Tag: statistics

Int Dent J. 2026 May 20;76(4):109636. doi: 10.1016/j.identj.2026.109636. Online ahead of print.

ABSTRACT

PURPOSE: The integration of artificial intelligence (AI) into prosthodontics represents a paradigm shift in the design and fabrication of removable partial dentures (RPDs). This study evaluates the current AI technologies, including large language models such as ChatGPT, Copilot, Gemini, and DeepSeek, for designing RPDs.

METHODS: Standardized prompts were submitted to four AI-assisted systems (ChatGPT, Copilot, Gemini, and DeepSeek) to generate RPD designs for 25 partially edentulous clinical scenarios based on Kennedy classifications. The outputs were compared with reference models (AiDENTAL), a validated retention prediction model, and evaluations by six blinded experts. Statistical comparisons were performed using a mixed-effects ordinal regression model (p < 0.05).

RESULTS: Compared with the reference standards, Copilot and Gemini produced the most consistent and accurate RPD designs, whereas DeepSeek showed the greatest deviation, despite achieving the highest predicted retention scores. Expert evaluations confirmed that AiDENTAL achieved the highest overall design quality, followed by Copilot, whereas ChatGPT and DeepSeek demonstrated lower and more variable performances.

CONCLUSIONS: The design of RPDs using different large language models, including ChatGPT, Copilot, Gemini, and DeepSeek, resulted in notable variations in the design output. AiDENTAL achieved the highest overall RPD design quality, whereas Copilot and Gemini produced the most consistent and accurate designs across all the evaluated criteria.

PMID:42160812 | DOI:10.1016/j.identj.2026.109636

J Craniomaxillofac Surg. 2026 May 20;54(8):104587. doi: 10.1016/j.jcms.2026.104587. Online ahead of print.

ABSTRACT

Anterior disc displacement without reduction of the temporomandibular joint is a prevalent condition associated with pain and functional limitation, and minimally invasive arthroscopic approaches are increasingly favored over open surgery due to lower morbidity. This study compared three arthroscopic interventions: classical myotomy (CM), minimally invasive anterior arthroscopic myotomy (MIAAM), and posterior ligament electrocoagulation (PLE). A total of 86 patients were included: 24 (27.9%) underwent CM, 30 (34.8%) underwent MIAAM, and 32 (37.2%) underwent PLE. Outcomes were assessed using visual analog scale (VAS) pain, maximum mouth opening (MMO), and joint function at baseline and at 1 and 6 months postoperatively. Pain improved significantly over time in all groups (F = 5.02; df = 2; p < 0.05), with no significant differences between techniques. Maximum interincisal opening (MIO) and mandibular protrusion also improved significantly (F = 14.6; df = 2; p < 0.05 and F = 8.949; df = 2; p < 0.05, respectively), again without inter-group differences. MIAAM was associated with faster pain relief at 1 month and slightly better 12-month outcomes, although these differences were not statistically significant. Overall, PLE showed comparatively less favorable results, suggesting MIAAM may represent a balanced option in terms of efficacy and safety.

PMID:42160800 | DOI:10.1016/j.jcms.2026.104587

Clinics (Sao Paulo). 2026 May 20;81:100939. doi: 10.1016/j.clinsp.2026.100939. Online ahead of print.

ABSTRACT

OBJECTIVE: To evaluate the association between lipid profile, statin use, metabolic syndrome, and clinic. Prostate Enlargement (PE) in adult men attending a urology outpatient clinic.

METHODS: A cross-sectional study was conducted among 1117 men aged 40-years or older. Prostate volume was measured by ultrasonography; a volume ≥ 40 mL was considered the threshold for enlargement. Independent variables included lipid fractions, prescription-based statin use, and components of metabolic syndrome. Multivariate logistic regression models were applied, adjusted for age, hypertension, and medication exposure.

RESULTS: The median age was 63-years (IQR: 55-71), and the median prostate volume was 34.0 mL (IQR: 26.0-48.0). Statin use was identified in 36.5% of the sample, and the prevalence of PE was 38.9%. Age was the only factor independently associated with PE (OR = 1.07; 95% CI: 1.05-1.09; p < 0.001). Metabolic syndrome was associated with PE in crude analysis; however, this association lost statistical significance after adjustment for potential confounders.

CONCLUSION: Age was the only independent determinant of prostate enlargement in this metabolically controlled cohort. Lipid parameters and prescription-based statin use showed no adjusted association with prostate volume; however, the lack of detailed statin exposure data warrants cautious interpretation of these findings.

