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A simple clinical risk score (ABCDMP) for predicting mortality in patients with AECOPD and cardiovascular diseases
Jiarui Zhang1, Qun Yi1,2, Chen Zhou3
1Department of Respiratory and Critical Care Medicine, West China Hospital, Sichuan University, Guo-xue-xiang 37#, Wuhou District, Chengdu, 610041, Sichuan Province, China.
Insights
A new ABCDMP risk score accurately predicts mortality in patients with acute exacerbations of chronic obstructive pulmonary disease (AECOPD) and cardiovascular diseases (CVDs). This score outperforms existing models and aids in stratifying patients for better management.
Area of Science:
- Cardiology
- Pulmonology
- Clinical Risk Prediction
Background:
- High morbidity and mortality in hospitalized patients with AECOPD and CVDs.
- Lack of a specific risk score for predicting mortality in this population.
- Need for a tool to assess prognosis in patients with AECOPD and CVDs.
Purpose of the Study:
- To derive and validate a simple clinical risk score for predicting mortality in patients with AECOPD and CVDs.
- To identify independent prognostic risk factors.
- To compare the new score with existing risk models.
Main Methods:
- Prospective, noninterventional, multicenter cohort study.
- Multivariable logistic regression for risk factor identification.
- Derivation and validation of the ABCDMP risk score.
- Comparison with BAP-65, CURB-65, DECAF, and NIVO scores.
Main Results:
- The ABCDMP score includes age, BUN, consolidation, diastolic blood pressure, mental status, and pulse.
- Good discrimination (AUC 0.847 in derivation, 0.811 in validation) and calibration.
- Significantly better predictivity for in-hospital mortality compared to existing scores (P < 0.001).
- Moderate predictive performance for 3-year mortality.
Conclusions:
- The ABCDMP risk score effectively predicts mortality in AECOPD and CVDs patients.
- The score can guide clinical research and risk-based treatment strategies.
- Facilitates patient stratification for tailored management.
Background:
The morbidity and mortality among hospital inpatients with AECOPD and CVDs remains unacceptably high. Currently, no risk score for predicting mortality has been specifically developed in patients with AECOPD and CVDs. We therefore aimed to derive and validate a simple clinical risk score to assess individuals' risk of poor prognosis.
Study Design And Methods:
We evaluated inpatients with AECOPD and CVDs in a prospective, noninterventional, multicenter cohort study. We used multivariable logistic regression analysis to identify the independent prognostic risk factors and created a risk score model according to patients' data from a derivation cohort. Discrimination was evaluated by the area under the receiver-operating characteristic curve (AUC), and calibration was assessed by the Hosmer-Lemeshow goodness-of-fit test. The model was validated and compared with the BAP-65, CURB-65, DECAF and NIVO models in a validation cohort.
Results:
We derived a combined risk score, the ABCDMP score, that included the following variables: age > 75 years, BUN > 7 mmol/L, consolidation, diastolic blood pressure ≤ 60 mmHg, mental status altered, and pulse > 109 beats/min. Discrimination (AUC 0.847, 95% CI, 0.805-0.890) and calibration (Hosmer‒Lemeshow statistic, P = 0.142) were good in the derivation cohort and similar in the validation cohort (AUC 0.811, 95% CI, 0.755-0.868). The ABCDMP score had significantly better predictivity for in-hospital mortality than the BAP-65, CURB-65, DECAF, and NIVO scores (all P < 0.001). Additionally, the new score also had moderate predictive performance for 3-year mortality and can be used to stratify patients into different management groups.
Conclusions:
The ABCDMP risk score could help predict mortality in AECOPD and CVDs patients and guide further clinical research on risk-based treatment.
Clinical Trial Registration:
Chinese Clinical Trail Registry NO.:ChiCTR2100044625; URL: http://www.chictr.org.cn/showproj.aspx?proj=121626 .
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