Identification of the prognostic horizon of the predictive model of risk of cardiac complications in patients with acute myocardial infarction
Abstract
The proposed predictive model for in-hospital cardiac complications in patients with acute myocardial infarction stands out for its prognostic horizon (24-48 h post-admission), based on clinical and echocardiographic variables (LVEF ≤40%, RV TDI ≤9.5 cm/s, IAP ≥15 mmHg), with high sensitivity (89.68%) and positive predictive value (94.17%), although limited by moderate specificity (79.41%) and low negative predictive value (67.50%). It outperforms traditional models (GRACE, TIMI) by integrating structural parameters, but its dependence on echocardiography restricts its use in resource-limited settings. Calibration (Hosmer-Lemeshow, p=0.760) and Nagelkerke R² (0.65) support its fit, although 34% of variability remains unexplained. Its validity in contexts outside of Cuba (thrombolytic therapy vs. angioplasty) requires external validation. Although useful for early stratification and optimization of care, its implementation requires adaptation to local conditions, technical training, and consideration of socioeconomic factors.
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1. Rosabal García Y, Guzmán Pérez N, Rosales Guibert EA. Modelo predictivo de riesgo de complicaciones cardiacas en pacientes con infarto agudo de miocardio [Internet]. Rev Cubana Med Milit. 2025 [acceso: 18/04/2025];54(2):e025063831. Disponible en: https://revmedmilitar.sld.cu/index.php/mil/article/view/63831
2. Salari N, Morddarvanjoghi F, Abdolmaleki A, Rasoulpoor S, Khaleghi AA, Hezarkhani LA, et al. The global prevalence of myocardial infarction: a systematic review and meta-analysis [Internet]. BMC Cardiovasc Disord. 2023 [acceso: 18/04/2025];23:206. Disponible en: https://doi.org/10.1186/s12872-023-03231-w
3. Gao H, Wang K, Wang X, Zeng D, Chen Z. Integration of two-dimensional echocardiography: A novel risk indicator for ST-segment elevation myocardial infarction [Internet]. ESC Heart Fail. 2024 [acceso: 18/04/2025];11(5):3312-3321. Disponible en: https://pmc.ncbi.nlm.nih.gov/articles/PMC11424358/
4. González de la Cuesta DM. Errores y sesgos en investigación clínica [Internet]. Enferm Intensiva (Engl ). 2021[acceso: 18/04/2025];32:220-3. Disponible en: https://doi.org/10.1016/j.enfi.2021.03.003
5. Martínez Pérez JA, Pérez Martín PS. Logistic regression. Semergen [Internet]. 2024 [acceso: 18/04/2025];50:102086. Disponible en: https://doi.org/10.1016/j.semerg.2023.102086
6. Roy García IA, Paredes Manjarrez C, Moreno Palacios J, Rivas Ruiz R, Flores Pulido AA. Curvas ROC: características generales y su uso en la práctica clínica [Internet]. Rev Med Inst Mex Seguro Soc. 2023 [acceso: 18/04/2025];61(Suppl 3):S497-S502. Disponible en: https://pmc.ncbi.nlm.nih.gov/articles/PMC10754459/
7. Yanqiao L, Shen L, Yutong M, Linghong S, Ben H. Comparison of GRACE and TIMI risk scores in the prediction of in-hospital and long-term outcomes among East Asian non-ST-elevation myocardial infarction patients [Internet]. BMC Cardiovasc Disord. 2022 [acceso: 18/04/2025];22(1):4. Disponible en: https://pubmed.ncbi.nlm.nih.gov/34996365/
8. Rendón-Macías ME, Castillo-Ivón AS. Metodología para la elaboración de los estudios sobre pronóstico [Internet]. Rev. alerg. Méx. 2022 [acceso: 18/04/2025]; 69(1): 48-55. Disponible en: http://www.scielo.org.mx/scielo.php?script=sci_arttext&pid=S2448-91902022000100048&lng=es
9. Mühlhoff R. Predictive privacy: towards an applied ethics of data analytics [Internet]. Ethics Inf Technol. 2021 [acceso: 18/04/2025];23:675-90. Disponible en: https://doi.org/10.1007/s10676-021-09606-x
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