Predicting length of stay of older patients with exacerbated chronic obstructive pulmonary disease

Citation
Ra. Incalzi et al., Predicting length of stay of older patients with exacerbated chronic obstructive pulmonary disease, AGING-CLIN, 13(1), 2001, pp. 49-57
Citations number
34
Categorie Soggetti
General & Internal Medicine","Medical Research General Topics
Journal title
AGING-CLINICAL AND EXPERIMENTAL RESEARCH
ISSN journal
03949532 → ACNP
Volume
13
Issue
1
Year of publication
2001
Pages
49 - 57
Database
ISI
SICI code
0394-9532(200102)13:1<49:PLOSOO>2.0.ZU;2-V
Abstract
Our study objective was to identify factors predicting length of hospital s tay of older patients with exacerbated chronic obstructive pulmonary diseas e (COPD) through a multicenter, cross-sectional, retrospective study. We ex amined 3789 patients aged 74.3 +/- 11.1 years (mean +/- SD), 66.1% males, c onsecutively hospitalized in 32 wards of General Medicine and 31 of Geriatr ics in acute care hospitals for exacerbated COPD in 10 bimonthly periods be tween 1988 and 1997. On admission, patients underwent a structured assessme nt of demographic data, nutritional status, cognitive and physical Junction s, comorbidity, and pharmacological therapy in the two weeks prior to admis sion. Patients were grouped according to whether their length of stay excee ded or nor the 75(th) percentile of stay distribution in each bimonthly per iod. Variables univariately distinguishing groups were entered into a logis tic regression analysis having long-stay as the dependent variable. Living alone (Odds Ratio 1.33, 95% Confidence Limits 1.03-1. 70), use of move than 3 drugs prior to admission (OR 1.29, CL 1.09-1.51), use of drugs with resp iratory depressant properties prior to admission (OR 1.24, CL 1.05-1.46), a nd the presence of move than 3 comorbid diseases (OR 1.88 CL 1.61-2.19) wer e independent correlates of long-stay. Age did not predict length of stay. In conclusion, selected health outcomes and indicators of disease severity, but not age, target COPD patients at risk of long-stay. Research is needed to verify whether these data can help program interventions aimed at short ening length of stay and, thus, at reducing annual hospitalization costs of the elderly.