Background Red blood cell distribution width (RDW) to platelet ratio (RPR) is a novel inflammatory indicator. It integrates the risk prediction of RDW and platelet, which is associated with adverse outcomes. However, the predictive power of RPR in mortality for patients with acute myocardial infarction (AMI) remains uncertain. Thus, we aimed to explore the association between RPR and 180-day in-hospital mortality in patients with AMI. Methods Data on patients with AMI were extracted from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. Patients were divided into two groups according to the optimal RPR cut-off value. The survival curve between high and low RPR groups was plotted via the Kaplan-Meier (KM) method. Univariate and multivariate Cox regression analyses were performed to determine the association between RPR on admission and 180-day in-hospital mortality. Results A total of 1266 patients were enrolled, of which 83 (6.8%) died within 180 days during the hospitalization. Compared with the survivor group, the non-survivor group had higher RPR on admission (0.11 ± 0.07 vs. 0.08 ± 0.06, P < 0.001). The KM curve indicated that the survival probability of low RPR group was higher than that of high RPR group. Multivariate Cox regression analysis demonstrated that higher RPR on admission was an independent and effective predictor of 180-day mortality in patients with AMI (hazard ratio [HR]: 2.677, 95% confidence interval [CI]: 1.159–6.188, P = 0.021). Conclusion Higher RPR was associated with higher in-hospital 180-day mortality in patients with AMI.

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Background: Red blood cell distribution width (RDW) has been showed to have independent predictive ability of mortality in patients with coronary artery disease and HF. However, no relevant research is established to demonstrate the relationship between RDW and heart failure hospitalization (HFH) in patients who received pacemaker. Methods: The baseline RDW was individually recorded at admission in patients with pacemaker implantation. Patients were assigned to high and low RDW groups based on cut-off values. Restricted cubic splines were used to model the RDW-HFH association. The curve of patients free of HFH was plotted via the Kaplan-Meier method. And the significance of association between RDW and HFH was analyzed using both crude and adjusted cox proportional hazard model with hazard ratios (HR) and 95% confidence intervals (CI). Results: A total of 927 patients who successfully received pacemaker implantation were enrolled. Seventy and seven (8.3%) patients met the endpoint, and 61(12.8%) patients had RDW≥13.45. Analysis of the receiver operating characteristicscurve for RDW demonstrated an optimal cut-off value of 13.45. The incidence of HFH in patients with high level of RDW were higher than that in those patients with low level of RDW (P＜0.001). Moreover, despite controlling for other potential risk factors, the incidence of HFH was higher than the high RDW group (HR=2.197, 95% CI:1.638-5.196, P<0.001). Conclusion: High RDW contributes to HFH in patients with pacemaker implantation during the long-term follow-up, suggesting that RDW can effectively predict the probability of HFH for patients with pacemaker implantation.

Background Prognostic nutritional index (PNI) score is a useful indicator to evaluate the nutritional status of patients. However, the nutritional significance of the PNI score and its ability to predict clinical prognosis in patients with surgical valve replacement (SVR) are unknown. The goal of this study was to analyze the association between PNI on admission and adverse events in patients following SVR.Methods This study included 485 patients who underwent successful SVR. Baseline PNI score was calculated before SVR on admission. The patients were divided into high and low PNI groups according to the cut-off value of PNI using the receiver operating characteristic (ROC) curve. Primary outcomes were composite adverse events, defined as worsening heart failure, myocardial infarction, major bleeding, uncontrolled infection, second surgery, post-operative arrhythmia or all-cause death during the follow-up. The association of PNI score and primary outcomes was presented as hazard ratios (HR) with 95% confidence intervals (CI) calculated by adverse events in the crude and multivariate-adjusted Cox Proportional Hazards models.Results Overall, adverse events were observed in 61(13%) patients. ROC curves revealed an area under curve of 0.676 for PNI with a cut-off of 46. The cumulative event rate by Kaplan–Meier analysis was higher in low PNI group (P < 0.001). Adjusted multivariate analysis showed that low PNI was associated with adverse outcomes (HR: 2.303, 95% CI: 1.338-3.964, P = 0.003). Conclusion Low PNI on admission in patients with SVR was associated with higher incidence of clinical adverse events. Using the PNI score to identify individuals with poor nutritional status might be an important method for clinical prognosis prediction, and improving nutritional status during follow-up might help to reduce the risks of adverse outcomes in these patients.