Tag: statistics

Int J Pediatr Otorhinolaryngol. 2026 Jul 8;207:112928. doi: 10.1016/j.ijporl.2026.112928. Online ahead of print.

ABSTRACT

BACKGROUND: Theory of mind refers to the ability to attribute mental states to oneself and others and is foundational for effective social interaction. Children with hearing impairments often experience delays in theory of mind development, potentially due to limited access to language-based communication. While cochlear implants (CIs) and hearing aids (HAs) improve auditory access, the extent to which theory of mind skills can be enhanced through targeted intervention remains underexplored-particularly in Persian-speaking populations.

OBJECTIVE: To evaluate the effectiveness of a structured theory of mind intervention in improving theory of mind skills, comprehension of mental verbs, and mean length of utterance in Persian-speaking children aged 5-7 years with hearing impairments using CIs or HAs.

METHODS: A randomized controlled trial was conducted with 60 children (n = 15 per group), stratified into four groups: CI-Intervention, CI-Control, HA-Intervention, and HA-Control. The 8-week intervention (16 sessions) was adapted from existing theory of mind training programs and delivered by trained facilitators in rehabilitation centers across Kerman, Iran. Primary outcomes were theory of mind skills assessed using a validated Persian version of the theory of mind. Secondary outcomes included comprehension of mental verbs and mean length of utterance. Assessments were conducted at baseline, mid-intervention, post-intervention, and one-month follow-up. Repeated-measures ANOVA and post hoc tests were used for data analysis.

RESULTS: Both intervention groups demonstrated significant improvements in theory of mind performance across all three levels (p < 0.001), with moderate to large effect sizes (0.58-0.75). Comprehension of mental verbs significantly improved in the CI-intervention group post-intervention (p = 0.03). While mean length of utterance increased over time in both intervention groups, no statistically significant difference was observed between groups post-intervention. Children with cochlear implants consistently outperformed those using hearing aids across multiple outcome measures. Gains in theory of mind and mental verb comprehension were maintained at one-month follow-up, though some attenuation was observed.

CONCLUSION: Structured theory of mind intervention is effective in enhancing theory of mind skills and mental verb comprehension in Persian-speaking children with hearing impairments, particularly those using cochlear implants. However, the limited impact on MLU and the partial maintenance of gains at follow-up suggest that sustained and linguistically enriched interventions may be necessary to consolidate and generalize improvements.

TRIAL REGISTRATION: IRCT20230827059274N1.

PMID:42424679 | DOI:10.1016/j.ijporl.2026.112928

Clinics (Sao Paulo). 2026 Jul 9;81:101034. doi: 10.1016/j.clinsp.2026.101034. Online ahead of print.

ABSTRACT

CONTEXT: Stroke causes upper limb disability. The literature shows the effectiveness of radial Extracorporeal Shock Wave Therapy (rESWT) in reducing spasticity and promoting functional recovery of the upper limb of patients with stroke.

OBJECTIVE: Demonstrate the effect of rESWT on functional recovery of the upper extremity after ischemic stroke in the middle cerebral artery territory.

METHODS: Randomized, doubleblind, sham-controlled trial.

INTERVENTIONS: Weekly sessions of 5,000 rESWs (3.5 to 4.0 bar, 15 Hz), diffusely over the elbow and wrist flexors in the forearm and hand interosseous muscles for four weeks, delivered with a 36 mm device. A control treatment was conducted by a sham handpiece that did not emit the rESWs.

OUTCOMES: Changes in Fugl-Meyer Assessment for upper limb function (FMA-UE) at four weeks after the end of the treatment was the primary outcome. Spasticity, strength, and cortical integrity by transcranial magnetic stimulation were also assessed before and four weeks after the end of the treatment .

