Category: Statistics

J Neurosurg Pediatr. 2026 Jan 30:1-6. doi: 10.3171/2025.9.PEDS25140. Online ahead of print.

ABSTRACT

OBJECTIVE: Up to 30% of children with focal epilepsy have drug-resistant epilepsy and may be candidates for epilepsy surgery. Intraoperative electrocorticography (iECoG) is a method to acutely delineate the epileptogenic zone during epilepsy resections, but its effectiveness is debated. The authors assessed the association between iECoG findings and seizure outcomes in pediatric epilepsy patients undergoing resective epilepsy surgery.

METHODS: The authors conducted a retrospective cohort analysis of 115 patients at UPMC Children’s Hospital of Pittsburgh who underwent resective epilepsy surgery for focal epilepsy. They assigned patients to subgroups based on the extent of resection in concordance with iECoG findings. Patients in group A had postresection iECoG without epileptiform activity at the margins. Patients in group B had persistent epileptiform activity on postresection iECoG and underwent an extended resection. Patients in group C had persistent epileptiform activity on postresection iECoG, but further resection was contraindicated due to involvement of eloquent cortex.

RESULTS: The primary outcome was seizure freedom at 1 year (Engel class I), which was achieved in 64% (n = 74) of all patients; however, there was no statistically significant difference in seizure freedom or antiseizure medication reduction between the three groups. Notably, there was also no significant relationship between patient group and transient or long-term postoperative complications, such as unexpected postoperative deficits, infection, or symptomatic intracranial hemorrhage.

CONCLUSIONS: The authors found no statistically significant difference between groups A, B, and C regarding postoperative seizure reduction and freedom. While iECoG provides a biomarker for the purposes of resection, in this cohort, iECoG findings were not associated with postoperative seizure freedom.

PMID:41616320 | DOI:10.3171/2025.9.PEDS25140

JMIR Serious Games. 2026 Jan 30;14:e86290. doi: 10.2196/86290.

ABSTRACT

BACKGROUND: In the context of global aging, cognitive decline among older adults has become a prevalent issue, significantly impacting their daily lives. Serious games have demonstrated potential in enhancing cognitive abilities in this population. However, most existing serious games designed for older adults rely heavily on visual interfaces, which are often potentially detrimental for those with pre-existing visual impairments.

OBJECTIVE: This study had two primary objectives: (1) to design a theoretical prototype for a haptic-driven serious game for older adults based on the Design-Play-Experience (DPE) framework, aiming to enhance cognitive abilities, including attention, logical reasoning, and decision-making while simultaneously mitigating challenges associated with visual impairment, and (2) to conduct a pilot study evaluating the prototype’s usability, accessibility, and user experience within the target population.

METHODS: We used a cross-sectional, mixed methods pilot study with a single-group observational design, comprising a theoretical design and a pilot user study. First, the DPE framework was systematically applied to develop a game prototype by integrating haptic feedback technology (using built-in smartphone vibration motors) across its 3 core dimensions: design (haptic symbol system, accessible interface), play (dynamic difficulty adjustment), and experience (emotional engagement). Subsequently, a pilot study was conducted with 10 older adults recruited via convenience sampling (mean age 62.9, SD 3.35 years; 5 male, 5 female; all with self-reported mild visual impairments, such as presbyopia). Following interaction with the prototype, data were collected remotely using the System Usability Scale (SUS) and semistructured interviews administered via videoconferencing. Quantitative data from the SUS were analyzed using descriptive statistics, while qualitative data from the interviews were processed using thematic analysis.

RESULTS: Pilot user studies showed that the game prototype had good usability, with an average SUS score of 89.5 (SD 2.72; 95% CI 87.6-91.4), which is considered “excellent.” Thematic analysis of the interviews revealed three significant themes. The first theme was intuitive haptic feedback, which reflected that participants were able to quickly grasp and value the vibrational cues used to identify cards. The second theme was based on reduced eye strain, in which the combination of large fonts, high-contrast interfaces, and haptic feedback was praised for its effectiveness in relieving eye strain. The third theme was simplicity, where the simplified card game mechanics were considered both fun and challenging.

