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PubMed2026

Diagnostic Performance of Machine Learning for Systemic Lupus Erythematosus: Systematic Review and Meta-Analysis.

BACKGROUND: Early and accurate diagnosis of systemic lupus erythematosus (SLE) and its organ involvement is essential. Previous reviews of machine learning (ML) in SLE combined heterogeneous tasks and validation strategies and may have overinterpreted model performance. OBJECTIVE: This study evaluated the diagnostic performance of ML and deep learning (DL) models for 3 clinically distinct SLE-related tasks: SLE classification or diagnosis, lupus nephritis (LN) diagnosis, and neuropsychiatric systemic lupus erythematosus (NPSLE) discrimination. We also assessed methodological quality and certainty of evidence. METHODS: PubMed, Embase, Cochrane Library, Web of Science, and IEEE Xplore were searched from January 2014 to April 2026. Eligible peer-reviewed diagnostic accuracy studies developed or validated ML or DL models for 1 of the 3 prespecified tasks, used an accepted reference standard, and provided data for a 2×2 contingency table. Bivariate random-effects meta-analyses with the Hartung-Knapp-Sidik-Jonkman adjustment were used to pool sensitivity and specificity. We reported 95% prediction intervals (PIs), assessed risk of bias using the Quality Assessment of Diagnostic Accuracy Studies for Artificial Intelligence tool (QUADAS-AI; Viknesh Sounderajah [Imperial College London]), and evaluated certainty of evidence using the Grading of Recommendations Assessment, Development, and Evaluation framework for diagnostic test accuracy. RESULTS: Twenty-nine studies were included: 17 for SLE classification, 5 for LN diagnosis, and 7 for NPSLE discrimination. In the primary task-stratified analysis, pooled sensitivity was 0.91 (95% CI 0.86-0.94; 95% PI 0.56-0.99), and pooled specificity was 0.94 (95% CI 0.91-0.96; 95% PI 0.69-0.99), with low heterogeneity (I²=23.9% and 22.9%, respectively). DL models showed a sensitivity of 0.93 and specificity of 0.95, compared with 0.88 and 0.94 for traditional ML models. Certainty of evidence was high for most analyses but low for LN diagnosis because of inconsistency and imprecision. All studies were retrospective, and only 9 of 29 (31%) performed independent external validation. Overall risk of bias was high or unclear in 22 of 29 (75.9%) studies. No study reported model calibration, decision-curve analysis, or net clinical benefit. CONCLUSIONS: ML models showed promising diagnostic accuracy across 3 distinct SLE-related tasks, but wide PIs, limited external validation, and pervasive risk of bias restrict conclusions about real-world generalizability. Prospective multicenter studies with standardized tasks and reference standards, independent external validation, and formal assessment of calibration and clinical utility are required before clinical implementation.

Humans↗

PubMed2026

Community pharmacists' perspectives on resupplying and prescribing contraceptives: a descriptive qualitative study in Australia.

OBJECTIVES: Australia has commenced implementing contraceptive resupply and prescribing by community pharmacists to improve equity in method access. This study aimed to investigate pharmacist's acceptability of hormonal contraceptive resupply and prescribing. METHODS: Participants were recruited via convenience sampling and had provided contraceptive counseling consistent with the ALLIANCE intervention (i.e. structured, patient-centered, effectiveness-based care) to women seeking the emergency contraceptive pill or presenting prescriptions for medical abortion medicines. This qualitative descriptive study was embedded within the ALLIANCE trial, whose process evaluation included semi-structured interviews with pharmacist participants. The interview guide, containing questions on pharmacists' views of the resupply and prescribing service, was reviewed by the ALLIANCE Trial Chief Investigators and piloted in June 2024 with the SPHERE Pharmacy Advisory Circle. Thirteen questions were developed using the Theoretical Framework of Acceptability (TFA). Two researchers conducted line-by-line coding using an iteratively refined codebook, with codes mapped to TFA constructs to examine operationalization in pharmacists' delivery of hormonal contraception. KEY FINDINGS: Although pharmacists (n = 24) perceived that the service could be cost- and time-saving to patients, they raised concerns of unintentionally removing general practitioner (GP)-led monitoring of patients and overstepping GPs' roles. While pharmacists felt confident in their expertise and generally supported the service, they expressed hesitation about initiating contraceptive prescriptions, for which they felt further training and access to comprehensive medical records were required. Additional barriers included increased workload pressures, lack of reimbursement, and inadequate staffing. CONCLUSIONS: Overall, providing a resupply service appears to be acceptable to community pharmacists because it relies on the GP's initial assessment but prescribing less so. However, evaluation is needed post-implementation to explore sustainability, feasibility, and long-term impact on patient outcomes.

contraception↗

PubMed2026

Ten years on, still out of reach: barriers to PrEP access and retention in France according to frontline actors (QualiPrEP Study).

