Tag: pubmed

Eur Stroke J. 2026 May 6;11(5):aakag050. doi: 10.1093/esj/aakag050.

ABSTRACT

INTRODUCTION: Although epidemiological studies often group the Baltic states together, they differ significantly in national stroke care legislation and infrastructure. Our study aimed to explore and compare the current state of stroke care in Lithuania, Latvia and Estonia.

PATIENTS AND METHODS: We analysed the Stroke Action Plan for Europe (SAP-E) Stroke Service Tracker data from 2022, including data from the respective National Health Insurance Funds and direct centre-level queries. Geographic Information System-based modelling assessed population access to stroke-ready hospitals within 1 h. Key metrics, including hospitalised stroke incidence, stroke unit admission, recanalisation therapy and in-hospital as well as 30-day mortality, were compared using Z-tests for proportions.

RESULTS: The hospitalised stroke incidence per 100,000 inhabitants was similar in Lithuania (353) and Latvia (354), but lower in Estonia (246), despite similar population structures. Lithuania had the highest proportion of its population (94.0%) with access to a stroke-ready hospital within 1 h, followed by Latvia (87.1%) and Estonia (84.7%, P < .001). Estonia had the highest proportion of stroke unit admission rates and the lowest mortality rates-9.6% (in-hospital) and 15.0% (30-day) for ischaemic stroke. Endovascular treatment was most frequent in Lithuania (8.6% of all strokes, P < .001), while Estonia had the highest rate of intravenous thrombolysis (29.0%, P < .001).

CONCLUSIONS: Despite broadly comparable populations and formal SAP-E alignment, the Baltic states exhibit marked differences in stroke access, treatment and outcomes. High stroke unit admissions and high recanalisation rates in Estonia may be associated with lower ischaemic stroke mortality, underscoring the importance of system design beyond geographic coverage alone.

PMID:42202277 | DOI:10.1093/esj/aakag050

JMIR Med Educ. 2026 May 27;12:e87483. doi: 10.2196/87483.

ABSTRACT

BACKGROUND: The Objective Structured Clinical Examination (OSCE) is a prevalent method for evaluating clinical competence in medical education. As OSCEs become increasingly standardized and resource intensive, alternative evaluation methods are being explored, particularly because of the limited availability of certified examiners. However, few studies have investigated whether wearable technologies can support OSCE assessment. Wearable devices may provide a means of recording clinical skills from the examiner’s perspective.

OBJECTIVE: This pilot study, conducted in 2024, aimed to investigate the feasibility of using an examiner-worn neck-mounted camera for recording OSCE scenarios and to evaluate the evaluability of clinical performance from the recorded footage.

METHODS: In total, 9 experienced medical educators participated in a simulated OSCE scenario involving electrocardiogram lead placement. All participants completed the initial live assessment and the postuse questionnaire, while 8 of 9 (89%) participants completed the subsequent video-based reassessment. Video recordings from both a fixed camera and a neck-mounted camera (THINKLET) were used to assess the evaluability of each OSCE item. Following a washout period, evaluators reassessed the neck-mounted camera recordings by using the original checklist, while fixed-camera recordings were used to judge the evaluability of each item. Agreement between live and video-based scoring was analyzed using percent agreement and the Cohen κ coefficient. A postevaluation questionnaire captured evaluators’ experiences with the wearable device.

RESULTS: Cohen κ ranged from 0.258 to 0.913 (mean 0.67, SD 0.20). Across checklist observations, more items were judged to be evaluable in the neck-mounted camera recordings than in the fixed-camera recordings, particularly for tasks requiring observation of fine motor skills. Evaluators reported generally positive experiences with the device, although some noted issues related to audio quality, comfort, posture restriction, and limited visibility at low angles.

CONCLUSIONS: Although further investigation is needed, this pilot study suggests that an examiner-worn neck-mounted camera may be a valuable supplementary assessment tool for selected OSCE tasks. Further work is needed to refine the device, standardize recording protocols, and clarify how it can best support review and verification alongside live evaluation.

