Routine Laboratory Tests can Predict In-hospital Mortality in Acute Exacerbations of COPD

Abstract

Chronic obstructive pulmonary disease (COPD) has a rising global incidence and acute exacerbation of COPD (AECOPD) carries a high health-care economic burden. Classification and regression tree (CART) analysis is able to create decision trees to classify risk groups. We analysed routinely collected laboratory data to identify prognostic factors for inpatient mortality with AECOPD from our large district hospital. Data from 5,985 patients with 9,915 admissions for AECOPD over a 7-year period were examined. Randomly allocated training (n = 4,986) or validation (n = 4,929) data sets were developed and CART analysis was used to model the risk of all-cause death during admission. Inpatient mortality was 15.5%, mean age was 71.5 (±11.5) years, 56.2% were male, and mean length of stay was 9.2 (±12.2) days. Of 29 variables used, CART analysis identified three (serum albumin, urea, and arterial pCO(2)) to predict in-hospital mortality in five risk groups, with mortality ranging from 3.0 to 23.4%. C statistic indices were 0.734 and 0.701 on the training and validation sets, respectively, indicating good model performance. The highest-risk group (23.4% mortality) had serum urea >7.35 mmol/l, arterial pCO(2) >6.45 kPa, and normal serum albumin (>36.5 g/l). It is possible to develop clinically useful risk prediction models for mortality using laboratory data from the first 24 h of admission in AECOPD.

Predictive score for mortality in patients with COPD exacerbations attending hospital emergency departments

“…Although previous authors have proposed predictive models for death or ICU admission, and some have created severity scores for patients with eCOPD, these did not evaluate such a complete range of variables as in our study, including arterial blood gases and other relevant data from the ED, and this limits their results [7-9,25,26]. …”

Clinical characteristics associated with adverse events in patients with exacerbation of chronic obstructive pulmonary disease: a prospective cohort study

“…[26][27][28][29][30] Others involved retrospective analyses of existing databases, were focused on inpatients or mortality, and were not directly applicable to the emergency department. [31][32][33][34][35] Strengths and limitations Our study had several strengths, including multi centre and rigorous prospective collection of real-time clinical data, comprehensive followup and unique use of the 3-minute walk test. Nonetheless, some aspects of the study warrant discussion.…”

Development of a diagnostic decision tree for obstructive pulmonary diseases based on real-life data

“…In the field of respiratory medicine, several decision trees have been developed to predict severity [6], mortality [22], hospitalisation [4] and clinical outcomes [23]. In this article, we have presented the first real-life decision tree to predict diagnosis in patients suspected to have an OPD in primary care daily clinical practice.…”