Risk factors for and prediction of mortality in critically ill medical-surgical patients receiving heparin thromboprophylaxis

Guowei Li, Lehana Thabane, Deborah J Cook, Renato D Lopes, John C Marshall, Gordon Guyatt, Anne Holbrook, Noori Akhtar-Danesh, Robert A Fowler, Neill K J Adhikari, Rob Taylor, Yaseen M Arabi, Dean Chittock, Peter Dodek, Andreas P Freitag, Stephen D Walter, Diane Heels-Ansdell, Mitchell A H Levine, Guowei Li, Lehana Thabane, Deborah J Cook, Renato D Lopes, John C Marshall, Gordon Guyatt, Anne Holbrook, Noori Akhtar-Danesh, Robert A Fowler, Neill K J Adhikari, Rob Taylor, Yaseen M Arabi, Dean Chittock, Peter Dodek, Andreas P Freitag, Stephen D Walter, Diane Heels-Ansdell, Mitchell A H Levine

Abstract

Background: Previous studies have suggested that prediction models for mortality should be adjusted for additional risk factors beyond the Acute Physiology and Chronic Health Evaluation (APACHE) score. Our objective was to identify risk factors independent of APACHE II score and construct a prediction model to improve the predictive accuracy for hospital and intensive care unit (ICU) mortality.

Methods: We used data from a multicenter randomized controlled trial (PROTECT, Prophylaxis for Thromboembolism in Critical Care Trial) to build a new prediction model for hospital and ICU mortality. Our primary outcome was all-cause 60-day hospital mortality, and the secondary outcome was all-cause 60-day ICU mortality.

Results: We included 3746 critically ill non-trauma medical-surgical patients receiving heparin thromboprophylaxis (43.3 % females) in this study. The new model predicting 60-day hospital mortality incorporated APACHE II score (main effect: hazard ratio (HR) = 0.97 for per-point increase), body mass index (BMI) (main effect: HR = 0.92 for per-point increase), medical admission versus surgical (HR = 1.67), use of inotropes or vasopressors (HR = 1.34), acetylsalicylic acid or clopidogrel (HR = 1.27) and the interaction term between APACHE II score and BMI (HR = 1.002 for per-point increase). This model had a good fit to the data and was well calibrated and internally validated. However, the discriminative ability of the prediction model was unsatisfactory (C index < 0.65). Sensitivity analyses supported the robustness of these findings. Similar results were observed in the new prediction model for 60-day ICU mortality which included APACHE II score, BMI, medical admission and invasive mechanical ventilation.

Conclusion: Compared with the APACHE II score alone, the new prediction model increases data collection, is more complex but does not substantially improve discriminative ability.

Trial registration: ClinicalTrials.gov Identifier: NCT00182143.

Keywords: APACHE; Critical care; Intensive care unit; Mortality; Prediction model.

Figures

Fig. 1
Fig. 1
Kaplan–Meier survival curves for 60-day hospital mortality in derivation and validation sets
Fig. 2
Fig. 2
Observed versus expected in derivation set for 60-day hospital mortality: a results from Model 1; b results from Model 3 (solid diagonal line represents ideal calibration)
Fig. 3
Fig. 3
Observed versus expected in validation set for 60-day hospital mortality: a results from Model 1; b results from Model 3 (solid diagonal line represents ideal calibration)
Fig. 4
Fig. 4
Observed versus expected in the whole dataset for 60-day ICU mortality: a results from Model 1; b results from Model 3 (solid diagonal line represents ideal calibration)

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