Baseline characteristics of patients
After reviewing the data of 62,699 critically ill patients, a total of 798 patients with AMI were enrolled in our study (Figure 1). Based on tertiles of admission NPAR level, participants were categorized into three groups (tertile 1: <21.58; tertile 2: ≥21.58, <26.77; and tertile 3: ≥26.77), and each group included 266 AMI patients. The baseline characteristics were displayed in Table 1. Patients in the highest tertile of admission NPAR level were older than other groups, and most of them were white. In addition, they reported more medical history of AF, but less comorbidities of CAD, hypertension and CHF. Moreover, patients in the highest tertile of admission NPAR level were less likely to use aspirin, clopidogrel, metoprolol, ACEI/ARBs and statin, and to receive PTCA or PCI. Finally, they had lower MBP, weight, albumin, hemoglobin, urine output in 24 hours, and higher values of heart rate, neutrophils, WBC, PT, RDW, creatinine, BUN, ALT, AST, SAPS II and SOFA.
Admission NPAR and outcome
As it had been shown in Table 2, the overall length of ICU stay (LOS) was 3.69 days, and the overall in-hospital, 30-day, 90-day, 180-day and 365-day all-cause mortality were 17.92%, 19.67%, 25.44%, 29.82% and 33.21%, respectively. Furthermore, as admission NPAR levels increased, the all-cause death rate of in-hospital, 30-day, 90-day, 180-day and 365-day were distinctly raised.
There were the survival curves of 30-day (log-rank, p<0,0001), 90-day (log-rank, p<0,0001), 180-day (log-rank, p<0,0001) and 365-day (log-rank, p<0,0001) all-cause mortality stratified by the tertiles of admission NPAR, which were manifested in Figure 2. The trends indicated that the higher NPAR level had a worse survival probability.
Admission NPAR as a predictor of the clinical endpoints
In cox regression models, admission NPAR levels were stratified by tertiles and quartiles, to appraise whether admission NPAR was related to 30-day, 90-day, 180-day and 365-day all-cause mortality (Table 3). In model I, after adjustments for age, race and gender, higher admission NPAR was associated with increased risk of all-cause mortality. In model II, age, gender, race, respiratory rate, MBP, heart rate, ALT, AST, CK-peak, CK-MB-peak, glucose, PT, hemoglobin, RDW, creatinine, potassium, sodium, BUN, WBC, platelet, CAD, AF, COPD, hypertension, diabetes, prior MI, CHF, CKD, stroke, SOFA and SAPS II were incorporated into the regression model.There was a prominent correlation between high admission NPAR, 180-day and 365-day all-cause mortality (tertile 3 vs. tertile 1: adjusted HR, 95% CI: 1.71,1.10-2.66, p<0.05; 1.66,1.10-2.51, p<0.05). However, the relationship between admission NPAR ,30-day and 90-day all-cause mortality was not as relevant as the other groups. Unexpectedly, a merely different trend was observed in admission NPAR levels stratified by quartiles; highest admission NPAR levels were independently associated with 90-day, 180-day and 365-day all-cause mortality (quartile 4 vs. quartile 1: adjusted HR, 95% CI: 2.36,1.32-4.23; 2.58,1.49-4.47; 2.61,1.56-4.37, p<0.05).
The ROC test was employed to measure the sensitivity and specificity of admission NPAR with an AUC of 0.6421 (95% CI 0.6016–0.6826, p<0.0001). Then the AUC area of admission NPAR was compared with SAPS II and SOFA score. There was no difference between NPAR and SOFA. Thus, it ascertained the quality of NPAR as a reliable predictor of 365-day all-cause mortality (Figure 3).
Subgroup Analysis
In most subgroups, no significant interaction between admission NPAR and 180-day all-cause mortality was observed (Table 4). Patients with high values of heart rate SAPS II, ICU LOS and age had higher risks of all-cause mortality for high admission NPAR.