RESULTS: 23 patients were randomized, and 16 were included in the per-protocol analysis. Baseline measures were were balanced. FMA-UE was significantly different between the groups for proximal muscles (p = 0.004) and overall score (p = 0.038). Muscle strength by the Medical Research Council (MRC) score was also significantly different between both groups (p = 0.012). Three patients of the rESWT group and four patients of the sham rESWT group were excluded due to the use of Botulinum toxin, declined participation soon after they were randomized, or did not return four weeks after the end of treatment to follow-up. A limitation of this study is its small sample size, which limits the statistical power and the generalizability of our findings.

CONCLUSION: Four weekly sessions of rESWT improved the functional recovery of patients with chronic ischemic stroke and absent MEPs at baseline. This suggests rESWT may act via peripheral mechanisms to improve proximal muscle function, reflected in the overall improvement of the global measure of FMA-UE.

PMID:42424664 | DOI:10.1016/j.clinsp.2026.101034

JMIR Med Inform. 2026 Jul 9;14:e80377. doi: 10.2196/80377.

ABSTRACT

BACKGROUND: Cardiovascular diseases (CVDs) and type 2 diabetes (DM2) are influenced not only by biomedical risk factors but also by social determinants of health (SDOH). While the inclusion of SDOH in predictive models is increasingly advocated, few studies have quantified their specific contribution in a high-risk clinical cohort using robust statistical and machine-learning approaches.

OBJECTIVE: This study aims to quantify the added predictive value of SDOH in predicting CVD or DM2 disease onset within 5 years, within 10 years, and at any time during follow-up among individuals already at elevated risk and to compare this added value across multiple modeling setups and frameworks.

METHODS: We used a large, linked dataset of over 58,000 inclusion events from the Extramural Leiden University Medical Center Academic Network data warehouse in the Netherlands, combining structured coded diagnosis and medication records from general practitioners with individual-level socioeconomic data from Statistics Netherlands. Individuals aged 30 years and older without prior DM2 or CVD were followed to assess disease progression. We trained Cox proportional hazards (CPH) and Extreme Gradient Boosting (XGBoost) models to predict progression to DM2 or CVD within 5 and 10 years and overall. All analyses were performed using the R programming language. Experiments included comparisons of Systematic Coronary Risk Evaluation 2, CPH, and XGBoost models; evaluation of time-bound and survival-based formulations; and quantification of SDOH impact using feature subset XGBoost models and Shapley additive explanations (SHAP)-based importance.

RESULTS: For the 5-year prediction of CVD or DM2, the combined XGBoost model using biomedical and SDOH predictors achieved an area under the receiver operating characteristic curve (AUC) of 0.738, significantly outperforming the biomedical-only model (AUC=0.728; P=.01) and the SDOH-only model (AUC=0.691; P<.001). For 10-year CVD prediction, XGBoost achieved an AUC of 0.729, outperforming CPH (AUC=0.718; P=.02) and Systematic Coronary Risk Evaluation 2 (AUC=0.697; P<.001). For overall event prediction, XGBoost again performed best (AUC=0.719), significantly higher than CPH (AUC=0.704; P<.001). SHAP analyses showed that biomedical predictors contributed most strongly on a per-feature basis, while a subset of SDOH variables, particularly income- and benefit-related indicators, provided complementary predictive signal and ranked among the most influential predictors.

CONCLUSIONS: Incorporating SDOH improved the prediction of CVD and DM2 onset in a clinically defined high-risk cohort. Across hundreds of linked predictors, SDOH provided measurable incremental discrimination beyond biomedical risk factors, and income- and benefit-related variables ranked among the most influential features. SHAP analyses indicated that this added value was largely driven by a limited subset of highly informative social predictors. These findings support integrating structured SDOH into clinically actionable risk stratification models.

PMID:42424628 | DOI:10.2196/80377

Obstet Gynecol. 2026 Jul 9. doi: 10.1097/AOG.0000000000006364. Online ahead of print.

ABSTRACT

OBJECTIVE: To evaluate the risks of severe coronavirus disease 2019 (COVID-19)-related outcomes among pregnant and postpartum individuals and nonpregnant women during the Delta variant period and after the pandemic emergency ended in the United States.

