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Background Acute exacerbation of chronic obstructive pulmonary disease (AECOPD) is a common undesirable event associated with significant morbidity and mortality. Several clinical prediction tools for predicting in-hospital mortality in patients with AECOPD have been developed in the past decades. However, some issues concerning the validity and availability of some predictors in the existing models may undermine their clinical applicability in resource-limited clinical settings. Methods We developed a multivariable model for predicting in-hospitality from a retrospective cohort of patients admitted with AECOPD to one tertiary care center in Thailand from October 2015 to September 2017. Multivariable logistic regression with fractional polynomial algorithms and cluster variance correction was used for model derivation. Results During the study period, 923 admissions from 600 patients with AECOPD were included. The in-hospital mortality rate was 1.68 per 100 admission-day. Eleven potential predictors from the univariable analysis were included in the multivariable logistic regression. The reduced model, named MAGENTA, incorporated seven final predictors: age, body temperature, mean arterial pressure, the requirement of endotracheal intubation, serum sodium, blood urea nitrogen, and serum albumin. The model discriminative ability based on the area under the receiver operating characteristic curve (AuROC) was excellent at 0.82 (95% confidence interval 0.77, 0.86), and the calibration was good. Conclusion The MAGENTA model consists of seven routinely available clinical predictors upon patient admissions. The model can be used as an assisting tool to aid clinicians in accurate risk stratification and making appropriate decisions to admit patients for intensive care.

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BackgroundAcute exacerbation of chronic obstructive pulmonary disease (AECOPD) is a common and deteriorating event leading to in-hospital morbidity and mortality. Identification of predictors for in-hospital mortality of AECOPD patients could aid clinicians in identifying patients with a higher risk of death during their hospitalisation.ObjectiveTo explore potential prognostic indicators associated with in-hospital mortality of AECOPD patients.SettingGeneral medical ward and medical intensive care unit of a university-affiliated tertiary care centre.MethodsA prognostic factor research was conducted with a retrospective cohort design. All admission records of AECOPD patients between October 2015 and September 2016 were retrieved. Stratified Cox’s regression was used for the primary analysis.ResultsA total of 516 admission records of 358 AECOPD patients were included in this study. The in-hospital mortality rate of the cohort was 1.9 per 100 person-day. From stratified Cox’s proportional hazard regression, the predictors of in-hospital mortality were aged 80 years or more (HR=2.16, 95% CI: 1.26 to 3.72, p=0.005), respiratory failure on admission (HR=2.50, 95% CI: 1.12 to 5.57, p=0.025), body temperature more than 38°C (HR=2.97, 95% CI: 1.61 to 5.51, p=0.001), mean arterial pressure lower than 65 mm Hg (HR=4.01, 95% CI: 1.88 to 8.60, p<0.001), white blood cell count more than 15 x 109/L (HR=3.51, 95% CI: 1.90 to 6.48, p<0.001) and serum creatinine more than 1.5 mg/dL (HR=2.08, 95% CI: 1.17 to 3.70, p=0.013).ConclusionSix independent prognostic indicators for in-hospital mortality of AECOPD patients were identified. All of the parameters were readily available in routine practice and can be used as an aid for risk stratification of AECOPD patients.