Tag: pubmed

Drugs. 2026 Jul;86(7):1103-1119. doi: 10.1007/s40265-026-02335-9. Epub 2026 May 27.

ABSTRACT

BACKGROUND: Sedative-hypnotics, including benzodiazepines (BZDs) and non-benzodiazepine hypnotics (Z-drugs), are widely prescribed for insomnia and anxiety, particularly in older adults. Their long-term cognitive safety and potential association with Alzheimer’s disease (AD) remain uncertain. We examined whether use of BZDs and Z-drugs is associated with incident AD and assessed variation by drug class, pharmacokinetics, and methodological factors.

METHODS: PubMed, Embase, and the Cochrane Central Register of Controlled Trials were searched from inception to 16 August 2025 without language restrictions. Reference lists of eligible articles and reviews were screened. We included observational cohort and nested case-control studies enrolling adults without dementia at baseline that compared BZD or Z-drug users with non-users and reported incident AD diagnosed using validated clinical or administrative criteria (e.g., ICD-9/10, NINCDS-ADRDA, or NIA-AA). We excluded reviews, case reports, conference abstracts, studies with overlapping populations, and studies without extractable effect estimates. Two reviewers independently screened studies, extracted data, and assessed risk of bias using ROBINS-E. Random-effects meta-analyses were performed separately for odds ratios (ORs) and hazard ratios (HRs). Heterogeneity was quantified with I². Publication bias was evaluated with funnel plots and Egger test when applicable. Subgroup and meta-regression analyses assessed clinical and methodological modifiers. Certainty of evidence was rated using GRADE. The protocol was prospectively registered (PROSPERO CRD420251141623).

RESULTS: Thirteen studies (N = 721,354 subjects) were included. Overall sedative-hypnotic use was associated with higher odds of AD (OR 1.29; 95% CI, 1.10-1.53; I² = 86.5%). Estimates restricted to HRs were attenuated and not statistically significant (HR 1.17; 95% CI, 0.87-1.58; I² = 73.1%). In subgroup analyses, BZDs overall (OR 1.21; 95% CI 1.07-1.36), Z-drugs (OR 1.14; 95% CI 1.10-1.18; I² = 0%), and short-acting agents (OR 1.19; 95% CI 1.04-1.36) were associated with higher odds of AD, whereas broad-acting BZDs were not (OR 1.01; 95% CI 0.98-1.05). Long-acting agents showed a borderline estimate (OR 1.44; 95% CI 0.99-2.09). Age-stratified analyses showed higher odds in individuals aged <75 years (OR 1.36; 95% CI 1.24-1.49), but not in those aged ≥75 years (OR 1.14; 95% CI 0.61-2.11). Estimates were also higher in studies using ICD-based definitions (OR 1.47; 95% CI 1.16-1.86) than in those using clinical criteria (OR 1.13; 95% CI 0.84-1.52). Meta-regression identified drug class and publication year as significant moderators. Risk of bias was rated moderate to serious in several studies, mainly due to residual confounding and exposure misclassification. Certainty of evidence ranged from very low to moderate.

CONCLUSIONS: Use of BZDs and Z-drugs was associated with increased odds of AD, with variation across drug classes and pharmacokinetic profiles. Short-acting agents, BZDs overall, and Z-drugs were associated with higher risk, whereas broad-acting BZDs were not; this finding should be interpreted with caution given subgroup heterogeneity and limited statistical power. Residual confounding and reverse causation limit causal inference. These results support careful prescribing and the need for prospective studies with detailed characterization of exposure, dose, duration, and clinical indication to clarify whether observed associations reflect drug-related effects or underlying disease processes.

TRIAL REGISTRATION: PROSPERO protocol number: CRD420251141623.

PMID:42334823 | DOI:10.1007/s40265-026-02335-9

Eur Arch Paediatr Dent. 2026 Jun 23. doi: 10.1007/s40368-026-01241-8. Online ahead of print.

ABSTRACT

PURPOSE: Paediatric dental anxiety remains a significant challenge in clinical practice, often impacting co-operation and treatment outcomes. This randomised controlled trial compares the anxiety-reducing effects of AI-based self-modelling versus standard video modelling.

METHODS: A single-blind, parallel-arm randomised controlled trial was conducted on 80 children aged 6-12 years requiring restorative dental treatment. Participants were randomised into two groups. Dental fear and anxiety were assessed using CFSS-DS and MCDASf, along with pulse and heart rate monitoring. Data were collected pre- and post-intervention by a blinded assessor and statistically analysed.

