An Easy-to-Use Nomogram Based on SII and SIRI to Predict in-Hospital Mortality Risk in Elderly Patients with Acute Myocardial Infarction

Abstract

Aim

Inflammatory response is closely associated with poor prognosis in elderly patients with acute myocardial infarction (AMI). The aim of this study was to develop an easy-to-use predictive model based on medical history data at admission, systemic immune inflammatory index (SII), and systemic inflammatory response index (SIRI) to predict the risk of in-hospital mortality in elderly patients with AMI.

Methods

We enrolled 1550 elderly AMI patients (aged ≥60 years) with complete medical history data and randomized them 5:5 to the training and validation cohorts. Univariate and multivariate logistic regression analyses were used to screen risk factors associated with outcome events (in-hospital death) and to establish a nomogram. The discrimination, calibration, and clinical application value of nomogram were evaluated based on receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA), respectively.

Results

The results of multivariate logistic regression showed that age, body mass index (BMI), previous stroke, diabetes, SII, and SIRI were associated with in-hospital death, and these indicators will be included in the final prediction model, which can be obtained by asking the patient’s medical history and blood routine examination in the early stage of admission and can improve the utilization rate of the prediction model. The areas under the ROC curve for the training and validation cohorts nomogram were 0.824 (95% CI 0.796 to 0.851) and 0.809 (95% CI 0.780 to 0.836), respectively. Calibration curves and DCA showed that nomogram could better predict the risk of in-hospital mortality in elderly patients with AMI.

Conclusion

The nomogram constructed by combining SII, SIRI, and partial medical history data (age, BMI, previous stroke, and diabetes) at admission has a good predictive effect on the risk of in-hospital death in elderly patients with AMI.

Keywords:

• coronary artery disease
• elderly
• systemic inflammatory markers
• nomogram
• prediction model

Data Sharing Statement

The data that support the results of this study are available from the corresponding author upon reasonable request.

Statement of Ethics

The study protocol has been reviewed and approved by the Ethics Committee of the Second Hospital of Dalian Medical University. The Ethics Committee of the Second Hospital of Dalian Medical University waived the need for informed consent based on the following reasons: (1) The purpose of the study was important; (2) The possible risk to patients was not higher than the minimum one; (3) The waiver of informed consent would not adversely affect the rights and health of patients; (4) The patients’ privacy and personal identity information were well protected. We have desensitized the patient ‘s personal identity to protect patient privacy. The protocol of the study is compliant with the Declaration of Helsinki.

Patient Privacy Protection Statement

We desensitized all the data that can be used to identify patient personal information, such as their names, hospitalization ID, and telephone numbers, to protect the privacy of patients.

Author Contributions

All authors made a significant contribution to the work reported, whether that is in the conception, study design, execution, acquisition of data, analysis and interpretation, or in all these areas; took part in drafting, revising or critically reviewing the article; gave final approval of the version to be published; have agreed on the journal to which the article has been submitted; and agree to be accountable for all aspects of the work.

Disclosure

The authors declare no conflicts of interest in this work.