Observational studyBMC geriatrics2018
Age effect on the prediction of risk of prolonged length hospital stay in older patients visiting the emergency department: results from a large prospective geriatric cohort study.
Observational study in BMC geriatrics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
10 citing papers in PubMed.
- Risk stratification tool for older emergency department patients: the 6-items brief geriatric assessment.BMC geriatrics · 2026Observational
- Article
- Malnutrition Screening Tools for Geriatric Patients Presenting to Emergency Department: Agreement and Prognostic Utility for Hospital Admission and Length of Stay.Healthcare (Basel, Switzerland) · 2026Article
- The effect of frailty on hospitalisation trajectories in adults aged 65 and older across 10 European countries: a 14-year longitudinal analysis from the Survey of Health, Ageing, and Retirement in Europe (SHARE).European journal of ageing · 2026Article
- Validity of Smartphone-Based Measurement for Assessing Lower Limb Power for Sarcopenia and Frailty Discrimination: Cross-Sectional Study.JMIR formative research · 2026Article
- A comprehensive review of machine learning algorithms and their application in geriatric medicine: present and future.Aging clinical and experimental research · 2023Review
- Older patients referred for geriatric consultation in the emergency department: characteristics and healthcare utilization.BMC geriatrics · 2023Observational
- Machine learning-based prediction of hospital prolonged length of stay admission at emergency department: a Gradient Boosting algorithm analysis.Frontiers in artificial intelligence · 2023Article
- Machine learning in patient flow: a review.Progress in biomedical engineering (Bristol, England) · 2021Review
- Association Between Preoperative Blood Glucose Level and Hospital Length of Stay in Patients With Kidney Stones Undergoing Percutaneous Nephrolithotomy.Frontiers in surgery · 2021Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundWith the rapid growth of elderly patients visiting the Emergency Department (ED), it is expected that there will be even more hospitalisations following ED visits in the future. The aim of this study was to examine the age effect on the performance criteria of the 10-item brief geriatric assessment (BGA) for the prolonged length of hospital stay (LHS) using artificial neural networks (ANNs) analysis.
methodsBased on an observational prospective cohort study, 1117 older patients (i.e., aged ≥ 65 years) ED users were admitted to acute care wards in a University Hospital (France) were recruited. The 10-items of BGA were recorded during the ED visit and prior to discharge to acute care wards. The top third of LHS (i.e., ≥ 13 days) defined the prolonged LHS. Analysis was successively performed on participants categorized in 4 age groups: aged ≥ 70, ≥ 75, ≥ 80 and ≥ 85 years. Performance criteria of 10-item BGA for the prolonged LHS were sensitivity, specificity, positive predictive value [PPV], negative predictive value [NPV], likelihood ratios [LR], area under receiver operating characteristic curve [AUROC]). The ANNs analysis method was conducted using the modified multilayer perceptron (MLP).
resultsValues of criteria performance were high (sensitivity> 89%, specificity≥ 96%, PPV > 87%, NPV > 96%, LR+ > 22; LR- ≤ 0.1 and AUROC> 93), regardless of the age group.
conclusionsAge effect on the performance criteria of the 10-item BGA for the prediction of prolonged LHS using MLP was minimal with a good balance between criteria, suggesting that this tool may be used as a screening as well as a predictive tool for prolonged LHS.
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