LACE+ Index as Predictor of 30-Day Readmission in Brain Tumor Population.


Journal

World neurosurgery
ISSN: 1878-8769
Titre abrégé: World Neurosurg
Pays: United States
ID NLM: 101528275

Informations de publication

Date de publication:
Jul 2019
Historique:
received: 30 01 2019
revised: 14 03 2019
accepted: 15 03 2019
pubmed: 31 3 2019
medline: 15 1 2020
entrez: 31 3 2019
Statut: ppublish

Résumé

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. 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. 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). 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.

Sections du résumé

BACKGROUND 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.
METHODS 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.
RESULTS 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).
CONCLUSIONS 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.

Identifiants

pubmed: 30926557
pii: S1878-8750(19)30849-6
doi: 10.1016/j.wneu.2019.03.169
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

e443-e448

Informations de copyright

Copyright © 2019 Elsevier Inc. All rights reserved.

Auteurs

Ian F Caplan (IF)

Department of Neurosurgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.

Patricia Zadnik Sullivan (PZ)

Department of Neurosurgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.

David Kung (D)

Department of Neurosurgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.

Donald M O'Rourke (DM)

Department of Neurosurgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.

Omar Choudhri (O)

Department of Neurosurgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.

Gregory Glauser (G)

Department of Neurosurgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.

Benjamin Osiemo (B)

McKenna EpiLog Fellowship in Population Health, University of Pennsylvania, Philadelphia, Pennsylvania, USA; West Chester University, The West Chester Statistical Institute and Department of Mathematics, West Chester, Pennsylvania, USA.

Stephen Goodrich (S)

McKenna EpiLog Fellowship in Population Health, University of Pennsylvania, Philadelphia, Pennsylvania, USA; West Chester University, The West Chester Statistical Institute and Department of Mathematics, West Chester, Pennsylvania, USA.

Scott D McClintock (SD)

West Chester University, The West Chester Statistical Institute and Department of Mathematics, West Chester, Pennsylvania, USA.

Neil R Malhotra (NR)

Department of Neurosurgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA; McKenna EpiLog Fellowship in Population Health, University of Pennsylvania, Philadelphia, Pennsylvania, USA. Electronic address: NRM@uphs.upenn.edu.

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