Predicting Hospital Admission and Prolonged Length of Stay in Older Adults in the Emergency Department: The PRO-AGE Scoring System - 20/08/20
, Luiz A. Gil-Junior, MD a, b, Christian V. Morinaga, MD a, Fernando Ganem, MD, PhD a, Jose A.E. Curiati, MD, PhD b, Thiago J. Avelino-Silva, MD, PhD b, cAbstract |
Study objective |
We developed prediction models for hospital admission and prolonged length of stay in older adults admitted from the emergency department (ED).
Methods |
This was a retrospective cohort study of patients aged 70 years or older who visited a geriatric ED in Brazil (N=5,025 visits). We randomly allocated participants to derivation and validation samples in a 2:1 ratio. We then selected 21 variables based on their clinical relevance and generated models to predict the following outcomes: hospital admission and prolonged length of stay, defined as the upper tertile of hospital stay. We used backward stepwise logistic regressions to select our final predictors and developed risk scoring systems based on the relative values of their β coefficients.
Results |
Overall, 57% of the participants were women, 31% were hospitalized, and 1% died in the hospital. The upper tertile of hospital stay was greater than 7 days. Hospital admission was best predicted by a model including male sex, aged 90 years or older, hospitalization in the previous 6 months, weight loss greater than or equal to 5% in the previous year, acute mental alteration, and acute functional decline. The prediction of prolonged length of stay retained the same variables, except male sex, which was substituted for fatigue. The final scoring system reached areas under the receiver operating characteristic curve of 0.74 for hospital admission and 0.79 for prolonged length of stay, and their accuracies were confirmed in the validation models.
Conclusion |
The PRO-AGE scoring system predicted hospital admission and prolonged length of stay in older adults with good accuracy, using a simple approach and only 7 easily obtained clinical variables.
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| Supervising editor: Timothy F. Platts-Mills, MD, MSc. Specific detailed information about possible conflict of interest for individual editors is available at editors. |
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| Author contributions: All authors contributed to study concept and design, interpretation of data, and preparation of the article, and gave final approval of the current version of the article. PKC and TJA-S contributed to data analysis. PKC, LAG-J, and TJA-S contributed to acquisition of data. PKC takes responsibility for the paper as a whole. |
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| Funding and support: By Annals policy, all authors are required to disclose any and all commercial, financial, and other relationships in any way related to the subject of this article as per ICMJE conflict of interest guidelines (see www.icmje.org). The authors have stated that no such relationships exist. |
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Vol 76 - N° 3
P. 255-265 - septembre 2020 Retour au numéro
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