PMID:42160783 | DOI:10.1016/j.clinsp.2026.100939

JMIR Form Res. 2026 May 20;10:e64409. doi: 10.2196/64409.

ABSTRACT

BACKGROUND: Quality of life (QOL) is an important aspect of every chronic disease, including interstitial lung disease (ILD). QOL is perceived as a significant patient-centered outcome.

OBJECTIVE: This study aims to identify factors correlating with different aspects of QOL in patients with various ILDs.

METHODS: We recruited 57 participants hospitalized in a tertiary care clinical center to this pilot observational cross-sectional study. These included 22 patients with idiopathic interstitial pneumonia (IIP), 19 patients with connective tissue disease-associated ILD (CTD-ILD), and 16 patients with interstitial pneumonia with autoimmune features (IPAF). The Saint George’s Respiratory Questionnaire (SGRQ) and World Health Organization Quality of Life Questionnaire (WHOQOL-BREF) were used to assess QOL, and the Hospital Anxiety and Depression Scale – Modified Version (HADS-M) and Patient Health Questionnaire – 9 (PHQ-9) were used to evaluate depression severity. Functional parameters including forced vital capacity (FVC), forced expiratory volume in 1 second (FEV1), transfer lung capacity for carbon monoxide (TLCO), and 6-minute walk distance (6MWD) were assessed. Assessment of QOL was a secondary outcome measure in a multicenter prospective study aimed at determining the characteristics of Polish patients with interstitial pneumonia with autoimmune features.

RESULTS: In each study group, positive correlations existed between the WHOQOL-BREF physical domain score and FEV1 % predicted value (P=.001) and TLCO % predicted value (P=.03). Regardless of diagnosis, higher depression, anxiety, and aggression scores (ie, worse mental health) correlated negatively with multiple domains of QOL measured using the WHOQOL-BREF. Predictors of QOL aspects varied in each study group. In the IPAF group, the TLCO % predicted value was a predictor of QOL expressed as the SGRQ total score (P=.005). In the CTD-ILD group, short 6MWD (P<.001) and high HADS-M aggression score (P=.01) correlated with low QOL (expressed as a high SGRQ total score). In the IIP group, 6MWD (P=.002) and PHQ-9 scores (P<.001) were predictors for SGRQ symptoms score. Gender-based differences were revealed: In all study groups, men had higher scores in the psychological, social, and environmental domains of the WHOQOL-BREF, indicating better QOL, without a statistically significant difference in the physical domain scores between genders. Diagnosis-based differences in the psychological aspects of QOL were also revealed: The QOL psychological domain scores were significantly lower in the CTD-ILD and IPAF groups than in the IIP group, indicating worse QOL (P=.01).

CONCLUSIONS: QOL is a multifaceted issue with various factors impacting its assessment. 6MWD, TLCO predicted value, and worse functional ability might specifically impact QoL in ILD. Mental health is an important aspect of QOL in the ILD population, as patients with a chronic, potentially life-limiting disease may be more prone to developing depression or anxiety. Assessment of QOL should be taken into account in clinical decision-making and research on chronic diseases, as this patient-related outcome may impact therapeutic decisions and patient compliance.

PMID:42160779 | DOI:10.2196/64409

JMIR Public Health Surveill. 2026 May 20;12:e81767. doi: 10.2196/81767.

ABSTRACT

BACKGROUND: Geospatial analysis plays an essential role in informing targeted human immunodeficiency virus (HIV) intervention. The Dai-Jingpo Autonomous Prefecture of Dehong (hereinafter referred to as Dehong), located along the China-Myanmar border in the Yunnan province, has been heavily impacted by HIV infection. Given the complex local epidemic context, particularly frequent cross-border population movement, there is an urgent need to apply spatiotemporal analytical approaches to guiding resource allocation. Existing evidence has demonstrated the substantial spatial variations of newly diagnosed HIV infection this region. However, these spatiotemporal variations have not been fully explored at a finer geographic and temporal resolution.

OBJECTIVE: This study aims to comprehensively investigate the spatiotemporal variations of newly diagnosed HIV infection at a finer scale in this border region to inform targeted interventions.