PMID:42202275 | DOI:10.2196/87483

JMIR Res Protoc. 2026 May 27;15:e92264. doi: 10.2196/92264.

ABSTRACT

BACKGROUND: Mis-triage represents a global concern, with reported rates ranging from 15% to 33%. Understanding its causes and contributing factors is essential for ensuring patient safety. Currently, available studies have mainly focused on evaluating triage systems rather than investigating the human factors affecting triage performance. A major limitation in triage evaluation studies is the lack of standardized criteria to assess patient acuity and the absence of a clear consensus on how to measure triage accuracy. Most studies rely on retrospective data, which often fail to capture real-life clinical complexity. Therefore, the underlying causes and consequences of mis-triage remain partially understood.

OBJECTIVE: This study aims to improve triage by defining the optimal triage evaluation process and identifying clinician-, patient-, and system-level factors that compromise its accuracy and safety.

METHODS: Reducing Mis-Triage in Emergency Departments (RemEDy) will be a 4-phase, mixed methods project conducted across 7 Swiss emergency departments. The first phase will focus on developing a standardized triage evaluation instrument, combining evidence from a scoping review of triage evaluation processes, workshops with triage clinicians using design thinking methodology, and a modified Research and Development-University of California Delphi involving international experts and patient representatives. The second phase will prospectively implement this instrument in real time within a multicenter observational cohort study to evaluate triage performance; quantify mis-triage; and identify predictors at the patient level (eg, demographics), clinician level (eg, training), and system level (eg, crowding and length of stay). The third phase will focus on designing and validating an artificial intelligence-based decision support tool, applying multimodal models that integrate real-time triage data to enhance acuity prediction and minimize human error. The fourth phase will develop and evaluate a targeted training program, guided by the Capability, Opportunity, Motivation, and Behavior model, to strengthen triage accuracy and mitigate cognitive biases.

RESULTS: The project was funded by the Swiss National Science Foundation in March 2025 (grant 10004535). At submission, the scoping review is ongoing and expected to be completed in early 2026. Development and piloting of the triage evaluation instrument will take place in 2026. A multicenter cohort study is planned between October 2026 and June 2027. The intervention study is scheduled between October 2027 and December 2028. Final results are expected in 2029.

CONCLUSIONS: The RemEDy project addresses key limitations of current triage research, including the lack of standardized evaluation methods. By combining expert and clinician consensus; real-time assessment; and multilevel analysis of patient-, clinician-, and emergency department-level factors, RemEDy is expected to provide a more comprehensive understanding of mis-triage and its causes. RemEDy will establish a novel framework for real-time triage evaluation and inform the development of targeted training programs with the potential to improve triage accuracy, safety, and equity.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/92264.

PMID:42202274 | DOI:10.2196/92264

JMIR Perioper Med. 2026 May 27;9:e89277. doi: 10.2196/89277.

ABSTRACT

BACKGROUND: Effective postoperative communication is vital for patient recovery, yet traditional text-based discharge instructions often lead to poor comprehension and adherence, particularly among patients with limited health literacy. Although educational videos improve understanding and retention, their widespread use has been hampered by high production costs. Generative artificial intelligence (AI) offers a scalable solution for creating engaging video content.

OBJECTIVE: The primary objective of this pilot study was to assess the feasibility of creating and deploying AI-generated, avatar-led videos for postoperative instruction delivery. Secondary objectives included comparing knowledge retention, engagement, perceived clarity, and user experience between AI-generated video and traditional text-based handout formats among health care workers.

METHODS: In this randomized pilot study, 38 health care worker volunteers were recruited as a convenience sample to pilot-test the intervention before patient implementation. Participants were assigned to either a text handout group (n=19, 50%) or an AI-generated video group (n=19, 50%). Both groups received information on 10 common postoperative topics. The primary outcome was objective knowledge, assessed via a 10-item quiz. Secondary outcomes, measured through surveys with 5-point Likert scales, included engagement time, subjective engagement, perceived clarity, usefulness, confidence in understanding, and information retention. Qualitative feedback was also collected.

