Predicting in-hospital mortality using Elixhauser comorbidity in patients underwent single and multiple coronary artery bypass surgery
Coronary Artery Bypass Grafting (CABG) is a high-risk surgery. Cardiovascular diseases are strongly associated with comorbidities. This study aimed to assess the prediction of in-hospital mortality by comorbidities in patients who underwent CABG. The National Inpatient Sample database was used to ex...
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Veröffentlicht in: | Surgery in practice and science 2024-06, Vol.17, p.100246, Article 100246 |
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Zusammenfassung: | Coronary Artery Bypass Grafting (CABG) is a high-risk surgery. Cardiovascular diseases are strongly associated with comorbidities. This study aimed to assess the prediction of in-hospital mortality by comorbidities in patients who underwent CABG.
The National Inpatient Sample database was used to extract patients who received 1, 2, 3, and 4+ CABG between Q4 2015 and 2020. Best-fit model by logistic regressions was used to predict in-hospital mortality by Elixhauser Comorbidity Index (ECI). Moreover, age was adjusted in ECI prediction.
There were 190,524, 83,725, 48,147, and 13,540 patients who underwent 1, 2, 3, and 4+ CABG, respectively. In-hospital mortality was best predicted by ECI in 3 CABG (c-statistic = 0.63, 95 % CI = 0.62–0.65), followed by 4+ CABG (c-statistic = 0.63, 95 % CI = 0.60–0.66), 1 CABG (c-statistic = 0.62, 95 % CI = 0.61–0.63), and 2 CABG (c-statistic = 0.62, 95 % CI = 0.61–0.63). After adjusting for age, ECI adequately predicted in-hospital mortality in 4+ CABG (c-statistic = 0.72, 95 % CI = 0.69–0.75) and 3 CABG (c-statistic = 0.69, 95 % CI = 0.68–0.71). Predictive powers for age-adjusted ECI were comparable in 1 CABG (c-statistic=0.67, 95 % CI = 0.66–0.68) and 2 CABG (c-statistic = 0.67, 95 % CI = 0.65–0.68).
ECI was a moderate (c-statistic 0.6–0.7) predictor of in-hospital mortality in all CABG. Age-adjusted ECI could effectively predict in-hospital mortality, especially in patients who underwent 3 and 4+ CABG. |
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ISSN: | 2666-2620 2666-2620 |
DOI: | 10.1016/j.sipas.2024.100246 |