METHODS: Data on newly diagnosed HIV cases at the township level in Dehong were collected from 2010 to 2022. The rate of newly diagnosis HIV cases was calculated annually. GeoDetector q statistics were performed to assess the spatially stratified heterogeneity of the rate of newly diagnosed HIV cases. The Bayesian space-time hierarchical model was applied to detect the spatiotemporal patterns of newly diagnosed HIV infection across the region.

RESULTS: A total of 5045 newly diagnosed HIV cases were identified in Dehong from 2010 to 2022. The rate of newly diagnosed HIV cases decreased from 57.1 cases per 100,000 population in 2010 to 13.3 cases per 100,000 population in 2022, a decrease of 76.7% over the past 13 years. The overall temporal relative risk decreased from 2.11 (95% CI 1.84-2.41) in 2010 to 0.48 (95% CI 0.40-0.56) in 2022. There was substantial spatiotemporal heterogeneity in the risk of newly diagnosed HIV infection, with townships near the China-Myanmar border having a higher spatial relative risk. Notable spatially stratified heterogeneity in the rate of newly diagnosed HIV cases when stratified by the distance of townships to the China-Myanmar border was observed (q=0.27; P=.004). Among the 51 townships in Dehong, 22 (43.1%) hotspots and 22 (43.1%) coldspots were identified. Notably, in comparison to the overall declining temporal trend, 2 hotspots and 4 coldspots exhibited a slower declining trend, suggesting that these regions may require additional intervention efforts.

CONCLUSIONS: This study comprehensively estimated the spatiotemporal risk of newly diagnosed HIV infection across Dehong, revealing high-risk areas concentrated near the China-Myanmar border. Priority should be given to implementing targeted interventions to control cross-border HIV transmission, including the establishment of cross-border HIV control mechanisms, as well as the strengthening of management measures for cross-border populations. Furthermore, this study offers methodological insights into the use of routine surveillance data and Bayesian spatiotemporal modeling to better understand HIV transmission dynamics at finer geographic scales and to support precision-oriented HIV prevention services.

PMID:42160778 | DOI:10.2196/81767

J Med Internet Res. 2026 May 20;28:e69634. doi: 10.2196/69634.

ABSTRACT

BACKGROUND: Digital approaches to weight management have the potential to produce cost-effective and scalable weight management solutions. Effective behavior change interventions typically promote self-regulation of energy balance behaviors, which may be enhanced by incorporating emotion regulation strategies.

OBJECTIVE: This study aimed to evaluate the effectiveness of a digital behavior change toolkit for weight loss maintenance in European adults who had achieved ≥5% weight loss in the previous 12 months. We hypothesized that a combined intervention targeting self-regulation or motivation and emotion regulation would be more effective than either component alone, and that each would outperform an active control.

METHODS: The Navigating to a Healthier Weight (NoHoW) trial was a 2×2 factorial randomized, single-blind, controlled trial involving 1627 adults who had achieved ≥5% weight loss in the previous 12 months (initial BMI ≥25 kg/m2) across 3 European centers (the United Kingdom, Denmark, and Portugal). The trial evaluated a digital toolkit for weight management subsequent to an initial ≥5% weight loss in the prior 12 months. Participants were assigned using adaptive stratified sampling to one of four groups: (1) self-regulation or motivation (n=403), (2) emotion regulation (n=416), (3) combined motivation and emotion (n=408), or (4) active control (generic content, regular self-weighing, and Fitbit use, n=400). The primary outcome was weight change from baseline to 12 months. Prespecified secondary outcomes included cardiometabolic markers. Linear models adjusted for recruitment center, sex, age group, BMI group, and pretrial weight loss. Subgroup analyses were conducted by sex.

RESULTS: At 12 months, 76% (364/1627) of participants remained in the study. In the primary ITT analysis in all participants, none of the intervention arms (motivation, emotion, or combined) differed significantly from the active control for weight change at 12 months. Completer and per-protocol analyses produced similar patterns and did not change the overall interpretation. In the per-protocol sample, men regained 0.14 kg, and women regained 0.54 kg of their pretrial weight loss. Subgroup analyses indicated a small effect of the motivation intervention in men, but this was not clinically meaningful and did not alter the primary null findings. Nearly half of ITT participants regained weight, and no significant intervention effects were observed for cardiometabolic secondary outcomes.