CONCLUSIONS: This study developed and validated a haptic, serious game for older adults. Its innovation lies in the systematic application of the DPE framework to achieve “haptic substitution for vision,” which differs from previous research that focused on general immersive experiences. The main contribution of this study is providing a reusable design blueprint for creating easy-to-use cognitive training tools. These findings have practical implications in the real world, providing a feasible approach for deploying low visual load interventions in communities and care facilities.

PMID:41616308 | DOI:10.2196/86290

J Med Internet Res. 2026 Jan 30;28:e71363. doi: 10.2196/71363.

ABSTRACT

BACKGROUND: Mobile health (mHealth) apps target diverse health behaviors, but engagement may vary by purpose.

OBJECTIVE: This study examined the prevalence, usage patterns, and user characteristics of mHealth apps among Czech adults with internet access, focusing on sociodemographics, digital knowledge and use, and health indicators predicting wellness- and illness-related app use.

METHODS: Overall, 4775 Czech adults (2365/4775, 49.53% women) aged 18-95 (mean 45.37, SD 16.40) years completed an online survey. Sociodemographic factors included age, gender, education, and income. Digital knowledge and use were measured using the eHealth Literacy Scale and the passive/active use of social networking sites (SNS) for health information. Health indicators covered symptom severity, physical activity, BMI, and eating disorder-related risk propensity (body dissatisfaction, dietary restraint, and weight/shape overvaluation). Participants reported app use for sports, number of steps, nutrition, vitals, sleep, diagnosed conditions, reproductive health, diagnosis assistance, mood and mental well-being, and emergency care guidance. Multivariate hierarchical binary logistic regression analysis identified characteristics of app users. Exploratory structural equation modeling (ESEM) clustered apps into “promoting wellness” and “managing illness” and examined the predictors of frequency of use.

RESULTS: Of 4440 respondents, 2172 (48.92%) used mHealth apps. Users were younger (odds ratio [OR] 0.98, 95% CI 0.98-0.99, P<.001), had a monthly income more than 50,000 CZK (1 CZK=US $0.048; vs ≤20,000 CZK: OR 0.54, 95% CI 0.41-0.7, P<.001; 20,001-35,000 CZK: OR 0.78, 95% CI 0.65-0.93, P=.006; 35,001-50,000 CZK: OR 0.83, 95% CI 0.7-0.99, P=.03), were more eHealth literate (OR 1.17, 95% CI 1.06-1.3, P=.003), used SNS passively for health information (OR 1.35, 95% CI 1.21-1.51, P<.001), and had higher eating disorder risk (OR 1.18, 95% CI 1.12-1.25, P<.001) and physical activity (OR 1.18, 95% CI 1.13-1.23, P<.001) than nonusers. Step-counting apps were most common; 65.99% (1430/2167) used them daily or several times a day, followed by apps for sleep (691/2163, 31.95%), vitals (611/2165, 28.22%), and sports (407/2158, 18.86%). ESEM confirmed a 2-factor structure (“promoting wellness” and “managing illness”; χ²₂₆=71.9, comparative fit index=0.99, Tucker-Lewis index=0.99, root-mean-square error of approximation=0.03, and standardized root-mean-square residual=0.03). Frequent use of wellness apps was associated with younger age (standardized β=-0.22, P<.001), higher eHealth literacy (standardized β=0.10, P<.001), and physical activity (standardized β=0.15, P<.001). Illness-management app use was associated with active use of SNS for health information (standardized β=0.62, P<.001) and eating disorder risk (standardized β=0.11, P<.001). Digital knowledge, digital use, and health indicators mediated the association between age and mHealth app use.

CONCLUSIONS: mHealth app engagement reflects broader social, digital, and psychological inequalities rather than individual preferences alone. Encouraging digital inclusion and addressing body image- and diet-related use may help ensure that mHealth technologies do not exacerbate existing health inequalities across age and user groups.

PMID:41616306 | DOI:10.2196/71363

JMIR Mhealth Uhealth. 2026 Jan 30;14:e68737. doi: 10.2196/68737.

