An admission prediction model based on seven variables accurately described hospital mortality in 1,997 ICU patients, whereas a 24-hour model did not.
Observational (n=1,997)
1,997 consecutive admissions to a general medical/surgical ICU evaluated for hospital mortality prediction.
Admission and 24-h mortality prediction models
Hospital mortality
We tested recently developed admission and 24-h models of hospital mortality on 1,997 consecutive admissions to a general medical/surgical ICU. This study population was independent of the group used to develop the models. The admission prediction model estimated each patient's probability of hospital mortality based on seven routinely collected admission variables. The 24-h model utilized seven variables routinely available at 24 h in the ICU. The admission model accurately described the mortality experience of the new cohort, while the 24-h model did not. Advantages of the admission model are that it is evaluable at the time of ICU admission, is independent of ICU treatment, and can be used to stratify patients by severity of illness, thereby making ICU comparisons possible. Its excellent goodness-of-fit, correct classification rate, sensitivity, and specificity suggest that this model is now ready for multihospital testing.
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Daniel Teres
Tufts University
Stanley Lemeshow
The Ohio State University
Jill Spitz Avrunin
Tufts University
Critical Care Medicine
PAST Foundation
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Teres et al. (Sun,) conducted a observational in ICU admission (n=1,997). Admission and 24-h mortality prediction models was evaluated on Hospital mortality. An admission prediction model based on seven variables accurately described hospital mortality in 1,997 ICU patients, whereas a 24-hour model did not.
synapsesocial.com/papers/6a216ffb84d1906bac5faa19 — DOI: https://doi.org/10.1097/00003246-198703000-00005