Development of a nomogram for the prediction of in-hospital mortality in patients with acute ST-elevation myocardial infarction after primary percutaneous coronary intervention: a multicentre, retrospective, observational study in Hebei province, China

Abstract

Objectives: To establish a clinical prognostic nomogram for predicting in-hospital mortality after primary percutaneous coronary intervention (PCI) among patients with ST-elevation myocardial infarction (STEMI).

Design: Retrospective, multicentre, observational study.

Setting: Thirty-nine hospitals in Hebei province.

Participants: Patients with STEMI who underwent PCI from January 2018 to December 2019.

Interventions: A multivariable logistic regression model was used to identify the factors associated with in-hospital mortality, and a nomogram was established using these factors. The performance of the nomogram was evaluated by the discrimination, calibration and clinical usefulness.

Primary and secondary outcome measures: The outcome was the factors associated with in-hospital mortality.

Results: This study included 855 patients, among whom 223 died in hospital. Age, body mass index, systolic pressure on admission, haemoglobin, random blood glucose on admission, ejection fraction after PCI, use aspirin before admission, long lesions, thrombolysis in myocardial infarction flow grade and neutrophils/lymphocytes ratio were independently associated with in-hospital mortality (all p<0.05). In the training set, the nomogram showed a C-index of 0.947, goodness-of-fit of 0.683 and area under the receiver operating characteristic curve (AUC) of 0.947 (95% CI 0.927 to 0.967). In the testing set, the C-index was 0.891, goodness-of-fit was 0.462 and AUC was 0.891 (95% CI 0.844 to 0.939). The results indicate that the nomogram had good discrimination and good prediction accuracy and could achieve a good net benefit.

Conclusions: A nomogram to predict in-hospital mortality in patients with STEMI after PCI was developed and validated in Hebei, China and showed a satisfactory performance. Prospective studies will be necessary to confirm the performance and clinical applicability and practicality of the nomogram.

Keywords: coronary heart disease; coronary intervention; myocardial infarction.

Figure 1

Flow chart illustrating the process of patient selection. DCA, decision curve analysis; PCI, percutaneous coronary intervention; ROC, receiver operator characteristic; STEMI, ST-elevation myocardial infarction.

Figure 2

The nomogram for the prediction of in-hospital mortality in patients with acute ST-elevation myocardial infarction after primary PCI. BMI, body mass index; EF, ejection fraction; HGB, haemoglobin; N/LR, neutrophils/lymphocytes ratio; PCI, percutaneous coronary intervention; SBP, systolic blood pressure; TIMI, thrombolysis in myocardial infarction.

Figure 3

The calibration curves of the nomogram for the training set (A) and the testing set (B).

Figure 4

The received operating characteristics (ROC) curves of the nomogram for the training set (A) and the testing set (B). AUC, area under the curve.

Figure 5

The decision curve analysis for the risk model for the training set (A) and the testing set (B).