CONCLUSIONS: The NoHoW trial was the first large-scale, multicountry 2×2 factorial randomized controlled trial to evaluate a digital-only toolkit based on self-regulation or motivation and emotion regulation techniques for weight loss maintenance. NoHoW found no evidence in the primary ITT analysis that digital interventions targeting self-regulation or emotion regulation improved weight loss maintenance compared with the active control. A small subgroup effect in men should be interpreted cautiously and does not change this conclusion. The trial provides evidence on both the limitations and potential of digital behavior change interventions for long-term weight outcomes. Future digital interventions may benefit from enhanced engagement and tailored content to improve long-term weight outcomes.

PMID:42160776 | DOI:10.2196/69634

JMIR Form Res. 2026 May 20;10:e83363. doi: 10.2196/83363.

ABSTRACT

BACKGROUND: The Technology Adoption Model (TAM) offers a potential framework for elucidating the relationships between data privacy or security concerns and behavioral intention, perceived usefulness (PU), and perceived ease of use (PEOU) of mobile health (mHealth) apps, particularly for patients’ self-care management. In Saudi Arabia, limited information is available on these pertinent research areas despite the government’s relentless efforts to bolster the use of mHealth apps.

OBJECTIVE: This study applies the TAM and the psychosociocultural framework to explore the influence of patients’ data privacy and security concerns on the PU, PEOU, and behavioral intention to use mHealth apps for self-care management in Saudi Arabia.

METHODS: A cross-sectional study was conducted by recruiting patients using mHealth apps for self-care from various provinces in Saudi Arabia. Research instruments were developed based on the components of 2 theories: the psychosociocultural framework and TAM, which were then piloted, validated, and distributed to participants via Google Forms. Linear regression models were performed to test the hypothesized relationships.

RESULTS: Overall, 567 patients using mHealth apps participated in the study. Slightly more than one-third (217/567, 38.2%; range 35.6%-41.4%) of the participants expressed a high level of concern regarding data privacy, confidentiality, and security, with significant predictors being female gender, higher educational qualifications, and younger age groups (<46 years). About 18% to 25% of the variance in PU, PEOU, and behavioral intention to use mHealth apps was explained by the tested factors. Patients were more likely to have higher PU following a unit decrease in data confidentiality (β=.31; P=.01) and security concerns (β=.47; P=.01). The PEOU of mHealth apps increased as users demonstrated less concern regarding data privacy (β=.18; P=.001), confidentiality (β=.24; P<.001), and security (β=.43; P=.02). Likewise, behavioral intention to use mHealth apps also increased significantly following a reduction in respondents’ concerns toward data privacy (β=.18; P=.02), confidentiality (β=.24; P=.03), and security issues (β=.36; P=.01).

CONCLUSIONS: Specific demographic factors and concerns regarding data security and privacy influence patients’ PU, PEOU, and behavioral intention to use mHealth apps for self-care management. Targeting the age-, education-, and gender-based differences regarding the usage of mHealth apps. Health care providers and policymakers may consider age-, education-, and gender-based differences when developing strategies to improve the adoption of mHealth apps among the Saudi patient population.

PMID:42160774 | DOI:10.2196/83363

Neurology. 2026 Jun 23;106(12):e218123. doi: 10.1212/WNL.0000000000218123. Epub 2026 May 20.

ABSTRACT

BACKGROUND AND OBJECTIVES: Smoking cessation is universally prioritized for the prevention of cardiovascular disease and cancer, but its impact on dementia risk remains uncertain. We aimed to evaluate the associations of smoking cessation and postcessation weight gain with long-term risk of dementia and cognitive trajectories.

METHODS: We conducted a prospective cohort study using data from the US Health and Retirement Study (1995-2020). A total of 32,802 dementia-free adults (mean age 60.5 years [SD 10.7]; 57.1% female) were included. Smoking status and body weight were assessed biennially through structured interviews. The primary outcome was incident dementia identified using the Langa-Weir algorithm, and the secondary outcome was cognitive function measured on a 27-point scale.

RESULTS: Over 25 years of follow-up (median 9.9 years, interquartile range 4.4-16.4 years), 5,868 dementia cases were documented. Compared with current smokers, individuals who quit during follow-up had a lower dementia risk after quitting (hazard ratio 0.84, 95% CI 0.73-0.95), similar to those who had quit before baseline (0.79, 0.72-0.87) and to never smokers (0.75, 0.69-0.83). The benefits of cessation were largely limited to participants with no or modest 2-year postcessation weight gain (≤5 kg). By contrast, the association of quitting accompanied by >10-kg weight gain was not statistically significant (1.33, 0.87-1.82). Restricted cubic spline analysis showed decreasing dementia risk with longer time since quitting, and the risk approached that of never smokers and plateaued at around 7 years after cessation. Cognitive trajectory analyses showed that quitting was associated with long-term slower cognitive decline (slope difference 0.19 points per decade, 95% CI 0.00-0.38) but no transient cognitive change (0.57; 95% CI -0.69 to 1.83), especially among those with minor weight gain (slope difference 0.23 per decade, 95% CI 0.03-0.43).