METHODS: We conducted a retrospective cohort study of 18- to 49-year-old women identified in a national U.S. commercial insurance claims database during the Delta variant (July 1-December 20, 2021) and postemergency periods (May 11, 2023-September 10, 2024). Pregnant and postpartum individuals unvaccinated for COVID-19 during the year before follow-up were propensity score-matched to four nonpregnant women. Primary outcomes were laboratory-confirmed or clinically diagnosed COVID-19 with subsequent COVID-19 hospitalization, pneumonia hospitalization, or a severe composite COVID-19 hospitalization such as acute respiratory failure, intensive care unit admission, acute respiratory distress syndrome, or respiratory support.

RESULTS: Among the individuals followed during the Delta variant (1,109,384) and postemergency (878,003) periods, hospitalization rates with COVID-19 were substantially higher among pregnant individuals than among postpartum individuals or nonpregnant women. In propensity score-matched analyses, the risks of all primary outcomes were elevated for individuals who were pregnant during the Delta period, compared with matched nonpregnant women. Although absolute risks of severe COVID-19 outcomes were lower during the postemergency period, the relative risks (RRs) of COVID-19 hospitalization (RR 4.09; 95% CI, 3.65-4.59) and pneumonia hospitalization (RR 2.78; 95% CI, 1.38-4.81) during pregnancy remained elevated. The RR for severe composite COVID-19 hospitalization (RR 2.17; 95% CI, 0.35-6.67) was imprecise, reflecting substantial uncertainty. Risks for severe COVID-19-related outcomes were also elevated postpartum. Sensitivity analyses reinforced these findings.

CONCLUSION: Higher risks of severe COVID-19-related outcomes among pregnant and postpartum individuals have persisted since the resolution of the pandemic emergency.

PMID:42424625 | DOI:10.1097/AOG.0000000000006364

Syst Biol. 2026 Jul 9:syag045. doi: 10.1093/sysbio/syag045. Online ahead of print.

ABSTRACT

Reticulate processes such as hybridization, introgression, and horizontal gene transfer cannot be fully represented by a bifurcating tree. Enter phylogenetic networks: first as split graphs to visualize tree discordance, then as explicit probabilistic models that capture biological phenomena. Here, we describe the broad taxonomy of network representations, distinguishing the principal classes of explicit networks, their biological interpretability and our ability to accurately estimate them from empirical data. We also trace the evolution of the main network inferential methods from hybrid detection tests, distance- and subgraph-based amalgamation methods, probabilistic approaches under the multispecies network coalescent, composite-likelihood and divide-and-conquer frameworks, while highlighting the selective pressures of statistical identifiability and computational scalability that have shaped this evolution. As we move towards a network thinking paradigm, previously isolated methodological lineages from population genetics, phylogenomics, and mathematical network theory are now introgressing, uniting diverse network models into a shared framework that can integrate sequence- and species-level reticulate processes, increase robustness to systematic errors, and refine algorithms for genome-scale data, expanding the tree of life into a richer, more entangled yet clearer picture of evolution.

PMID:42424608 | DOI:10.1093/sysbio/syag045

J Craniofac Surg. 2026 Jul 10. doi: 10.1097/SCS.0000000000013148. Online ahead of print.

ABSTRACT

This study was performed to evaluate the maxillary sinus in patients with isolated cleft palate (ICP). A total of 87 ICP patients and 93 controls, aged 4 to 22 years, were enrolled and stratified into 4 age groups. Cone-beam computed tomography scans were utilized to assess diameters and volume of the maxillary sinus. No statistically significant differences were detected between the left and right sides, nor between male and female subjects. All measurements in ICP patients were smaller than normal. In controls, significant variations of maxillary sinus parameters were observed between adjacent age groups, with the exception of the sagittal diameter between the juvenile and adolescent groups. In ICP patients, all measurements showed significant changes from the juvenile to adolescent stages; in addition, volume and sagittal diameters on both sides showed significant changes from the adolescent to adult stages. These findings indicated the absence of sexual dimorphism and bilateral asymmetry in maxillary sinus morphology among all subjects. The maxillary sinus of ICP patients was significantly smaller than normal. In controls, the maxillary sinus increased progressively with age from preschool to adulthood. In contrast, ICP patients demonstrated relatively restricted maxillary sinus increase during the preschool and juvenile stages, followed by a continuous increase that persisted until adulthood.

