Category: Statistics

J Saudi Heart Assoc. 2025 Aug 26;37(3):13. doi: 10.37616/2212-5043.1445. eCollection 2025.

ABSTRACT

BACKGROUND: The interventricular septum (IVS)/anterior aortic angle is typically measured at 120° in healthy individuals but is more acute in patients with left ventricular outflow tract (LVOT) narrowing, aortic valve anomalies, and discrete subaortic membrane (SAM).

OBJECTIVES: This study aimed to assess this angle in pediatric patients with abnormal aortic valves and/or LVOT obstruction and evaluate its association with SAM development.

METHODOLOGY: A prospective cohort observational study was conducted in the pediatric cardiology department at PSCC-Qassim from September 2022 to June 2023. Echocardiographic assessments were performed on pediatric patients (neonates to 14 years) with bicuspid aortic valve (BAV), with or without SAM. Patients with ventricular septal defect (VSD), atrioventricular septal defect (AVSD), or single ventricle pathology were excluded. The Aortoseptal angle was measured in the long-axis parasternal view.

RESULT: Among 319 cases, 153 served as controls with normal cardiac anatomy. The remaining 194 cases included 104 (53 %) with isolated BAV, 51 (26 %) with isolated SAM, and 11 (6 %) with BAV and SAM. The male-to-female ratio was 2.2:1. SAM was observed in 64 (33 %) cases, and significant aortic stenosis in 13 (6.7 %). Cardiac surgery was performed in SAM resection (4.1 %). The Aortoseptal angle ranged from 110° to 135° across groups, with no statistically significant differences between patients with SAM and controls. However, ROC analysis indicated that an angle <116° predicted SAM presence with 97 % sensitivity and 87 % specificity.

CONCLUSION: While a more acute Aortoseptal angle was common in SAM patients, no statistically significant differences were found. An angle <115° may warrant close monitoring for SAM development.

PMID:41036468 | PMC:PMC12483079 | DOI:10.37616/2212-5043.1445

Plast Surg (Oakv). 2025 Sep 29:22925503251379895. doi: 10.1177/22925503251379895. Online ahead of print.

ABSTRACT

Introduction: This study assesses how Canadian Plastic Surgery Residency Instagram accounts are utilized and perceived by residents, fellows, and attending physicians, and evaluates their influence on medical students’ residency program selection. Methods: This 2-part study includes: (1) a descriptive analysis of Instagram activity, content, and engagement, along with a national survey of Canadian plastic surgery residents, fellows, and attendings assessing account utility; and (2) a survey of medical students who attended the University of Toronto Plastic Surgery Residency Information Session, evaluating Instagram’s influence on residency selection. Descriptive statistics were reported. Results: Twelve of 13 Canadian Plastic Surgery Residency Programs had active Instagram accounts. Canadian Plastic Surgery Residency Instagram accounts had an average of 119 posts (SD = 94) over 5 years (SD = 2). Among surveyed residents (N = 27/77, 35%) and fellows/attendings (N = 83/328, 25%), Instagram use was reported by 93% and 81%, respectively. Resident recruitment ranked as the top goal (residents 1.75, fellows/attendings 3.17), followed by achievement highlights. Most residents (80%) and fellows/attendings (53%) felt medical students benefitted most. Preferred content included program culture (85%, 84%), resident profiles (90%, 73%), and research highlights (70%, 70%). Among medical student respondents (N = 25/112, 22%), 95% followed Canadian programs on Instagram, seeking program culture, resident profiles, and educational opportunities (all 89%). Over half (56%) said Instagram influenced their perception of a program, with all reporting a positive impact. Conclusion: Instagram is a valuable platform for Canadian Plastic Surgery Residency Programs to share insights and influence medical student decision-making.

PMID:41036453 | PMC:PMC12479458 | DOI:10.1177/22925503251379895

MedEdPORTAL. 2025 Sep 30;21:11549. doi: 10.15766/mep_2374-8265.11549. eCollection 2025.

ABSTRACT

INTRODUCTION: Despite the extensive amount of literature available on bruising and child abuse, there are few open access teaching materials on this topic.

METHODS: An interactive module on abusive bruising and cutaneous mimics was created as part of a comprehensive child maltreatment curriculum. The module was evaluated in four formats: pilot presentation to a large audience of pediatric practitioners at a CME conference; presentation to an audience of family medicine residents; individual, self-paced completion by a large cohort of medical students; and presentation by a family medicine resident to a group of colleagues, to evaluate the accessibility of presentation by a non-child abuse pediatrician. In all formats, the module took 45-60 minutes to complete. Module effectiveness was evaluated with pre- and postmodule assessments.

