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).

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.

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.

Background: About 4 out of 10 fibromyalgia patients suffer from depression. The European Alliance of Associations for Rheumatology (EULAR) guidelines recommend using antidepressants to treat fibromyalgia. Objective: To determine predictors of improved outcomes following a multicomponent treatment program. Design: We designed this longitudinal treatment outcome study to evaluate the prevalence of depression symptoms in patients diagnosed with fibromyalgia at a tertiary care facility, and the impact of depression on functional outcomes after completing a multicomponent fibromyalgia treatment program. Setting: Tertiary care center. Patients: This study included 411 adult patients with fibromyalgia who completed a multicomponent treatment program for fibromyalgia. Expert physicians performed comprehensive evaluations following American College of Rheumatology (ACR) criteria to confirm fibromyalgia before referral to the program. Intervention: An intensive outpatient multicomponent treatment program consisting of 16 hours of cognitive behavioral strategies served as the intervention. Measurements: Functional status was assessed using the Fibromyalgia Impact Questionnaire Revised (FIQR). Depression was evaluated with the Center for Epidemiologic Study of Depression (CES-D) measure. Measures were administered prior to participation in the program and approximately 5 months following completion of the program. Results: The cohort had a high prevalence of depressive symptoms (73.2% had depression at admission). Higher depression scores at baseline predicted poorer outcomes following multi-component treatment. Effectively treated depression resulted in improved functioning at follow-up. Limitations: Findings limited to tertiary care center cohort of fibromyalgia patients. Patients did not undergo a structured clinical diagnostic interview to diagnose depression. Conclusions: The current data links depression to poorer outcomes in patients with fibromyalgia. Depression is an important modifiable factor in the management of fibromyalgia. Guidelines should reflect the importance of assessing and effectively treating depression at the time of diagnosis of fibromyalgia, to improve functional outcomes. Registration: Specific registry and specific study registration number—Institutional Review Board—(IRB# 19-000495). Funding Source: No funding.

AbstractThe purpose of this study was to estimate the extent of potential antidepressant overprescribing in a geographically defined U.S. population, and to determine the indications and factors that account for it. We conducted a cohort study of new antidepressant prescriptions for elderly residents of Olmsted County, Minnesota, 2005‐2012, using the Rochester Epidemiology Project medical records‐linkage system. Indications for antidepressants were abstracted from health records for all cohort members. Potential antidepressant overprescribing was defined based on regulatory approval, the level of evidence identified from a standardized drug information database, and multidisciplinary expert review. Predictors of potential antidepressant overprescribing were investigated using logistic regression models, stratified by general antidepressant indication (general medical indication, specific psychiatric diagnosis, and non‐specific psychiatric symptoms). Potential antidepressant overprescribing occurred in 24% of 3199 incident antidepressant prescriptions during the study period, and involved primarily newer antidepressants that were prescribed for non‐specific psychiatric symptoms and subthreshold diagnoses. Potential antidepressant overprescribing was associated with nursing home residence, having a higher number of comorbid medical conditions and outpatient prescribers, taking more concomitant medications, having greater use of urgent or acute care services in the year preceding the index antidepressant prescription, and being prescribed antidepressants via telephone, e‐mail, or patient portal. In conclusion, potential antidepressant overprescribing occurred in elderly persons and involved mainly newer antidepressants used for non‐specific psychiatric symptoms and subthreshold diagnoses, and was associated with indicators of higher clinical complexity or severity and with prescribing without face‐to‐face patient contact.