Relationship Between Inflammatory Markers and Long-Term Prognosis in ICU Patients with Acute Non-ST-Segment Elevation Myocardial Infarction

Li YanzeJin HongjinGuolin ZhangYangyou ZhangYanchun Ding^*

• Department of Cardiology, Second Affiliated Hospital of Dalian Medical University, Dalian, China

Objective: This study aims to investigate the relation of inflammatory markers to the long-term prognosis of patients with severe non-ST-segment elevation myocardial infarction (NSTEMI) in the intensive care unit (ICU), and to further develop a predictive model for their long-term outcomes. Methods: This study utilized data on eligible NSTEMI patients from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. Patients were grouped based on mortality outcomes. The link of inflammatory markers to all-cause mortality (ACM) at 180 and 360 days in the ICU was analyzed through the Cox proportional hazards model and restricted cubic spline (RCS) curves. Survival differences across groups were evaluated via Kaplan-Meier (KM) survival analysis. The sample population was randomized into training and validation sets, and a novel prediction model for the risk of long-term death in ICU-admitted NSTEMI patients was constructed in the training group and validated in both groups. Results: 1,607 NSTEMI patients were encompassed, with ACM rates of 9.7% at 180 days and 12.9% at 360 days. Multivariable Cox proportional hazards model analysis revealed that, in contrast to the low-level group (Q1), higher levels of neutrophil-to-lymphocyte ratio(NLR), neutrophil-to-lymphocyte-platelet ratio (NLPR), red blood cell distribution width (RDW), systemic immune-inflammation index (SII), and systemic inflammation response index (SIRI) were positively associated with ACM within 180 days and 360 days (all P < 0.05). The novel predictive model demonstrated high prognostic accuracy for long-term death in ICU-admitted NSTEMI individuals, with areas under the receiver operating characteristic (ROC) curve (AUC) of 0.730 in the training set and 0.751 in the validation set. Calibration curves revealed good concordance between predicted and observed probabilities. Conclusion: NLR, NLPR, and RDW are independent risk factors for long-term death in the ICU-admitted NSTEMI population. The long-term prognostic prediction model constructed for NSTEMI patients based on the aforementioned associations demonstrates high clinical predictive value.