Background: Stroke misdiagnosis, associated with poor outcomes, is estimated to occur in 9% of all stroke patients.
Objectives: We hypothesized that machine learning (ML) could assist in the diagnosis of ischemic stroke in emergency departments (EDs).
Design: The study was conducted and reported according to the Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis guidelines. We performed model development and prospective temporal validation, using data from pre- and post-COVID periods; we also performed a case study on a small cohort of previously misdiagnosed stroke patients.
Methods: We used structured and unstructured electronic health records (EHRs) of 56,452 patient encounters from 13 hospitals in Pennsylvania, from September 2003 to January 2021. ML pipelines, including natural language processing, were created using pre-event clinical data and provider notes in the EDs.
Results: Using pre-event information, our model's area under the receiver operating characteristics curve (AUROC) ranged from 0.88 to 0.92 with a similar range accuracy (0.87-0.90). Using provider notes, we identified five models that reached a balanced performance in terms of AUROC, sensitivity, and specificity. Model AUROC ranged from 0.93 to 0.99. Model sensitivity and specificity reached 0.90 and 0.99, respectively. Four of the top five performing models were based on the post-COVID provider notes; however, no performance difference between models tested on pre- and post-COVID was observed.
Conclusion: This study leveraged pre-event and at-encounter level EHR for stroke prediction. The results indicate that available clinical information can be used for building EHR-based stroke prediction models and ED stroke alert systems.
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http://dx.doi.org/10.1177/17562864241239108 | DOI Listing |
BMJ Open Qual
January 2025
Emergency Medicine, Mayo Clinic, Rochester, Minnesota, USA.
Objective: Understanding patients' wishes and preferences during hospitalisation is a crucial component of care. We identified a gap related to documentation of advance directives and patient preferences for care and focused on ensuring appropriate goals of care discussions were occurring and documented. Our aim was to improve the documentation of advance care planning notes to include 80% of targeted hospitalised patients.
View Article and Find Full Text PDFBMC Infect Dis
January 2025
University of California, San Francisco, San Francisco, CA, USA.
Background: Point-of-care HIV viral load testing may enhance patient care and improve HIV health services. We aimed to evaluate the feasibility and acceptability of implementing such testing in a high-volume community sexual health clinic in the United States.
Methods: We conducted a cross-sectional, mixed-methods study.
J Gen Intern Med
January 2025
Center for Health System Sciences, Atrium Health, Charlotte, NC, USA.
Background: Hypertension management is a national priority. However, hypertension control rates are suboptimal and vary across clinics, even among those in the same health system and geographic region.
Objective: To identify organizational barriers and facilitators that impact hypertension management at the provider, clinic, and health system level.
J Med Internet Res
January 2025
Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom.
Background: The rapid shift to video consultation services during the COVID-19 pandemic has raised concerns about exacerbating existing health inequities, particularly for disadvantaged populations. Intersectionality theory provides a valuable framework for understanding how multiple dimensions of disadvantage interact to shape health experiences and outcomes.
Objective: This study aims to explore how multiple dimensions of disadvantage-specifically older age, limited English proficiency, and low socioeconomic status-intersect to shape experiences with digital health services, focusing on video consultations.
Retin Cases Brief Rep
January 2025
Chair of Ophthalmology division; Tel Aviv Sourasky Medical Center, Sackler Faculty of Medicine, Tel Aviv, Israel.
Purpose: To evaluate the potency and security of Pneumatic Vitreolysis (PVL) as the primary treatment for Full-Thickness Macular Holes (FTMHs) and provide insights into patient selection criteria and procedural outcomes.
Patients And Methods: A retrospective analysis of three clinical cases presenting with FTMHs treated initially with PVL was conducted. Cases were evaluated for anatomical and functional outcomes through comprehensive ophthalmic examination and optical coherence tomography (OCT) imaging.
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