TY - JOUR
T1 - Clinical congestion score enhanced by age and lung ultrasound improves utility over clinical congestion score alone in patients with acute heart failure presenting to emergency intensive care unit
AU - Xu, Ping
AU - Zhou, Dehao
AU - Chen, Meiling
AU - Li, Liang
AU - Huang, Wenbin
AU - Xu, Ziyin
AU - Fan, Mingyan
AU - Li, Kefeng
AU - Zhang, Cheng
N1 - Publisher Copyright:
© 2026 The Author(s). Hong Kong Journal of Emergency Medicine published by John Wiley & Sons Australia, Ltd on behalf of Hong Kong College of Emergency Medicine Limited.
PY - 2026/2
Y1 - 2026/2
N2 - Background: Existing mortality prediction models for intensive care unit (ICU) patients with heart failure (HF) often rely on variables collected at ICU admission and lacked adequate discriminative ability. This study aimed to develop a new prediction model based on ICU discharge variables to improve predictive performance in patients with acute HF. Methods: This single-center prospective observational study aimed to assess all-cause mortality within 30 days of emergency ICU admission. Candidate variables with p < 0.05 in univariable analysis were dichotomized based on clinical characteristics or a restricted cubic spline model, and included in the multivariate logistic regression model. The clinical congestion score (CCS) score was revised using forward multivariable regression analysis. The discrimination, calibration, and clinical utility of CCS, lung ultrasound (LUS) score, age, LUS score combined with age, CCS combined with LUS score, CCS combined with age, the new prognostic model, and APACHE-HF were assessed using the bootstrap method with 500 resamples. Results: Seventy-one participants were enrolled in this study, with a median age of 79 years (71.5–84), and 50.7% (36/71) were male. The multivariate logistic regression model revealed that a 1-point increase in CCS (OR: 2.883, 95% CI: 1.358–6.121, p = 0.006), age ≥85 years (OR: 15.271, 95% CI: 2.434–95.803, p = 0.004), and LUS score ≥3 (OR: 4.646, 95% CI: 1.366–15.799, p = 0.014) were significantly associated with higher all-cause mortality risk. Based on 500 bootstrap resamples, the new prognostic model (CCS combined with age and LUS score) had the highest AUC of 0.849 among prediction models. Furthermore, this new model demonstrated superior calibration and clinical utility compared to other scoring systems. Conclusion: The CCS enhanced by age and LUS score enabled good prediction of all-cause mortality within 30 days after admission to ICUs, potentially aiding clinical decision-making for acute HF patients in ICUs including emergency intensive care units.
AB - Background: Existing mortality prediction models for intensive care unit (ICU) patients with heart failure (HF) often rely on variables collected at ICU admission and lacked adequate discriminative ability. This study aimed to develop a new prediction model based on ICU discharge variables to improve predictive performance in patients with acute HF. Methods: This single-center prospective observational study aimed to assess all-cause mortality within 30 days of emergency ICU admission. Candidate variables with p < 0.05 in univariable analysis were dichotomized based on clinical characteristics or a restricted cubic spline model, and included in the multivariate logistic regression model. The clinical congestion score (CCS) score was revised using forward multivariable regression analysis. The discrimination, calibration, and clinical utility of CCS, lung ultrasound (LUS) score, age, LUS score combined with age, CCS combined with LUS score, CCS combined with age, the new prognostic model, and APACHE-HF were assessed using the bootstrap method with 500 resamples. Results: Seventy-one participants were enrolled in this study, with a median age of 79 years (71.5–84), and 50.7% (36/71) were male. The multivariate logistic regression model revealed that a 1-point increase in CCS (OR: 2.883, 95% CI: 1.358–6.121, p = 0.006), age ≥85 years (OR: 15.271, 95% CI: 2.434–95.803, p = 0.004), and LUS score ≥3 (OR: 4.646, 95% CI: 1.366–15.799, p = 0.014) were significantly associated with higher all-cause mortality risk. Based on 500 bootstrap resamples, the new prognostic model (CCS combined with age and LUS score) had the highest AUC of 0.849 among prediction models. Furthermore, this new model demonstrated superior calibration and clinical utility compared to other scoring systems. Conclusion: The CCS enhanced by age and LUS score enabled good prediction of all-cause mortality within 30 days after admission to ICUs, potentially aiding clinical decision-making for acute HF patients in ICUs including emergency intensive care units.
KW - acute heart failure
KW - clinical congestion score
KW - emergency intensive care unit
KW - lung ultrasound
UR - https://www.scopus.com/pages/publications/105029768740
U2 - 10.1002/hkj2.70070
DO - 10.1002/hkj2.70070
M3 - Article
AN - SCOPUS:105029768740
SN - 1024-9079
VL - 33
JO - Hong Kong Journal of Emergency Medicine
JF - Hong Kong Journal of Emergency Medicine
IS - 1
M1 - e70070
ER -