DISCUSSION: Smoking cessation was associated with a sustained lower dementia risk and slower cognitive decline, comparable to never smokers and those without short-term risk increase. However, postcessation weight gain may attenuate these advantages, highlighting the need for weight management in cessation programs. These findings should be interpreted cautiously, given the potential residual confounding and measurement error.

PMID:42160746 | DOI:10.1212/WNL.0000000000218123

Brief Bioinform. 2026 May 4;27(3):bbag245. doi: 10.1093/bib/bbag245.

ABSTRACT

Bioinformatics is entering a new phase characterized by the integration of universal biological models and multi-agent systems to enable end-to-end scientific discoveries. This review argues that the next paradigm shift will go beyond traditional predictive models and generative artificial intelligence (AI) toward agentic AI: systems capable of planning, acting through tools, reflecting on results, and iterating until a goal is achieved. We first examine recent foundational models that produce transferable representations across omic modalities, such as scGPT, Nicheformer, and EpiAgent, and discuss their architectural choices, training regimes, and interpretability constraints. We then analyze biomedical agent frameworks through their main components (planning, action, reflection, and memory), highlighting representative systems such as ClinicalAgent and Biomni that operationalize these ideas in controlled environments. Next, we focus on hypothesis validation mechanisms, including retrieval-augmented generation for evidence grounding, sequential statistical testing, and benchmarking methodologies designed to quantify robustness and reproducibility. Finally, we summarize emerging applications in drug discovery and personalized medicine, from molecular literature analysis and protocol automation to drug repurposing for rare diseases and closed-loop synthesis. We conclude by outlining the main challenges ahead, namely hallucinations, interpretability, systemic biases, integration with clinical infrastructures, and regulatory and ethical requirements, and propose a roadmap for the development of scientific agents that are not only high-performing but also reliable, verifiable, and implementable in real biomedical contexts.

PMID:42160738 | DOI:10.1093/bib/bbag245

Intern Med J. 2026 May 20. doi: 10.1111/imj.70482. Online ahead of print.

ABSTRACT

BACKGROUND AND AIMS: Metabolic (dysfunction)-associated steatotic liver disease (MASLD) has been linked to an increased risk of extrahepatic cancers. Whether MASLD or metabolic (dysfunction)-associated fatty liver disease (MAFLD) is associated with an increased risk of extrahepatic cancer incidence or death in Australia is unknown.

METHODS: This was a study from the Crossroads 1 cohort, enrolling randomly selected adults from regional Australia between 2001 and 2003 to partake in a comprehensive evaluation of health. MASLD is defined as fatty liver index (FLI) ≥60, one metabolic risk factor and no alternate liver disease, while MAFLD was defined as FLI ≥60 with overweight/obesity, type 2 diabetes mellitus (T2DM) and/or metabolic dysfunction. Longitudinal outcomes linked through cancer registry, hospital admission and death registry datasets and defined according to the International Statistical Classification of Diseases and Related Health Problems, 10th revision codes.

RESULTS: In total, 1324 and 1444 participants respectively are included in the MASLD and MAFLD analyses. Prevalence was 35.4% (MASLD) and 40.7% (MAFLD). Median follow-up time was 19.7 years (interquartile range 19.1-20.1). Neither form of fatty liver disease (FLD) was associated with an increased risk of death related to extrahepatic cancer compared to those without FLD. Both forms of FLD were associated with an increased incidence of colorectal cancer (MASLD adjusted sub-hazard ratio (sHR) 2.90, 95% CI 1.17-7.17; MAFLD: sHR 3.15, 95% CI 1.43-6.96) following adjustment for confounding factors. This was primarily influenced by a difference seen among females (sHR 3.89-4.32).

CONCLUSION: Neither MASLD nor MAFLD was associated with an increased risk of extrahepatic cancer-related death, but they were associated with an increased risk of colorectal cancer incidence, particularly among females.

PMID:42160725 | DOI:10.1111/imj.70482