RESULTS: Both groups showed significant within-group reductions in dental fear and anxiety (p < 0.001); however, no statistically significant between-group difference was observed for the primary outcome (CFSS-DS). The AI-based personalised video self-modelling app group demonstrated a greater reduction in heart rate (7.65 vs. 2.18 bpm), with a significant between-group difference (p < 0.001; Cohen’s d = 0.89), indicating reduced short-term physiological arousal rather than overall superiority of the intervention and specific anxiety parameters, particularly related to injections and dental examinations. Intergroup analysis revealed a large effect size for heart rate (Cohen’s d = 0.89) and moderate-to-large effects for selected anxiety items with some item-level differences observed. However, overall CFSS-DS score differences between groups were not statistically significant.

CONCLUSION: Both interventions were effective in reducing dental fear and anxiety. However, no superiority was demonstrated for the primary psychological outcome. The AI-based personalised intervention showed greater reduction in physiological arousal (heart rate), suggesting potential benefits in short-term anxiety modulation.

PMID:42334822 | DOI:10.1007/s40368-026-01241-8

Updates Surg. 2026 Jun 23. doi: 10.1007/s13304-026-02724-5. Online ahead of print.

ABSTRACT

Robotic liver surgery (RLS) is expanding in recent years. Complication prediction is crucial for postoperative outcomes. Traditional MIS scores are poorly studied in RLS, and conventional statistics often oversimplify the multifactorial and interrelated nature of these complications. This study aimed to evaluate the three-level complexity Institut Mutualiste Montsouris (IMM) classification in RLS and assess its integration into an AI algorithm to predict major complications. We retrospectively analyzed data of patients underwent RLS. Surgical complexity was stratified into grades I (low complexity), II (intermediate), and III (high). The cumulative incidence rate and conditional probability of postoperative complication and risk factors for complication ≥ Clavien-Dindo grade II were assessed. The prediction model was developed by training/testing a machine learning (ML) algorithm after feature selection with uni-multivariate analysis. We calculated the receiver operating characteristic (ROC) curve and model accuracy. We analyzed 1,045 patients who underwent RLS, classifying them into three complexity levels: Grade I (n = 581), Grade II (n = 267), and Grade III (n = 109). Significant differences were observed in intra- and postoperative outcomes across the three grades. Multivariate analysis identified ASA score (HR 2.1, p = 0.02), number of lesions (HR 1.8, p = 0.001), and operative time (OR 1, p = 0.004) as key predictors of complications. Associated with the three-level complexity classification, the Neural Network showed the best performance with AUC (0.653) and a precision of 0.996. Three-level complexity IMM classification is a useful tool in RLS for predicting intra-postoperative outcomes. It can be integrated into the Neural Network algorithm to predict major complications.

PMID:42334817 | DOI:10.1007/s13304-026-02724-5

Updates Surg. 2026 Jun 23. doi: 10.1007/s13304-026-02730-7. Online ahead of print.

ABSTRACT

Self-expandable metal stents (SEMS) are routinely used in malignant colorectal obstruction (MCO) for palliation or as a bridge to surgery. However, the association between treatment intent and complication risk, as well as the potential role of clinical success as an intermediate procedural endpoint, remains unclear. We retrospectively analyzed 413 patients with MCO who underwent SEMS placement between 2014 and 2024. Patients were categorized by therapeutic intent (palliation vs. bridge to surgery), and complication rates were compared. Mediation analysis was performed using the Sobel test, structural equation modeling (SEM), and bootstrap-based causal mediation to assess whether clinical success mediated the relationship between therapeutic purpose and complications. Complications occurred in 60 patients (14.5%). Palliation was associated with a higher complication rate compared to bridging (20.0% vs. 8.0%, p = 0.001). Clinical success showed a statistically significant indirect association in the exploratory mediation analysis Therapeutic intent effects (Sobel p = 0.035). SEM confirmed a positive association between therapeutic purpose and clinical success (standardized β = 0.171, p < 0.001) and a negative association between clinical success and complications (β = – 0.191, p = 0.009). Bootstrap mediation analysis revealed that 13.0% of the total effect was mediated through clinical success (p = 0.031). Therapeutic intent was associated with complication risk after SEMS placement, and clinical success may partially account for this association. However, the modest mediated proportion suggests that complications are likely influenced by multiple additional clinical and procedural factors. Optimizing decompression remains important but should be integrated with careful patient selection and follow-up management, particularly in palliative settings.

PMID:42334812 | DOI:10.1007/s13304-026-02730-7

Ir J Med Sci. 2026 Jun 23. doi: 10.1007/s11845-026-04512-x. Online ahead of print.

ABSTRACT

BACKGROUND: Interest in the use of ChatGPT-4o in scenario-based clinical assessment has increased substantially in recent years. However, studies evaluating ChatGPT-4o in pediatric head trauma scenarios and comparing it with different physician groups remain limited.

