Tag: statistics

JMIR Form Res. 2025 Oct 10;9:e70495. doi: 10.2196/70495.

ABSTRACT

BACKGROUND: The 6-minute walk test (6MWT) measures exercise capacity in cardiorespiratory, neurological, and musculoskeletal conditions. It consists of observing how far a patient can walk in 6 minutes and is usually performed in a corridor in a clinic. During the COVID-19 pandemic, as health care systems cancelled nonurgent outpatient appointments, many tests were conducted online. At Oxford University Hospitals National Health Service Foundation Trust, patients followed up on by cardiovascular outpatient clinics were asked to use the open-source Timed Walk app to perform the 6MWT in their community as a substitute for the regular tests in the clinic.

OBJECTIVE: This study aimed to assess the clinical usefulness of the app within the context of the pandemic.

METHODS: Consented patients were invited to perform a 6MWT outdoors using the app at least once a month and report the results through periodic telephone calls and visits. Clinical decisions made for the same cohort were registered, with a focus on the effect of the app in supporting decision-making. Data collected through the app during the study period were compared with 6MWTs performed in the prepandemic period.

RESULTS: This study was conducted between October 2021 and December 2022. A total of 55 participants consented (n=25, 45% female; mean age 44.80, SD 17.49 y). In total, 741 events were logged. A total of 51 medical decisions were made for 25 patients; in 41% (21/51) of the decisions, the app played a role, affecting 44% (11/25) of the patients. Between 2018 and 2022, a cohort of 49 patients for whom data were available performed 63 6MWTs in the clinic (18 in 2021), whereas the same patients performed 605 tests using the app in 2022 (ie, October 2021 to December 2022).

CONCLUSIONS: The use of the Timed Walk app for remote 6MWTs allowed clinicians to obtain frequent and objective indications of the status of the patients during the pandemic, compensating for the absence of regular clinic appointments and providing 33 times more tests than in the prepandemic period. These tests supported approximately half of the clinical decisions made regarding the consented patients, showing that the app is useful in clinical practice.

PMID:41071986 | DOI:10.2196/70495

JMIR Diabetes. 2025 Oct 10;10:e68948. doi: 10.2196/68948.

ABSTRACT

BACKGROUND: Exercise is an important aspect of diabetes self-management. Patients with type 1 diabetes frequently struggle with exercise-induced hyperglycemia and hypoglycemia, decreasing their willingness to exercise.

OBJECTIVE: We aim to build accurate and easy-to-deploy models to forecast exercise-induced glycemic events in real-world settings.

METHODS: We analyzed free-living data from the Type 1 Diabetes Exercise Initiative study, where adults with type 1 diabetes wore a continuous glucose monitor (CGM) while performing video-guided exercises (30-minute exercises at least 6 times over 4 weeks), along with concurrent detailed phenotyping of their insulin program and diet. We built models to predict glycemic events (blood glucose ≤54 mg/dL, ≤70 mg/dL, ≥200 mg/dL, and ≥250 mg/dL) during and 1 hour post exercise with variables from 4 data modalities, such as demographic and clinical (eg, glycated hemoglobin; CGM (blood glucose value and their summary statistics); carbohydrate intake and insulin administration; and exercise type, duration, and intensity. We used repeated stratified nested cross-validation for model selection and performance estimation. We evaluated the relative contribution of the 4 input data modalities for predicting glycemic events, which informs the cost and benefit for including them in the decision support tool for risk prediction. We also evaluated other important aspects related to model translation into decision support tools, including model calibration and sensitivity to noisy inputs.

RESULTS: Our models were built based on 1901 exercise episodes for 329 participants. The median age for the participants was 34 (IQR 26-48) years. Of the participants, 74.8% (246/329) are female and 94.5% (311/329) are White. A total of 182/329 (55.3%) participants used a closed-loop insulin delivery system, while the rest used a pump without a closed-loop system. Models incorporating information from all 4 data modalities showed excellent predictive performance with cross-validated area under the receiver operating curves (AUROCs) ranging from mean 0.880 (SD 0.057) to mean 0.992 (SD 0.001) for different glycemic events. Models built with CGM data alone have statistically indistinguishable performance compared to models using all data modalities, indicating the other 3 data modalities do not add additional information with respect to predicting exercise-related glycemic events. The models based solely on CGM data also showed outstanding calibration (Brier score ≤0.08) and resilience to noisy input.

