Construction of a predictive model for depressive symptoms following acute myocardial infarction and its impact on prognosis
ObjectiveTo construct a predictive model for depressive symptoms following acute myocardial infarction (AMI) and analyze its impact on patient outcomes.MethodsA retrospective analysis was conducted on the clinical data of 216 patients who successfully underwent percutaneous coronary intervention (PC...
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| Language: | English |
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Frontiers Media S.A.
2025-04-01
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| Series: | Frontiers in Psychiatry |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fpsyt.2025.1431182/full |
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| author | Lei Ren Hongqi Wang Xin Su Yangyang Yang Yuanzhuo Zhang Xiaoyan Yin Dapeng Zhang Guangquan Hu Bin Ning |
| author_facet | Lei Ren Hongqi Wang Xin Su Yangyang Yang Yuanzhuo Zhang Xiaoyan Yin Dapeng Zhang Guangquan Hu Bin Ning |
| author_sort | Lei Ren |
| collection | DOAJ |
| description | ObjectiveTo construct a predictive model for depressive symptoms following acute myocardial infarction (AMI) and analyze its impact on patient outcomes.MethodsA 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.ResultsAt 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).ConclusionKillip 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. |
| format | Article |
| id | doaj-art-39dc44d2c6c147bfbd5ce5ec965867d5 |
| institution | OA Journals |
| issn | 1664-0640 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | Frontiers Media S.A. |
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| series | Frontiers in Psychiatry |
| spelling | doaj-art-39dc44d2c6c147bfbd5ce5ec965867d52025-08-20T02:29:24ZengFrontiers Media S.A.Frontiers in Psychiatry1664-06402025-04-011610.3389/fpsyt.2025.14311821431182Construction of a predictive model for depressive symptoms following acute myocardial infarction and its impact on prognosisLei Ren0Hongqi Wang1Xin Su2Yangyang Yang3Yuanzhuo Zhang4Xiaoyan Yin5Dapeng Zhang6Guangquan Hu7Bin Ning8Department of Cardiovascular Medicine, Fuyang People’s Hospital Affiliated to Anhui Medical University (Fuyang People’s Hospital), Fuyang, ChinaDepartment of Cardiovascular Medicine, Fuyang People’s Hospital Affiliated to Anhui Medical University (Fuyang People’s Hospital), Fuyang, ChinaDepartment of Cardiovascular Medicine, Fuyang People’s Hospital Affiliated to Anhui Medical University (Fuyang People’s Hospital), Fuyang, ChinaDepartment of Cardiovascular Medicine, Fuyang Hospital Affiliated to Bengbu Medical College (Fuyang People’s Hospital), Fuyang, ChinaDepartment of Cardiovascular Medicine, Fuyang Hospital Affiliated to Bengbu Medical College (Fuyang People’s Hospital), Fuyang, ChinaDepartment of Cardiovascular Medicine, Fuyang Hospital Affiliated to Bengbu Medical College (Fuyang People’s Hospital), Fuyang, ChinaDepartment of Psychiatry, Fuyang Third People’s Hospital, Fuyang, ChinaDepartment of Cardiovascular Medicine, The Second Affiliated Hospital of Anhui Medical University, Hefei, ChinaDepartment of Cardiovascular Medicine, Fuyang People’s Hospital Affiliated to Anhui Medical University (Fuyang People’s Hospital), Fuyang, ChinaObjectiveTo construct a predictive model for depressive symptoms following acute myocardial infarction (AMI) and analyze its impact on patient outcomes.MethodsA 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.ResultsAt 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).ConclusionKillip 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.https://www.frontiersin.org/articles/10.3389/fpsyt.2025.1431182/fullacute myocardial infarctiondepressive symptomspredictive modelprognosismajor adverse cardiovascular events |
| spellingShingle | Lei Ren Hongqi Wang Xin Su Yangyang Yang Yuanzhuo Zhang Xiaoyan Yin Dapeng Zhang Guangquan Hu Bin Ning Construction of a predictive model for depressive symptoms following acute myocardial infarction and its impact on prognosis Frontiers in Psychiatry acute myocardial infarction depressive symptoms predictive model prognosis major adverse cardiovascular events |
| title | Construction of a predictive model for depressive symptoms following acute myocardial infarction and its impact on prognosis |
| title_full | Construction of a predictive model for depressive symptoms following acute myocardial infarction and its impact on prognosis |
| title_fullStr | Construction of a predictive model for depressive symptoms following acute myocardial infarction and its impact on prognosis |
| title_full_unstemmed | Construction of a predictive model for depressive symptoms following acute myocardial infarction and its impact on prognosis |
| title_short | Construction of a predictive model for depressive symptoms following acute myocardial infarction and its impact on prognosis |
| title_sort | construction of a predictive model for depressive symptoms following acute myocardial infarction and its impact on prognosis |
| topic | acute myocardial infarction depressive symptoms predictive model prognosis major adverse cardiovascular events |
| url | https://www.frontiersin.org/articles/10.3389/fpsyt.2025.1431182/full |
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