Construction of a predictive model for depressive symptoms following acute myocardial infarction and its impact on prognosis.

OBJECTIVE

To construct a predictive model for depressive symptoms following acute myocardial infarction (AMI) and analyze its impact on patient outcomes.

METHODS

A retrospective analysis was conducted on the clinical data of 216 patients who successfully underwent percutaneous coronary intervention (PCI) for AMI at the hospital from January 2022 to June 2023. One month post-PCI, patients were categorized into groups with and without depressive symptoms based on the Self-Rating Depression Scale (SDS) scores. Logistic regression was used to identify factors influencing depressive symptoms, and a nomogram model for post-PCI depressive symptoms risk in AMI patients was developed using these factors. Internal validation of the model was performed using the Bootstrap method and Hosmer-Lemeshow goodness-of-fit test. The model's value was assessed through Receiver Operating Characteristic (ROC) curve analysis. Outcomes at six months post-PCI were also compared between patients with different levels of depressive symptoms.

RESULTS

At one month post-PCI, the incidence of depressive symptoms was 54.63%. Logistic regression revealed that Killip class III, monocyte count, albumin levels, C-reactive protein (CRP), and left ventricular ejection fraction (LVEF) were significant predictors of post-AMI depressive symptoms (P < 0.05). The nomogram, based on these five primary indicators, showed good concordance with acceptable and ideal curves (Hosmer-Lemeshow test χ2 = 10.593, P = 0.226); the area under the ROC curve was 0.767 (95% CI: 0.702-0.831). At six months post-PCI, the rates of rehospitalization and major adverse cardiovascular events were higher in the group with depressive symptoms compared to those without (P < 0.05); severe depressive symptoms were associated with a higher rate of major adverse cardiovascular events than mild depressive symptoms (P < 0.05).

CONCLUSION

Killip class III, monocyte count, albumin levels, CRP, and LVEF are significant predictors of post-AMI depressive symptoms. The predictive model based on these factors demonstrates good calibration and discriminative ability; moreover, depressive symptoms adversely affect the prognosis of AMI patients, with more severe symptoms correlating with a higher incidence of major adverse cardiovascular events.