Prediction of bleeding complications using platelet aggregation testing and thromboelastography in patients undergoing kidney biopsy: a prospective cohort study

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However, bleeding remains a major complication. This study aimed to evaluate predictive factors, including platelet aggregation testing and thromboelastography, and to develop a prediction model to estimate the probability of bleeding complications in patients undergoing kidney biopsy. Methods In this prospective cohort study, adult patients (aged ≥ 18 years) with renal failure were enrolled. Platelet aggregation testing and thromboelastography were performed within 24 h prior to kidney biopsy. A prediction model was developed using backward stepwise regression. Model performance was assessed using discrimination and calibration, and internal validation was performed using bootstrap resampling. Results A total of 119 patients were included. Bleeding complications occurred in 66 patients. Neutrophil-to-lymphocyte ratio ≥ 15, fibrinogen ≥ 500 mg/dL, time to maximum aggregation of epinephrine ≥ 450 s, and time to maximum aggregation of ristocetin ≥ 420 s were associated with a reduced risk of bleeding complications. In contrast, maximum lysis at 60 min (ML60) in extrinsic pathway thromboelastometry (EXTEM) ≥ 5% was associated with an increased risk of bleeding. The BENREEF model demonstrated good performance, with strong discrimination and calibration, including in internal validation. Conclusions Both protective and risk factors for bleeding complications following kidney biopsy were identified. The BENREEF model showed good predictive performance for estimating bleeding risk. However, external validation is required before clinical application. Health sciences/Biomarkers Health sciences/Diseases Health sciences/Medical research Health sciences/Nephrology Health sciences/Risk factors prediction model thromboelastography platelet aggregation kidney biopsy bleeding complications Figures Figure 1 Figure 2 Figure 3 Background Renal disease is a common clinical condition. Early diagnosis and treatment can reduce disease progression to end-stage kidney disease and improve survival ( 1 ). Kidney biopsy is a medical procedure in which small samples of renal tissue are obtained for the diagnosis of kidney diseases, evaluation of renal function, and monitoring of treatment response. This procedure aids clinicians in making appropriate therapeutic decisions. However, bleeding remains a major complication of kidney biopsy. About 1.4–10.3% of patients undergoing kidney biopsy experience bleeding complications ( 2 – 4 ). The severity of bleeding varies, ranging from gross hematuria to hypovolemic shock. Patients who develop bleeding complications have an increased risk of mortality ( 5 ). Several factors have been associated with an increased risk of bleeding following kidney biopsy. Patients with renal failure, particularly those with serum creatinine ≥ 2.0 mg/dL, are at higher risk ( 6 , 7 ). The mechanisms underlying abnormal bleeding in these patients include platelet dysfunction, nitric oxide accumulation, anemia, dialysis-induced vascular changes, and impaired platelet-vessel wall interactions ( 8 , 9 ). Uncontrolled hypertension is another important risk factor. A systolic blood pressure ≥ 160 mmHg or diastolic blood pressure ≥ 100 mmHg is associated with an increased risk of bleeding in patients undergoing kidney biopsy ( 10 ). Therefore, blood pressure should be adequately controlled prior to the procedure to minimize bleeding complications. In addition, thrombocytopenia and coagulopathy are well-recognized risk factors for bleeding during invasive procedures, including kidney biopsy. Thus, the procedure should be performed with caution in patients at high risk of bleeding. The platelet aggregation test is considered the gold standard for diagnosing platelet dysfunction, including conditions such as Glanzmann thrombasthenia, Bernard–Soulier syndrome, and drug-induced platelet dysfunction. It has also been used to predict bleeding risk in thrombocytopenic patients with acute myeloid leukemia and the risk of recurrent stroke or major bleeding in patients with stroke ( 11 , 12 ). Thromboelastography (TEG) is a laboratory technique used to assess hemostasis by measuring the viscoelastic properties of whole blood during clot formation and dissolution. It has been shown to predict perioperative bleeding risk and reduce blood transfusion requirements in trauma and surgical settings ( 13 ). A limited number of studies have evaluated the utility of the platelet aggregation test or TEG in predicting bleeding risk following kidney biopsy. However, their findings remain inconclusive. Therefore, this study aimed to evaluate predictive factors, including platelet aggregation testing and TEG, for bleeding complications following kidney biopsy and to develop a prediction model to estimate the probability of bleeding in patients undergoing kidney biopsy. Such a model may improve clinical decision-making, reduce bleeding risk, and ultimately improve patient outcomes. Materials and Methods Study population This prospective cohort study was conducted at Songklanagarind Hospital, the largest tertiary care center in Southern Thailand, between June 2020 and July 2024. Patients (age ≥ 18 years) with renal failure, defined as creatinine clearance < 60 mL/min calculated using the Cockcroft–Gault formula, were enrolled prior to undergoing kidney biopsy. Exclusion criteria included: kidney transplant recipients; current use of anticoagulants or antiplatelet agents; prolonged activated partial thromboplastin time (aPTT), prothrombin time/international normalized ratio (PT/INR) > 1.5; platelet count < 100,000 cells/µL; hemodynamic instability; requirement for invasive mechanical ventilation; use of herbal products or medications known to interfere with hemostasis; and uncontrolled hypertension (systolic pressure ≥ 140 mmHg or diastolic pressure ≥ 100 mmHg) prior to kidney biopsy. This study was approved by the institutional review board of our institution and conducted in accordance with the Declaration of Helsinki (approval number: REC. 63-131-14-1). Written informed consent was obtained from all participants prior to enrollment. Kidney biopsy procedure All kidney biopsies were performed based on clinical indications and at the discretion of the treating nephrologist. Percutaneous kidney biopsies were performed under real-time ultrasound guidance in the prone position by experienced radiologists or radiology trainees under direct supervision. An automated spring-loaded biopsy device with a 16-gauge needle was used. A minimum of three core samples were obtained, as determined by the radiologist based on specimen adequacy. Post-biopsy ultrasonography was performed immediately to assess for bleeding complications. Following the procedure, patients remained in the supine position for at least 6 h and were monitored for signs and symptoms of bleeding complications for a minimum of 24 h during hospitalization. Platelet aggregation test and thromboelastography Platelet aggregation was assessed using a Helena AggRAM aggregometer (Helena Biosciences, UK) based on the light transmission method. Citrated venous blood samples were stored at room temperature and analyzed within 4 h of collection. Platelet-rich plasma (PRP) was prepared by centrifugation at 200 × g for 10 min, and platelet-poor plasma (PPP) was obtained by further centrifugation at 2,000 × g for 10 min. The platelet count in PRP was adjusted to 200,000–300,000 cells/µL using autologous PPP. Aggregation was induced by adding 25 µL of platelet agonists to 225 µL of PRP. The agonists included adenosine diphosphate (ADP), collagen (5 µg/mL), epinephrine (10 µM), and ristocetin (1.0 mg/mL). The final concentrations of each agonist were applied according to standard protocols. Parameters recorded included primary slope, secondary slope, maximum aggregation, and time to maximum aggregation. Measurements were continuously recorded for 10 min after agonist addition. Internal quality control was performed daily, and instrument calibration and performance verification were conducted according to the manufacturer’s instructions. TEG was performed using a rotational thromboelastometry (ROTEM) delta analyzer (Werfen/Instrumentation Laboratory, Germany). Citrated whole-blood samples were stored at room temperature and analyzed within 60 min of collection. For each assay, 300 µL of blood was mixed with assay-specific reagents and calcium chloride (CaCl 2 ). The EXTEM (extrinsic pathway thromboelastometry), INTEM (intrinsic pathway thromboelastometry), APTEM (aprotinin-modified thromboelastometry), and FIBTEM (fibrin-based thromboelastometry) assays were performed. Parameters recorded included clotting time (CT), clot formation time, α angle, amplitude 10 min after CT, amplitude 20 min after CT, maximum clot firmness, and maximum lysis at 60 min (ML60). All measurements were continuously monitored for at least 60 min. Daily internal quality control and instrument calibration were performed according to the manufacturer’s instructions. Predictors and outcome Predictors were selected based on literature review and investigator expertise. Cardiovascular diseases included hypertension, diabetes mellitus, dyslipidemia, and myocardial infarction. Baseline patient characteristics and laboratory data were collected within 1 week prior to kidney biopsy. Platelet aggregation testing, TEG, and fibrinogen levels were performed within 24 h before the procedure. Bleeding events were monitored from the time of kidney biopsy until hospital discharge. Major bleeding was defined as bleeding requiring therapeutic intervention, requiring blood transfusion, associated with a decrease in hemoglobin ≥ 1 g/dL, or resulting in death. Minor bleeding included gross hematuria, perinephric hematoma, or bleeding that did not require therapeutic intervention or blood transfusion ( 14 ). Statistical analysis All statistical analyses were performed using R software (version 4.3.2). Categorical variables were presented as frequencies and percentages, and continuous variables as medians with interquartile ranges (IQR). Comparisons between patients with and without bleeding complications were performed using chi-square test, Student’s t -test, or Fisher’s exact test, as appropriate. Maximally selected rank statistics were used to determine optimal cutoff values for continuous variables. Univariate and multivariate logistic regression analyses were conducted to identify predictors of bleeding complications following kidney biopsy. Variables with P < 0.05 in univariate analysis were included in the multivariable model. A prediction model was developed using backward stepwise regression, and the model with the lowest Akaike Information Criterion (AIC) was selected. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC) for discrimination and calibration plots for calibration. Internal validation was performed using bootstrap resampling (1,000 iterations). Model performance was assessed using AUC and calibration plots in the bootstrap samples. This study adhered to the Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) guidelines ( 15 ). Results A total of 121 patients were enrolled in this study. Two patients were excluded due to immediate contraindications on the day of kidney biopsy. Consequently, 119 patients were included in the final analysis. The median age was 45.3 years, with a female predominance (54.6%). The median time from symptom onset to kidney biopsy was 90.0 days. Approximately 58.0% of patients had cardiovascular disease. The median hematocrit (Hct) and platelet count were 32.7% and 261,000 cells/µL, respectively. The median neutrophil-to-lymphocyte ratio (NLR) was 3.83, and the median serum creatinine level was 2.06 mg/dL. Most baseline characteristics were similar between patients with and without bleeding complications (Table 1 ). However, fibrinogen levels were significantly higher in patients without bleeding complications than in those with bleeding complications. Table 1 Baseline characteristics in 119 patients who underwent kidney biopsy according to bleeding complications Characteristics Patients with bleeding complications (N = 66) Number (%) Patients without bleeding complications (N = 53) Number (%) P value Age (years), median (IQR) 45.3 (31.1,54.9) 45.3 (34.5,59.8) 0.395 Gender (female) 39 (59.1) 26 (49.1) 0.275 Weight (kg), median (IQR) 63.3 (56.8,70.2) 67.7 (57.2,78.2) 0.137 Height (cm), median (IQR) 160.0 (152.0,165.0) 160.0 (155.0,169.0) 0.436 Time from symptoms to kidney biopsy (days), median (IQR) 90.0 (47.5,240.0) 90.0 (41.0,218.0) 0.927 Underlying disease 53 (80.3) 44 (83.0) 0.704 Cardiovascular disease 37 (56.1) 32 (60.4) 0.635 Hematologic disease 7 (10.6) 5 (9.4) 0.833 Liver disease 2 (3.0) 2 (3.8) 1.000 Systolic blood pressure, median (IQR) 132.0 (124.2,138.0) 130.0 (120.0,136.0) 0.349 Hemoglobin (g/dL), median (IQR) 10.5 (9.4,12.2) 11.1 (9.7,11.8) 0.562 Hematocrit (%), median (IQR) 32.7 (28.3,37.8) 33.0 (29.3,35.9) 0.571 Platelet (cells/µL), median (IQR) 261000 (204800,318800) 263000 (201000,329000) 0.783 White blood cell (cells/µL), median (IQR) 8815 (6510,10910) 8250 (6360,10730) 0.409 Neutrophil to lymphocyte ratio, median (IQR) 3.3 (2.2,7.1) 4.2 (2.6,12.8) 0.190 aPTT (s), median (IQR) 25.1 (21.5,29.1) 25.1 (23.7,27.1) 0.785 PT(s), median (IQR) 1.00 (0.93,1.05) 1.01 (0.93,1.10) 0.421 Fibrin (mg/dL), median (IQR) 480.7 (336.1,627.7) 600.2 (452.8,833.5) 0.017 Blood urea nitrogen (mg/dL), median (IQR) 30.3 (21.0,49.5) 32.2 (22.1,49.1) 0.989 Creatinine (mg/dL), median (IQR) 2.3 (1.1,4.2) 2.0 (1.3,2.8) 0.474 aPTT, activated partial thromboplastin time; cm, centimeters; dL, deciliters; IQR, interquartile range; kg, kilograms; mg, milligrams; PT, prothrombin time. Platelet aggregation test and thromboelastography In the platelet aggregation test, the median maximum aggregation percentages were 88.0%, 91.2%, 88.5%, and 89.3% for ADP, collagen, epinephrine, and ristocetin, respectively. These values did not differ significantly between patients with and without bleeding complications. The primary and secondary slopes for all agonists were also similar between the two groups. However, the median time to maximum aggregation of epinephrine and ristocetin was shorter in patients with bleeding complications (Table 2 ). Regarding TEG, the median ML60 in EXTEM was higher in patients with bleeding complications. Other TEG parameters, including INTEM, APTEM, and FIBTEM, were comparable between patients with and without bleeding complications (Table 3 ). Table 2 Platelet aggregation test of 119 patients before kidney biopsy Platelet aggregation test Patients with bleeding complication (N = 66) Median (IQR) Patients without bleeding complication (N = 53) Median (IQR) P value Adenosine diphosphate Primary slope (%/min) 123.6 (106.8,143.2) 126.3 (104.4,136.7) 0.925 Secondary slope (%/min) 24.4 (21.3,27.5) 24.3 (21.6,27.2) 0.783 Maximum aggregation (%) 87.5 (80.9,92.0) 88.9 (83.2,92.0) 0.499 Time to maximum aggregation (s) 366.5 (320.5,411.8) 364.0 (322.0,478.0) 0.301 Collagen Primary slope (%/min) 23.7 (2.1,29.1) 24.1 (2.1,31.0) 0.874 Secondary slope (%/min) 133.0 (119.6,152.6) 141.9 (114.9,154.4) 0.998 Maximum aggregation (%) 90.8 (87.2,93.4) 91.7 (88.6,93.5) 0.243 Time to maximum aggregation (s) 429.0 (362.0,490.8) 429.0 (362.0,548.0) 0.539 Epinephrine Primary slope (%/min) 72.4 (38.1,111.1) 