RESULTS: Objective knowledge quiz scores did not differ significantly between groups (mean 8.89, SD 1.20 for the AI-generated video group vs mean 8.21, SD 1.78 for the text handout group; P=.17; Cohen d=0.45). Participants in the AI-generated video group demonstrated significantly higher engagement time (mean 15.11, SD 7.78 minutes vs mean 8.84, SD 4.03 minutes; P=.004; Cohen d=1.04). They also rated instructions as significantly clearer (mean 4.63, SD 0.50 vs mean 4.00, SD 0.82; P=.007; Cohen d=0.93), more engaging (mean 4.05, SD 0.78 vs mean 3.32, SD 1.00; P=.02; Cohen d=0.81), and more effective for retention (mean 4.42, SD 0.84 vs mean 3.37, SD 0.68; P<.001; Cohen d=1.38). Qualitative feedback highlighted the engaging nature of AI-generated videos but noted areas for avatar refinement.

CONCLUSIONS: In this pilot study with health care workers, AI-generated avatar videos did not improve objective knowledge scores but significantly enhanced engagement, perceived retention and perceived clarity (Cohen d=0.81-1.38). Future studies in actual patient populations with diverse health literacy levels are needed to determine whether these engagement advantages translate into improved knowledge outcomes.

PMID:42202261 | DOI:10.2196/89277

J Clin Oncol. 2026 May 27:JCO2501441. doi: 10.1200/JCO-25-01441. Online ahead of print.

ABSTRACT

NRG Oncology RTOG 0539 was a prospective phase II trial of risk-adapted radiotherapy for patients with WHO grade 1-3 meningioma. Low-risk (group 1, n = 60) was defined as a grade 1 tumor after gross total resection or subtotal resection (GTR/STR) and prospectively monitored. Intermediate-risk (group 2, n = 52) was defined as recurrent grade 1 or newly diagnosed grade 2 tumor after GTR and treated with radiotherapy (54 Gy). High-risk (group 3, n = 53) included a newly diagnosed grade 2 tumor after STR, newly diagnosed grade 3 tumor, or recurrent grade 2 or 3 tumor and treated with radiotherapy (60 Gy). Progression-free survival (PFS) and overall survival (OS) were estimated using the Kaplan-Meier method. The median follow-up times for the low-, intermediate-, and high-risk cohorts were 12.1, 12.0, and 11.1 years, respectively. The 10-year PFS and OS rates for the low-, intermediate-, and high-risk cohorts were 85.2% and 94.1%, 72.2% and 84.7%, and 42.5% and 51.1%, respectively. Five patients (9.6%) and eight patients (15.1%) had a grade 3+ toxicity attributed to radiotherapy in the intermediate- and high-risk cohorts, respectively. The long-term outcomes using this risk-adapted approach support observation for low-risk patients, inform radiotherapy patient selection and practice standards for intermediate- and high-risk patients, and provide comparative benchmarks for future trials.

PMID:42202246 | DOI:10.1200/JCO-25-01441

IEEE J Biomed Health Inform. 2026 May 27;PP. doi: 10.1109/JBHI.2026.3694093. Online ahead of print.

