Related Experiment Video
Updated: Aug 5, 2026

Cutoff Value of Phase Angle by Bioelectrical Impedance Analysis at Admission as a Prognostic Factor in Patients with Acute Heart Failure
Published on: June 10, 2025
Predicting Disease Severity and Mortality Using a Simple Clinical Risk Score (ABCDMP) in Patients with AECOPD in the
1Newcastle University, Sharjah, United Arab Emirates.
Abstract:
Chronic Obstructive Pulmonary Disease (COPD) stands as a leading cause of death globally, with AECOPD significantly worsening patient outcomes. The intersection of COPD with CVDs further escalates the risk, highlighting the need for precise prognostic tools. The ABCDMP score, previously validated in China, offers a simple clinical approach to risk stratification but has not been tested internationally. This study explores the efficacy of the ABCDMP score in predicting disease severity and mortality among AECOPD patients with concurrent CVDs in the UAE. This multicenter retrospective study was conducted in 18 hospitals across the UAE and assessed the predictive accuracy of the ABCDMP score for inpatient mortality, 30-day mortality, and 90-day readmission among AECOPD patients with CVDs. The study included 512 participants, of whom 343 (67.0%) were female, 391 (76.4%) were aged 65 years or older, and 89 (17.4%) had a hospital stay of more than 30 days. The ABCDMP score was evaluated using the Area Under the Receiver Operating Characteristic (AUROC). The ABCDMP score curves for inpatient death, 30-day death, and 90-day readmission were 0.55 (95% CI: 0.49-0.61), 0.48 (95% CI: 0.40-0.55), and 0.58 (95% CI: 0.52-63), respectively. Significant differences in mortality rates were observed among patients with different lengths of stay (P = .012) and in abilities to wash independently (P = .001), dress (P = .001), and feed (P = .001). Moreover, the analysis revealed significant differences in the occurrence of patient deaths across various comorbidities, notably renal diseases (P = .003) and atrial fibrillation (P = .001). The ABCDMP score's effectiveness in predicting mortality and readmission rates among AECOPD patients with cardiovascular conditions was found to be limited, indicating the need for its enhancement or the development of more accurate tools.