61.0 (46.7,78.4) 0.334 Secondary slope (%/min) 26.2 (21.2,29.8) 25.5 (23.0,36.5) 0.225 Maximum aggregation (%) 86.8 (80.1,91.1) 90.0 (84.0,92.7) 0.065 Time to maximum aggregation (s) 489.5 (438.5,579.8) 550.0 (486.0,582.0) 0.039 Ristocetin Primary slope (%/min) 86.5 (61.3,104.1) 84.7 (65.5,105.4) 0.961 Maximum aggregation (%) 88.2 (84.8,91.8) 89.7 (84.8,93.4) 0.324 Time to maximum aggregation (s) 316.5 (251.8,370.0) 336.0 (260.0,432.0) 0.023 IQR, interquartile range. Table 3 Thromboelastography of 119 patients before kidney biopsy Thromboelastography Patients with bleeding complication (N = 66) Median (IQR) Patients without bleeding complication (N = 53) Median (IQR) P value EXTEM Coagulation time (s) 49.0 (44.0,52.0) 48.0 (38.0,54.3) 0.452 Clot formation time (s) 60.5 (44.3,77.8) 54.0 (42.3,77.5) 0.575 α angle (degree) 80.0 (75.3,82.8) 80.0 (76.0,82.0) 0.824 Amplitude 10 min after CT (mm) 61.0 (55.3,67.0) 65.0 (55.8,69.3) 0.444 Amplitude 20 min after CT (mm) 66.5 (59.3,70.8) 69.0 (61.0,73.3) 0.209 Maximum clot firmness (mm) 68.0 (61.3,72.0) 69.5 (62.8,75.0) 0.252 Maximum lysis within 60 min (%) 9.0 (5.0,12.0) 6.0 (3.0,11.0) 0.049 INTEM Coagulation time (s) 175.5 (146.2,206.0) 173.5 (136.8,221.8) 0.797 Clot formation time (s) 64.0 (51.3,82.0) 63.0 (49.0,84.0) 0.717 α angle (degree) 78.0 (75.0,79.8) 78.0 (74.8,81.0) 0.590 Amplitude 10 min after CT (mm) 58.0 (53.3,64.8) 62.0 (55.0,66.3) 0.391 Amplitude 20 min after CT (mm) 64.0 (60.0,70.0) 67.0 (60.8,71.3) 0.366 Maximum clot firmness (mm) 64.5 (61.0,71.0) 67.0 (60.8,72.0) 0.554 Maximum lysis within 60 min (%) 4.0 (3.0,7.8) 4.0 (3.0,7.0) 0.861 APTEM Maximum clot firmness (mm) 8.0 (4.0,49.0) 5.5 (4.0,64.0) 0.898 FIBTEM Amplitude 10 min after CT (mm) 21.0 (16.0,26.8) 24.0 (18.8,31.3) 0.080 Amplitude 20 min after CT (mm) 22.5 (17.0,28.8) 25.0 (19.0,32.3) 0.167 Maximum clot firmness (mm) 23.0 (17.0,31.8) 26.0 (20.0,33.3) 0.142 CT, coagulation time; mm, millimeters; s, seconds. Bleeding complications Among the 119 patients who underwent kidney biopsy, 66 (55.5%) experienced bleeding complications. Major bleeding occurred in approximately 10.1% of patients. Specifically, four patients required therapeutic intervention, two patients experienced a significant decline in Hct, and four patients required blood transfusion. Minor bleeding occurred in 54 patients (45.4%), including 52 cases of perinephric hematoma and 2 cases of gross hematuria. No deaths occurred during the study period. Factors associated with bleeding complications In the univariate analysis, body weight, NLR, fibrinogen, serum creatinine, time to maximum aggregation for ADP, collagen, epinephrine, and ristocetin, primary and secondary slopes of epinephrine, coagulation time, and ML60 in EXTEM were associated with bleeding complications. In the multivariate analysis, NLR ≥ 15, fibrinogen ≥ 500 mg/dL, time to maximum aggregation of epinephrine ≥ 450 s, and time to maximum aggregation of ristocetin ≥ 420 s were identified as protective factors against bleeding complications. In contrast, ML60 in EXTEM ≥ 5% was independently associated with an increased risk of bleeding complications in patients undergoing kidney biopsy (Supplementary Table S1 ). Prediction model generation for bleeding complications A prediction model (BENREEF model) was developed using backward stepwise regression to estimate the risk of bleeding complications in patients undergoing kidney biopsy (Supplementary Table S2). The model included B ody weight, time to maximum aggregation of E pinephrine, N eutrophil-to-lymphocyte ratio, time to maximum aggregation of R istocetin, coagulation time in E XTEM, ML60 in E XTEM, and F ibrinogen level. A nomogram of the prediction model is presented in Fig. 1 . The model demonstrated good discriminative ability, with an AUC of 0.88 (95% CI: 0.81–0.95) (Fig. 2 ). The calibration plot indicated good agreement between predicted and observed outcomes (Fig. 3 ). Internal validation of prediction model Internal validation was performed using bootstrap resampling with 1,000 iterations. The validated model showed an AUC of 0.88 (95% CI: 0.80–0.94). The calibration plot also demonstrated good calibration (Supplementary Fig. S1 ). Discussion In this study, approximately 10.1% of patients who underwent kidney biopsy experienced major bleeding. NLR ≥ 15, fibrinogen ≥ 500 mg/dL, time to maximum aggregation of epinephrine ≥ 450 s, and time to maximum aggregation of ristocetin ≥ 420 s were associated with a decreased risk of bleeding complications. In contrast, ML60 in EXTEM ≥ 5% was associated with an increased risk of bleeding complications in patients undergoing kidney biopsy. The BENREEF model demonstrated good performance in predicting the probability of bleeding in these patients. The incidence of major bleeding complications for kidney biopsy in this study was higher than that reported in previous studies (10.1% vs. 0.9–7.2%) ( 4 , 16 , 17 ). All kidney biopsies were performed by experienced radiologists or supervised trainees according to standard protocols. The higher incidence observed in this study may reflect a population with a greater baseline bleeding risk. Additionally, variations in the definition of major bleeding across studies may contribute to differences in reported incidence. Minor bleeding occurred in 45.4% of patients, predominantly as asymptomatic perinephric hematoma, which is higher than the 8.9–17.2% reported previously ( 14 , 16 ). This increased incidence may be explained by routine post-kidney biopsy ultrasonography, enabling detection of otherwise asymptomatic hematomas. This study identified seven predictors associated with bleeding risk following kidney biopsy. NLR reflects the balance between innate and adaptive immune responses ( 18 ). Interestingly, a high NLR was associated with a reduced risk of bleeding complications. Elevated NLR indicates increased systemic inflammation, which promotes a procoagulant state through cytokine-mediated upregulation of tissue factor, resulting in increased thrombin generation and fibrin formation. It may also enhance platelet activation, suppress natural anticoagulant pathways, and inhibit fibrinolysis ( 19 , 20 ). These mechanisms may reduce bleeding risk but may also increase the risk of thrombosis. Previous studies have not evaluated the association between elevated NLR and bleeding risk in kidney biopsy. However, elevated NLR has been associated with increased bleeding complications in other clinical settings, including gastrointestinal bleeding in acute ischemic stroke, Henoch–Schönlen purpura, major bleeding in atrial fibrillation, and rebleeding in aneurysmal subarachnoid hemorrhage ( 21 – 24 ). The underlying mechanisms of hemostasis in patients with elevated NLR undergoing kidney biopsy remain unclear and warrant further investigation. Body weight was not significantly associated with bleeding risk in this study, consistent with previous reports ( 25 , 26 ), but it remained an important component of the prediction model. This highlights that predictors in multivariable models do not necessarily represent independent risk factors. Fibrinogen plays a central role in the coagulation cascade and is essential for maintaining hemostasis ( 27 ). Patients with afibrinogenemia, hypofibrinogenemia, or dysfibrinogenemia are at increased risk of spontaneous and perioperative bleeding ( 28 , 29 ). Low fibrinogen levels have also been associated with bleeding during medical interventions ( 30 ). In this study, higher fibrinogen levels (≥ 500 mg/dL) were associated with a reduced risk of bleeding following kidney biopsy. However, prophylactic elevation of fibrinogen to this threshold is not recommended, as excessively high levels may increase thrombotic risk. Instead, patients with fibrinogen