Based on body temperature, CRP, Platelet and Age Scoring Models in distinguishing sterile inflammatory fever and infectious fever in patients with acute Myocardial Infarction

BackgroundFever is a common clinical manifestation following acute myocardial infarction(AMI). However, differentiating its etiology-specifically, distinguishing between fever caused by the absorption of necrotic tissue and fever due to concurrent infection is critical, as this distinction directly influences treatment decisions and patient prognosis. MethodsThis retrospective study reviewed AMI patients from two centers. Participants were divided into two groups: a fever of non-infectious origin group and patients with fever secondary to infection.We initially identified candidate risk factors demonstrating significant differences, Then,a stepwise selection technique was applied to potential univariate correlates (P < 0.1) to construct a multivariable risk score model. Results69 out of 1507 AMI patients were included, with 32 patients (46.4%) presenting AMI complicated by infection and 37 patients (53.6%) having AMI without infection but presenting with fever.Twelve dichotomous characteristics were screened as candidate predictor variables. Using stepwise elimination, four independent predictors were retained in the final logistic model: age, peak body temperature (BT), baseline platelet count, and peak CRP. Multivariate analysis identified the following independent predictors:age (OR=1.11, 95% CI: 1.041-1.186), peak BT (OR=9.83, 95% CI: 1.954-49.441), baseline platelet count (OR=1.01, 95% CI: 0.999-1.029), and peak CRP (OR=1.01, 95% CI: 0.998-1.026).A risk score was calculated by assigning points to categorized levels of each predictor weighted by their respective regression coefficients. The scoring distribution were: age (0,1,2,3,4,5 points), peak BT (0, 1, 3, 5 points), baseline platelet count (0, 1, 3, 5, 6 points), and peak CRP (0, 1, 2 points), which ranged from a minimum of 0 to a maximum of 18 .The score could predict the risk of infection with good discriminative ability (AuROC: 0.899, 95% CI: 0.823-0.975 P=0.000) in fever of AMI patients. ConclusionsWe first demonstrate that a simple bedside score incorporating BT, CRP, platelet count, and age can effectively discriminate between sterile inflammatory fever and infectious fever in patients with AMI.