Differential leukocyte counts and cardiovascular mortality in very old patients with acute myocardial infarction: a Chin
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RESEARCH ARTICLE
Open Access
Differential leukocyte counts and cardiovascular mortality in very old patients with acute myocardial infarction: a Chinese cohort study Xiao‑Ni Yan1,2†, Jing‑Lu Jin1†, Meng Zhang1, Li‑Feng Hong2, Yuan‑Lin Guo1, Na‑Qiong Wu1, Cheng‑Gang Zhu1, Qian Dong1 and Jian‑Jun Li1*
Abstract Background: Total leukocyte and differential Leukocyte counts are prognostic indictors in patients with coronary artery disease (CAD). However, there is no data available regarding their prognostic utility in very old patients with acute myocardial infarction (AMI). The aim of this study is to investigate the potential role of different leukocyte parameters in predicting the mortality among very old patients with AMI. Methods: A total of 523 patients aged over 80 years with AMI were consecutively enrolled into this study. Leukocyte and its subtypes were obtained at admission in each patient. The primary study endpoint was cardiovascular mortal‑ ity. Patients were followed up for an average of 2.2 years and 153 patients died. The associations of leukocyte param‑ eters with mortality were assessed using Cox regression analyses. The concordance index was calculated to test the model efficiency. Results: In multivariable regression analysis, neutrophils-plus-monocytes-to-lymphocytes ratio (NMLR) and neutro‑ phils-to-lymphocytes ratio (NLR) were two most significant predictors of mortality among all the leukocyte parame‑ ters (HR = 3.21, 95% CI 1.75–5.35; HR = 2.79, 95% CI 1.59–4.88, respectively, all p 1, systolic blood pressure 100 beats/ min, respectively [21]. Study endpoints
Follow-up data were acquired by interviewing each patient face to face or by telephone. The primary endpoint used for the analysis was cardiovascular mortality
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mainly including death caused by AMI, congestive heart failure, stroke, malignant arrhythmia and other structural or functional cardiac diseases as our previous studies [22]. Mortality data were obtained from interviewing and medical records. Statistical analysis
Research data were analyzed using SPSS version 22.0 software (Chicago, IL, USA) and R language version 3.6.0 (Feather Spray). The Kolmogorov–Smirnov test was used to test the normality distribution. Data were shown as mean ± standard deviations (SD) or median with interquartile range for continuous variables and as numbers and percentages for categorical variables. Comparisons were made using Student’s t test, Mann–Whitney U test, Kruskal–Wallis test, chi-square test, or Fisher’s exact test when appropriate. Kaplan–Meier analysis was performed to illustrate mortality differences by tertiles of NMLR and NLR and Log-rank test was carried out to assess significance. Univariable and multivariable Cox regression analyses were used to calculate the hazard ratios (HRs). The adjusted Cox models included traditional cardiovascular risk factors as follows: age, male gender, body mass index (BMI), family history of CAD, smoking, hypertension, DM, HDL-C, non-HDL-C, hsCRP, creatinine, LVEF, troponin I, percutane
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