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. 2025 May 3;30(1):357.
doi: 10.1186/s40001-025-02624-1.

A nomogram risk prediction model for ischemic mitral regurgitation after primary percutaneous coronary intervention in patients with ST-segment elevation myocardial infarction

Jiangping Ye  1   2   3 , Rikang Yuan  1   3 , Yehong Liu  1 , Weijian Wang  1 , Dongxia Xu  1   3 , Yimeng Li  1   4 , Gangyong Wu  5   6   7 , Gangjun Zong  8   9   10
Affiliations

A nomogram risk prediction model for ischemic mitral regurgitation after primary percutaneous coronary intervention in patients with ST-segment elevation myocardial infarction

Jiangping Ye et al. Eur J Med Res. .

Abstract

Aim: This study developed a nomogram to predict the risk of ischemic mitral regurgitation (IMR) after percutaneous coronary intervention (PCI) in patients with ST-segment elevation myocardial infarction (STEMI) patients and evaluate their long-term prognosis.

Methods: Data from 342 STEMI patients were collected. Logistic regression identified independent risk factors for IMR during hospitalization, while Cox regression assessed risk factors during follow-up. The nomogram was developed based on these factors. ROC evaluated its predictive value, and decision curve analysis/clinical impact curves assessed clinical utility. Kaplan-Meier analysis evaluated the model's prognostic value.

Results: The independent risk factors for hospitalized IMR after PCI in STEMI patients included Gensini score (OR 1.009; P = 0.047), left ventricular ejection fraction (LVEF) (OR 0.941; P = 0.007), albumin (OR 0.941; P = 0.046), and systemic immune-inflammatory index (SII) (OR 1.096; P < 0.001). During follow-up, diabetes mellitus (HR: 1.154; P = 0.019), hemoglobin (HR: 0.991; P = 0.028), Gensini score (HR: 1.007; P = 0.022), LVEF (HR: 0.972; P = 0.015), and SII/100 (HR: 1.034; P < 0.001) were identified as independent predictors of IMR. The nomogram showed strong clinical benefit, good calibration, and predictive value. Patients with lower scores had better long-term outcomes.

Conclusion: This nomogram effectively predicts the occurrence of IMR after PCI in STEMI patients, providing valuable prognostic insights.

Keywords: Major adverse cardiovascular events; Mitral regurgitation; Nomogram; Prognosis; ST-segment elevation myocardial infarction.

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Conflict of interest statement

Declarations. Ethics approval and consent to participate: The research was carried out in compliance with the Declaration of Helsinki and granted approval by the Joint Logistics Support Force of the Chinese People's Liberation Army, 904 Hospital Ethics Committee, Wuxi, China (Clinical trial number: 20240405). Written informed consent was obtained from all patients, allowing for the retrospective utilization of their de-identified data for health-related research purposes. Consent for publication: Not applicable. Competing interests: The authors declare no competing interests.

Figures

Fig. 1
Fig. 1
Flowchart of patient inclusion. PCI: percutaneous coronary intervention; STEMI: ST-segment elevation myocardial infarction; IMR: ischemic mitral regurgitation
Fig. 2
Fig. 2
Development and verification of a nomogram risk prediction model for the incidence of IMR in STEMI patients hospitalized following PCI. A Nomogram predicting the risk of IMR during hospitalization in STEMI patients following PCI; (B) Model calibration curves predicting the risk of IMR during hospitalization; (C) Clinical impact curves of the model; (D) Model decision curve analysis; (E) ROC curves to evaluate the diagnostic performance of the model; (F) Comparison of the SII/100, LVEF, Gensini score, albumin and ROC curves of the nomogram risk prediction model. LVEF: Left ventricular ejection fraction; SII: Systemic immune-inflammation index
Fig. 3
Fig. 3
Nomogram showing the incidence of IMR in STEMI patients 12, 24, and 36 months following PCI. LVEF: Left ventricular ejection fraction; SII: Systemic immune-inflammation index
Fig. 4
Fig. 4
ROC curves of the nomogram risk prediction model indicating the likelihood of IMR in STEMI patients following PCI at 12, 24, and 36 months of follow-up
Fig. 5
Fig. 5
The nomogram risk prediction model's calibration curves and decision curve analysis (DCA). The nomogram risk prediction model's calibration curves for the probability and proportion of actual IMR occurrence at 12 months (A), 24 months (B), and 36 months (C) are shown. Risk prediction model of DCA validation nomogram for IMR occurrence at 12 months (D), 24 months (E), and 36 months (F)
Fig. 6
Fig. 6
MACEs in STEMI patients with IMR during hospitalization and during post-discharge follow-up following PCI. A Comparison of MACEs that patients in the IMR and non-IMR groups experienced during hospitalization. B Comparison of MACEs that occurred at discharge follow-up between patients in the IMR and non-IMR groups
Fig. 7
Fig. 7
Kaplan–Meier survival analysis of STEMI patients in the nomogram risk prediction model ≤ 95.67 and > 95.67 groups with follow-up MACEs
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