A Clinical Tool for Prediction of Bleeding Complications After Percutaneous Renal Biopsy

Background: Kidney biopsy is a diagnostic procedure which may result in bleedingrelated complications. Developing a tool for risk stratification could help predict such risk and would benefit shared decision-making. The aim of the present study was to derive and verify such a tool from training and validation cohorts. Methods: This is a single-center study of 1450 ultrasound-guided native kidney biopsies performed for diagnosis of kidney disease between 2007 and 2020 at a tertiary academic hospital in Quebec, Canada. Major bleeds were defined by hematoma/hematuria with 1 g/dL drop in hemoglobin (Hb) and requiring transfusion, bleeding requiring hospitalization or transfer to ICU, hemorrhagic shock, angioembolization, nephrectomy, or death. Two thirds of the cohort was randomly selected and used as the training set (n=987) for the identification of the determinants of major bleeds, using univariate and multivariate logistic regression analysis, and the rest was used as validation cohort. Results: In the training cohort (59% male) the mean age, weight, Hb and platelet counts were 55±17 years, 79±20 kg, 11.4± 2.5 g/dL, and 243± 100 × 109/L, respectively, while the median eGFR was of 33 mL/min/1.73m2 (IQR: 12-62). In this group, major bleeding occurred in 57 patients (5.8%). Major bleeding was higher with younger age, lower pre-biopsy Hb, the use of anticoagulant within the week prior to the biopsy (defined as the use of direct-acting oral anticoagulants, warfarin, i.v. heparin, therapeutic doses of low molecular weight heparin), and higher INR at the time of kidney biopsy. The probability of risk was defined by the following equation: Probability of bleeding= e(-2.426054-0.017820*Age + 0.910106*Anti_Coag -0.026364*Hb + 3.142164*INR)/(1 + e(-2.426054-0.017820*Age + 0.910106*Anti_Coag -0.026364*Hb + 3.142164*INR)) The AUC of the equation was 0.741 (Min-Max: 0.740 - 0.742) in the training cohort. In our validation cohort, with similar characteristics, major bleedings occurred in 18 patients (3.9%). The AUC of the equation predicted well the risk in the validation cohort (AUC of 0.733 (Min-Max: 0.711 - 0.747)). Conclusions: This study proposes an equation for the estimation of the probability of major bleeding after percutaneous renal biopsy.

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