Measurement of mortality during hospitalization due cardiovascular disease through the development of an artificial intelligence algorithm
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Abstract
Introduction: determining the cause of death of hospitalized patients with cardiovascular disease is of the utmost importance in order to take measures and thus improve the quality of care of these patients and prevent preventable deaths.
Objectives: to determine the main causes of death during hospitalization due to cardiovascular diseases.
To development and validate a natural language processing algorithm to automatically classify deceased patients according to their cause for hospitalization.
Design: retrospective exploratory study. Development of a natural language processing classification algorithm.
Results: of the total 6161 patients in our sample who died during hospitalization, 21.3% (1316) were hospitalized due to cardiovascular causes. The stroke represent 30.7%, heart failure 24.9%, and ischemic cardiac disease 14%.
The classification algorithm for detecting cardiovascular vs. Non-cardiovascular admission diagnoses yielded an accuracy of 0.9546 (95% CI 0.9351, 0.9696), the algorithm for detecting specific cardiovascular cause of admission resulted in an overall accuracy of 0.9407 (95% CI 0.8866, 0.9741).
Conclusions: cardiovascular disease represents 21.3% of the reasons for hospitalization of patients who die during hospital stays. The classification algorithms generally showed good performance, particularly the classification of cardiovascular vs non-cardiovascular cause for admission and the specific cardiovascular admission cause classifier.
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