CONCLUSIONS: We successfully constructed models to forecast exercise-induced glycemic events using only CGM data as input with excellent predictive performance, calibration, and robustness. In addition, these models are based on automatically captured CGM data, thus easy to deploy and maintain and incurring minimal user burden, enabling model translation into a decision support tool.

PMID:41071985 | DOI:10.2196/68948

JMIR Mhealth Uhealth. 2025 Oct 10;13:e72372. doi: 10.2196/72372.

ABSTRACT

BACKGROUND: Head and neck cancer (HNC) survivors face profound functional and quality-of-life deficits due to disease- and treatment-related sequelae, ranging from mild fatigue to debilitating dysphagia. Wearable technology, by monitoring biometric data such as step counts or providing swallowing biofeedback, offers a unique method for tracking and monitoring the negative effects of HNC.

OBJECTIVE: The aim of this study was to explore the current applications of wearable technology in HNC.

METHODS: A scoping review was conducted following the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) guidelines. A search strategy was built, and a literature search was performed across 5 databases. The initial search yielded 5256 studies, which underwent a 2-phase screening process: title and abstract review followed by full-text review. Inclusion criteria included peer-reviewed, English-language articles published between January 2002 and April 2024 that used wearable technology in HNC care. After full-text review, 9 studies met the inclusion criteria. Data were manually extracted and synthesized narratively.

RESULTS: The included studies examined 3 main types of wearable devices: radioactivity (2 studies), physical activity (4 studies), and throat physiology monitors (3 studies). Radioactivity monitors detected residual radioactivity and thyroidal radioiodine uptake. They demonstrated potential to reduce radioactivity exposure risk and personalize radiation doses for patients with thyroid cancer. Physical activity monitors tracked step counts, heart rate, and sleep habits. Low step counts were significantly associated with increased anxiety, radiation-related toxicity, hospital admission rates, and feeding tube placement. One study also linked poor sleep patterns to declines in quality of life. Throat physiology monitors measured pharyngeal electromyography data as well as extrinsic laryngeal muscle movements. Throat sensors achieved high accuracy in classifying swallowing events and translating muscle movements into speech. While earliest in the development continuum, they are promising tools for swallowing and vocal rehabilitation therapy. Barriers to wearable adoption included wearable discomfort, technical difficulties, and patient withdrawal due to treatment side effects. As the definition of wearable adherence varied widely, we propose that future studies report wearable adherence as “percentage of prescribed wear time achieved” to facilitate cross-study comparisons.

CONCLUSIONS: Wearable technology may enhance treatment monitoring, prognostication, and rehabilitation in head and neck oncology. Radioactivity and physical activity monitors provide actionable insights for clinical decision-making, while throat physiology monitors offer innovative solutions for speech and swallowing therapy. However, challenges such as device adherence, data integration, and patient comfort must be addressed to realize their full potential. Future research should prioritize larger, longitudinal studies, standardized adherence metrics, and consider the integration of artificial intelligence to refine predictive capabilities. By overcoming these barriers, wearable technology could transform survivorship care, improving functional outcomes and quality of life for patients with HNC.

PMID:41071984 | DOI:10.2196/72372

J Med Internet Res. 2025 Oct 10;27:e73142. doi: 10.2196/73142.

ABSTRACT

BACKGROUND: Stroke frequently leads to various functional impairments. Both virtual reality (VR) and mirror therapy (MT) have shown efficacy in stroke rehabilitation. In recent years, the combination of these 2 approaches has emerged as a potential treatment for patients with stroke.

OBJECTIVE: This study aimed to evaluate the efficacy of combined immersive and nonimmersive VR with MT in stroke rehabilitation.

METHODS: Five electronic databases were systematically searched for relevant papers published up to January 2025. Randomized controlled trials (RCTs) that investigated the combination treatment of VR and MT for patients with stroke were included. A gray literature search was also conducted. The risk of bias and the certainty of the evidence were assessed using the Cochrane Collaboration’s tool and the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) guidelines, respectively.