Pre-exposure prophylaxis (PrEP) for HIV has been available in France since 2014, and reimbursed since 2016, with general practitioners allowed to prescribe it since 2021. Despite these policy advances, uptake remains low among some of the most affected populations. This community-based qualitative study explored barriers to PrEP access and retention ten years into its implementation.Interviews were conducted with 28 PrEP frontline actors (healthcare professionals and community-based workers involved in promoting, prescribing, or supporting PrEP). The sample included one group discussion (n = 5), two triads (n = 6), two dyads (n = 4), and nine individual interviews (n = 13). Thematic analysis was inductive, with barriers classified across four main domains.Participants were mostly cisgender men, median age 48, born in France and abroad, and employed by NGOs in Paris. Thirteen barriers and four major themes emerged: (1) Internal psychosocial barriers: lack of knowledge, negative health-related reactions; HIV stigma; STI risk perception, taboos; (2) Internal pragmatic barriers: perceived limits of protection, usage and follow-up constraints; (3) External psychosocial barriers: limited physician knowledge and reluctance; (4) External pragmatic barriers: communication failures; structural constraints, lack of human and financial resources.Findings call for more targeted messaging, simplified care models and provider training. They highlight the need to address social and symbolic dimensions of PrEP, with insights from those supporting users to ensure more equitable implementation.

Humans↗

PubMed2026

An automated geometric modeling framework in GATE for the design and optimization of high-sensitivity converging-beam SPECT collimators.

Objective.The trade-off between detection sensitivity and spatial resolution is a fundamental challenge in designing organ-dedicated Single-photon emission computed tomography (SPECT) collimators. While converging-hole geometries offer a solution, their optimization is often hindered by the lack of flexible computational tools capable of modeling large-scale, non-parallel hole arrays. This study aims to develop an automated geometric modeling framework to facilitate the design and evaluation of complex converging- and diverging-hole collimators within standard Monte Carlo environments.Approach.We developed a specialized modeling framework by implementing custom C++ classes and a vector-based alignment algorithm within GATE. This platform enables automated, orientation-consistent construction of large-scale converging arrays not natively supported by standard implementations. A high-sensitivity pure cone-beam collimator (CBC) was designed using this framework. The evaluation used hot-rod, disc, and Jaszczak phantoms for physical characterization, while XCAT and dedicated brain models were employed for clinical tasks, including cardiac, brain perfusion, and DaTscan SPECT simulations.Main results.The CBC achieved a nearly fourfold sensitivity increase compared to a conventional low-energy high-resolution parallel-hole collimator at a 20 cm radius of rotation, while maintaining comparable spatial resolution. Despite a 52.3% field of view reduction, the CBC yielded a 2.2-fold noise reduction (CV: 11.7% vs 25.9%) and mitigated partial volume effects via geometric magnification. XCAT and brain phantom simulations confirmed enhanced anatomical definition and contrast recovery in cardiac, perfusion, and DaTscan tasks.Significance.This work provides an efficient computational tool for rapid design space exploration of advanced collimator geometries. The results demonstrate that the proposed CBC design offers a significant sensitivity advantage, making it highly suitable for high-performance, small-volume clinical applications such as brain and cardiac molecular imaging.

Tomography, Emission-Computed, Single-Photon↗

PubMed2026

Feasibility and barriers to same-day physical therapy following lumbar fusion surgery.

