Nomogram for predicting the 28-day mortality risk of patients with subendocardial infarction
BackgroundSubendocardial myocardial infarction (SEMI) represents a more severe form of myocardial infarction. Currently, there lacks a comprehensive clinical index for predicting mortality in cases of subendocardial myocardial infarction. The objective of our study was to develop and evaluate a nomo...
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Frontiers Media S.A.
2025-06-01
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| Series: | Frontiers in Cardiovascular Medicine |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fcvm.2025.1459855/full |
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| author | Menglei Li Menglei Li Beiping Song Xianjing Zeng Xunguo Wang Ao Ma Zhichao Meng Jiehao Zhu Xiubao Song Xianwu Lan Minghui Tan |
| author_facet | Menglei Li Menglei Li Beiping Song Xianjing Zeng Xunguo Wang Ao Ma Zhichao Meng Jiehao Zhu Xiubao Song Xianwu Lan Minghui Tan |
| author_sort | Menglei Li |
| collection | DOAJ |
| description | BackgroundSubendocardial myocardial infarction (SEMI) represents a more severe form of myocardial infarction. Currently, there lacks a comprehensive clinical index for predicting mortality in cases of subendocardial myocardial infarction. The objective of our study was to develop and evaluate a nomogram for predicting the 28-day risk of mortality among patients with SEMI.MethodsPatients diagnosed with subendocardial infarction were identified from the MIMIC-III database based on ICD-9 codes. Independent risk factors were screened utilizing the least absolute shrinkage and selection operator (LASSO) method alongside multivariate logistic regression. These identified risk factors were then employed to construct a nomogram aimed at predicting the 28-day mortality risk in patients with subendocardial infarction. The performance of the nomogram was evaluated by the Area Under the Curve (AUC), calibration curves, Hosmer-Lemeshow test, Integrated Discrimination Improvement (IDI), Net Reclassification Improvement (NRI), Decision Curve Analysis (DCA).ResultsA total of 3046 patients with subendocardial infarction were included in the study. Logistic regression analysis revealed that age, GCS score, creatinine level, hematocrit, hemoglobin, international normalized ratio, blood urea nitrogen level, urine output, heart rate, respiratory rate, peripheral oxygen saturation, peripheral vascular disease, diabetes complications, and solid tumors were independent risk factors for 28-day mortality. The AUC values of the nomogram surpassed those of the Acute Physiology Score III (APSIII), Simplified Acute Physiology Score II (SAPSII), and Sequential Organ Failure Assessment (SOFA) scoring systems in both the training and validation cohorts. Calculation of the IDI and NRI, along with DCA analysis, indicated a greater net benefit of the nomogram model.ConclusionThis study successfully identified independent risk factors for 28-day mortality in patients with SEMI. A nomogram model was developed to predict mortality, offering potential assistance in improving the prognosis of SEMI patients. |
| format | Article |
| id | doaj-art-f0a378c19ebc4c9a80259fe24f9fca66 |
| institution | OA Journals |
| issn | 2297-055X |
| language | English |
| publishDate | 2025-06-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Cardiovascular Medicine |
| spelling | doaj-art-f0a378c19ebc4c9a80259fe24f9fca662025-08-20T02:23:51ZengFrontiers Media S.A.Frontiers in Cardiovascular Medicine2297-055X2025-06-011210.3389/fcvm.2025.14598551459855Nomogram for predicting the 28-day mortality risk of patients with subendocardial infarctionMenglei Li0Menglei Li1Beiping Song2Xianjing Zeng3Xunguo Wang4Ao Ma5Zhichao Meng6Jiehao Zhu7Xiubao Song8Xianwu Lan9Minghui Tan10Department of Orthopedics, The First Affiliated Hospital of Jinan University, Guangzhou, ChinaCollege of Life Science and Technology, Jinan University, Guangzhou, ChinaDepartment of Nuclear Medicine, Hunan Provincial People’s Hospital (The First Affilated Hospital of Hunan Normal University), Changsha, Hunan, ChinaDepartment of Orthopedics, The First Affiliated Hospital