RESULTS: A total of 475 patients from 14 RCTs were included, of which 7 were eligible for meta-analysis. Meta-analysis revealed significant improvements in upper extremity (UE) motor function and hand dexterity, as evidenced by the Fugl-Meyer Assessment-Upper Extremity (FMA-UE; mean difference, MD 3.50, 95% CI 1.47 to 5.53; P=.<001), the manual function test (MD 2.15, 95% CI 1.22 to 3.09; P<.001), and the Box and Block Test (MD 1.09, 95% CI 0.14 to 2.05; P=.03). Subgroup analyses based on disease duration (>6 months or not) revealed significant differences in the FMA-UE outcome. However, the pooled FMA-UE improvement did not consistently exceed the established minimal clinically important difference (4.25-7.25), indicating that while statistically significant, the clinical significance of the observed effect remains uncertain. Narrative evidence also suggested potential benefits for lower extremity function, dynamic balance, and quality of life, though these findings were not meta-analyzed and should be interpreted with caution.

CONCLUSIONS: Moderate-quality evidence supports combined VR and MT as a promising nonpharmacological intervention to improve upper extremity function and hand dexterity in stroke rehabilitation. While the intervention demonstrates statistically significant effects, it does not reach the minimum clinically important difference for the FMA-UE outcome. Preliminary descriptive evidence indicates possible advantages for lower extremity function, balance, and quality of life.

PMID:41071983 | DOI:10.2196/73142

J Bras Nefrol. 2026 Jan-Mar;48(1):e20250010. doi: 10.1590/2175-8239-JBN-2025-0010en.

ABSTRACT

OBJECTIVE: To conduct a systematic review and meta-analysis to evaluate the effectiveness of artificial intelligence (AI) models aimed at identify Wilms tumor on computed tomography (CT) scans.

METHODS: A search was carried out across MEDLINE, Embase, Web of Science, and Cochrane databases in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines. Diagnostic studies using AI-based CT to diagnose Wilms tumor were included if they reported sensitivity, specificity, and AUC. Studies with incomplete data or lacking full-text availability were excluded. Statistical analysis was conducted in R (v4.3.3) using a random-effects model, with logit transformation for univariate analysis and SROC curve construction for bivariate analysis. Heterogeneity (I2 ≥ 40%) was assessed and explored via sensitivity analysis.

RESULTS: The analysis included four studies (three studies from China and one from Turkey) with 177 patients with Wilms tumors and 62 without Wilms tumors. The combined analysis of all models demonstrated a sensitivity of 63.9% (95% CI: 0.533-0.734), a specificity of 82.8% (95% CI: 0.716-0.902), and an area under the curve (AUC) of 0.831 (95% CI: 0.607-0.883).

CONCLUSION: This study demonstrated that AI models exhibit moderate sensitivity and high specificity to identify Wilms tumor on CT scans, with an overall AUC of 0.831. These results underscore the promise of AI as a supportive tool in diagnostic imaging, although the limited number of studies and notable methodological heterogeneity warrant cautious interpretation and reinforce the need for validation in larger, more representative populations.

PMID:41071978 | DOI:10.1590/2175-8239-JBN-2025-0010en

JMIR Res Protoc. 2025 Oct 10;14:e64066. doi: 10.2196/64066.

ABSTRACT

BACKGROUND: Frozen shoulder is an ailment that denotes dysfunction in the arm characterized by limited range of motion accompanied by pain. The prevalence of adhesive capsulitis is 3% to 5% in the general population and up to 20% in those with diabetes. Physiotherapy, analgesics, corticosteroids, and surgical capsulotomy are common forms of treatment. Administering oil through the nasal route (or nasya karma) is mentioned in the Ayurvedic scriptures for managing neck and clavicle disorders. Thermal microcautery (or agni karma) is a parasurgical procedure for treating related pathologies of bodily humors (vata and kapha). This study will aim to compare the efficacy of honey thermal microcautery, standard physiotherapy, and Sida cordifolia oil via nasal administration in the treatment of frozen shoulder to determine which provided the most relief.

OBJECTIVE: The primary aim is to evaluate the efficacy of honey thermal microcautery, standard physiotherapy, and S cordifolia oil via nasal administration using the visual analogue scale, range of motion, the Shoulder Pain and Disability Index, and the McGill Pain Questionnaire and compare these interventions. The secondary objective is to assess sustained relief in all 3 groups.