OBJECTIVE: To evaluate the feasibility of same-day (postoperative day 0; POD0) physical therapy (PT) following lumbar fusion and to identify factors associated with failure to participate. METHODS: This retrospective study analyzed prospectively collected data from patients undergoing single-level posterior spinal fusion (PSF), with or without anterior (ALIF) or lateral (LLIF) interbody fusion, between January and December 2024 at a single institution. A standardized POD0 PT protocol was implemented for eligible patients. Patients were categorized into two groups: successful POD0 PT (ambulatory on POD0) and unable to participate. Demographic and surgical variables were compared between groups. Reasons for inability to participate were recorded and categorized. RESULTS: Among 129 patients in whom POD0 PT was attempted, 84 (65%) successfully participated, while 45 (35%) were unable. There were no significant differences in age, sex, BMI, ASA class, operative time, estimated blood loss, or surgical approach between groups. Patients who successfully completed POD0 PT had a significantly shorter hospital length of stay compared to those who did not (3.4 ± 1.6 vs 5.8 ± 2.9 days, P < 0.001), with no differences in complication rates, discharge disposition, emergency department visits, or reoperation rates. The most common barriers to POD0 PT were postoperative pain, medical issues (e.g., orthostatic hypotension, nausea, dizziness), and anesthesia-related somnolence. Less common factors included postoperative restrictions and logistical issues such as brace availability. CONCLUSIONS: POD0 PT following lumbar fusion is feasible in the majority of patients and is associated with a shorter hospital stay without increased complications. Failure to participate was not associated with the baseline patient or surgical characteristics evaluated in this study. Instead, the most common barriers were postoperative pain, transient medical issues, and anesthesia-related somnolence, suggesting that optimization of modifiable perioperative factors may improve the implementation of POD0 PT.

Humans↗

PubMed2026

Patient and Public Involvement and Engagement in Pediatric Health Research: A Systematic Review.

BACKGROUND: Patient and public involvement and engagement (PPIE) can increase the relevance and efficiency of research projects. An overview of PPIE approaches and implementation in pediatric research studies is needed to facilitate learning from others' experiences. OBJECTIVE: We aimed to systematically review practices in PPIE across all pediatric health research disciplines regarding characteristics and recruitment of PPIE participants, timepoints and methods used for PPIE, levels of involvement, benefits and barriers of PPIE. SEARCH STRATEGY: We searched Pubmed, EMBASE, Cochrane and PsycInfo using a comprehensive set of terms based on the concepts 'Patient and Public Involvement,' 'Health Research' and 'Pediatrics.' INCLUSION CRITERIA: We included original research articles describing PPIE implementation in pediatric health research published in English or German between 01/2003-10/2024. DATA EXTRACTION AND SYNTHESIS: Data was extracted using predefined categories and synthesized by narrative summary and thematic synthesis. PPIE reporting quality was assessed using the GRIPP2 short form checklist. MAIN RESULTS: Out of 1910 references, we included 37 original research articles, representing 35 studies. PPIE participants were mostly children, adolescents or caregivers involved in all research stages, especially in study design (89%) and recruitment (51%). Key positive impacts of PPIE on research included enhanced recruitment and retention rates and personal benefits for PPIE participants. Barriers to PPIE were financial and time resources required and challenges in recruiting representative PPIE participants. The level of involvement and PPIE reporting quality varied highly between studies. DISCUSSION: Common benefits and barriers of PPIE exist across pediatric research disciplines. Reporting quality varied highly between studies. CONCLUSIONS: PPIE is valuable in pediatric health research. Adherence to guidelines for conducting and reporting PPIE is important to enhance mutual learning. PATIENT OR PUBLIC CONTRIBUTION: PPIE input contributed to the understandability of the lay summary. The findings of this review, together with parent and public input, will inform guidelines for future PPIE activities at the authors' institutions.

Humans↗

PubMed2026

Data-centric, robust, and explainable multimodal deep learning for clinical decision support: A systematic review.

PURPOSE: Multimodal deep learning is increasingly proposed for clinical decision support (CDS) under a "data-centric" framing that prioritizes label quality, missing-modality robustness, distribution shift, calibration, and explainability. Prior reviews have examined multimodal medical AI, CDS, and data-centric methods separately, but none address their intersection. We mapped the modalities, fusion strategies, and data-centric and explainability techniques used in this recent literature, quantified how often each is implemented rather than merely mentioned, assessed deployment-relevant evidence (external validation, clinical-outcome measurement, equity), and formally appraised study-level risk of bias. METHODS: Following the PRISMA 2020 statement (PROSPERO CRD420261427815; registered retrospectively), we screened 150 records and included primary, clinical, multimodal studies that applied machine or deep learning to a decision-support task and reported at least one quantitative result. Two reviewers screened and extracted data with consensus adjudication. Each study was coded against pre-specified operational definitions, separating implemented or empirically evaluated techniques from those only mentioned. Study-level risk of bias was assessed with PROBAST + AI. Synthesis was narrative. RESULTS: Thirty-one studies met inclusion; 30 (97%) were published between 2024 and 2026, with a median of three modalities (range 2-6), most commonly structured EHR (71%) and imaging (39%). Data-centric techniques were frequently reported (74-84% across label-noise, distribution-shift, calibration, missing-modality and class-imbalance handling; equity 61%). However, external validation was reported in only 4/31 studies (13%), a clinical or provider outcome in 3/31 (10%), and no study reported routine deployment. Overall risk of bias was high in 27/31 studies (87%), driven by the analysis domain. CONCLUSION: Within this recent, self-selected slice of the field, technical robustness and explainability techniques are widely reported but rarely validated out-of-distribution or against clinical outcomes, and the underlying evidence is at high risk of bias. Progress requires external multi-site validation, clinical-outcome measurement, formal bias appraisal, and adherence to AI reporting standards (e.g., TRIPOD + AI) before deployment can be justified.