PMID:42424605 | DOI:10.1097/SCS.0000000000013148

J Med Internet Res. 2026 Jul 9;28:e87280. doi: 10.2196/87280.

ABSTRACT

BACKGROUND: Patients frequently access laboratory results through patient portals, but many struggle to interpret these values and formulate relevant questions for their clinicians. Question prompt lists (QPLs) can enhance communication but are rarely tailored to individual clinical contexts.

OBJECTIVE: This study evaluated the feasibility of using large language models (LLMs) to generate patient-friendly, clinically relevant questions grounded in electronic health record (EHR) laboratory data.

METHODS: We extracted deidentified clinical profiles, including laboratory results, diagnoses, and medications, from patients with chronic conditions (eg, diabetes and chronic kidney disease). Using 9 deidentified clinical profiles from the OneFlorida Data Trust, we generated 486 questions across all rounds: 126 with GPT-4o in round 1, 120 with GPT-4o in round 2, 180 with GPT-4o in round 3, and 60 with LLaMA 3.2 in round 3. Prompt refinements were informed by clinician ratings consisting of 2 binary questions (ie, clear phrasing and clinical validity) and 3 Likert-scale questions (ie, significance for the patient’s health; clinical appropriateness, that is, the likelihood of being asked in primary care setting; and willingness to answer). Refinements were incorporated after each round. Patient participants then evaluated selected questions for understandability, perceived usefulness, and intention to use. Readability was assessed with standard indices.

RESULTS: Iterative clinician feedback improved question clarity and reduced clinically irrelevant suggestions. Across rounds, GPT-4o consistently produced more coherent and patient-friendly questions, while LLaMA 3.2 demonstrated competitive performance on Likert-scale metrics. It exhibited greater variability in clinical appropriateness as noted by clinicians. In round 3, the binary metric “clear phrasing” reached a ceiling effect for both models, while clinical validity ratings showed greater variability, particularly from one clinician. Likert-scale evaluations tended to favor LLaMA 3.2 across all 3 clinicians for clinical appropriateness (3.37-4.82 vs 3.02-4.67), significance for the patient’s health (3.38-4.28 vs 2.97-3.83), and willingness to answer (3.17-4.70 vs 2.82-4.47), with multiple comparisons reaching statistical significance after Bonferroni correction. Patient evaluation (N=134) of GPT-4o-generated questions showed that 25 of 30 questions had moderate to high understandability (average Likert score ≥3.5), and 19 of 30 questions had moderate to high usefulness (average Likert score ≥3.5).

CONCLUSIONS: This study supports the feasibility of using LLMs with structured EHR-derived laboratory data to generate contextualized QPLs, but model outputs varied in clinical appropriateness and readability. Clinician-in-the-loop review remains necessary before patient-facing use.

PMID:42424593 | DOI:10.2196/87280

Br Med Bull. 2026 Jul 3;159(1):ldag018. doi: 10.1093/bmb/ldag018.

ABSTRACT

BACKGROUND: Even after surgical repair, acute Achilles tendon rupture (ATR) may leave residual strength and function deficits. Augmenting percutaneous repair with the flexor hallucis longus (FHL) tendon may limit elongation and reinforce the repair. We report 5-year outcomes of acute ATR managed with percutaneous repair alone or with minimally invasive FHL augmentation.

SOURCES OF DATA: A prospective comparative cohort of 53 patients (27 percutaneous repair alone, 26 with FHL augmentation) with a minimum 5 years follow-up. Objective and subjective outcomes were collected.

AREAS OF AGREEMENT: At 5 years, both procedures gave equivalent results on all patient-reported outcome measures. FHL augmentation reduced tendon elongation (lower Achilles tendon Resting Angle) and produced statistically significantly greater isometric strength and smaller calf circumference difference.