ABSTRACT

Autism Spectrum Disorder (ASD) is a complex neurodevelopmental condition with increasing global prevalence and no standardized biological test for early detection. Current diagnosis methods rely heavily on behavioral assessments, which are subjective, time-consuming, and prone to variability. This study proposes a hybrid feature fusion framework for non-invasive ASD diagnosis using electroencephalogram (EEG) signals, specifically event-related potentials (ERPs) such as P300 components obtained from the BCIAUT-P300 dataset. EEG recordings were captured using a g.Nautilus wireless system with eight scalp electrodes, and preprocessed using 0.5-30 Hz bandpass filtering and baseline subtraction to enhance signal quality. Twenty-two EEG features were extracted across time, frequency, and time-frequency domains using methods such as Wavelet Transform, power spectral density, higher-order statistics, and principal component analysis. Five optimal methods, PCA, HOS, PSD, FDA, and CWT, were selected based on their classification potential and fused using both feature-level and decision-level strategies. Ensemble classifiers including SVM, XGBoost, LDA, and Random Forest were trained and evaluated on the fused feature set. The proposed hybrid fusion framework achieved a classification accuracy of 97.7%, sensitivity of 96.8%, and specificity of 98.5%, outperforming traditional single feature or single classifier approaches. The integration of multi-domain feature descriptors with ensemble learning contributes to increased robustness, generalizability, and diagnostic precision. Our work demonstrates the feasibility of combining EEG-based biomarkers with machine learning to support early ASD diagnosis. The framework offers a scalable approach that is aligned with biomedical informatics objectives, with potential for clinical deployment and integration into portable EEG-based screening systems.

PMID:42202207 | DOI:10.1109/JBHI.2026.3694093

JMIR Diabetes. 2026 May 27;11:e95855. doi: 10.2196/95855.

ABSTRACT

BACKGROUND: The triglyceride-glucose (TyG) index has demonstrated promising predictive capability in clinical studies, but its distribution characteristics across different age and sex groups in the Chinese population have not been fully characterized.

OBJECTIVE: This study aimed to describe the population-based distribution of the TyG index.

METHODS: A total of 4621 participants aged 20-80 years from the China National Health Survey were included in this study. The TyG index was calculated from fasting blood glucose and triglycerides. The age- and sex-specific distribution values of the TyG index were obtained using the percentiles method.

RESULTS: Males had higher BMI (23.32, SD 2.63 vs 22.72, SD 2.60 kg/m2), triglyceride (133.78, SD 78.07 vs 111.58, SD 61.18 mg/dL), fasting glucose (97.05, SD 11.95 vs 94.34, SD 10.46 mg/dL), and TyG index values (8.63, SD 0.54 vs 8.45, SD 0.50) than females. The TyG index of males reached its peak value at approximately 40 years of age. The lower limit percentile values for females exceeded that of males around age 50. After the age of 60, the upper limit of the distribution values in females was higher than in males.

CONCLUSIONS: This study characterized the age- and sex-specific distribution of the TyG index among Chinese adults aged 20-80 years. The results of this study contribute to a more precise assessment of glucolipid metabolism.

PMID:42201745 | DOI:10.2196/95855

JAMA Netw Open. 2026 May 1;9(5):e2614490. doi: 10.1001/jamanetworkopen.2026.14490.

ABSTRACT

IMPORTANCE: Peer support is a promising strategy to improve breastfeeding outcomes, but evidence for online formats is limited.

OBJECTIVE: To evaluate whether structured peer support delivered via video calls improves exclusive breastfeeding rates and maternal breastfeeding self-efficacy.

DESIGN, SETTING, AND PARTICIPANTS: This multicenter, randomized clinical trial enrolled first-time mothers with low breastfeeding confidence from 4 public postnatal wards in Hong Kong from January 31, 2021, to June 30, 2024. Participants were randomly assigned (1:1) to intervention or control. The primary analysis was conducted from July 1 to 31, 2024, with final data analysis completed by December 31, 2025.

INTERVENTION: The intervention included usual postnatal care, consisting of access to lactation consultants and standard breastfeeding information from the Department of Health, plus at least 2 video call sessions with trained peer support volunteers at 10 days and 1 month post partum.

MAIN OUTCOMES AND MEASURES: The primary outcome was the proportion of infants who were exclusively breastfed at 6 months post partum. Secondary outcomes included exclusive breastfeeding at 1, 2, and 4 months post partum and maternal self-efficacy (measured using the Breastfeeding Self-Efficacy Scale-Short Form) at 2 and 4 months. All outcomes were analyzed on an intention-to-treat basis.

