Mohamed ELGhanamAin Shams University Hospitals, Egypt
Title: Index of deterioration of patients with prosthetic valve malfunction
Background: Mechanical valves used for treatment of rheumatic heart disease (RHD) have long term durability, yet, prosthetic valve dysfunction is one of the most life-threatening complications. Various Risk stratification models (STS score, EuroScore I and EuroScore II ) have been used to estimate perioperative mortality in cardiac surgery patients but none of them addressed the rate of deterioration of New York heart association (NYHA) class in this specific category of patients with prosthetic valve malfunction, as an ominous sign of poor outcome. We propose a numerical index relating deterioration in NYHA functional class in patients with prosthetic valve dysfunction to the duration of its occurrence “Index of Deterioration” (ID) and validate its use in predicting in-hospital mortality and incidence of postoperative complications.
Methods: 100 patients with prosthetic valve malfunction presented to our hospital between January 2016 and October 2019, all patients underwent urgent redo sternotomy and valve re-replacement. ID was applied to all of them; the patient’s numerical NYHA class on admission to the hospital (x) was subtracted from his base line NYHA class [during the period were he was asymptomatic (y)], then divided by the length of symptomatic period in months (z) . The result was a rate, assigned as the Index of Deterioration.
Results: In-hospital mortality was 21 cases, Index of Deterioration (ID) value of 12.400 showed sensitivity of 73% and specificity of 70% in predicting in-hospital mortality. Univariant analysis showed that manifest period of malfunction and preoperative NYHA class along with the proposed index was a good predictor of mortality. Other predictors were low preoperative ejection fraction, elevated serum creatinine and serum glutamic-oxaloacetic transaminase (SGOT). Multi variant analysis showed that cardiopulmonary bypass time and post-operative ejection fraction were independent predictors of mortality.
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