 7-day sleep diary while simultaneously wearing their smartwatch to sleep (November 7, 2023 - June 30, 2024). Participants self-reported sleep timestamps and perceived sleep quality using the Sleep Quality Scale. Sleep timestamps and quality were also derived from their smartwatches (Garmin Vívoactive 4 2019, Garmin Venu 2 Plus 2022, and Garmin Venu 3/3S 2023). Statistical analyses included paired t-tests, equipercentile linking, and chi-square tests to assess agreement between smartwatch and self-reported sleep parameters. Exploratory analyses established the difference between reported and recorded sleep duration in healthcare shift workers. Results From 841 sleep instances reported by 130 participants wearing three different generation smartwatches, the mean difference in sleep duration between smartwatch-recorded and participant-reported was 21.22 (Garmin Vívoactive), 11.67 (Garmin Venu 2 Plus), and 6.58 (Garmin Venu 3/3S) minutes, respectively. There were statistically significant between-group differences in mean sleep durations assessed by participant self-report vs. Vívoactive 4 smartwatches, but not self-report vs. Venu 2 Plus or Venu 3/3S smartwatches. Equipercentile linking revealed concordance between smartwatch sleep scores and self-reported sleep quality using the Sleep Quality Scale (SQS) between 4 and 7, with disagreements observed at the SQS ranges from 0–4 and 7-10. Conclusions These results suggest that wearables can reliably measure sleep duration, and future research warrants improvements in algorithms that estimate sleep quality with validations across different wearable vendors.

Background Ketamine has demonstrated efficacy in treatment-resistant depression, primarily in psychiatric or outpatient populations. Its use in ICU patients remains underexplored, with limited data beyond case reports and small series. This study evaluated the association between subanesthetic ketamine infusions and improvement in depressive symptoms and hemodynamic changes in ICU patients. Methods We conducted a retrospective study of adults admitted to the ICU who received IV ketamine (0.3-0.75 mg/kg over 40 min on three consecutive days) for depressive symptoms. Changes in depressive symptoms were assessed using routine clinical documentation by physicians, nurses, and occupational and physical therapists. Hemodynamic parameters (blood pressure and heart rate) were recorded before and up to 120 min after infusion. The primary outcome was to evaluate depressive symptoms while the secondary outcome was to assess hemodynamic changes post transfusion. Results Thirty-four patients met criteria, including 18 solid organ transplant recipients. Median age was 59 years; 61.8% were male. Ketamine was associated with improvement in apparent sadness (90.0% vs 52.2%, P < .05) and reported sadness (95.0% vs 59.1%, P < .05). In transplant recipients, improvement in apparent sadness remained significant (80.0% vs 41.7%, P < .05). Hemodynamic parameters remained stable; heart rate increased transiently at 15-30 min post-infusion, returning to baseline by 60-90 min. Adverse effects observed were anxiety (12.5%), restlessness and/or agitation (10.4%), and dissociation (8.16%). Conclusion Subanesthetic ketamine improved specific depressive symptoms in critically ill ICU patients without significant hemodynamic instability. These findings support its potential as a rapid-acting antidepressant in the ICU, warranting further prospective trials.

Background: Invasive and non-invasive neuromodulation in psychiatry represents a burgeoning field that leverages advanced neuromodulation techniques to address substance use disorders (SUDs). Aims: This narrative review synthesizes findings from multiple reviews to evaluate the efficacy of neuromodulation in treating SUDs. Methods: A comprehensive literature search was conducted between December 2024 and April 2025, focusing on systematic reviews and meta-analyses that examined various neuromodulation modalities, including repetitive transcranial magnetic stimulation (rTMS), transcranial direct current stimulation (tDCS), and deep brain stimulation (DBS). The selected reviews were analyzed to identify common themes, outcomes, and gaps in the current understanding of these treatments for SUDs. Results: 11 reviews met the final inclusion criteria; 5 focused on non-invasive neuromodulation (rTMS, tDCS) and 6 on invasive neuromodulation (DBS). Non-invasive neurostimulation was associated with modest improvements in craving and cognitive dysfunction in individuals with SUDs. Similarly, invasive neuromodulation (DBS), through high-frequency stimulation of the bilateral nucleus accumbens, appeared to reduce cravings and improve comorbid psychiatric symptoms in both preclinical and human studies. Importantly, small sample sizes, heterogeneity in targets and stimulation protocols, and short follow-up periods significantly limit the generalizability of current findings from both non-invasive and invasive neuromodulation studies. Conclusions: As novel and more effective therapies for the treatment of SUD are desperately needed, procedural interventional psychiatry holds promise. However, despite encouraging results, existing evidence is still preliminary, and larger, rigorously designed studies are warranted to further establish the safety and efficacy of neuromodulatory interventions for SUD treatment.

Background Intolerance of Uncertainty (IU) has never been explored in functional motor disorder (FMD) or any functional neurological disorder but perceptions of control are theoretically relevant. Objective To evaluate if IU changes in people with FMD completing intensive 1-week motor retraining treatment, and if IU change associates with outcome. Methods A consecutive cohort of 45 FMD patients completed a 1-week intensive outpatient motor retraining treatment. At program beginning and end, patients self-rated IU using the Intolerance of Uncertainty Scale-12 (IUS-12) and four functional impairment measures. Paired t-tests analyzed program changes in IU and functional outcomes. Linear regressions analyzed association strength between IU change and outcome. Results IU improved with FMD treatment (p < 0.001). Pre- to post-treatment IU was improved in 32/45 (71%), stable in 5/45 (11%), and worsened in 8/45 (18%). Age, symptom duration, and FMD phenotype did not predict IU improvement. Self-rated function improved across measures with treatment (p < 0.001). Program change in IU positively predicted outcome on 3 of 4 measures. Conclusions IU improves with FMD rehabilitation, even without explicit psychological focus of treatment, regardless of age or FMD phenotype. Improving IU associates with positive FMD treatment outcomes suggesting an important treatment target in FMD.