ABSTRACT

BACKGROUND: Mobile apps are being increasingly used to foster healthy lifestyles. There is a growing need for clear, standardized guidelines to help users select safe and effective health apps.

OBJECTIVE: Our study aimed to highlight the importance of establishing a structured framework for quality evaluation in mobile health (mHealth) through a case study of mobile apps promoting healthy eating.

METHODS: We conducted a systematic review of apps promoting healthy eating that had already been evaluated by one or more of 28 recognized health app certification bodies. Three rounds of app evaluations were conducted by experts in nutrition and behavior change. The first two rounds focused on the quality of the content of the recommendations and were performed pairwise using the Quality Evaluation Scoring Tool (QUEST), which has not been previously used by the certification bodies. In addition, in the second and third rounds, each reviewer answered the question “How probable is it that you would recommend this app?” using a subjective scale score from 0 to 10. In the third round, this score was weighed by usability (30%), content quality (40%), and promotion of behavior change (30%). Discussions were held to resolve scoring discrepancies and to identify the top-quality apps. We also assessed correlations among QUEST, Google Play Store, and certification body scores.

RESULTS: Of the 41 apps identified by five certification bodies, 19 (46.3%) met the inclusion criteria and were examined. Only 16 (84.2%) of these remained accessible for the second round. Eight of these surpassed 20 points (out of a maximum of 28) on the QUEST scale and were evaluated by all six experts in the third round, and the top 5 (62.5%) apps were selected. No correlations were found among QUEST, Google Play Store, and certification body scores.

CONCLUSIONS: Despite numerous evaluations by various certification bodies, only 5 (12.2%) of the 41 apps met the quality standards set by our experts. Our results mark the importance of rigorous, transparent, and standardized app evaluation processes to guide users toward making informed decisions about health apps. Guidelines for developers for the design of evidence-based, unbiased, high-quality apps, as well as technological solutions for real-time monitoring of the health apps, would address these challenges and improve reliability.

PMID:41616297 | DOI:10.2196/68737

JMIR Dermatol. 2026 Jan 30;9:e83922. doi: 10.2196/83922.

ABSTRACT

In this analysis of dermatology e-consults at a large academic health system, advanced practice providers had nearly threefold higher conversion rates to in-person visits compared to board-certified dermatologists, with potential implications for access and resource utilization.

PMID:41616275 | DOI:10.2196/83922

J Am Coll Surg. 2026 Jan 30. doi: 10.1097/XCS.0000000000001814. Online ahead of print.

ABSTRACT

BACKGROUND: Robotic surgery benefits include a binocular vision, increased dexterity, and adjustable hand control speed. We hypothesized perforation rate of robotic Heller myotomy (RH) was lower than laparoscopic Heller myotomy (LH).

STUDY DESIGN: A retrospective cohort study of a prospectively maintained database of 135 patients diagnosed with achalasia or esophagogastric junction outlet obstruction who underwent Heller myotomy by a single surgeon were identified for inclusion. After exclusions 107 patients were analyzed. Primary outcome was intraoperative perforation rate. Secondary outcomes were length of stay, short and long-term GERD Health Related Quality of Life (GERD-HRQL), dysphagia and Eckardt scores. Results are expressed mean + SD and statistical analysis performed with GraphPad Prism (10.4.2).

RESULTS: RH had a lower rate of intraoperative perforation (n=0), compared to LH (n=3, 13.6%) (p<0.01). The median length of stay was shorter for the RH group 1 day verses 2 days for LH (p<0.01). RH and LH significantly improved both GERD-HRQL and Eckardt scores in short term and long-term follow-up. Long term success (Eckardt score <3) was achieved in 88% of LH and in RH (p=0.03).

CONCLUSIONS: Robotic surgery allows for a safer myotomy with a significant reduction in intraoperative perforation rate and in LOS. Robotic surgery enhanced the surgeon’s performance of an extended myotomy resulting in long term success of RH. RH has decreased complication rates and is superior to LH and is our technique of choice.