Deep Learning↗

PubMed2026

Molecular Landscape and Advanced Diagnostic Technologies for BRAF Mutations in Cancer: From Quantitative PCR and ddPCR to CRISPR-Based Platforms.

BRAF mutations are key oncogenic alterations across multiple malignancies, including melanoma, thyroid carcinoma, colorectal cancer, non-small cell lung cancer, glioma, and hairy cell leukemia. The most prevalent variant, BRAF-V600E, induces constitutive activation of the MAPK signaling pathway, promoting tumor progression and influencing therapeutic responsiveness. Accurate detection of BRAF alterations is therefore essential for molecular classification, prognostic assessment, treatment selection, and resistance surveillance. This review summarizes the molecular heterogeneity of BRAF mutations and critically evaluates current diagnostic methodologies. Conventional approaches such as allele-specific PCR and Sanger sequencing are compared with advanced quantitative platforms, including high-resolution melting analysis, droplet digital PCR, and next-generation sequencing, with emphasis on analytical sensitivity, mutation coverage, and clinical applicability. Emerging technologies such as CRISPR-based assays, rolling circle amplification systems, and nanoparticle-based biosensors and point-of-care diagnostic platforms are also discussed for their potential to enhance ultra-sensitive detection, particularly in liquid biopsy settings. These emerging tools are highlighted for their potential to enable ultra-sensitive, rapid, and decentralized mutation detection, particularly in liquid biopsy settings. Key challenges, including intratumoral heterogeneity, low allele-frequency variants, FFPE-associated artifacts, and clonal evolution under therapeutic pressure, are examined within a translational framework. In addition, we examine critical barriers to clinical implementation, including standardization, cost, and global accessibility of molecular diagnostics, and outline potential solutions through scalable technologies and decentralized testing strategies. We propose that optimal BRAF testing requires a mutation subclass-informed and clinically integrated strategy combining comprehensive baseline profiling with longitudinal molecular monitoring. Future diagnostic paradigms will likely integrate multi-omics data and artificial intelligence (AI)-assisted interpretation to refine precision oncology implementation. Looking forward, we propose that optimal BRAF testing will require integration of multi-omics profiling with AI-assisted interpretation, enabling automated variant classification, real-time clinical decision support, and improved prediction of therapeutic response and resistance.

Humans↗

PubMed2026

Process evaluation of a nurse-led transitional care model (Cardiolotse) within a randomized controlled trial aiming to improve care coordination for patients with cardiovascular diseases in Germany.

BACKGROUND: Patients with higher age suffering from cardiovascular disease discharged from hospital are at greater risk of readmission within 30 days. We evaluated an innovative care program providing post-discharge support and helping patients to navigate through the healthcare system. This paper reports the findings of the process evaluation of the randomized controlled trial Cardiolotse, a nurse-led transitional care model improving care coordination for patients with cardiovascular diseases in Germany. METHODS: A process evaluation, following the guidelines of the Medical Research Council (MRC) Framework, was performed. Semi-structured interviews with all relevant target groups were conducted to gain more insight about implementation processes. Questionnaires and medical records were used to explore mechanisms of impact and understand how change was produced in the intervention. Qualitative data were analysed using content analysis with deductive and inductive categories. Descriptive statistics and subgroup analyses were utilized to explore quantitative data. RESULTS: Overall, the designed training programme was perceived positively by the study nurses, so called Cardiolotsen (CLs). Patients receiving support by the CLs reported positive satisfaction ratings. Interactions between CLs and patients were reported as trustworthy and reliable. A total of approximately 12,500 contacts were made over the course of the intervention. However, changes in satisfaction scores between intervention and control groups in terms of medical treatment or the interaction between medical health providers involved in the treatment could not be determined. Furthermore, data suggested reach issues with respect to office-based physicians, as regular CL contact could not be achieved with 90% of the participating general practitioners and cardiologists. CONCLUSIONS: The CLs served as an important source of support for the participating patients throughout the intervention. At regular intervals, they checked a patient's health status and their adherence to therapies after discharge. However, the process evaluation identified cross-sectoral communication and information exchange between CLs and office-based physicians as an implementation challenge. TRIAL REGISTRATION: The study was retrospectively registered at German Clinical Trial Register, http://www.drks.de/DRKS00020424 (Trial Registration Number DRKS00020424) on 18 June 2020.