RESULTS: The CME conference audience (n = 137) provided favorable feedback about the content; four of 51 anonymous comments focused on areas for growth, which were used to improve the content. Among in-person resident (n = 18) and asynchronous medical student (n = 300) participants, increases in confidence were negligible but knowledge scores notably increased from pre- to postmodule, changing from a median of 25% to 100% and median of 50% to 100%, respectively. In evaluating accessibility, the presenting resident commented on increased engagement, ability to gauge the audience’s understanding, and ease of use of the script and technical guide.

DISCUSSION: This interactive, versatile module on abusive bruising and cutaneous mimics was well-received and effective at increasing short-term knowledge among medical student and physician audiences.

PMID:41036450 | PMC:PMC12479944 | DOI:10.15766/mep_2374-8265.11549

Digit Health. 2025 Sep 29;11:20552076251384233. doi: 10.1177/20552076251384233. eCollection 2025 Jan-Dec.

ABSTRACT

BACKGROUND: In recent years, potential applications of ChatGPT in medication-related practices have drawn great attention for its intuitive user interfaces, chatbot, and powerful analytical capabilities. However, whether ChatGPT can be broadly applied in clinical practice remains controversial. Early screening, monitoring, and timely treatment are crucial for improving outcomes of interstitial lung disease (ILD) in systemic autoimmune rheumatic diseases (SARDs) due to its high morbidity and mortality rate. This study aimed to evaluate the reliability, repeatability, and confidence of ChatGPT models (GPT-4, GPT-4o mini, and GPT-4o) in delivering guideline-based recommendations for the screening, monitoring, and treatment of ILD in SARD patients.

METHODS: Questions derived from the ACR/CHEST guideline for ILD patients with SARDs were used to benchmark three versions of ChatGPT (GPT-4, GPT-4o mini, and GPT-4o) across three separate attempts. The responses were recorded, and the reliability, repeatability, and confidence were analyzed with the recommendations from the guideline.

RESULTS: GPT-4 demonstrated significant variability in reliability across the three attempts (P = .007). In contrast, the other versions showed no significant differences. GPT-4 and GPT-4o mini exhibited substantial interrater agreement (Kendall’s W = 0.747 and 0.765, respectively), whereas GPT-4o demonstrated almost perfect interrater agreement (Kendall’s W = 0.816). All three versions showed statistically significant differences in high confidence ratings (confidence score of ≥ 8 on the 1-10 scale) across the three attempts (P < .01). Given the higher consistency of GPT-4o and GPT-4o mini, a further comparison was conducted between them on the third attempt. No significant difference was observed in accuracy percentages across the third attempt between GPT-4o and GPT-4o mini (P = .597). Similarly, interrater agreement across the three attempts was not significantly different for both GPT-4o and GPT-4o mini (P = .152). Furthermore, the overconfidence percentage (confidence score of ≥8 assigned to incorrect answers) was 100% (22 of 22) for GPT-4o and 22.7% (10 of 44) for GPT-4o mini, respectively (P < .01).

CONCLUSIONS: GPT-4o mini and GPT-4o demonstrated stable reliability across all three attempts, whereas GPT-4 did not. The repeatability of GPT-4o tended to perform better than GPT-4o mini, although this difference was not statistically significant. Additionally, GPT-4o exhibited a higher tendency toward overconfidence compared to GPT-4o mini. Overall, the GPT-4o models performed most effectively in managing SARD-ILD but may exhibit overconfidence in certain scenarios.

PMID:41036434 | PMC:PMC12480815 | DOI:10.1177/20552076251384233

Digit Health. 2025 Sep 29;11:20552076251382049. doi: 10.1177/20552076251382049. eCollection 2025 Jan-Dec.

ABSTRACT

BACKGROUND: Diabetes is a chronic disease affecting many people globally and is a significant health concern. Health services are focusing on managing the rising incidence of diabetes and its complications. A novel mobile health (mHealth) intervention intends to assist diabetics in managing the levels of their blood sugar and improving self-care. The study aimed to evaluate the effect of short message service (SMS) and mobile app interventions on patients’ capacity to improve hemoglobin A1c (HbA1c) levels.

METHOD: A targeted search was performed in PubMed, MEDLINE, EMBASE, the Cochrane Library, ScienceDirect, and Scopus for randomized controlled trials (RCTs) published from 2014 to 2024 that evaluated the effects of mobile apps and SMS-based self-care interventions on individuals with poorly managed diabetes.

RESULT: A rigorous review identified nineteen studies for analysis. Fifteen of these studies showed a statistically significant reduction in HbA1c levels in the intervention group, compared to baseline measurements. In contrast, control groups did not exhibit the same level of reduction, resulting in a significant difference between intervention and control groups over time. This suggests that the interventions were effective in lowering HbA1c levels.