levels < 500 mg/dL should be closely monitored. Patients with renal failure are at risk of uremia-related platelet dysfunction, which contributes to bleeding. Platelet function analyzers are commonly used to assess platelet-related bleeding risk in kidney biopsy. Prolonged closure time has been associated with increased bleeding risk in some studies ( 31 , 32 ), although others have reported no significant association ( 33 , 34 ). In this study, light transmission aggregometry, the gold standard for assessing platelet function ( 35 ), was used. Maximum platelet aggregation was not associated with bleeding risk. Shorter time to maximum aggregation of epinephrine and ristocetin was associated with an increased risk of bleeding complications. This may reflect dysregulated platelet activation kinetics and impaired clot stability, leading to unstable thrombus formation and premature disaggregation. However, clinical evidence supporting this association remains limited and requires further validation. TEG assesses the viscoelastic properties of clot formation in real time and is widely used to evaluate bleeding risk and guide transfusion strategies ( 36 ). EXTEM reflects the extrinsic coagulation pathway and may be particularly useful in this context. Evidence for the use of TEG in predicting bleeding during kidney biopsy remains limited and inconsistent. Davis et al. reported an association between abnormal TEG findings and bleeding in transplant kidney biopsies, whereas Gal-Oz et al. found no such association in native kidney biopsies ( 37 , 38 ). In the present study, prolonged coagulation time (CT) and increased ML60 in EXTEM were associated with an increased risk of bleeding complications. These findings suggest delayed clot formation and enhanced fibrinolysis, respectively, both of which contribute to clot instability and increased bleeding risk. We developed a BENREEF model to predict bleeding risk in patients undergoing kidney biopsy. This model incorporates seven predictors, including parameters from platelet aggregation testing and TEG, and represents the first model to integrate these two hemostatic assessments in this clinical setting. The model demonstrated strong predictive performance across a wide range of bleeding probabilities ranging from 5% to 99%. However, no specific cutoff was established to guide clinical decision-making. We suggest that patients with a bleeding probability ≥ 20% should undergo careful evaluation before proceeding with kidney biopsy. Modifiable risk factors should be optimized prior to the procedure, and patients should be closely monitored during the perioperative and postoperative periods. Early detection and management of bleeding may reduce complications. The model was internally validated using bootstrap resampling and demonstrated good discrimination and calibration. However, external validation is necessary to confirm its generalizability. This study has several limitations. First, it was conducted at a single center, which may limit generalizability and introduce the risk of model overfitting. Although internal validation demonstrated good performance, external validation is required. Second, the incidence of bleeding complications was higher than that reported in previous studies, which may reflect higher baseline risk or increased detection due to routine ultrasonography. Third, the study population consisted exclusively of Asian patients, and the applicability of the model to other populations requires further investigation. Conclusions Neutrophil-to-lymphocyte ratio ≥ 15, fibrinogen ≥ 500 mg/dL, time to maximum aggregation of epinephrine ≥ 450 s, and time to maximum aggregation of ristocetin ≥ 420 s were associated with a reduced risk of bleeding complications following kidney biopsy, whereas ML60 in EXTEM ≥ 5% was associated with an increased risk. The BENREEF model demonstrated good predictive performance for estimating bleeding risk in this population. However, external validation is required before routine clinical implementation. Abbreviations ADP Adenosine diphosphate AIC Akaike Information Criterion aPTT Activated partial thromboplastin time AUC Area under the curve BENREEF (Model name; expand if defined by authors) CI Confidence interval CT Coagulation time EXTEM Extrinsic pathway thromboelastometry FIBTEM Fibrin-based thromboelastometry Hct Hematocrit INTEM Intrinsic pathway thromboelastometry IQR Interquartile range ML60 Maximum lysis at 60 minutes NLR Neutrophil-to-lymphocyte ratio PRP Platelet-rich plasma PPP Platelet-poor plasma PT Prothrombin time PT/INR Prothrombin time/International normalized ratio ROC Receiver operating characteristic TEG Thromboelastography Declarations Ethics approval and consent to participate This study was approved by the institutional review board of Songklanagarind Hospital and conducted in accordance with the Declaration of Helsinki (approval number: REC. 63-131-14-1). Written informed consent was obtained from all participants prior to enrollment. Consent for publication Not applicable. Competing interests The authors declare no conflict of interest. Funding This study was supported by the Faculty of Medicine, Prince of Songkla University (grant number REC. 63-131-14-1). Author Contribution N.W. and P.S. designed the study. All authors collected the data. PS analyzed the data, interpreted the results, and drafted the manuscript. All authors critically revised the manuscript for intellectual content, approved the final version for publication, and agreed to be accountable for all aspects of the study. Acknowledgement We would like to thank the Division of Information Technology at Songklanagarind Hospital and Prince of Songkla University for their support. Data Availability The datasets are available from the corresponding author upon request. References Haarhaus, M. et al. 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B., Altman, D. G. & Moons, K. G. M. Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): The TRIPOD statement. Br. J. Cancer . 112 (2), 251–259. 10.1038/bjc.2014.639 (2015). Kajawo, S. et al. A systematic review of complications associated with percutaneous native kidney biopsies in adults in low- and middle-income countries. Kidney Int. Rep. 6 (1), 78–90. 10.1016/j.ekir.2020.10.019 (2020). Azmat, R., Siddiqui, A. B., Khan, M. T. R., Sunder, S. & Kashif, W. Bleeding complications post ultrasound guided renal biopsy – A single centre experience from Pakistan. Ann. Med. Surg. 21 , 85–88. 10.1016/j.amsu.2017.06.057 (2017). Song, M., Graubard, B. I., Rabkin, C. S. & Engels, E. A. Neutrophil-to-lymphocyte ratio and mortality in the United States general population. Sci. Rep. 11 (1), 464. 10.1038/s41598-020-79431-7 (2021). Levi, M. & van der Poll, T. Inflammation and coagulation. Crit. Care Med. 38 (2 Suppl), S26–34. 10.1097/CCM.0b013e3181c98d21 (2010). Esmon, C. T. The interactions between inflammation and coagulation. Br. J. Haematol. 131 (4), 417–430. 10.1111/j.1365-2141.2005.05753.x (2005). Fagundes, A. et al. Neutrophil-lymphocyte ratio and clinical outcomes in 19,697 patients with atrial fibrillation: analyses from ENGAGE AF-TIMI 48 trial. Int. J. Cardiol. 386 , 118–124. 10.1016/j.ijcard.2023.05.031 (2023). Wang, J. Y. et al. Admission neutrophil-lymphocyte ratio predicts rebleeding following aneurismal subarachnoid hemorrhage. World Neurosurg. 138 , e317–e322. 10.1016/j.wneu.2020.02.112 (2020). Hong, S. H., Kim, C. J. & Yang, E. M. Neutrophil-to-lymphocyte ratio to predict gastrointestinal bleeding in Henoch: Schönlein purpura. Pediatr. Int. 60 (9), 791–795. 10.1111/ped.13652 (2018). Huang, J., Liao, F., Luo, Y. & Shu, X. Neutrophil-to-lymphocyte ratio at admission is a risk factor for in-hospital gastrointestinal bleeding in acute ischemic stroke patients after dual antiplatelet therapy: A case control study. J. Stroke Cerebrovasc. Dis. 32 (10), 107325. 