PMID:41615705 | DOI:10.1097/XCS.0000000000001814

Rheumatology (Oxford). 2026 Jan 30:keag053. doi: 10.1093/rheumatology/keag053. Online ahead of print.

ABSTRACT

OBJECTIVES: The objective of the study was to explore left atrial (LA) strain, a quantitative index of left ventricular (LV) diastolic function, in risk stratifying patients with systemic sclerosis-related pulmonary hypertension (SSc-PH).

METHODS: This was an exploratory, retrospective single-centre study of 124 patients with SSc-PH confirmed on right heart catheterization. We quantified and clustered the three components of LA global longitudinal strain (GLS): 1) Reservoir (systole); 2) Conduit (early diastole); and 3) Contractile (late diastole) using echocardiograms closest to timing of right heart catheterization. We applied both the Kaplan-Meier method and a Cox proportional hazards model to determine associations with our primary outcome of all-cause mortality.

RESULTS: Using K-means clustering, we divided our cohort into three clusters: Cluster 1 (N = 40), Cluster 2 (N = 34), and Cluster 3 (N = 50). Compared with Cluster 1, Cluster 2 had the lowest median LA conduit strain, and Cluster 3 exhibited the lowest median LA contractile strain. There was a statistically significant difference in survival between clusters (log-rank p= 0.005). Median survival was 122.4 months, 67.9 months, and 48.4 months for Cluster 1, Cluster 2, and Cluster 3, respectively. Compared with those in Cluster 1, patients in Cluster 2 and Cluster 3 had adjusted HRs of 1.46 (95% CI: 0.71, 2.97) and 2.57 (95% CI: 1.32, 5.02) for all-cause mortality, respectively.

CONCLUSION: Of the three LA GLS clusters, Cluster 3 had the shortest median survival. LA GLS may provide further risk stratification of patients with SSc-PH.

PMID:41615697 | DOI:10.1093/rheumatology/keag053

JAMA Health Forum. 2026 Jan 2;7(1):e256442. doi: 10.1001/jamahealthforum.2025.6442.

ABSTRACT

IMPORTANCE: Firearm suicides constitute a crisis in the US, accounting for more than half (55.4%) of all suicide deaths in 2023. Extreme Risk Protection Orders (ERPOs; ie, red flag laws) authorize temporary firearm removal from individuals deemed at high risk of harming themselves or others. While ERPOs are designed to reduce firearm-related suicides, whether they result in a net reduction in suicide deaths or shift firearm suicides to suicides by other methods remains an important but unresolved issue in determining their effectiveness.

OBJECTIVE: To determine the association of ERPOs with firearm suicides and nonfirearm suicides in states with sufficient postpolicy data and no confounding firearm legislation that may bias findings on ERPO outcomes.

DESIGN, SETTING, AND PARTICIPANTS: In this cohort study, 2-way difference-in-differences event study analyses were conducted using county-level data from 2012 to 2022. All states that passed ERPO laws alone, with no other new firearm laws, from 2018 to 2020, and had at least 1 year post-ERPO laws during which no new firearm laws were passed were investigated. All states that had no existing ERPO laws and passed no new firearm legislation from 2016 to 2022 were used for comparison. The model accounted for staggered treatment timing, treatment heterogeneity, and key methodological assumptions. Data were analyzed between February 6 and October 9, 2025.

EXPOSURE: State-level ERPO law passage.

MAIN OUTCOMES AND MEASURES: County-level annual firearm suicides and nonfirearm suicides per 100 000 population, derived from Centers for Disease Control and Prevention Wide-Ranging Online Data for Epidemiologic Research.

RESULTS: This study examined county-level data from 4 states passing ERPO laws alone (Massachusetts, New Jersey, New Mexico, and Rhode Island) compared with 8 that did not (Alabama, Alaska, Michigan, Minnesota, Nebraska, North Carolina, Pennsylvania, and South Carolina). ERPO passage was associated with a mean reduction of 3.79 firearm suicides per 100 000 population after 1 year (95% CI, -6.74 to -0.83; P = .01), equivalent to an estimated 675 suicides. With regard to nonfirearm suicides, no association was found in the year ERPO laws were passed (0.41; 95% CI, -1.21 to 1.94; P = .60) or in the next year (-2.45; 95% CI, -6.84 to 1.93; P = .27).