CONCLUSION: Improving glycemic levels in inadequately managed diabetes is crucial. Better blood sugar management enhances patient well-being and lowers healthcare costs, making targeted interventions essential for improved outcomes and healthcare efficiency. When developing support services and educational programs for diabetes self-management, considering value-based care and public health models, it is important for organizations, diabetes educators, legislators, and funders to carefully consider these solutions.

PMID:41036432 | PMC:PMC12480833 | DOI:10.1177/20552076251382049

Mayo Clin Proc Innov Qual Outcomes. 2025 Sep 19;9(5):100663. doi: 10.1016/j.mayocpiqo.2025.100663. eCollection 2025 Oct.

ABSTRACT

OBJECTIVE: To develop predictive models that are compatible with vital signs monitoring devices to identify patients at risk of clinical deterioration, defined as requiring a rapid response team intervention or an unplanned intensive care unit transfer.

PATIENTS AND METHODS: Targeted vital signs from 227,858 inpatients admitted to general care or telemetry beds at a multihospital health care institution between January 1, 2019, and July 31, 2023, were selected. After filtering for high-quality data, 30,118 patients were used to train a Light Gradient Boosting Machine, and 30,095 were reserved for blind validation. We developed a machine learning model designed to minimize false positives while maintaining clinical relevance in identifying low-prevalence clinical deterioration events.

RESULTS: At a sensitivity of 73.4% (95% CI, 72.2%-74.4%), the model achieved a positive predictive value (PPV) of 30.4% (95% CI, 29.6%-31.3%), with a C-statistic of 0.874 (95% CI, 0.867-0.881), alert rate of 0.170 (95% CI, 0.167-0.173) per patient per day, and normalized alert rate of 2.41 (95% CI, 2.31-2.51). Stratified analysis by hospital revealed that PPV was highest at the Rochester site, reaching 54.9% (95% CI, 52.9%-57.0%) and outperforming the EPIC deterioration index by 46% or a factor of 6 (7.57%).

CONCLUSION: Achieving a high PPV is crucial because it ensures a larger proportion of alerts are true positives, reducing the burden of false alarms. The considerable improvement in results comes from the novel 2-window feature extraction method. This technique enables the model to capture both long-term trends and recent changes in patient status, enhancing predictive performance.

PMID:41036430 | PMC:PMC12482306 | DOI:10.1016/j.mayocpiqo.2025.100663

SoftwareX. 2025 Sep;31:102288. doi: 10.1016/j.softx.2025.102288. Epub 2025 Aug 7.

ABSTRACT

Stepped wedge cluster randomized trials (SWCRTs) have become increasingly popular across various disciplines, particularly in public health and clinical research, as they allow evaluations of interventions rolled out sequentially across clusters. SWCRTsimulator is a user-friendly, web-based RShiny application designed to facilitate sample size and statistical power estimation for an interval-censored time-to-event outcome in a SWCRT. Leveraging Monte Carlo simulations, the platform accommodates various study design features, including heterogeneity in intervention effect across different clusters, to provide a more accurate and reliable statistical approach to sample size and power estimates as compared to the approximate methods based on study design features when a closed-form solution is not feasible. SWCRTsimulator provides customizable visualizations for simulation results. We also illustrate the practical application of this platform using the Sankofa 2 trial, an active multi-clinic SWCRT of a pediatric HIV disclosure intervention in Ghana, underscoring the importance of accounting for real-world complexities in the design and analysis of such trials.

PMID:41036414 | PMC:PMC12483528 | DOI:10.1016/j.softx.2025.102288

BMC Psychiatry. 2025 Oct 1;25(1):908. doi: 10.1186/s12888-025-07391-1.

ABSTRACT

BACKGROUND: Motivational Interviewing (MI) is a counseling approach that promotes behavior change by eliciting “change talk” and minimizing “sustain talk.” Traditional methods for assessing MI quality, such as manual coding, are labor-intensive, subjective, and difficult to scale. This study introduces an automated framework integrating large language models (LLMs) and Hidden Markov Models (HMMs) for evaluation of MI session quality.

AIMS: This study evaluates the effectiveness of an LLM-HMM framework in predicting MI session quality and examines motivational state transitions in high- and low-quality sessions.

METHOD: A dataset of 40 MI sessions was analyzed. Client utterances were classified and numerically scored by an LLM based on their intention toward or away from change. With HMMs, we used these scores to examine the motivational state transitions across each session. Differences between high- and low-quality sessions were quantified by comparing transition matrices using Frobenius norms. Statistical significance was assessed via a permutation test. Predictive performance was evaluated using logistic regression with leave-one-out cross-validation (LOOCV), where transition matrix elements served as independent variables and interview quality as the dependent variable.

RESULTS: High-quality MI sessions exhibited fluid transitions between motivational states, whereas low-quality sessions showed persistence in resistance-oriented states. A statistically significant difference in transition matrices was observed between session groups (p < 0.001). The framework achieved a mean LOOCV accuracy of 0.80, demonstrating strong predictive performance in identifying MI session quality.

