Abstract
Background and objective:
Length of Stay (LOS) in the ICU may serve as a marker for the effectiveness of care. In intensive care medicine, prediction models and scoring systems are frequently used for prognosis, quality assessments, and comparing different intensive care units (ICUs) and resource allocation. To measure morbidity and distinguish patients in ICUs, a collection of models has been developed. The purpose of this research is to evaluate and compare the prognostic performance of the SAPS II, SOFA, APACHE II, and APACHE IV models for predicting length of stay in the Cardiovascular Surgery Intensive Care Unit (CSICU) on a large sample of Cardiovascular surgery patients.
Method
In a retrospective cohort study, data on 2587 consecutive CSICU patients were collected in the Imam Reza hospital between December 2013 and April 2022. These data gathered in an CSICU registry. We used these four models to predict ICU LOS via linear regression and the original and recalibrated, SOFA, APACHE IV, APACHE II, and SAPS II for all cardiovascular patients. We assessed the predictive performance of the models (R squared (R2), Adjusted R2, Intraclass Correlation Coefficient (ICC) for agreement, F-test, Akaike information criterion (AIC), Bayesian Information Criterion (BIC), Root Mean Squared Prediction Error (RMSPE)), discrimination using Area Under the Curve (AUC), and calibration by calibration graph.
Results
Of 3114, only 2587 patients were included. They were 56.8 (13) years old on mean (SD), 40.2% were female, the mean (SD) score for SOFA, SAPS II, APACHE IV, and APACHE II were 8,5 (2.1), 50.4 (14.3), 82.7 (20.2), and 22.8 (6), respectively. they had 11.1% overall mortality rate, and 29.7% were mechanically ventilated. Aggregate mean observed ICU stay was 3.6 (5) days and the means estimated by SOFA, SAPS II, APACHE IV, and APACHE II were 4, 4, 5.67, and 3.03 days, accordingly. For the APACHE II and APACHE IV, the R-squared was 0.005, while it was zero for the SOFA and SAPS II. The RMSE for SOFA, SAPS II, APACHE IV, and APACHE II were 5.181, 5.182, 5.878, and 5.170 respectively. APACHE II and ICU LOS had a very significant correlation (r = 0.89). Mortality, mechanical ventilation, gender, GCS, Serum creatinine, blood sugar, white blood cell, respiratory rate, age, and APACHE II were the variables that had an effect on length of stay (p < = 0.05).
Conclusion
These four models were studied to predict CSICU LOS in Iran as a developing country for the first time. The APACHE IV and APACHE II models better results than the other two models. Furthermore, APACHE IV's calibration for estimating length of stay, discriminations, and fit for data than others was just moderate. Although, APACHE II had better prediction the target value (accuracy) than the other three models. None of these four models completely satisfies our demands for CSICU LOS prediction models or our particular needs for models for resource allocation planning or benchmarking purposes. External validation, customizing the models, and using machine learning techniques could be helpful to predict CSICU LOS via these models.