AIMS: To evaluate the scenario-based performance of ChatGPT-4o in pediatric head trauma and compare it with that of emergency physicians, neurosurgeons, and pediatricians.

METHODS: This study included 60 pediatric patients who presented between 15 December 2024 and 15 June 2025 and met the inclusion criteria. After clinical follow-up, cases were converted into multiple-choice case scenarios and classified into red, yellow, and green zones according to PECARN. These scenarios were answered by 42 physicians from emergency medicine, neurosurgery, and pediatrics (n=14 per group) and by ChatGPT-4o. Concordance of scenario-based management responses with PECARN recommendations was compared statistically.

RESULTS: Of the 60 cases, 25.0% (n=15) were classified as red zone, 50.0% (n=30) as yellow zone, and 25.0% (n=15) as green zone. ChatGPT-4o showed lower scenario-based performance than all physician groups in red-zone cases. When non-contrast brain CT was accepted as the correct option in the yellow zone, ChatGPT-4o had the lowest overall accuracy (median: 24.50). When observation was accepted as correct, ChatGPT-4o showed the highest accuracy both in the yellow zone (median: 17.00; p=0.001) and overall (median: 35.50; p<0.001). ChatGPT-4o showed the highest accuracy in green-zone cases (median: 8.50).

CONCLUSION: ChatGPT-4o did not demonstrate adequate scenario-based performance in critical pediatric head trauma cases. However, it may have potential as a supportive tool in non-critical case scenarios.

PMID:42334770 | DOI:10.1007/s11845-026-04512-x

Ir J Med Sci. 2026 Jun 23. doi: 10.1007/s11845-026-04510-z. Online ahead of print.

ABSTRACT

BACKGROUND: Oxidative stress and antioxidant balance play critical roles in carcinogenesis, particularly among older adults who experience increased oxidative burden. This study explored the association between the composite dietary antioxidant index (CDAI) and cancer prevalence in the elderly.

METHODS: Data from 4,907 elderly participants were analyzed and categorized into quartiles (Q1-Q4) according to CDAI. Logistic regression models estimated odds ratios (ORs) and 95% confidence intervals (CIs) for cancer across quartiles, adjusting for demographic and clinical covariates. Subgroup analyses were performed to evaluate the consistency across subgroups.

RESULTS: Participants with higher CDAI levels were more likely to be male, educated, and have lower diabetes prevalence. The prevalence of cancer increased across CDAI quartiles (19.6% in Q1 to 27.5% in Q4, P < 0.001). In fully adjusted models, Q4 had higher odds of cancer (OR = 1.26, 95% CI 1.02-1.54, P = 0.029). Subgroup analyses indicated stronger associations among women and those with diabetes.

CONCLUSIONS: Unexpectedly, higher CDAI was associated with a greater prevalence of cancer among elderly individuals, suggesting complex, context-dependent effects of dietary antioxidants on cancer prevalence.

PMID:42334769 | DOI:10.1007/s11845-026-04510-z

Intern Emerg Med. 2026 Jun 23. doi: 10.1007/s11739-026-04422-x. Online ahead of print.

ABSTRACT

In recent years, several stakeholders in Italy have suggested a crisis of vocation for Emergency Medicine (EM). This study aimed to verify the accuracy of such claims. We conducted an observational cross-sectional study on data from the Italian national test for residency positions assignments from 2019 to 2025. We analyzed trends in the number of medicine graduates, participants in the national test and available and filled training positions. We then compared EM to other residency programs and four “competitors” considering the ratio among filled and available positions; the absolute and relative variation in available and filled positions; the rate of filled positions over the number of exams’ participants. From 2019 to 2025 training positions grew, while the number of medical school graduates remained stable, the number of candidates decrease and was outnumbered by training positions in 2023-2024. The rate of filled positions in EM dropped from 90% in 2019 to 25% in 2024, then increased to 47% in 2025. Available positions in EM increased from 391 in 2019 to 954 in 2025, at a faster rate than most residency programs. EM absolute filled positions grew from 2022 to 2025, at a faster rate than most competitors. Recent years high rates of unfilled positions in EM is related to the abrupt increase in available positions. Our findings do not confirm a vocational crisis for EM in Italy.

PMID:42334765 | DOI:10.1007/s11739-026-04422-x

Intern Emerg Med. 2026 Jun 23. doi: 10.1007/s11739-026-04398-8. Online ahead of print.

