Predictive value of NLR, PLR and MPVLR for recent major cardiovascular adverse events in elderly patients with heart...

To evaluate the application value of neutrophil to lymphocyte ratio (NLR), platelet to lymphocyte ratio (PLR), and mean platelet volume to lymphocyte ratio (MPVLR) levels in identifying recent major cardiovascular adverse events (MACE) in elderly patients with heart failure (HF).

A total of 103 elderly HF patients admitted to Suzhou Hospital affiliated to Anhui Medical University from January 2022 to February 2025 were selected as the model group, and 74 patients from the same period served as the external validation group. All patients were followed up for 3 months after treatment. Patients were categorized into a MACE group and a non-MACE group based on the occurrence of MACE. Clinical data and levels of NLR, PLR, and MPVLR, were compared between the two groups. Multivariate logistic regression analysis was conducted to identify the independent risk factors for recent MACE. A forest plot was drawn using Graphpad Prism 8.0 software. Predictive models were evaluated using receiver operating characteristic (ROC) curves and calibration curves.

Patients in the MACE group were older and had a higher prevalence of diabetes compared to the non-MACE group. Levels of NLR, PLR, and MPVLR were significantly elevated in the MACE group. Multivariate logistic regression analysis identified NLR (OR = 7.928, 95 CI 2.633-23.869), PLR (OR = 1.077, 95 CI 1.038-1.117), MPVLR (OR = 1.688, 95 CI 1.134-2.513) as risk factors for recent MACE in elderly HF patients (all P < 0.05). ROC curve analysis showed that the combined use of NLR, PLR, and MPVLR had superior predictive performance compared to individual indicators (P < 0.05). The predictive model demonstrated superior discriminative ability compared to individual indicators (AUC = 0.919), which was further validated in the external validation group (AUC = 0.810), indicating consistent predictive accuracy.

Elevated levels of NLR, PLR, and MPVLR can serve as independent risk factors for assessing the risk of recent MACE in elderly HF patients. The combined predictive model demonstrates high accuracy and may assist in early risk stratification and personalized preventive strategies to reduce the risk of MACE.