CONCLUSIONS AND RELEVANCE: In this cohort study, ERPO laws in Massachusetts, New Jersey, New Mexico, and Rhode Island were associated with substantial reductions in firearm suicides, with no evidence of substitution with nonfirearm methods. These findings support ERPOs as targeted public health interventions to reduce firearm suicides without increasing suicides by other methods.

PMID:41615664 | DOI:10.1001/jamahealthforum.2025.6442

Ann Biomed Eng. 2026 Jan 30. doi: 10.1007/s10439-025-03970-1. Online ahead of print.

ABSTRACT

PURPOSE: To establish an automated, landmark-based patellar coordinate system for standardized alignment, develop a patellar statistical shape model (SSM), and quantify 3D morphological variations associated with patellar dislocation (PD).

METHODS: Patellar surface models were reconstructed from CT/MRI scans of 54 participants (33 PD, 21 controls). An automated coordinate system was established and quantitatively validated. Demographic/morphometric risk factors were assessed using logistic regression. An SSM was built for the entire cohort, and principal component analysis (PCA) was used to extract major 3D shape modes. Between-group differences in PC scores were evaluated with multiple-testing control and covariate adjustment. A logistic regression classifier based on shape modes and demographics was evaluated using stratified 10-fold cross-validation.

RESULTS: The automated coordinate system showed high repeatability. Patellar linear dimensions and centroid size did not differ between groups and were not independent predictors. Two robust shape modes differentiated PD from controls: PC4 (thickness/facet morphology) and PC7 (facet-edge morphology). A cross-validated classifier showed good in-cohort discrimination (mean AUC ≈ 0.91).

CONCLUSION: In this cohort, PD was associated with localized 3D articular-surface shape patterns, characterized by a prominent medial facet, a flattened posterolateral facet, and accentuated facet margins, without corresponding differences in linear dimensions. The automated coordinate system and SSM provide a reproducible approach for quantitative patellar phenotyping. These shape modes may deepen understanding of PD pathomechanics and provide a quantitative basis for future, externally validated risk modeling in diverse populations.

PMID:41615643 | DOI:10.1007/s10439-025-03970-1

J Imaging Inform Med. 2026 Jan 30. doi: 10.1007/s10278-026-01843-0. Online ahead of print.

ABSTRACT

Otosclerosis is a disease affecting the middle and inner ear, characterized by abnormal bone remodeling that leads to stapes fixation and progressive hearing loss. Although high-resolution computed tomography (HRCT) is the standard imaging modality for diagnosis, its sensitivity is limited, with a high false-negative rate (FNR). This study investigates the use of radiomics and machine learning (ML) to improve diagnostic accuracy. HRCT scans from 99 subjects (48 otosclerosis, 51 controls) were analyzed, focusing on the stapes, antefenestral region (AF), and oval window (OW). From each scan, 6048 radiomic features were extracted and reduced to 1317 through feature selection. Statistical analyses and ML modeling were performed using the selected features. Sixty-seven biomarkers showed significant differences between cases and controls, primarily in the AF (56) and stapes (11); none were found in the OW. Both the AF and stapes exhibited increased heterogeneity in otosclerosis, reflecting the bone remodeling process. A reduction in the stapes’ major axis was also observed, possibly related to torsional deformation. Image transformation filters enhanced disease visibility. Among several ML classifiers tested, L2-regularized logistic regression performed best, achieving an AUC of 0.90 ± 0.06, thereby enhancing the diagnostic accuracy reported in some studies for radiologists. Hierarchical clustering of the most predictive features further confirmed their strong discriminative power. Our findings highlight the potential of radiomics and ML to standardize otosclerosis diagnosis, reduce FNR, and support surgical decision-making. Future studies should validate these results using larger cohorts and advanced imaging technologies such as Photon-Counting CT.

PMID:41615634 | DOI:10.1007/s10278-026-01843-0