ABSTRACT Adherence in digital health studies with extended observation periods (≥ 12 months) is limited, and participant retention considerably reduces with time. The US Food and Drug Administration has issued guidelines for improving participant engagement, adherence, and diversity in digital health studies combined with decentralized procedures. A decentralized digital health study on well‐being was designed with protocolized procedures to study the feasibility of participant engagement and technology support to facilitate adherence (wearing the smartwatch ≥ 70% of time) sustained over a 12‐month period. At the end of the study, participants were asked about their ease of participation and free‐response questions about how wearing the smartwatches impacted their physical wellness. An inductive thematic analysis (ITA) was performed to assess themes of those responses and association with adherence. A total of 298 participants were recruited between 2022 and 2023 ( n = 129 in Cohort A in October 22, n = 169 in Cohort B in April 23), with 23% non‐white participants accrued. Among the 298 participants accrued, 273 (92% of accrued participants) completed the 12‐month study with an average overall adherence of 77.4% (SD = 32.64) wear‐time across 12 months. Median adherence of participants whose responses exemplified an ITA theme encompassing perceived behavior changes in sleep and physical activity was higher than those who did not have a response exemplifying that theme. Conversely, those expressing perceived discomfort or intrusiveness of the smartwatch had a statistically lower adherence. These results highlight the crucial roles of technology support and robust engagement efforts to enable sustained adherence over extended follow‐up periods in decentralized digital health studies.

Introduction: Despite advances in obstetric care, postpartum hemorrhage (PPH) is a leading cause of maternal mortality worldwide. Prior reviews of studies published through 2016 suggest an association of antidepressant use during late pregnancy and increased risk of PPH. However, a causal link between prenatal antidepressants and PPH remains controversial. Objectives: This systematic literature review aimed to synthesize the empirical evidence on the association of antidepressant exposure in late pregnancy with the risk of PPH, including studies published before and after 2016. Methods: A systematic literature search was conducted using PubMed, OVID Medline, EMBASE, SCOPUS, PsycINFO, and CINAHL from inception to September 9, 2023. Original, peer-reviewed studies (published in English) that reported on the frequency or risk of PPH in women with evidence of antidepressant use during pregnancy and included at least one control group were included. Results: Twenty studies (eight published after 2016) met inclusion criteria, most of which focused on the risks of PPH associated with selective serotonin reuptake inhibitors (SSRIs) or serotonin-norepinephrine reuptake inhibitors (SNRIs). The main findings from the individual studies were mixed, but the majority documented statistically significant associations of PPH with late prenatal exposure, especially for exposures occurring within 30 days of delivery, compared with unexposed deliveries. Fourteen studies addressed underlying antidepressant indications or their correlates. Few studies focused on prenatal antidepressants and the risk of well-defined severe PPH or on antidepressant dose changes and general PPH risk. None examined competing risks of antidepressant discontinuation on mental health outcomes. Conclusions: Late pregnancy exposure to antidepressants may be a minor risk factor for PPH, but it is unclear to what extent reported associations are causal in nature, as opposed to correlational (effects related to nonpharmacological factors including maternal indication). For patients needing antidepressants during pregnancy, current evidence does not favor routinely discontinuing antidepressants specifically to reduce the risk of PPH.

Fibromyalgia (FM) affects 2% to 8% of the general population. FM patients often experience self-stigma and feel rejected by healthcare providers and families, resulting in isolation and distressing symptoms of pain, fatigue, and poor cognitive functioning, increasing the risk of depressive symptoms. Major Depressive Disorder (MDD) is the most common comorbidity in FM patients (Any depression: 43%; MDD: 32%). Genome-wide association studies (GWAS) have identified a common genetic risk loci for major depression and fibromyalgia. Given that even minor symptoms of depression worsen the outcomes of FM patients, clinicians are challenged to identify and manage depression in these patients. However, due to overlapping symptoms, limited screening, and contamination bias, MDD often goes undiagnosed and presents a critical challenge. Unrecognized and untreated MDD in FM patients can exacerbate fatigue, sleep disturbances, and pain, reduce physical functioning, and increase the risk of developing comorbid conditions, such as substance abuse and cardiovascular disease. These comorbidities are associated with a lower treatment response rate, a higher dropout rate, and a greater risk of relapse. Clinicians may effectively identify and treat MDD in FM patients with appropriate pharmacologic agents combined with aerobic exercise and cognitive-behavioral therapies for core FM symptoms, thus significantly reducing symptom severity for both MDD and FM. Such a comprehensive approach will result in a much-improved quality of life. MedLine content was searched via PubMed to identify eligible articles between 1995 and 2023 using search terms fibromyalgia, major depressive disorder, and treatment of depression in fibromyalgia, and the most current information is presented. In this primer for clinicians caring for FM patients, we describe clinically relevant pharmacologic and non-pharmacologic management approaches for treating MDD in FM patients.