Prediction Models for Prolonged Intensive Care Unit Stay After Cardiac Surgery

Abstract

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 curveϭ0.75 [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. (Circulation. 2010;122:682-689.)Key Words: cardiovascular diseases Ⅲ complications Ⅲ epidemiology Ⅲ risk factors Ⅲ surgery I n the past decades, mortality during or shortly after cardiac surgery has decreased. 1 However, morbidity has increased, 2 mainly because cardiac surgery is increasingly utilized in older and more vulnerable patients. This often results in more complications after surgery and potential reduction in quality of life. [3][4][5] One method of assessing complications occurring directly after cardiac surgery is a prolonged stay in the intensive care unit (ICU). 6 -9 Prolonged ICU stay also leads to incremental use of resources. In practice, prediction models are being used for efficient use of ICU resources. Patients with a low risk of complications are being scheduled for surgery before patients with a high risk. [5][6][7][8][9][10][11][12][13] Various prediction models have been developed to preoperatively identify patients with an increased risk for postoperative complications and prolonged ICU stay. [12][13][14][15][16][17][18][19][20][21][22][23][24][25][26][27][28] Interestingly, all of these prediction models were derived from samples including different patients, as reflected by the different distributions of patient and outcome characteristics. Hence, which model should be preferred in which situation is still unclear. Recently, in a qualitative review, Messaoudi and colleagues 14 reviewed 13 of these prediction models by comparing their published prognostic values for predicting ICU stay. They found that the 13 different prediction models indeed used...

Does EuroSCORE Predict intensity of Postoperative Care and Rehabilitation Parameters? A Prospective Evaluation

“…With respect to the outcome measures ICU LOS and hospital LOS, our study confirms previous findings [5,26]: Ettema and associates validated several prediction models for prolonged ICU stay after cardiac surgery and found that both Parsonnet score and EuroSCORE had superior discrimination compared to other predictive scores [27]. Interestingly, both models widely implemented in clinical practice, were originally derived and validated only for the prediction of mortality after cardiac surgery.…”

Postoperative Delirium in a Substudy of Cardiothoracic Surgical Patients in the BAG-RECALL Clinical Trial

“…24,25 While some features of the EuroSCORE had to be estimated in our population, composite metrics reduce the risk of a type 1 error compared with including individual characteristics. EuroSCORE is a significant predictor of other adverse outcomes in cardiac surgical patients, including prolonged ICU length of stay 26 and mortality, both in a large multicenter population 27 and in a population from our institution. 28 While the association between ASA PS and postoperative delirium has been better studied in noncardiac surgical populations, 29,30 it is not surprising that ASA PS is related to postoperative delirium in this cardiothoracic surgical population as well.…”

Predictive Model for Length of Stay in Intensive Care Unit Based on Preoperative and Perioperative Variables. Four-Year Analysis of Mitral Valve Surgery in One Single Center

“…Ettema et al [5] performed an external validation of 14 risk scores capable to identify patients who are likely to have a prolonged ICU stay. The Parsonnet model and the EuroSCORE showed the best performance in terms of discrimination, accuracy, and calibration.…”

“…Those scores have been successfully validated also for prediction of prolonged LOSI. Parsonnet model and EuroSCORE were superior in identifying patients with prolonged LOSI [5].…”

“…Those scores have been successfully validated also for prediction of prolonged LOSI. Parsonnet model and EuroSCORE were superior in identifying patients with prolonged LOSI [5].Predicting LOSI after mitral valve surgery is challenging due to the wide spectrum of comorbidities these patients sustain, and to the cardiovascular procedures and potential complications related to the surgical procedures. In addition, patients with a …”