Abstract | BACKGROUND: METHODS: This single-center, retrospective, observational study included 3,366 consecutive ACS patients in Zhongda Hospital, Southeast University from July 2013 to January 2018. The clinical and laboratory data were extracted, and the in-hospital death and hospitalization days were also recorded. RESULTS: All patients were equally divided into four groups according to quartiles of HAR: Q1 (HAR < 1.0283), Q2 (1.0283 ≤ HAR < 1.0860), Q3 (1.0860 ≤ HAR < 1.1798), and Q4 (HAR ≥ 1.1798). Overall, HAR was positively associated with the counts of neutrophils and monocytes, whereas negatively correlated to lymphocyte counts. HAR was negatively correlated to left ventricular ejection fraction (LVEF). Compared to other three groups, in-hospital mortality (vs. Q1, Q2, and Q3, p < 0.001) and hospitalization length (vs. Q1, Q2, and Q3, p < 0.001) were significantly higher in the Q4 group. When grouped by LBR, however, there was no significant difference in LVEF, in-hospital mortality, and hospitalization length among groups. After adjusting potential impact from age, systolic blood pressure, creatine, lactate dehydrogenase, albumin, glucose, and uric acid, multivariate analysis indicated that HAR was an independent factor predicting in-hospital death among ACS patients. CONCLUSIONS: HAR had good predictive value for patients' in-hospital death after the occurrence of acute coronary events, but LBR was not related to in-hospital adverse events.
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Authors | Zhenjun Ji, Guiren Liu, Rui Zhang, Abdlay Carvalho, Jiaqi Guo, Wenjie Zuo, Xiaoguo Zhang, Yangyang Qu, Jie Lin, Ziran Gu, Yuyu Yao, Genshan Ma |
Journal | Cardiology journal
(Cardiol J)
Vol. 31
Issue 2
Pg. 251-260
( 2024)
ISSN: 1898-018X [Electronic] Poland |
PMID | 35762073
(Publication Type: Journal Article, Observational Study)
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Chemical References |
- Biomarkers
- Cholesterol, HDL
- Apolipoprotein A-I
- APOA1 protein, human
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Topics |
- Humans
- Acute Coronary Syndrome
(blood, mortality, diagnosis)
- Male
- Female
- Retrospective Studies
- Hospital Mortality
(trends)
- Middle Aged
- Biomarkers
(blood)
- Cholesterol, HDL
(blood)
- Aged
- Apolipoprotein A-I
(blood)
- Risk Factors
- Prognosis
- Predictive Value of Tests
- Risk Assessment
(methods)
- China
(epidemiology)
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