Humans↗

PubMed2026

Artificial intelligence-supported double reading in European population breast cancer screening: A systematic review and meta-analysis of prospective programs.

BACKGROUND: Most European population mammography screening programs rely on double reading with arbitration, a model that delivers mortality benefit but is increasingly challenged by radiologist workload, variable specificity, and interval cancers. Artificial intelligence (AI) is being evaluated to support or optimize these established European screening pathways. PURPOSE: To synthesize prospective or program-embedded evaluations of AI conducted within European-style population screening programs and to estimate exploratory program-level absolute risk differences (RDs) per 1000 examinations for cancer detection rate (CDR) and recall. MATERIALS AND METHODS: We performed a prespecified, focused evidence synthesis of three large studies embedded within routine population screening programs operating under European-relevant workflows: MASAI (randomized AI-supported risk triage within a national program), ScreenTrustCAD (prospective paired-reader evaluation with AI as an independent reader in a double-reading framework), and PRAIM (nationwide decision-referral implementation). Outcomes were harmonized as AI-control RDs per 1000 examinations. Random-effects pooling used Hartung-Knapp-Sidik-Jonkman models. For the paired-reader design, sensitivity analyses applied a Kish effective sample-size approach across plausible within-examination correlations (ρ = 0.3-0.8). Positive predictive value (PPV) and workflow/time outcomes were summarized descriptively. RESULTS: Across 597,419 examinations, the pooled CDR RD was +0.9 per 1000 (95% CI -0.0 to +1.8; I2 ≈ 12%), consistent with a modest directional increase with borderline statistical uncertainty. The pooled recall RD was -0.6 per 1000 (95% CI -3.1 to +2.1; I2 ≈ 41-43%), indicating no consistent recall increase across screening programs. Where reported, PPV was higher with AI-supported screening. Efficiency signals included 44.3% fewer total readings in MASAI and shorter reading times for AI-normal examinations in PRAIM; in PRAIM, a program-level safety-net mechanism recovered 204 cancers that would otherwise have been missed. CONCLUSION: In European population screening programs characterized by double reading and arbitration, prospective program-embedded evidence suggests that AI integration may yield a small absolute increase in cancer detection (≈1/1000) without a consistent increase in recall, alongside improved PPV and efficiency signals. These findings suggestAI primarily as a complementary reader within European screening workflows, with implementation requiring explicit quality assurance and monitoring of interval cancers and stage distribution.

Humans↗

PubMed2026

Changes in heroin-related ambulance attendances following the introduction of a medically supervised injecting room in Victoria, Australia.

BACKGROUND: Injecting drug use contributes significantly to morbidity, mortality and broader social harms globally. Supervised Injecting Facilities (SIFs) are harm reduction interventions that reduce overdose risk and facilitate access to health services for marginalised individuals. While international evidence supports the effectiveness of SIFs, Australian population-level surveillance data quantifying their impact on emergency medical service utilisation remain limited. METHODS: Using data from the National Ambulance Surveillance System, we conducted a retrospective, interrupted time series analysis of heroin-related ambulance attendances within the local catchment of the Medically Supervised Injecting Room (MSIR) between January 2015 and December 2023. Supplementary analysis included comparisons with central Melbourne suburbs and the broader state of Victoria. Key intervention timepoints, including the opening of the MSIR on 30 June 2018, expansion of its operating hours in July 2019, and the COVID-19 pandemic from April 2020 to October 2021, were examined to assess changes in heroin-related attendances over time. Segmented regression models were used to assess changes in heroin-related ambulance attendance trends over time. RESULTS: At the time the MSIR opened, the model-predicted heroin-related ambulance attendance rate within the MSIR catchment was 123 per 100,000 population per month, equivalent to approximately 48 heroin-related ambulance attendances per month. Prior to implementation, the attendance rate was increasing by an estimated 0.74 per 100,000 population per month. Following the opening of the MSIR, the previously increasing trajectory reversed, with ambulance attendance rates declining by approximately 2.3 per 100,000 population per month relative to the pre-intervention trend. By the end of the study period (December 2023), the predicted monthly heroin-related ambulance attendance rate had declined to 36 per 100,000 population (approximately 14 attendances per month), representing an overall reduction of 70.7% from the time of MSIR implementation. These reductions persisted throughout the COVID-19 lockdown period and were sustained after restrictions lifted. Supplementary analysis showed no comparable reductions in the central Melbourne region or the remainder of Victoria. CONCLUSIONS: The introduction of the MSIR in Richmond was associated with a sustained reduction in heroin-related ambulance attendances within its catchment area. These findings provide strong population-level evidence that SIFs reduce acute heroin-related harms requiring emergency ambulance response, reinforcing their role as an effective harm reduction strategy within the Australian context.