ABSTRACT

Sodium-glucose co-transporter 2 (SGLT2) inhibitors have emerged as cornerstone therapies for heart failure with reduced ejection fraction (HFrEF), owing to their cardioprotective and hematologic effects. While their impact on hemoglobin and hematocrit levels is increasingly recognized, the influence of SGLT2 inhibitors on mean platelet volume (MPV), a surrogate marker of platelet activation and cardiovascular risk, remains underexplored in HFrEF patients. While SGLT2 inhibitors’ effects on MPV have been studied in DM, this is the first study examining MPV changes specifically in HFrEF patients with adjustment for diuretic therapy. This retrospective study included 80 HFrEF patients receiving guideline-directed medical therapy to which SGLT2 inhibitors were subsequently added. Baseline and 6-month follow-up data on hematological and biochemical parameters were collected. Exclusion criteria included active infection, malignancy, advanced renal failure, hematologic disorders, and recent transfusions. MPV and platelet counts were analyzed using standardized protocols and equipment. Following 6 months of SGLT2 inhibitor therapy, MPV values decreased significantly (p < 0.05), while platelet counts increased significantly (p < 0.05). Although hemoglobin and hematocrit levels showed upward trends, these changes were not statistically significant. No significant correlation was observed between ΔMPV and ΔPLT. Other biochemical markers remained stable throughout the study period. SGLT2 inhibitor therapy was associated with a significant reduction in MPV and an increase in platelet count among patients with HFrEF. These hematological changes may represent an additional mechanism by which SGLT2 inhibitors exert cardiovascular benefit. However, prospective, randomized trials are needed to validate these findings and explore the clinical significance of MPV modulation in heart failure management.

PMID:42334763 | DOI:10.1007/s11739-026-04398-8

J Racial Ethn Health Disparities. 2026 Jun 23. doi: 10.1007/s40615-026-03080-1. Online ahead of print.

ABSTRACT

Racial and ethnic disparities in diabetes prevalence and outcomes are well documented; however less is known about whether the selection of treatment modality itself differs across racial groups after adjustment for clinical correlates of disease severity. This cross-sectional analysis used National Health and Nutrition Examination Survey (NHANES) data from the 2017-March 2020 and August 2021-August 2023 cycles. The primary analytical sample comprised 1,688 adults aged 18 years and older with physician-confirmed diabetes, after excluding 46 probable Type 1 cases. Treatment modality was categorized as insulin-only, oral medication-only (base outcome), combination therapy, or no medication, based on self-reported use of insulin and oral antidiabetic medications. Survey-weighted multinomial logistic regression adjusted for age, gender, education, income, birthplace, insurance, HbA1c, body mass index (BMI), and self-reported diabetes duration. Race and ethnicity remained a significant overall predictor of treatment modality after full adjustment (joint Wald p = 0.012). Other/Multi-Racial adults had 57% lower relative risk of insulin-only therapy than Non-Hispanic White (NHW) adults (relative risk ratio [RRR] = 0.43, 95% CI: 0.24-0.76, p = 0.005), and Other Hispanic and Other/Multi-Racial adults had lower relative risk of combination therapy (RRR = 0.56, p = 0.034 and RRR = 0.47, p = 0.043, respectively). Non-Hispanic Black (NHB) adults did not differ from NHWs at the population level. HbA1c, diabetes duration, BMI, and insurance status were the strongest predictors of treatment modality. An exploratory race-by-income interaction model produced a non-significant joint test (p = 0.259) and is reported as hypothesis-generating. Differences in modality use persist after adjustments, suggesting that structural and healthcare-system factors may contribute to treatment variation independently of measured clinical and socioeconomic characteristics.

PMID:42334756 | DOI:10.1007/s40615-026-03080-1

Stat Med. 2026 Jul;45(15-17):e70653. doi: 10.1002/sim.70653.

ABSTRACT

Brain image analysis presents significant challenges due to limitations in precision, computational efficiency, and interpretability. Although neural networks have proven effective for modeling complex patterns, they often function as black-box systems, making their predictions difficult to interpret and limiting their clinical utility. To address these challenges, we propose the adaptive spatial key-region identification (ASKRI) framework-a novel method to identify region of interest, which combines adaptive sampling based on Shannon entropy, probability-mean-driven selection, and spatial uncertainty quantified via kriging method. ASKRI integrates block-to-block kriging with statistical inference to interpolate CNN-derived classification performance, significantly reducing the computational burden of exhaustive model training without sacrificing predictive accuracy. Designed for seamless integration with convolutional neural networks (CNNs), ASKRI enhances both the accuracy and interpretability of ROI identification. Its effectiveness is demonstrated using the traumatic brain injury (TRACK-TBI) dataset, where ASKRI reliably identifies spatially consistent and biologically meaningful regions associated with aging. These results underscore the framework’s potential to advance brain image analysis, while offering transparent and resource-efficient diagnostic support in clinical settings.

PMID:42334752 | DOI:10.1002/sim.70653