METHODS: We will enroll 60 patients, 20 in each group, for this single-blind assessor-controlled study. Group A will receive Ayurvedic treatment, that is, thermal microcautery using honey for 2 days (the first and seventh) and placebo capsules (twice per day) for 7 days, group B will receive standard physiotherapy and placebo capsules (twice per day) for 7 days, and group C will be given S cordifolia oil via nasal administration with 8 drops in each nostril and placebo capsules (twice per day) for 7 days. The evaluation parameters are pain (visual analogue scale), range of motion measured using a goniometer, the Shoulder Pain and Disability Index, and the McGill Pain Questionnaire. On September 18, 2023, approval was received from the Institutional Ethics Committee of Mahatma Gandhi Ayurved College Hospital and Research Centre (MGACHRC/IEC/Sep-2023/740).

RESULTS: The results will be subjected to statistical analysis using appropriate methods such as ANOVA. If the ANOVA shows significance, post hoc tests (eg, the Tukey honestly significant difference test) will identify group differences, with P<.05 considered significant. As of January 2025, a total of 16 patients have been recruited, divided into 3 groups, and the final results are expected to be published in November 2025.

CONCLUSIONS: This comparative study seeks to establish the most effective treatment among honey thermal microcautery, standard physiotherapy, and S cordifolia oil nasya for managing frozen shoulder, potentially offering new integrative approaches to treating this condition.

PMID:41071977 | DOI:10.2196/64066

Eur Heart J Qual Care Clin Outcomes. 2025 Oct 10:qcaf122. doi: 10.1093/ehjqcco/qcaf122. Online ahead of print.

ABSTRACT

BACKGROUND: Current European Cardiovascular Disease (CVD) prevention guidelines recommend 10-year risk assessment using the SCORE2 model to identify individuals eligible for preventive treatment. Risk can be estimated using conventional risk charts or online calculators, though these methods may differ in precision and treatment classification.

METHODS AND RESULTS: Individuals without established CVD or diabetes mellitus were included from CPRD (United Kingdom, Europe’s low risk region, n=977,616) and HAPIEE (Czech Republic and Poland, high risk region and Lithuania, very high risk region, n=11,739). During median 8.4 years (IQR 5.0-10.4), 22,898 CVD events occurred. SCORE2 risk was estimated via two methods: an online calculator (unrounded SCORE2 algorithm) and risk charts from the 2021 ESC Prevention Guidelines. Predicted risks were higher with the risk charts than with the online calculator. In the low risk region, the median 10-year risk was 4.0% (IQR 2.0-6.0) with the risk charts versus 3.7% (IQR 2.3-5.8) with the calculator. In the high/very high-risk region, risk was 9.0% (IQR 5.0-15.0) and 8.4% (IQR 4.5-13.9), respectively. Chart-based risk assessment resulted in higher treatment eligibility (6.3% versus 4.0% in the low risk region; 51% versus 43% in high/very high risk region). Discrimination was higher with the online calculator: difference in C-statistic +0.010 (95%CI 0.008-0.012) in low risk region, +0.008 (95%CI 0.005-0.010) in high/very high risk region. Calibration was adequate for both approaches. Assuming a 50% relative risk reduction for preventive treatment, this corresponded to 53 vs. 46 events prevented per 1000 treated in the low-risk region and 80 vs. 74 in the high/very-high-risk region (calculator vs. risk charts).

CONCLUSION: Risk assessment using SCORE2 risk charts yields too high predicted risks and too broad treatment eligibility. By avoiding rounding of risk factors, the online calculator shows better discrimination.

PMID:41071935 | DOI:10.1093/ehjqcco/qcaf122

J Alzheimers Dis. 2025 Oct 10:13872877251384967. doi: 10.1177/13872877251384967. Online ahead of print.