Humans↗

PubMed2026

Leveraging traveller genomics for LMIC diarrhoeal disease management.

Diarrhoeal pathogens impose a substantial global health burden, disproportionately affecting low- and middle-income countries (LMICs). However, in these settings, health-seeking behaviours, suboptimal microbiological capacity, and challenges in establishing genomics capacity constrain effective surveillance, including surveillance of antimicrobial resistance (AMR). In contrast, high-income countries routinely generate and share large volumes of diarrhoeal pathogen genomes through established systems, with a significant proportion originating from travellers returning from LMICs. These data reveal strong geographical structuring of lineages and clinically relevant AMR patterns, demonstrating untapped potential to support improvements in geographically granulated surveillance to support antimicrobial treatment recommendations. In this opinion article, we outline the potential to integrate traveller-derived microbial genomic data into LMIC public health decision-making and highlight the scientific, ethical, practical, and governance considerations for implementation.

antimicrobial resistance↗

PubMed2026

External ventricular drain safety campaign and opportunities for global neuroanesthesiology quality and safety.

PURPOSE OF REVIEW: This review describes the conceptualization and implementation of the External Ventricular Drain (EVD) Safety Campaign, a global patient safety initiative by the Society for Neuroscience in Anesthesiology and Critical Care. It summarizes recent literature on EVD insertion and maintenance, highlights opportunities to advance quality and safety in neuroanesthesiology, and outlines priorities and a framework for future work. RECENT FINDINGS: The Society for Neuroscience in Anesthesiology and Critical Care launched a global initiative to improve EVD management. EVD insertion and maintenance remain key areas of ongoing research and quality improvement, particularly in reducing complications. SUMMARY: The EVD Safety Campaign provides a structured framework to improve care delivery and patient outcomes worldwide. Continued focus on standardization, education, and complication reduction, especially infection prevention, will be essential to advancing the field.

Humans↗

PubMed2026

Perioperative Depression and Anxiety Care in Older Patients: A Randomized Clinical Trial.

IMPORTANCE: Depression and anxiety are common among older adults undergoing surgery and are associated with adverse postoperative outcomes. However, effective tailored perioperative mental health interventions are lacking. OBJECTIVE: To evaluate a perioperative intervention to optimize mental health. DESIGN, SETTING, AND PARTICIPANTS: A single-blind, hybrid, type 1, effectiveness-implementation randomized clinical trial was conducted (November 1, 2022, to March 31, 2025), with 3-month postoperative follow-up, at a US academic and community practice hospital network. Participants were 60 years or older; scheduled for cardiac, oncologic, or orthopedic surgery; and had clinically meaningful symptoms of depression and/or anxiety based on the Patient Health Questionnaire-Anxiety and Depressive Symptom (PHQ-ADS) scale. A total of 3159 patients were screened for eligibility, with 1518 ineligible, 1079 declining participation, and 236 excluded for other reasons. A total of 326 patients were enrolled and randomized (1:1), with 20 excluded after surgery cancelation. INTERVENTION: Participants were assigned to receive a perioperative intervention combining psychological management and pharmacologic optimization or enhanced usual care (materials for self-managing symptoms). MAIN OUTCOMES AND MEASURES: The primary outcome was change in PHQ-ADS score from baseline to 3 months after surgery. Other outcomes included persistent postsurgical pain, delirium, falls, quality of life, patient satisfaction, length of stay, and rehospitalizations. Implementability was evaluated through semistructured interviews and reach, acceptability, feasibility, appropriateness, and fidelity measures. RESULTS: A total of 306 older adults were included in analysis (mean [SD] age, 68.5 [6.1] years; 209 [68.3%] female; 153 randomized to intervention and 153 randomized to enhanced usual care): 102 cardiac, 100 oncologic, and 104 orthopedic patients. Participants' mean (SD) baseline PHQ-ADS score was 18.5 (7.4). At 3 months, there was a significant decrease in PHQ-ADS scores in the intervention group compared with the enhanced usual care group (mean difference, 2.20; 95% CI, 0.16-4.24; P = .03). Effects varied by surgical subgroups (oncologic patients: mean difference, 4.93; 95% CI, 1.51-8.36; P = .005; cardiac patients: mean difference, 2.68; 95% CI, -0.98 to 6.35; P = .15; and orthopedic patients: mean difference, -1.11; 95% CI, -4.62 to 2.40; P = .54). Patients and interventionists perceived the intervention as appropriate, with high-fidelity delivery and broad reach across the target population. CONCLUSIONS AND RELEVANCE: In this randomized clinical trial, psychological management and pharmacologic optimization reduced anxiety and depression in older adults undergoing surgery. Future studies should assess reproducibility and determine which patients benefit most. TRIAL REGISTRATION: ClinicalTrials.gov Identifiers: NCT05575128, NCT05685511, and NCT05697835.