CONCLUSIONS: This study presents a scalable, objective alternative to manual MI evaluation. Future applications may include real-time therapist support, training, and prognosis prediction, pending further validation on field-collected data.

PMID:41034852 | DOI:10.1186/s12888-025-07391-1

BMC Musculoskelet Disord. 2025 Oct 1;26(1):899. doi: 10.1186/s12891-025-09034-8.

ABSTRACT

BACKGROUND: Idiopathic scoliosis is a three-dimensional spinal deformity that typically develops during childhood or adolescence but may affect individuals across the lifespan. Regular monitoring is often necessary to detect progression and assess treatment effectiveness. Radiography remains the clinical gold standard; however, repeated ionizing radiation exposure is associated with increased cancer risks, highlighting the need for reliable, non-invasive, and radiation-free assessment methods. This systematic review and meta-analysis evaluated the diagnostic accuracy and criterion validity of emerging radiation-free scoliosis monitoring techniques compared to radiographic standards.

METHODS: A comprehensive literature search across six databases (Cochrane, EMBASE, IEEE Xplore, PUBMED, Scopus, Web of Science) identified 56 eligible studies involving 4,774 patients diagnosed with idiopathic scoliosis (median number of patients per study: 38; range: 5 to 952, mean patient age: 15.2 years, female-to-male ratio: 3:1). Criterion validity was assessed by pooling Pearson correlation coefficients between radiographic and non-ionizing measurements. Measurement accuracy was assessed by pooling their mean absolute differences in Cobb angles. Additionally, sensitivity and specificity for detecting deformity progression were assessed. Statistical analyses employed multilevel linear mixed-effects models, introducing moderators to explain study heterogeneity.

RESULTS: Ultrasonography demonstrated the highest overall validity, consistently correlating strongly (r≈0.9) with radiographic Cobb angles. Surface topography also showed robust correlation (r > 0.8), although evidence remains insufficient for patients with higher body mass indices or more severe spinal curvatures for both methods. Magnetic resonance imaging exhibited a very strong correlation (r = 0.93) with radiographic measurements; however, correlation varied significantly depending on patient positioning. Upright MRI provided more consistent results compared to supine positioning.

CONCLUSIONS: Ultrasonography and surface topography represent promising radiation-free alternatives that could significantly reduce radiographic assessment frequency, minimizing radiation exposure, particularly in suitable patient groups. While MRI also demonstrates excellent validity, its broader clinical applicability remains constrained by substantial costs, limited availability, and extended examination durations. Although these non-ionizing modalities are not yet viable replacements for routine radiography, their demonstrated validity and accuracy supports their potential as complementary technologies, particularly for screening or supplementary monitoring of scoliosis.

PMID:41034849 | DOI:10.1186/s12891-025-09034-8

BMC Geriatr. 2025 Oct 1;25(1):753. doi: 10.1186/s12877-025-06361-2.

ABSTRACT

BACKGROUND: The SUGAR Handshake is a pharmacist-led educational intervention to prevent hypoglycaemia in elderly people with type 2 diabetes mellitus (T2DM). A process evaluation was conducted alongside the ROSE-ADAM pragmatic randomized controlled trial (RCT) to assess the implementation of the intervention and study procedures, explore mechanisms of impact, and examine future scalability.

METHODS: This mixed-methods process evaluation was nested within a single-centre RCT conducted at outpatient clinics in a Jordanian hospital. Routine monitoring quantitative data assessed adherence to the intervention components and study activities, and estimated reach. Qualitative data, collected through semi-structured interviews with 12 purposively selected participants on Days 45 and 90 of enrolment, captured experiences with the intervention and usual care. Thematic analysis was used for qualitative data; descriptive statistics and inferential tests were applied to quantitative data.

RESULTS: The intervention was well implemented: 104 of 106 participants (98.11%) continued the full intervention, with a 100% reach to those enrolled in the trial. Participants showed high adherence to study activities (mean ± SD: 88.07 ± 9.33 documented days on diaries; 77.97 ± 18.87 fasting blood glucose measurements). Intervention reach was 100%. Participants described the intervention as informative, easy to follow, and helpful in avoiding hypoglycaemia and the side-effects of antidiabetic medications. Key facilitators included trust in pharmacists, altruism, and social support. Reported barriers were people’s health status, age-related conditions, and stress.

CONCLUSIONS: This process evaluation highlights the SUGAR Handshake’s potential for broader implementation and scale-up. By addressing identified barriers, future educational interventions may enhance adherence, improve patient outcomes, and advance hypoglycaemia management in diabetes care.

TRIAL REGISTRATION: Clinicaltrials.gov (NCT04081766), registration date 4,920,219.

PMID:41034834 | DOI:10.1186/s12877-025-06361-2