RESULTS: Among 442 participants, 224 were allocated to the intervention group and 218 were allocated to the control group. The mean (SD) maternal age was 32.4 (4.0) years (32.4 [4.2] years in the intervention group and 32.3 [3.9] years in the control group). The primary 6-month outcome did not differ significantly between groups (37 of 184 [20.1%] vs 29 of 186 [15.6%]; adjusted odds ratio [AOR], 1.57 [95% CI, 0.85-2.89]; P = .15); however, exclusive breastfeeding at 2 months (a secondary outcome) was significantly higher in the intervention group (54 of 199 [27.1%] vs 38 of 200 [19.0%]; AOR, 1.80 [95% CI, 1.08-3.01]; P = .02). Longitudinal analysis confirmed higher odds of exclusive breastfeeding in the intervention group over time, with the largest difference at 2 months. Breastfeeding self-efficacy showed significantly greater improvement in the intervention group (time × intervention interaction: β = 1.01 [95% CI, 0.21-1.81]; P = .01), with a higher score at 4 months (adjusted β, 4.65 [95% CI, 1.60-7.70]; P = .01).

CONCLUSIONS AND RELEVANCE: In this randomized clinical trial, video call-based peer support did not increase exclusive breastfeeding at 6 months; however, it significantly increased exclusive breastfeeding at 2 months and improved maternal breastfeeding self-efficacy, offering a scalable model for postnatal care integration.

TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT04621266.

PMID:42201735 | DOI:10.1001/jamanetworkopen.2026.14490

JAMA Netw Open. 2026 May 1;9(5):e2614909. doi: 10.1001/jamanetworkopen.2026.14909.

ABSTRACT

IMPORTANCE: Surveillance of postacute sequelae of SARS-CoV-2 infection (PASC) depends on diagnostic coding systems that capture fewer than one-half of affected individuals, rendering millions invisible to health systems and policymakers.

OBJECTIVE: To quantify the gap between true PASC burden and diagnostic code-based estimates, determine the proportion representing chronic disease, and characterize organ system heterogeneity and temporal trends across diverse populations.

DESIGN, SETTING, AND PARTICIPANTS: This retrospective cohort study used electronic health record data from 58 hospitals and affiliated clinics in 4 US regions, from 2017 to 2025. Adults (aged ≥18 years) with laboratory-confirmed SARS-CoV-2 infection or a COVID-19 diagnosis code were included. A custom artificial intelligence algorithm, the Precision Phenotyping for Research Cohorts (P2RC), was implemented using federated infrastructure.

EXPOSURE: Laboratory-confirmed SARS-CoV-2 infection or COVID-19 diagnosis code.

MAIN OUTCOMES AND MEASURES: The primary outcomes were PASC prevalence, the proportion classified as chronic conditions, organ system distribution, and temporal trends from 2020 to 2024. χ2 Tests were used to assess organ system heterogeneity across regions, and negative binomial regression was used to model quarterly temporal trends, yielding incidence rate ratios (IRRs) with 95% CIs.

RESULTS: In this cohort study of 457 950 COVID-19 cases (mean age, 52.05 years; 275 107 [60.07%] female), the P2RC algorithm identified 74 560 PASC cases (16.28% overall; 28 585 [18.58%] in New England, 978 [19.55%] in Southeast Texas, 10 534 [22.69%] in Southern California, and 34 463 [13.64%] in Western Pennsylvania), more than 2-fold higher than the proportion identified by code-based surveillance (<7%). Of 883 International Statistical Classification of Diseases, Tenth Revision, Clinical Modification codes associated with PASC, 594 (67.27%) represented chronic or potentially chronic conditions. Of 74 560 patients with PASC, 66 587 (89.31%) developed chronic conditions requiring ongoing clinical management; this represents 14.54% of the total number of 457 950 patients with COVID-19. Substantial organ system heterogeneity was observed (χ2 = 2504.73; P < .001): New England demonstrated thyroid-predominant endocrine patterns, while Southeast Texas, Southern California, and Western Pennsylvania showed metabolic-predominant profiles. Negative binomial regression revealed increasing PASC prevalence through mid-2024 (IRR per quarter, 1.01 [95% CI, 1.00-1.01; P < .001] in New England; 1.00 [95% CI, 1.00-1.01; P < .001] in Southern California; and 1.02 [95% CI, 1.01-1.02; P < .001] in Western Pennsylvania), indicating an accumulating rather than resolving burden.

