[Identification of risk factors for allogenic transfusion in cardiac surgery from an observational study]

Prediction models for prolonged intensive care unit stay after cardiac surgery: systematic review and validation study

BACKGROUND

Several models have been developed to predict prolonged stay in the intensive care unit (ICU) after cardiac surgery. However, no extensive quantitative validation of these models has yet been conducted. This study sought to identify and validate existing prediction models for prolonged ICU length of stay after cardiac surgery.

METHODS AND RESULTS

After a systematic review of the literature, the identified models were applied on a large registry database comprising 11 395 cardiac surgical interventions. The probabilities of prolonged ICU length of stay based on the models were compared with the actual outcome to assess the discrimination and calibration performance of the models. Literature review identified 20 models, of which 14 could be included. Of the 6 models for the general cardiac surgery population, the Parsonnet model showed the best discrimination (area under the receiver operating characteristic curve=0.75 [95% confidence interval, 0.73 to 0.76]), followed by the European system for cardiac operative risk evaluation (EuroSCORE) (0.71 [0.70 to 0.72]) and a model by Huijskes and colleagues (0.71 [0.70 to 0.73]). Most of the models showed good calibration.

CONCLUSIONS

In this validation of prediction models for prolonged ICU length of stay, 2 widely implemented models (Parsonnet, EuroSCORE), although originally designed for prediction of mortality, were superior in identifying patients with prolonged ICU length of stay.

Development and validation of Transfusion Risk Understanding Scoring Tool (TRUST) to stratify cardiac surgery patients according to their blood transfusion needs

BACKGROUND

Allogeneic blood transfusion is associated with transfusion reactions, infection transmission, and postoperative morbidity and mortality. The objective of this study was to develop and validate an accurate and simple clinical index to stratify cardiac surgery patients according to their blood transfusion needs.

METHODS AND RESULTS

Data on consecutive adult patients who underwent cardiac surgery at Toronto General Hospital (n = 11,113) and Sunnybrook and Women's College Health Sciences Center (n = 5316) between May 1999 and June 2004 were collected for the development, validation, and external validation of the index. Primary outcome was the exposure to blood transfusion in the operative and first postoperative days. Multivariable logistic regression modeling techniques were used to determine the relationship between each independent variable and the exposure to allogeneic blood transfusion. Score assignment for each predictor variable was based on its regression coefficient. The predicted probabilities at each total score were compared to the observed proportions of patients exposed to blood transfusion. The clinical tool consists of eight preoperative variables: preoperative hemoglobin, weight, female sex, age, nonelective procedure, preoperative creatinine, previous cardiac surgical procedure, and nonisolated procedure.

CONCLUSIONS

Based on the standards of measurement in clinical research, a valid clinical tool was developed for predicting the need for blood transfusion in patients undergoing cardiac surgery. The clinical tool was internally and externally validated, and the results suggest that it should perform well at other institutions.