ABSTRACT

BackgroundAlzheimer’s disease (AD) is a progressive neurodegenerative disorder marked by cognitive decline and memory impairment. Identifying early markers of AD is critical for timely diagnosis and intervention.ObjectiveThis study aimed to characterize the neuropsychological and pathological features of cognitively unimpaired (CU) individuals who later progressed to mild cognitive impairment (MCI) or AD, referred to as At-Risk CU. The goal was to support accurate staging and inform early therapeutic strategies.MethodsParticipants were categorized into CU, At-Risk CU, MCI, and AD groups. Data analyses focused on neuroimaging scans, neuropsychological assessments, cerebrospinal fluid (CSF) biomarkers (including Aβ_1-40/Aβ_1-42 and p-Tau/t-Tau), and APOE genotypes. Voxel-based morphometry (VBM) was employed to assess gray matter (GM) volume and white matter (WM) integrity. Statistical analyses were conducted to evaluate group differences and associations.ResultsVBM revealed progressive GM atrophy and WM disruptions across the continuum from CU to At-Risk CU, MCI, and AD, particularly in the hippocampus and adjacent regions. Neuropsychological assessments showed significant cognitive decline across stages, while dynamic changes in CSF biomarkers in At-Risk CU suggested compensatory mechanisms. The APOE ε4 allele was strongly associated with AD progression, whereas the ε2 allele demonstrated protective effects. GM volume was significantly correlated with ADAS11 and ADAS13 scores.ConclusionsThis study identifies At-Risk CU as a distinct and clinically meaningful stage in AD progression, marked by structural, cognitive, and biomarker alterations. Integrating neuropsychological assessments, neuroimaging, and CSF biomarkers may facilitate early detection and enable targeted interventions to improve outcomes for individuals at elevated risk of AD.

PMID:41071913 | DOI:10.1177/13872877251384967

Future Med Chem. 2025 Oct 10:1-8. doi: 10.1080/17568919.2025.2570969. Online ahead of print.

ABSTRACT

AIMS: To design, synthesize, and characterize N-(4-bromophenyl)-2-(substituted fluorobenzylidene)hydrazine-1-carbothioamides (II-IV) and evaluate their in vitro cytotoxicity against DLD-1 and MDA-MB-231 cells, supported by molecular docking.

MATERIALS & METHODS: Compounds were obtained by condensations of substituted fluorobenzaldehydes with N-(4-bromophenyl)hydrazinecarbothioamide and characterized by NMR, FTIR, and MS. DLD-1 and MDA-MB-231 cells were exposed to 50-1600 µg/mL for 24 h; viability was measured using a commercial colorimetric assay. Statistics used one-way ANOVA with post hoc tests. Blind docking was performed with CB-Dock2 and interactions inspected in Discovery Studio.

RESULTS: All compounds decreased viability in a concentration-dependent manner. In MDA-MB-231, Compounds I, II, and IV showed significant effects (ANOVA p < 0.001). In DLD-1, Compound IV reached p ≤ 0.01 and Compounds I-II p < 0.001; the IC₅₀ of Compound I in DLD-1 was 1383.2 µg/mL. Docking suggested favorable binding poses stabilized by hydrogen bonding and hydrophobic/halogen interactions at key residues.

CONCLUSIONS: The 4-bromophenyl thiosemicarbazone/Schiff-base scaffold exhibits measurable antiproliferative activity with substitution-dependent trends supported by docking. These findings warrant structure optimization to enhance potency and selectivity and motivate follow-up mechanistic assays. (Not a clinical trial; CONSORT not applicable.).

PMID:41070604 | DOI:10.1080/17568919.2025.2570969

Leuk Lymphoma. 2025 Oct 10:1-8. doi: 10.1080/10428194.2025.2564769. Online ahead of print.

ABSTRACT

Allo-HSCT is a potentially curative treatment for hematologic diseases, but long-term quality of life (QoL) remains a concern. Factors like GVHD, comorbidities, and post-transplant complications can impact survivorship. Understanding QoL in long-term survivors is key to improving care strategies. This observational study included allo-HSCT patients aged ≥18 years, transplanted between January 2010 and December 2015. QoL was assessed by telephone using FACT-BMT and EQ-5D-5L, along with clinical data. Statistical analyses examined associations between QoL and clinical factors. Sixty-seven long-term survivors participated (median follow-up: 7 years). The mean FACT-BMT score was 115.2/148, indicating generally good QoL. However, patients with active GVHD showed reduced physical and emotional functioning. Stem cell source also influenced specific FACT-BMT subscores. Long-term QoL after allo-HSCT is generally favorable, but physical and emotional challenges persist, especially with active GVHD. Targeted interventions and proactive management are crucial to improving overall survivorship care.

PMID:41070598 | DOI:10.1080/10428194.2025.2564769