10.1016/j.jstrokecerebrovasdis.2023.107325 (2023). Lees, J. S. et al. Risk factors for bleeding complications after nephrologist-performed native renal biopsy. Clin. Kidney J. 10 (4), 573–577. 10.1093/ckj/sfx012 (2017). Qian, L. et al. Safety and adequacy of kidney biopsy procedure in patients with obesity. Kidney360 4 (1), 98–101. 10.34067/KID.0006602022 (2023). Kattula, S., Byrnes, J. R. & Wolberg, A. S. Fibrinogen and fibrin in hemostasis and thrombosis. Arterioscler. Thromb. Vasc Biol. 37 (3), e13–21. 10.1161/ATVBAHA.117.308564 (2017). Casini, A. & de Moerloose, P. How I treat dysfibrinogenemia. Blood 138 (21), 2021–2030. 10.1182/blood.2020010116 (2021). Casini, A. How I treat quantitative fibrinogen disorders. Blood 145 (8), 801–810. 10.1182/blood.2024025712 (2025). Jeppsson, A., Waldén, K., Roman-Emanuel, C., Thimour-Bergström, L. & Karlsson, M. Preoperative supplementation with fibrinogen concentrate in cardiac surgery: A randomized controlled study. Br. J. Anaesth. 116 (2), 208–214. 10.1093/bja/aev367 (2016). Fontana, C. et al. Bleeding risk after native and transplant kidney biopsy – a single-centre observational study. Swiss Med. Wkly. 155 (6), 4409–4409. 10.57187/s.4409 (2025). van den Hoogen, M. W. F., Verbruggen, B. W., Polenewen, R., Hilbrands, L. B. & Nováková, I. R. O. Use of the platelet function analyzer to minimize bleeding complications after renal biopsy. Thromb. Res. 123 (3), 515–522. 10.1016/j.thromres.2008.07.001 (2009). Ranghino, A. et al. Assessment of platelet function analyzer (PFA-100) in kidney transplant patients before renal allograft biopsy: a retrospective single-center analysis. Transplant Proc. ;46(7):2259–62. (2014). 10.1016/j.transproceed.2014.07.052 Islam, N. et al. Do platelet function analyzer-100 testing results correlate with bleeding events after percutaneous renal biopsy? Clin. Nephrol. 73 (3), 229–237. 10.5414/cnp73229 (2010). Blanc, J. L., Mullier, F., Vayne, C. & Lordkipanidzé, M. Advances in platelet function testing—light transmission aggregometry and beyond. J. Clin. Med. 9 (8), 2636. 10.3390/jcm9082636 (2020). Drotarova, M. et al. Basic Principles of Rotational Thromboelastometry (ROTEM®) and the Role of ROTEM—Guided Fibrinogen Replacement Therapy in the Management of Coagulopathies. Diagnostics 13 (20), 3219. 10.3390/diagnostics13203219 (2023). Davis, C. L. & Chandler, W. L. Thromboelastography for the prediction of bleeding after transplant renal biopsy. J. Am. Soc. Nephrol. 6 (4), 1250–1255. 10.1681/ASN.V641250 (1995). Gal-Oz, A. et al. Thromboelastography versus bleeding time for risk of bleeding post native kidney biopsy. Ren. Fail. 42 (1):10–18. 10.1080/0886022X.2019.1700805 Additional Declarations No competing interests reported. Supplementary Files Supplementarykidneybiopsypredictionmodelver1.0.docx FigureS1.tif Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9347196","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":625772137,"identity":"e1b7ec43-8f4b-4a69-a017-467774bc0a0e","order_by":0,"name":"Nattapon Wongworapanya","email":"","orcid":"","institution":"Navamindradhiraj University","correspondingAuthor":false,"prefix":"","firstName":"Nattapon","middleName":"","lastName":"Wongworapanya","suffix":""},{"id":625772138,"identity":"a4985f5d-9839-453f-80cb-9911dc32d287","order_by":1,"name":"Panarat Noiperm","email":"","orcid":"","institution":"Prince of Songkla University","correspondingAuthor":false,"prefix":"","firstName":"Panarat","middleName":"","lastName":"Noiperm","suffix":""},{"id":625772139,"identity":"e56a6bfb-cc33-4d97-9c39-c86cb3ad3136","order_by":2,"name":"Pirun Saelue","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA3ElEQVRIiWNgGAWjYDACZhBRIcHDz94D5vPwEafljIWMZM8ZBoYDQC1sRNnE2FZhY3AjB6yFgaAWc3beZ9IFbBI8kjPfHnz8McdOho2B+eGjG3i0WDazm0nP4AH6RTov2eDgtmSgw9iMjXPwaDE4zMYmzSMBtGV2jpnEwW3MQC08bNKEtRhI8BjcPAPSUk+slgSglhs8IC2HCWuxbGZjtuY5AHRYT46xwdltx3nYmAn4xZz/GONt3n919vzsZwwfVG6rBjKaHz7G6zBMIWY8ynFoGQWjYBSMglGABgCLtjn9JsEVQQAAAABJRU5ErkJggg==","orcid":"","institution":"Prince of Songkla University","correspondingAuthor":true,"prefix":"","firstName":"Pirun","middleName":"","lastName":"Saelue","suffix":""}],"badges":[],"createdAt":"2026-04-07 15:38:18","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9347196/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9347196/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":107615159,"identity":"fdacf6f2-cc01-4da1-9c1e-58e993f2ba51","added_by":"auto","created_at":"2026-04-23 09:10:59","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":401942,"visible":true,"origin":"","legend":"\u003cp\u003eA nomogram of the prediction model (BENREEF model) to predict the probability of bleeding risk in patients undergoing kidney biopsy\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-9347196/v1/d6f5ee3f842820f29a3e36f9.png"},{"id":107615248,"identity":"a62d9cda-8313-4e7f-a7b6-fc2fd367c9e1","added_by":"auto","created_at":"2026-04-23 09:11:10","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":382252,"visible":true,"origin":"","legend":"\u003cp\u003eThe area under the curve of the BENREEF model.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-9347196/v1/f4adf2e8e809c1944e9171c9.png"},{"id":107615330,"identity":"68cb148a-29ea-4c80-b429-d5dc07899932","added_by":"auto","created_at":"2026-04-23 09:11:22","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":204788,"visible":true,"origin":"","legend":"\u003cp\u003eThe calibration plot of the BENREEF model.\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-9347196/v1/11d549ab769bee0d3b2929ff.png"},{"id":107687576,"identity":"cadda59e-4aca-485a-8c7d-b14a15672a59","added_by":"auto","created_at":"2026-04-24 04:54:56","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1473232,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9347196/v1/7fb96bb9-eeaf-4462-a056-19dae8af7bd4.pdf"},{"id":107615504,"identity":"bd5caad1-608e-4938-84db-a33fceef71f3","added_by":"auto","created_at":"2026-04-23 09:11:43","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":94685,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarykidneybiopsypredictionmodelver1.0.docx","url":"https://assets-eu.researchsquare.com/files/rs-9347196/v1/bb1852d6640f36036c6293c4.docx"},{"id":107615284,"identity":"71ca0e22-a555-4709-9e6c-6d6505d07361","added_by":"auto","created_at":"2026-04-23 09:11:20","extension":"tif","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":62044,"visible":true,"origin":"","legend":"","description":"","filename":"FigureS1.tif","url":"https://assets-eu.researchsquare.com/files/rs-9347196/v1/13f6b99eb9c8d84a3874a2c3.tif"}],"financialInterests":"No competing interests reported.","formattedTitle":"Prediction of bleeding complications using platelet aggregation testing and thromboelastography in patients undergoing kidney biopsy: a prospective cohort study ","fulltext":[{"header":"Background","content":"\u003cp\u003eRenal disease is a common clinical condition. Early diagnosis and treatment can reduce disease progression to end-stage kidney disease and improve survival (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). Kidney biopsy is a medical procedure in which small samples of renal tissue are obtained for the diagnosis of kidney diseases, evaluation of renal function, and monitoring of treatment response. This procedure aids clinicians in making appropriate therapeutic decisions. However, bleeding remains a major complication of kidney biopsy. About 1.4\u0026ndash;10.3% of patients undergoing kidney biopsy experience bleeding complications (\u003cspan additionalcitationids=\"CR3\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). The severity