of Jinan University, Guangzhou, ChinaDepartment of Rehabilitation Medicine, The First Affiliated Hospital of Jinan University, Guangzhou, ChinaDepartment of Orthopedics, The First Affiliated Hospital of Jinan University, Guangzhou, ChinaDepartment of Orthopedics, The First Affiliated Hospital of Jinan University, Guangzhou, ChinaDepartment of Orthopedics, The First Affiliated Hospital of Jinan University, Guangzhou, ChinaDepartment of Rehabilitation Medicine, The First Affiliated Hospital of Jinan University, Guangzhou, ChinaDepartment of Cardiology, The First Affiliated Hospital of Jinan University, Guangzhou, ChinaDepartment of Orthopedics, The First Affiliated Hospital of Jinan University, Guangzhou, ChinaBackgroundSubendocardial myocardial infarction (SEMI) represents a more severe form of myocardial infarction. Currently, there lacks a comprehensive clinical index for predicting mortality in cases of subendocardial myocardial infarction. The objective of our study was to develop and evaluate a nomogram for predicting the 28-day risk of mortality among patients with SEMI.MethodsPatients diagnosed with subendocardial infarction were identified from the MIMIC-III database based on ICD-9 codes. Independent risk factors were screened utilizing the least absolute shrinkage and selection operator (LASSO) method alongside multivariate logistic regression. These identified risk factors were then employed to construct a nomogram aimed at predicting the 28-day mortality risk in patients with subendocardial infarction. The performance of the nomogram was evaluated by the Area Under the Curve (AUC), calibration curves, Hosmer-Lemeshow test, Integrated Discrimination Improvement (IDI), Net Reclassification Improvement (NRI), Decision Curve Analysis (DCA).ResultsA total of 3046 patients with subendocardial infarction were included in the study. Logistic regression analysis revealed that age, GCS score, creatinine level, hematocrit, hemoglobin, international normalized ratio, blood urea nitrogen level, urine output, heart rate, respiratory rate, peripheral oxygen saturation, peripheral vascular disease, diabetes complications, and solid tumors were independent risk factors for 28-day mortality. The AUC values of the nomogram surpassed those of the Acute Physiology Score III (APSIII), Simplified Acute Physiology Score II (SAPSII), and Sequential Organ Failure Assessment (SOFA) scoring systems in both the training and validation cohorts. Calculation of the IDI and NRI, along with DCA analysis, indicated a greater net benefit of the nomogram model.ConclusionThis study successfully identified independent risk factors for 28-day mortality in patients with SEMI. A nomogram model was developed to predict mortality, offering potential assistance in improving the prognosis of SEMI patients.https://www.frontiersin.org/articles/10.3389/fcvm.2025.1459855/fullsubendocardial infarctionnomogramMIMIC-III databaseprognosismortality |
| spellingShingle | Menglei Li Menglei Li Beiping Song Xianjing Zeng Xunguo Wang Ao Ma Zhichao Meng Jiehao Zhu Xiubao Song Xianwu Lan Minghui Tan Nomogram for predicting the 28-day mortality risk of patients with subendocardial infarction Frontiers in Cardiovascular Medicine subendocardial infarction nomogram MIMIC-III database prognosis mortality |
| title | Nomogram for predicting the 28-day mortality risk of patients with subendocardial infarction |
| title_full | Nomogram for predicting the 28-day mortality risk of patients with subendocardial infarction |
| title_fullStr | Nomogram for predicting the 28-day mortality risk of patients with subendocardial infarction |
| title_full_unstemmed | Nomogram for predicting the 28-day mortality risk of patients with subendocardial infarction |
| title_short | Nomogram for predicting the 28-day mortality risk of patients with subendocardial infarction |
| title_sort | nomogram for predicting the 28 day mortality risk of patients with subendocardial infarction |
| topic | subendocardial infarction nomogram MIMIC-III database prognosis mortality |
| url | https://www.frontiersin.org/articles/10.3389/fcvm.2025.1459855/full |
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