2003
DOI: 10.1046/j.1525-1497.2003.20615.x
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APACHE II Predicts long-term survival in COPD patients admitted to a general medical ward

Abstract: OBJECTIVE:The Acute Physiology and Chronic Health Evaluation II (APACHE II) was developed to predict intensive-care unit (ICU) resource utilization. This study tested APACHE II's ability to predict long-term survival of patients with chronic obstructive pulmonary disease (COPD) admitted to general medical floors. DESIGN:We performed a retrospective cohort study of patients admitted for COPD exacerbation outside the ICU. APACHE II scores were calculated by chart review. Mortality was determined by the Social Se… Show more

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Cited by 59 publications
(48 citation statements)
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“…The average APACHE score in patients who died and those who survived outside the ICU had a significant statistical difference (P < 0.05), which shows that APACHE is considerable out of the ICU from the pre-awareness point of view. This finding is compatible with the study of Goel, who showed APACHE results were a predictive tool for death in COPD patients' death treated in hospital units other that the ICU (15).…”
Section: Discussionsupporting
confidence: 92%
“…The average APACHE score in patients who died and those who survived outside the ICU had a significant statistical difference (P < 0.05), which shows that APACHE is considerable out of the ICU from the pre-awareness point of view. This finding is compatible with the study of Goel, who showed APACHE results were a predictive tool for death in COPD patients' death treated in hospital units other that the ICU (15).…”
Section: Discussionsupporting
confidence: 92%
“…Our results are congruent with recently published studies. 7,24,27,28 Whether co-morbidities are predictors of mortality among patients with COPD remains controversial. We did not observe an association between number of comorbidities, much as Domingo-Salvany et al found.…”
mentioning
confidence: 99%
“…The liver disease model is a composition of these two functions as shown below. The mapping from linear to logistic function is described as follows [23].…”
Section: B Pca and Logistic Regressionmentioning
confidence: 99%