of bleeding varies, ranging from gross hematuria to hypovolemic shock. Patients who develop bleeding complications have an increased risk of mortality (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSeveral factors have been associated with an increased risk of bleeding following kidney biopsy. Patients with renal failure, particularly those with serum creatinine\u0026thinsp;\u0026ge;\u0026thinsp;2.0 mg/dL, are at higher risk (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). The mechanisms underlying abnormal bleeding in these patients include platelet dysfunction, nitric oxide accumulation, anemia, dialysis-induced vascular changes, and impaired platelet-vessel wall interactions (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). Uncontrolled hypertension is another important risk factor. A systolic blood pressure\u0026thinsp;\u0026ge;\u0026thinsp;160 mmHg or diastolic blood pressure\u0026thinsp;\u0026ge;\u0026thinsp;100 mmHg is associated with an increased risk of bleeding in patients undergoing kidney biopsy (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). Therefore, blood pressure should be adequately controlled prior to the procedure to minimize bleeding complications. In addition, thrombocytopenia and coagulopathy are well-recognized risk factors for bleeding during invasive procedures, including kidney biopsy. Thus, the procedure should be performed with caution in patients at high risk of bleeding.\u003c/p\u003e \u003cp\u003eThe platelet aggregation test is considered the gold standard for diagnosing platelet dysfunction, including conditions such as Glanzmann thrombasthenia, Bernard\u0026ndash;Soulier syndrome, and drug-induced platelet dysfunction. It has also been used to predict bleeding risk in thrombocytopenic patients with acute myeloid leukemia and the risk of recurrent stroke or major bleeding in patients with stroke (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). Thromboelastography (TEG) is a laboratory technique used to assess hemostasis by measuring the viscoelastic properties of whole blood during clot formation and dissolution. It has been shown to predict perioperative bleeding risk and reduce blood transfusion requirements in trauma and surgical settings (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). A limited number of studies have evaluated the utility of the platelet aggregation test or TEG in predicting bleeding risk following kidney biopsy. However, their findings remain inconclusive. Therefore, this study aimed to evaluate predictive factors, including platelet aggregation testing and TEG, for bleeding complications following kidney biopsy and to develop a prediction model to estimate the probability of bleeding in patients undergoing kidney biopsy. Such a model may improve clinical decision-making, reduce bleeding risk, and ultimately improve patient outcomes.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy population\u003c/h2\u003e \u003cp\u003e This prospective cohort study was conducted at Songklanagarind Hospital, the largest tertiary care center in Southern Thailand, between June 2020 and July 2024. Patients (age\u0026thinsp;\u0026ge;\u0026thinsp;18 years) with renal failure, defined as creatinine clearance\u0026thinsp;\u0026lt;\u0026thinsp;60 mL/min calculated using the Cockcroft\u0026ndash;Gault formula, were enrolled prior to undergoing kidney biopsy. Exclusion criteria included: kidney transplant recipients; current use of anticoagulants or antiplatelet agents; prolonged activated partial thromboplastin time (aPTT), prothrombin time/international normalized ratio (PT/INR)\u0026thinsp;\u0026gt;\u0026thinsp;1.5; platelet count\u0026thinsp;\u0026lt;\u0026thinsp;100,000 cells/\u0026micro;L; hemodynamic instability; requirement for invasive mechanical ventilation; use of herbal products or medications known to interfere with hemostasis; and uncontrolled hypertension (systolic pressure\u0026thinsp;\u0026ge;\u0026thinsp;140 mmHg or diastolic pressure\u0026thinsp;\u0026ge;\u0026thinsp;100 mmHg) prior to kidney biopsy.\u003c/p\u003e \u003cp\u003e This study was approved by the institutional review board of our institution and conducted in accordance with the Declaration of Helsinki (approval number: REC. 63-131-14-1). Written informed consent was obtained from all participants prior to enrollment.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eKidney biopsy procedure\u003c/h3\u003e\n\u003cp\u003eAll kidney biopsies were performed based on clinical indications and at the discretion of the treating nephrologist. Percutaneous kidney biopsies were performed under real-time ultrasound guidance in the prone position by experienced radiologists or radiology trainees under direct supervision. An automated spring-loaded biopsy device with a 16-gauge needle was used. A minimum of three core samples were obtained, as determined by the radiologist based on specimen adequacy. Post-biopsy ultrasonography was performed immediately to assess for bleeding complications. Following the procedure, patients remained in the supine position for at least 6 h and were monitored for signs and symptoms of bleeding complications for a minimum of 24 h during hospitalization.\u003c/p\u003e\n\u003ch3\u003ePlatelet aggregation test and thromboelastography\u003c/h3\u003e\n\u003cp\u003ePlatelet aggregation was assessed using a Helena AggRAM aggregometer (Helena Biosciences, UK) based on the light transmission method. Citrated venous blood samples were stored at room temperature and analyzed within 4 h of collection. Platelet-rich plasma (PRP) was prepared by centrifugation at 200 \u0026times; g for 10 min, and platelet-poor plasma (PPP) was obtained by further centrifugation at 2,000 \u0026times; g for 10 min. The platelet count in PRP was adjusted to 200,000\u0026ndash;300,000 cells/\u0026micro;L using autologous PPP. Aggregation was induced by adding 25 \u0026micro;L of platelet agonists to 225 \u0026micro;L of PRP. The agonists included adenosine diphosphate (ADP), collagen (5 \u0026micro;g/mL), epinephrine (10 \u0026micro;M), and ristocetin (1.0 mg/mL). The final concentrations of each agonist were applied according to standard protocols. Parameters recorded included primary slope, secondary slope, maximum aggregation, and time to maximum aggregation. Measurements were continuously recorded for 10 min after agonist addition. Internal quality control was performed daily, and instrument calibration and performance verification were conducted according to the manufacturer\u0026rsquo;s instructions.\u003c/p\u003e \u003cp\u003eTEG was performed using a rotational thromboelastometry (ROTEM) delta analyzer (Werfen/Instrumentation Laboratory, Germany). Citrated whole-blood samples were stored at room temperature and analyzed within 60 min of collection. For each assay, 300 \u0026micro;L of blood was mixed with assay-specific reagents and calcium chloride (CaCl\u003csub\u003e2\u003c/sub\u003e). The EXTEM (extrinsic pathway thromboelastometry), INTEM (intrinsic pathway thromboelastometry), APTEM (aprotinin-modified thromboelastometry), and FIBTEM (fibrin-based thromboelastometry) assays were performed. Parameters recorded included clotting time (CT), clot formation time, α angle, amplitude 10 min after CT, amplitude 20 min after CT, maximum clot firmness, and maximum lysis at 60 min (ML60). All measurements were continuously monitored for at least 60 min. Daily internal quality control and instrument calibration were performed according to the manufacturer\u0026rsquo;s instructions.