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Murine Myocardial Infarction Model using Permanent Ligation of Left Anterior Descending Coronary Artery
Published on: August 16, 2019
New model predicts in-hospital complications in myocardial infarction
Geovedy Martinez-Garcia1, Miguel Rodriguez-Ramos2, Maikel Santos-Medina3
1Cardiology Service, Enrique Cabrera General Teaching Hospital, Havana, Cuba.
Insights
The leukoglycemic index has low prognostic value for in-hospital complications in ST-elevation myocardial infarction patients. A new predictive model, however, effectively identifies high-risk individuals for better healthcare management.
Area of Science:
- Cardiology
- Internal Medicine
- Biostatistics
Background:
- Ischemic cardiopathy is a leading global cause of death.
- ST-elevation myocardial infarction (STEMI) requires accurate risk stratification for in-hospital complications.
- The prognostic capacity of the leukoglycemic index (LGI) in STEMI patients is under investigation.
Purpose of the Study:
- To evaluate the prognostic capacity of the leukoglycemic index in STEMI patients.
- To develop a predictive model for in-hospital complications in STEMI patients.
Main Methods:
- A multicenter cohort study included 900 STEMI patients and 233 external validation subjects.
- Performance of the LGI was assessed using statistical C (discrimination) and the Hosmer-Lemeshow test (calibration).
- A logistic binary regression model identified predictive factors for in-hospital complications.
Main Results:
- An optimal LGI cut-point of 1188 was identified (AUC 0.623).
- LGI ≥ 1188 was significantly associated with increased risk of in-hospital complications (RR 2.4).
- A predictive model incorporating age ≥ 66, LGI ≥ 1188, Killip-Kimball ≥ II, and hypertension showed good discrimination.
Conclusions:
- The leukoglycemic index demonstrates low performance in predicting in-hospital complications in STEMI.
- The developed predictive model effectively estimates the risk of in-hospital complications.
- This model can aid healthcare systems, particularly in developing countries, in identifying high-risk patients without additional cost.
Introduction And Objectives:
Ischemic cardiopathy constitutes the leading cause of death worldwide. Our aim was to evaluate the prognostic capacity of the leukoglycemic index as well as to create a predictive model of in-hospital complications in patients with ST elevation myocardial infarction.
Materials And Methods:
This was a multicentral and cohort study, which included patients inserted in the Cuban Registry of acute myocardial infarction. The study investigated 900 patients with a validation population represented by 233 external subjects. In order to define the performance of the leukoglycemic index were evaluated the discrimination with the statistical C and the calibration by Hosmer - Lemeshow test. A model of logistic binary regression was employed in order to define the predictive factors. RESULTS: Optimal cut point of the leukoglycemic index to predict in-hospital complications was 1188 (sensibility 60%; specificity 61.6%; area under the curve 0.623; p < 0.001). In-hospital complications were significantly higher in the group with the leukoglycemic index ≥ 1188; a higher value was significantly associated with a higher risk to develop an in-hospital complication [RR (IC 95%) = 2.4 (1.804-3.080); p<0.001]. The predictive model proposed is composed by the following factors: age ≥ 66 years, leukoglycemic index ≥ 1188, Killip-Kimball classification ≥ II and medical history of hypertension. This scale had a good discrimination in both, the training and the validation population.
Conclusion:
The leukoglycemic index possesses a low performance when used to assess the risks for in hospital complications in patients with ST elevation myocardial infarction. The new predictive model has a good performance, which can be applied to estimate risk of in-hospital complications. This model would be able to contribute to the health systems of developing countries without additional cost; it enables prediction of the patients having a higher risk of complications and a negative outcome during the hospitable admission.
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