Literature DB >> 31055196

Validation of the LACE readmission and mortality prediction model in a large surgical cohort: Comparison of performance at preoperative assessment and discharge time points.

Brett K Shaffer1, Yu Cui2, Jonathan P Wanderer3.   

Abstract

STUDY
OBJECTIVE: The LACE index (Length of stay, admission Acuity, Charlson comorbidity index, and Emergency department visits within 6 months of current admission) is a practical tool designed to predict the risk of readmission or mortality within 30 days of hospital discharge. We sought to validate and examine its performance in a large surgical population at both the preoperative assessment and discharge time points.
DESIGN: Retrospective cohort study.
SETTING: We identified all admissions with a surgery or procedure at Vanderbilt University Medical Center (VUMC) between 2010 and 2015. PATIENTS: A total of 192,670 admissions (age ≥ 18) were included in the study.
INTERVENTIONS: None. MEASUREMENTS: LACE scores were calculated and analyzed with multivariable logistic regression. Discrimination was assessed with the c-statistic, calibration was assessed with calibration plots, and overall performance evaluated with the Brier score. Four models were created: admissions with any surgery or procedure, surgical admissions using actual length of stay (ALOS), surgical admissions using estimated length of stay (ELOS) and non-surgical procedural admissions. MAIN
RESULTS: 192,670 admissions were included. The all admissions model c-statistic was 0.77 with a Brier score of 0.13. Surgical admissions with ALOS and ELOS had a c-statistic of 0.80, 0.82 and a Brier score of 0.10, 0.08 respectively. Non-surgical procedural admissions had a c-statistic of 0.76 and a Brier score of 0.14. Calibration for all models was adequate.
CONCLUSIONS: The LACE model for surgical and procedural admissions had good discrimination and adequate calibration. Analysis of the model applied to surgical admissions using ELOS demonstrated slightly better overall performance than ALOS, suggesting that LACE could be utilized for readmission risk stratification at the time of preoperative assessment. Clinical Trial and Registry URL: Not applicable.
Copyright © 2019 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  LACE scores; Mortality; Readmissions; Surgical admissions

Mesh:

Year:  2019        PMID: 31055196     DOI: 10.1016/j.jclinane.2019.04.039

Source DB:  PubMed          Journal:  J Clin Anesth        ISSN: 0952-8180            Impact factor:   9.452


  4 in total

1.  High LACE index scores are associated with disproportionate excess deaths in hospital amongst patients with COVID-19.

Authors:  David Fluck; Christopher Henry Fry; Jonathan Robin; Thang Sieu Han
Journal:  Intern Emerg Med       Date:  2022-06-22       Impact factor: 5.472

2.  Prediction value of the LACE index to identify older adults at high risk for all-cause mortality in South Korea: a nationwide population-based study.

Authors:  Eunbyul Cho; Sumi Lee; Woo Kyung Bae; Jae-Ryun Lee; Hyejin Lee
Journal:  BMC Geriatr       Date:  2022-02-24       Impact factor: 3.921

3.  Assess the Performance and Cost-Effectiveness of LACE and HOSPITAL Re-Admission Prediction Models as a Risk Management Tool for Home Care Patients: An Evaluation Study of a Medical Center Affiliated Home Care Unit in Taiwan.

Authors:  Mei-Chin Su; Yi-Jen Wang; Tzeng-Ji Chen; Shiao-Hui Chiu; Hsiao-Ting Chang; Mei-Shu Huang; Li-Hui Hu; Chu-Chuan Li; Su-Ju Yang; Jau-Ching Wu; Yu-Chun Chen
Journal:  Int J Environ Res Public Health       Date:  2020-02-02       Impact factor: 3.390

4.  Derivation of age-adjusted LACE index thresholds in the prediction of mortality and frequent hospital readmissions in adults.

Authors:  Christopher Henry Fry; Erica Heppleston; David Fluck; Thang Sieu Han
Journal:  Intern Emerg Med       Date:  2020-07-28       Impact factor: 3.397

  4 in total

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