\u003c/p\u003e\n\u003ch3\u003ePredictors and outcome\u003c/h3\u003e\n\u003cp\u003ePredictors were selected based on literature review and investigator expertise. Cardiovascular diseases included hypertension, diabetes mellitus, dyslipidemia, and myocardial infarction. Baseline patient characteristics and laboratory data were collected within 1 week prior to kidney biopsy. Platelet aggregation testing, TEG, and fibrinogen levels were performed within 24 h before the procedure.\u003c/p\u003e \u003cp\u003eBleeding events were monitored from the time of kidney biopsy until hospital discharge. Major bleeding was defined as bleeding requiring therapeutic intervention, requiring blood transfusion, associated with a decrease in hemoglobin\u0026thinsp;\u0026ge;\u0026thinsp;1 g/dL, or resulting in death. Minor bleeding included gross hematuria, perinephric hematoma, or bleeding that did not require therapeutic intervention or blood transfusion (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e).\u003c/p\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eAll statistical analyses were performed using R software (version 4.3.2). Categorical variables were presented as frequencies and percentages, and continuous variables as medians with interquartile ranges (IQR). Comparisons between patients with and without bleeding complications were performed using chi-square test, Student\u0026rsquo;s \u003cem\u003et\u003c/em\u003e-test, or Fisher\u0026rsquo;s exact test, as appropriate. Maximally selected rank statistics were used to determine optimal cutoff values for continuous variables. Univariate and multivariate logistic regression analyses were conducted to identify predictors of bleeding complications following kidney biopsy. Variables with \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 in univariate analysis were included in the multivariable model.\u003c/p\u003e \u003cp\u003eA prediction model was developed using backward stepwise regression, and the model with the lowest Akaike Information Criterion (AIC) was selected. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC) for discrimination and calibration plots for calibration.\u003c/p\u003e \u003cp\u003eInternal validation was performed using bootstrap resampling (1,000 iterations). Model performance was assessed using AUC and calibration plots in the bootstrap samples.\u003c/p\u003e \u003cp\u003eThis study adhered to the Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) guidelines (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eA total of 121 patients were enrolled in this study. Two patients were excluded due to immediate contraindications on the day of kidney biopsy. Consequently, 119 patients were included in the final analysis. The median age was 45.3 years, with a female predominance (54.6%). The median time from symptom onset to kidney biopsy was 90.0 days. Approximately 58.0% of patients had cardiovascular disease. The median hematocrit (Hct) and platelet count were 32.7% and 261,000 cells/\u0026micro;L, respectively. The median neutrophil-to-lymphocyte ratio (NLR) was 3.83, and the median serum creatinine level was 2.06 mg/dL. Most baseline characteristics were similar between patients with and without bleeding complications (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). However, fibrinogen levels were significantly higher in patients without bleeding complications than in those with bleeding complications.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBaseline characteristics in 119 patients who underwent kidney biopsy according to bleeding complications\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePatients with bleeding complications (N\u0026thinsp;=\u0026thinsp;66)\u003c/p\u003e \u003cp\u003eNumber (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePatients without bleeding complications (N\u0026thinsp;=\u0026thinsp;53)\u003c/p\u003e \u003cp\u003eNumber (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years), median (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e45.3 (31.1,54.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e45.3 (34.5,59.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.395\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender (female)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e39 (59.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26 (49.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.275\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWeight (kg), median (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e63.3 (56.8,70.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e67.7 (57.2,78.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.137\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeight (cm), median (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e160.0 (152.0,165.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e160.0 (155.0,169.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.436\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTime from symptoms to kidney biopsy (days), median (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e90.0 (47.5,240.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e90.0 (41.0,218.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.927\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnderlying disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e53 (80.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e44 (83.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.704\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCardiovascular disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e37 (56.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32 (60.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.635\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHematologic disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7 (10.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (9.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.833\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiver disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (3.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (3.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSystolic blood pressure, median (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e132.0 (124.2,138.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e130.0 (120.0,136.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.349\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHemoglobin (g/dL), median (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10.5 (9.4,12.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11.1 (9.7,11.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.562\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHematocrit (%), median (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e32.7 (28.3,37.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33.0 (29.3,35.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.571\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePlatelet (cells/\u0026micro;L), median (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e261000 (204800,318800)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e263000 (201000,329000)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.783\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWhite blood cell (cells/\u0026micro;L), median (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8815 (6510,10910)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8250 (6360,10730)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.409\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNeutrophil to lymphocyte ratio, median (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.3 (2.2,7.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.2 (2.6,12.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.190\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eaPTT (s), median (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25.1 (21.5,29.