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LACE+ Index as Predictor of 30-Day Readmission in Brain Tumor Population.
- Source :
-
World neurosurgery [World Neurosurg] 2019 Jul; Vol. 127, pp. e443-e448. Date of Electronic Publication: 2019 Mar 27. - Publication Year :
- 2019
-
Abstract
- Background: The LACE+ index (Length of stay, Acuity of admission, Charlson Comorbidity Index score, and Emergency department [ED] visits in the past 6 months) is a tool used to predict 30-day readmissions. We sought to examine this predictive tool in patients undergoing brain tumor surgery.<br />Methods: Admissions and readmissions for patients undergoing craniotomy for supratentorial neoplasm at a single multihospital academic medical center were analyzed. All brain tumor cases for which the patient was alive at 30 days after surgery were included (n = 352). Simple logistic regression analyses were used to assess the ability of the LACE+ index and subsequent single variables to accurately predict the outcome measures of 30-day readmission, reoperation, and ED visit. Analysis of the model's or variable's discrimination was determined by the receiver operating characteristic curve as represented by the C-statistic.<br />Results: The sample included admissions for craniotomy for supratentorial neoplasm (n = 352). Assessment of the LACE+ index demonstrates a 1.02× increased odds of 30-day readmission for every 1-unit increase in LACE+ score (P = 0.031, CI = 1.00-1.03). Despite this, analysis of the receiver operating characteristic curve indicates that LACE+ index has poor specificity in predicting 30-day readmission (C-statistic = 0.58). A 1-unit increase in LACE+ score also predicts a 0.98× reduction in odds of home discharge (P < 0.001, CI = 0.97-0.99, C-statistic = 0.70). But LACE+ index does not predict 30-day reoperation (P = 0.945) or 30-day ED visits (P = 0.218).<br />Conclusions: The results of this study demonstrate that the LACE+ index is not yet suitable as a prediction model for 30-day readmission in a brain tumor population.<br /> (Copyright © 2019 Elsevier Inc. All rights reserved.)
- Subjects :
- Adult
Aged
Aged, 80 and over
Comorbidity
Emergency Service, Hospital
Female
Hospitalization statistics & numerical data
Hospitals statistics & numerical data
Humans
Length of Stay
Male
Middle Aged
ROC Curve
Risk Factors
Brain Neoplasms therapy
Logistic Models
Patient Discharge statistics & numerical data
Patient Readmission statistics & numerical data
Subjects
Details
- Language :
- English
- ISSN :
- 1878-8769
- Volume :
- 127
- Database :
- MEDLINE
- Journal :
- World neurosurgery
- Publication Type :
- Academic Journal
- Accession number :
- 30926557
- Full Text :
- https://doi.org/10.1016/j.wneu.2019.03.169