AREAS OF CONTROVERSY: Structural and strength differences were small, of doubtful clinical relevance, and did not improve patient-reported function. FHL augmentation is more demanding, longer, costlier, and required inpatient admission, whereas percutaneous repair was a day-case procedure under local anesthesia. A significant between-group age difference is an important confounder.

GROWING POINTS: Structural indices frequently dissociate from patient-reported function after ATR. Within the Italian National Health Service, the added resource use of FHL augmentation is hard to justify when no validated measure detects a clinically meaningful 5-year difference.

AREAS TIMELY FOR DEVELOPING RESEARCH: Adequately powered randomized trials with pre-specified age stratification are needed to establish whether particular subgroups, such as older patients or those with more degenerate tendons, derive a clinically relevant benefit from FHL augmentation.

PMID:42424592 | DOI:10.1093/bmb/ldag018

Am J Public Health. 2026 Jul 9:e1-e11. doi: 10.2105/AJPH.2026.308516. Online ahead of print.

ABSTRACT

Objectives. To gain a more comprehensive understanding of the morbidity associated with pedestrian risk in Chicago, Illinois, by probabilistically matching the data of injured pedestrians in standardized police traffic crash reports to their associated emergency department (ED) visit record. Methods. Between 2018 and 2022, we extracted information on pedestrians injured by vehicles as recorded by the Chicago Police Department pedestrians seen at a city ED for injuries sustained by a vehicle. Among matched records, we used descriptive statistics to describe temporal, geographic, and demographic patterns in ED-attended pedestrian injury. We used multivariable regression modeling to calculate incidence rates of ED-attended pedestrian injury across Chicago communities of varying economic hardship. Results. Among 2631 ED patients matched to a police department crash record, 73.9% were initially recorded by police with nonincapacitating injuries or less at the crash scene. Five of the 6 communities with the highest combination of crash frequency and injury severity were among the 40% most economically disadvantaged communities. Conclusions. Incorporation of ED data highlighted pedestrian injuries that would have been missed with police crash data alone, which disproportionately affects economically vulnerable neighborhoods. Public Health Implications. Regular incorporation of pedestrian-injury data from local EDs could help jurisdictions better understand broader public health implications and disparities in pedestrian risk and identify additional opportunities for intervention. (Am J Public Health. Published online ahead of print July 9, 2026:e1-e10. https://doi.org/10.2105/AJPH.2026.308516).

PMID:42424579 | DOI:10.2105/AJPH.2026.308516

J Med Internet Res. 2026 Jul 9;28:e89065. doi: 10.2196/89065.

ABSTRACT

Places have a significant impact on health. Thus, examining place-based structural and social determinants can help inform effective public health interventions. HealthAtlas.ucsf.edu provides a single online platform to explore multiple domains of place-based data. The initial California-only version of Health Atlas was launched in April 2020, and a national version was launched in October 2024. An artificial intelligence-assisted search function was integrated in January 2026. Health Atlas includes data on over 200 variables across 5 topical domains: demographics, socioeconomic, neighborhood, environment, and health and health care. The data were either (1) obtained from the American Community Survey, CDC PLACES, and other public sources or (2) obtained through collaboration with research partners. Users can visualize and aggregate data for 7 geographic levels: census tract, zip code tabulation area, county, congressional district, core-based statistical area, public use microdata area, and state. Most variables are available across all 50 states in the United States, the District of Columbia, and Puerto Rico. Users can explore Health Atlas to better understand the relationship between selected variables via maps, histograms, scatterplots, and summary plots. Users can select custom areas to suit specific needs. Customizable datasets can be downloaded for further use. Health Atlas provides freely available, user-friendly data and tools to support researchers, community organizations, government entities, and other public health professionals. We envision that Health Atlas will contribute to evidence-based, community-based initiatives; impactful health equity research; and effective public health programs.

PMID:42424556 | DOI:10.2196/89065