Development and External Validation of a Model for Predicting Sufficient Filter Lifespan in Anticoagulation-Free Continuous Renal Replacement Therapy Patients

Abstract

Background: Anticoagulation-free continuous renal replacement therapy (CRRT) was recommended by the current clinical guideline for patients with increased bleeding risk and contraindications of citrate. Nevertheless, anticoagulation-free CRRT yielded heterogeneous filter lifespan. Furthermore, the specific cutoff values for traditional coagulation parameters to predict sufficient filter lifespan of anticoagulation-free CRRT have not yet been determined. The purpose of our present study was to develop and validate a model for predicting sufficient filter lifespan in anticoagulation-free CRRT patients.

Methods: Patients who underwent anticoagulation-free CRRT in our center between June 2013 and June 2019 were retrospectively included. The primary outcome was sufficient filter lifespan (≥24 h). Thirty-seven predictors were included for modeling based on their clinical significance and previous reports. The final model was developed by using multivariable logistic regression analysis and was validated in a separate external cohort.

Results: The development cohort included 170 patients. Sufficient filter lifespan was observed in 80 patients. Thirteen variables were independent predictors for sufficient filter lifespan by logistic regression: body temperature, mean arterial pressure, activated partial thromboplastin time, direct bilirubin, alkaline phosphatase, blood urea nitrogen, vasopressor use, body mass index, white blood cell, platelet count, D-dimer, uric acid, and pH. The area under the curve (AUC) of the stepwise model and internal validation model was 0.82 (95% confidence interval [CI] [0.76-0.88]) and 0.8 (95% CI [0.74-0.87]), respectively. The positive predictive value and the negative predictive value of the stepwise model were 0.77 and 0.79, respectively. The validation cohort included 44 eligible patients and the AUC of the external validation model was 0.82 (95% CI [0.69-0.96]).

Conclusions: The use of a prediction model instead of an assessment based only on coagulation parameters could facilitate the identification of the patients with filter lifespan of ≥24 h when they accepted anticoagulation-free CRRT.

Keywords: Anticoagulation; Bleeding; Continuous renal replacement therapy; Filter failure; Prediction model.

Fig. 1

The participant flow diagram of the development cohort. CRRT, continuous renal replacement therapy; CVVH, continuous venovenous hemofiltration; RCA, regional citrate anticoagulation.

Fig. 2

Kaplan-Meier curve for filter survival in the development cohort illustrating survival rate and numbers of survival filters at 12 h, 24 h, 36 h, and 48 h. Overall filters (a). Filters stratified by the optimal cutoff value of the stepwise model (b).

Fig. 3

The predictive performance of the stepwise model and the internal validation model. ROC curve of the stepwise model (a); calibration curve of the stepwise model (b); ROC curve of the BS-stepwise model (c); calibration curve of the BS-stepwise model (d). AUC, area under the curve; BS, bootstrapping; ROC, receiver operating characteristic.

Fig. 4

The ROC curve of the external validation model and Kaplan-Meier curve for filter survival in the validation cohort. ROC curve and AUC of the external validation model (a); Kaplan-Meier curve for filter survival in the external validation cohort (b), which illustrated the filters survival rate and numbers of survival filters at 12 h, 24 h, 36 h, and 48 h in patients stratified by the optimal cutoff value of the development model. AUC, area under the curve; ROC, receiver operating characteristic; CI, confidence interval.