Evidence map›Paper›PMID 38389442›Full record

ArticleThe Permanente journal2024

Predictive Value of LACE Scores for Pediatric Readmissions.

Jelena Douillard, Sarah Lentz, Shaina Ganjian, Sherill Agdeppa, Ngoc Ho, Jane Chieh Lin, Paul Han

Abstract read
In one paragraph

Article in The Permanente journal, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Jelena DouillardSouthern California Permanente Medical Group, Los Angeles, CA, USA.ORCID 0000-0002-1362-3229
Sarah LentzKaiser Foundation Hospital, Los Angeles, CA, USA.
Shaina GanjianKaiser Foundation Hospital, Los Angeles, CA, USA.
Sherill AgdeppaSouthern California Permanente Medical Group, Los Angeles, CA, USA.
Ngoc HoSouthern California Permanente Medical Group, Los Angeles, CA, USA.
Jane Chieh LinSouthern California Permanente Medical Group, Los Angeles, CA, USA.
Paul HanSouthern California Permanente Medical Group, Los Angeles, CA, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionHospital readmissions are recognized as a prevalent, yet potentially preventable, personal and economic burden. Length of stay, Acuity of admission, Comorbidities, and number of Emergency Department visits in the preceding 6 months can be quantified into one score, the LACE score. LACE scores have previously been identified to correlate with hospital readmissions within 30 days of discharge, but research specific to the pediatric population is scant. The objective of the present study was to investigate if LACE scores, in addition to other factors, can be utilized to create a predictive pediatric hospital readmission model that may ultimately be used to decrease readmission rates.

methodsThis study included 25,616 hospitalizations of patients under the age of 18 years. Data were extracted from a hospital network electronic medical record. Demographics included LACE scores, age, gender, race/ethnicity, median household income, and medical centers. The primary exposure variable was LACE score. The main outcome measures were readmissions within 7, 14, and 30 days. The area under the curve (AUC) was used to assess the predictive capability of the regression model on patient 30-day admission.

resultsLACE scores, age, gender, race/ethnicity, median household income, and medical centers were examined in a multivariable model to assess patient risk of a 30-day readmission. Only age and LACE score were observed to be statistically significant. The AUC for the combined model was 0.69. DISCUSSION: As only age and LACE score were observed to be statistically significant and the AUC for the combined model was 0.69, this model is considered to have poor predictive capability.

conclusionsIn this study, LACE scores, as well the other factors, had a poor predictive capability for pediatric readmissions.

Indexed as

Patient ReadmissionAdolescentAge FactorsArea Under CurveChildChild, PreschoolEmergency Service, HospitalFemaleHumansInfantInfant, NewbornLength of StayMalePredictive Value of TestsRetrospective StudiesRisk Assessmentdecreasing readmission ratesLACE scorereadmission rates

Identifiers

PMID38389442
PMCPMC11232907

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.