Format

Send to

Choose Destination
See comment in PubMed Commons below
J Clin Epidemiol. 1999 Dec;52(12):1157-63.

Validation of a predictive model for asthma admission in children: how accurate is it for predicting admissions?

Author information

1
Epidemiology Unit, Southwestern Sydney Area Health Service, Australia. t.chey@unsw.edu.au

Abstract

We studied 364 index presentations to the Emergency Department of a children's hospital with a diagnosis of asthma. The admission rate for this group of children was about 31%. We developed a parsimonious multiple logistic regression model to predict asthma hospital admission based on asthma severity indicators. We then evaluated the model's predictive ability using two methods of cross-validation, using the same sample that was used for the predictive model, and using data from a split sample. The logistic regression model had a predictive accuracy of 90% (95% confidence interval 85-95%). The sensitivity and specificity were 86% and 88%, respectively. Cross-validation models confirmed that the predictive ability of the model was stable. In studies with limited sample sizes, it is possible to validate a model without setting aside a split sample for cross-validation.

PMID:
10580778
[Indexed for MEDLINE]
PubMed Commons home

PubMed Commons

0 comments
How to join PubMed Commons

    Supplemental Content

    Full text links

    Icon for Elsevier Science
    Loading ...
    Support Center