Humans↗

PubMed2026

Performance of AI-Based Screening Tools for Obstructive Sleep Apnea Across Apnea-Hypopnea Index Thresholds: Systematic Review and Meta-Analysis.

BACKGROUND: Obstructive sleep apnea (OSA) is highly prevalent but remains substantially underdiagnosed. Polysomnography (PSG) is the reference standard, but its cost and limited availability constrain large-scale case identification. AI-based screening tools may support risk stratification and referral prioritization, but their diagnostic accuracy across apnea-hypopnea index (AHI) thresholds remains uncertain. OBJECTIVE: This review aimed to systematically evaluate the diagnostic accuracy of AI-based OSA screening tools at AHI thresholds of ≥5, ≥15, and ≥30 events/hour, with emphasis on models using non-PSG-derived inputs. METHODS: PubMed, Embase, Scopus, and Web of Science were searched for studies published from January 1, 2016, to May 3, 2026. Eligible studies included adults evaluated for suspected OSA or recruited from population-based cohorts, assessed AI-based models intended or interpretable for OSA screening, risk prediction, or screening-oriented severity classification, used PSG as the reference standard, and reported sufficient data to construct or reconstruct 2×2 contingency tables. Diagnostic accuracy was synthesized separately by AHI threshold and input source using bivariate random-effects models, with 95% CIs and prediction intervals (PIs). Risk of bias and certainty of evidence were assessed using QUADAS-2 (Quality Assessment of Diagnostic Accuracy Studies 2) and GRADE (Grading of Recommendations Assessment, Development, and Evaluation), respectively. RESULTS: A total of 60 studies were included, of which 47 contributed data to the meta-analysis. At AHI thresholds of ≥5, ≥15, and ≥30 events/hour, pooled sensitivities were 0.94 (95% CI 0.92-0.96; 95% PI 0.71-0.99), 0.87 (95% CI 0.84-0.89; 95% PI 0.66-0.96), and 0.83 (95% CI 0.79-0.87; 95% PI 0.61-0.94), respectively; the corresponding specificities were 0.77 (95% CI 0.69-0.84; 95% PI 0.30-0.96), 0.81 (95% CI 0.75-0.85; 95% PI 0.39-0.96), and 0.91 (95% CI 0.87-0.94; 95% PI 0.55-0.99), respectively. The corresponding areas under the summary receiver operating characteristic curves were 0.943, 0.907, and 0.920. For non-PSG-derived tools, sensitivities were 0.92, 0.85, and 0.81, and specificities were 0.70, 0.74, and 0.85 at the 3 thresholds, respectively. For PSG-derived models, sensitivities were 0.96, 0.90, and 0.85, and specificities were 0.82, 0.88, and 0.96, respectively. Exploratory subgroup analyses suggested performance variation across selected study and model characteristics, including region, algorithmic framework, data source, and validation method. CONCLUSIONS: AI-based tools showed generally favorable screening performance for OSA across clinically relevant AHI thresholds, although wide PIs suggest variable performance across future comparable populations and settings. By synthesizing diagnostic accuracy across 3 AHI thresholds and distinguishing non-PSG-derived from PSG-derived models, this review extends previous broad or modality-specific reviews and offers a clinically interpretable, pathway-specific basis for linking model performance to intended use. The findings may clarify potential roles for non-PSG-derived tools in front-end screening and referral prioritization and for PSG-derived models in reduced-channel assessment and sleep-laboratory workflow support. Given substantial heterogeneity, limited external validation, and low or very low certainty of evidence, prospective validation is needed before routine implementation.

Humans↗

PubMed2026

Cost-Effectiveness of Electronic Patient-Reported Outcome Measure Interventions in Cancer: Systematic Review and Parameter Extraction for Economic Modeling.