CONCLUSIONS AND RELEVANCE: In this cohort study, approximately 1 in 6 patients with COVID-19 developed PASC, and 89.31% of these patients had at least 1 chronic condition. Current diagnostic coding captured fewer than one-half of the cases, obscuring a substantial chronic disease burden. The persistently increasing prevalence through 2024 indicated an accumulating health care burden requiring investment in surveillance infrastructure and integrated care pathways.

PMID:42201733 | DOI:10.1001/jamanetworkopen.2026.14909

JAMA Netw Open. 2026 May 1;9(5):e2614919. doi: 10.1001/jamanetworkopen.2026.14919.

ABSTRACT

IMPORTANCE: Broad genomic profiling (BGP) is recommended for several types of metastatic cancer but remains underused. Over half of Medicare beneficiaries are enrolled in Medicare Advantage (MA), where cost-containment strategies may limit access to BGP. Whether Medicare payer type and geographic region are associated with BGP use is not well established.

OBJECTIVES: To evaluate whether BGP use differs by Medicare payer type (MA vs fee-for-service Medicare [FFS]) and to characterize geographic variation in BGP use across hospital referral regions (HRRs).

DESIGN, SETTING, AND PARTICIPANTS: This nationwide retrospective cohort study used Medicare Chronic Conditions Data Warehouse claims and service records to identify beneficiaries aged 66 years or older with a new diagnosis of metastatic cancer, including bladder, breast, colorectal, endometrial, kidney, lung, melanoma, pancreatic, prostate, or thyroid, from January 1, 2020, to June 30, 2022. Data analysis was conducted from October 2024 to March 2026.

EXPOSURES: Medicare type (FFS vs MA) and HRR.

MAIN OUTCOMES AND MEASURES: The primary outcome was receipt of BGP within 2 months before through 6 months after diagnosis. Mixed-effects logistic regression models were used to estimate adjusted odds ratios (AORs) for the association between Medicare type and BGP use, controlling for demographic, clinical, and geographic factors. HRR-level variation was summarized using the median odds ratio (MOR). Subgroup analyses stratified cancers by the strength of guideline recommendations for BGP.

RESULTS: Of 254 720 Medicare beneficiaries with metastatic cancer (median age, 74 years [IQR, 70-79 years]; 141 964 female [55.7%]), 112 637 (44.2%) were enrolled in MA and 142 083 (55.8%) in FFS. Overall, 64 351 (25.3%) received BGP. FFS beneficiaries had higher BGP use than MA beneficiaries (36 633 of 142 083 [25.8%] vs 27 718 of 112 637 [24.6%]; AOR, 1.08 [95% CI, 1.06-1.10]). BGP use was more frequent among FFS vs MA beneficiaries for cancers with equivocal BGP recommendations (AOR, 1.15 [95% CI, 1.11-1.19]) and, to a lesser extent, cancers with explicit recommendations (AOR, 1.04 [95% CI, 1.02-1.07]). Adjusted BGP use varied widely across HRRs (range, 13.8%-35.9%; median, 24.5% [IQR, 21.8%-27.6%]; MOR, 1.28 [95% CI, 1.25-1.31]).

CONCLUSIONS AND RELEVANCE: In this cohort study of Medicare beneficiaries with metastatic cancer, BGP use differed by Medicare payer type and showed substantial regional variation. These findings highlight opportunities to improve guideline-concordant molecular testing.

PMID:42201732 | DOI:10.1001/jamanetworkopen.2026.14919