Purpose: It is important to identify which older patients attending the emergency department are at risk of adverse outcomes to introduce preventive interventions. This study aimed to assess the prognostic value of a shortened screening instrument based on the Dutch national Safety Management System [Veiligheidsmanagementsysteem (VMS)] guidelines for adverse outcomes in older emergency department patients.
Methods: A cohort study was performed including patients aged 70 years or older who visited the emergency department. Adverse outcomes included hospital admission, return emergency department visits within 30 days, and 90-day mortality. The prognostic value of the VMS-score was assessed for these adverse events and, in addition, a prediction model was developed for 90-day mortality.
Results: A high VMS-score was independently associated with an increased risk of hospital admission [OR 2.26 (95% CI 1.32-3.86)] and 90-day mortality [HR 2.48 (95% CI 1.31-4.71)]. The individual VMS-questions regarding history of delirium and help in activities of daily living were associated with these outcomes as well. A prediction model for 90-day mortality was developed and showed satisfactory calibration and good discrimination [AUC 0.80 (95% CI 0.72-0.87)]. A cut-off point that selected 30% of patients at the highest risk yielded a sensitivity of 67.4%, a specificity of 75.3%, a positive predictive value of 28.5%, and a negative predictive value of 94.1%.
Conclusion: The shortened VMS-based screening instrument showed to be of good prognostic value for hospitalization and 90-day mortality. The prediction model for mortality showed promising results and will be further validated and optimized.
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http://dx.doi.org/10.1007/s41999-020-00385-0 | DOI Listing |
Ann Med
December 2025
Department of Emergency Medicine, Second Affiliated Hospital, Department of Public Health, The Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Zhejiang University School of Medicine, Hangzhou, China.
Background: Update, the link between HIV infection and abnormal glucose metabolism (AGM) is still unclear. This study aims to investigate the impact of HIV infection on AGM, including insulin resistance (IR), impaired fasting glucose (IFG), and diabetes mellitus (DM).
Methods: A multicenter case-control study was conducted in Zhejiang province, China.
J Med Internet Res
January 2025
Department of Anesthesiology, Daping Hospital, Army Medical University, Chongqing, China.
Background: Recent research has revealed the potential value of machine learning (ML) models in improving prognostic prediction for patients with trauma. ML can enhance predictions and identify which factors contribute the most to posttraumatic mortality. However, no studies have explored the risk factors, complications, and risk prediction of preoperative and postoperative traumatic coagulopathy (PPTIC) in patients with trauma.
View Article and Find Full Text PDFJAMA
January 2025
Department of Emergency and Critical Care Medicine, Tokyo Bay Urayasu Ichikawa Medical Center, Urayasu, Japan.
JAMA Netw Open
January 2025
University Hospitals Cleveland Medical Center, Case Western Reserve University School of Medicine, Cleveland, Ohio.
Importance: A substantial number of individuals worldwide experience long COVID, or post-COVID condition. Other postviral and autoimmune conditions have a female predominance, but whether the same is true for long COVID, especially within different subgroups, is uncertain.
Objective: To evaluate sex differences in the risk of developing long COVID among adults with SARS-CoV-2 infection.
JAMA Surg
January 2025
Department of Surgery, State University of New York, Downstate Health Sciences University, Brooklyn.
Importance: Chronic limb-threatening ischemia (CLTI) is a major public health issue that requires considerable human and physical resources to provide optimal patient care. It is essential to characterize the disease severity and resource needs of patients with CLTI presenting to facilities of varying resource capacities.
Objective: To investigate the association between facility-level Medicaid payer proportions and the incidence of nonelective admissions among patients admitted for CLTI.
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