BACKGROUND: Complex digital interventions that integrate electronic patient-reported outcome measures (ePROM) into clinical practice in cancer have the potential to improve quality of life, increase survival, and reduce health resource use and costs. Such systems can help patients with cancer self-manage chemotherapy symptoms, reduce clinicians' workloads through automated decision support, and resolve problems earlier. However, more research on the cost-effectiveness of ePROM monitoring is needed. OBJECTIVE: This paper comprises two complementary components: (1) a systematic literature review summarizing and evaluating the quantitative and qualitative evidence related to the cost-effectiveness of ePROM monitoring and (2) a health economic model parameter extraction. We also conducted supplementary targeted searches and scoping to provide context to our findings. METHODS: We searched Ovid (including MEDLINE and Embase), Scopus, and the International Health Technology Assessment Database for original English-language papers published on or before March 2025 using search strings that combined terms related to ePROMs, health economics, and cancer/oncology. We included papers reporting health economic-related outcomes for ePROM interventions designed for adult cancer populations and excluded screening tools and conference abstracts. RESULTS: We included 34 publications from 27 unique studies and identified and analyzed 26 ePROM-integrated interventions within these. Most (23/26) of the included interventions explicitly described some form of alert handling and automated decision support based on remote ePROM monitoring. Of the 34 publications, 5 presented full cost-effectiveness analysis results, of which 3 were highly uncertain and lacked clear differences in costs and health outcomes between ePROMs and standard care; conversely, 2 presented strong evidence of cost-effectiveness due to quality-of-life improvements, reduced hospitalizations, and potentially more autonomy in health-related travel (eg, ePROM-monitored patients can drive or walk to the hospital instead of using taxis or ambulances). A further 5 publications reported partial health economic results (eg, cost-consequence and budget impact), of which 1 detected no difference in strategies; in contrast, 4 reported lower health resource use and costs of ePROMs, mainly due to hospitalization reductions. Overall, 12 of the 27 studies included a qualitative component but mostly focused on user experience and design-related themes; only 2 of these addressed economic-specific themes (eg, changes in workflow and resource use due to ePROM implementation and integration), indicating some potential for time saving due to ePROM monitoring. CONCLUSIONS: Some ePROM-integrated interventions demonstrated cost-effectiveness in cancer care, but the evidence base remains limited. Where evidence does exist, cost-effectiveness appears driven by reduced hospitalization and improved quality of life. Qualitative research within the included studies rarely addressed economic questions. We provide a detailed parameter extraction for use in future economic modeling and recommend research priorities, including quantitative mapping of ePROM symptom data onto health resource use patterns, and qualitative work exploring how ePROM implementation affects clinical workloads and patient-perspective costs.

Humans↗

PubMed2026

Nourishing collaboration: interdisciplinary nutrition education for health care professionals.

Nutrition education remains insufficient in many health care professional training programs despite the central role of diet in the prevention and management of chronic disease. Contemporary nutrition science increasingly recognizes that dietary behaviors and health outcomes are shaped by complex interactions among biological, behavioral, environmental, and food system factors. This perspective proposes an interdisciplinary framework for nutrition education that integrates the complementary expertise of physicians, dietitians, chefs, and farmers. By bridging clinical care, nutrition science, culinary practice, and agricultural systems, such an approach may strengthen the translation of evidence into practice, improve nutrition-related competencies among health care professionals, and ultimately enhance population health outcomes.

Humans↗

PubMed2026

Standardized visual overlays enhance laparoscopic instruction: A mixed-methods evaluation.

Effective communication during laparoscopic procedures is frequently undermined by spatial disorientation and inconsistent terminology between instructors and trainees. This study examined whether standardized visual overlays on endoscopic monitors could enhance communication and learning. We conducted a three-phase mixed-methods study: qualitative observation of 20 laparoscopic teaching cases; a randomized trial of 63 second-year medical students assigned to control, clock, or alphanumeric grid (AG) overlays during three trials of a standardized transfer task; and intraoperative implementation in 44 cases (30 AG, 14 clock) with post-case surveys and qualitative feedback. In simulation, the clock overlay produced the fastest completion times, whereas the AG yielded the lowest error scores, and both overlays outperformed the control. Intraoperatively, the AG was rated higher than the clock for communication clarity, spatial orientation, perceived operative efficiency, and trainee confidence. Standardized visual overlays, particularly the AG, appear to support intraoperative teaching by providing a shared spatial frame of reference.

Laparoscopy↗