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Asthma exacerbation comorbidity index (AECI): Predicting in-hospital adverse outcomes
Chongyang Zhao1, Lei Wang2, Li Zhang2
1Department of Evidence-based Medicine and Clinical Epidemiology, West China Hospital, Sichuan University, Chengdu, China; Division of Internal Medicine, Institute of Integrated Traditional Chinese and Western Medicine, West China Hospital, Sichuan University, Chengdu, China.
Background:
Despite optimal treatment, asthma exacerbations (AEs) can lead to severe adverse events, including mortality. Effective management of comorbidities is critical, as they are common in asthma patients and significantly impact quality of life, healthcare use, and treatment outcomes. Currently, no comprehensive clinical tool exists for assessing and managing these comorbidities during AE.
Methods:
We conducted a real-world study involving inpatients with AE. We assessed the risk of in-hospital composite outcome including death, intensive care unit admission, or invasive ventilation, associated with individual comorbidities, comorbidity systems, and the total number of comorbidities. We developed a predictive tool, the Asthma Exacerbation Comorbidity Index (AECI), which incorporates the major comorbidities identified. Patients were categorized into three risk groups based on their AECI scores.
Results:
Among the 43 comorbidities assessed, nine were significantly associated with the composite outcome. Each additional comorbidity increased the risk of the composite outcome by 25% (95% CI, 16.5%-34.1%; P < 0.001). The most prevalent comorbidity systems were the endocrine (51.7%), respiratory (50.9%), and cardiovascular (43.3%) systems, with 54.1% of patients exhibiting multiple comorbidity systems. The AECI exhibited an area under the curve (AUC) of 75.98%. A one-point increase in the AECI was associated with a 0.51-fold increase in the risk of composite outcome (95% CI, 0.41-0.62; P < 0.001).
Conclusion:
The high prevalence of comorbidities among patients with AEs is associated with a poorer prognosis. The AECI proves to be a valuable tool to assess comorbidities, enabling clinicians to identify inpatients at higher risk of adverse in-hospital events and to make informed treatment decisions.
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