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25.1 (23.7,27.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.785\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePT(s), median (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.00 (0.93,1.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.01 (0.93,1.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.421\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFibrin (mg/dL), median (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e480.7 (336.1,627.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e600.2 (452.8,833.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.017\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBlood urea nitrogen (mg/dL), median (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30.3 (21.0,49.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32.2 (22.1,49.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.989\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCreatinine (mg/dL), median (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.3 (1.1,4.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.0 (1.3,2.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.474\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eaPTT, activated partial thromboplastin time; cm, centimeters; dL, deciliters; IQR, interquartile range; kg, kilograms; mg, milligrams; PT, prothrombin time.\u003c/p\u003e\n\u003ch3\u003ePlatelet aggregation test and thromboelastography\u003c/h3\u003e\n\u003cp\u003eIn the platelet aggregation test, the median maximum aggregation percentages were 88.0%, 91.2%, 88.5%, and 89.3% for ADP, collagen, epinephrine, and ristocetin, respectively. These values did not differ significantly between patients with and without bleeding complications. The primary and secondary slopes for all agonists were also similar between the two groups. However, the median time to maximum aggregation of epinephrine and ristocetin was shorter in patients with bleeding complications (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eRegarding TEG, the median ML60 in EXTEM was higher in patients with bleeding complications. Other TEG parameters, including INTEM, APTEM, and FIBTEM, were comparable between patients with and without bleeding complications (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePlatelet aggregation test of 119 patients before kidney biopsy\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePlatelet aggregation test\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePatients with bleeding complication (N\u0026thinsp;=\u0026thinsp;66)\u003c/p\u003e \u003cp\u003eMedian (IQR)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePatients without bleeding complication (N\u0026thinsp;=\u0026thinsp;53)\u003c/p\u003e \u003cp\u003eMedian (IQR)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAdenosine diphosphate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrimary slope (%/min)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e123.6 (106.8,143.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e126.3 (104.4,136.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.925\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSecondary slope (%/min)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e24.4 (21.3,27.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e24.3 (21.6,27.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.783\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMaximum aggregation (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e87.5 (80.9,92.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e88.9 (83.2,92.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.499\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTime to maximum aggregation (s)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e366.5 (320.5,411.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e364.0 (322.0,478.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.301\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCollagen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrimary slope (%/min)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e23.7 (2.1,29.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e24.1 (2.1,31.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.874\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSecondary slope (%/min)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e133.0 (119.6,152.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e141.9 (114.9,154.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.998\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMaximum aggregation (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e90.8 (87.2,93.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e91.7 (88.6,93.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.243\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTime to maximum aggregation (s)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e429.0 (362.0,490.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e429.0 (362.0,548.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.539\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEpinephrine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrimary slope (%/min)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e72.4 (38.1,111.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e61.0 (46.7,78.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.334\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSecondary slope (%/min)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e26.2 (21.2,29.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e25.5 (23.0,36.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.225\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMaximum aggregation (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e86.8 (80.1,91.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e90.0 (84.0,92.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.065\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTime to maximum aggregation (s)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e489.5 (438.5,579.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e550.0 (486.0,582.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.039\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRistocetin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrimary slope (%/min)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e86.5 (61.3,104.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e84.7 (65.5,105.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.961\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMaximum aggregation (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e88.2 (84.8,91.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e89.7 (84.8,93.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.324\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTime to maximum aggregation (s)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e316.5 (251.8,370.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e336.0 (260.0,432.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.023\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eIQR, interquartile range.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThromboelastography of 119 patients before kidney biopsy\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThromboelastography\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePatients with bleeding complication (N\u0026thinsp;=\u0026thinsp;66)\u003c/p\u003e \u003cp\u003eMedian (IQR)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePatients without bleeding complication (N\u0026thinsp;=\u0026thinsp;53)\u003c/p\u003e \u003cp\u003eMedian (IQR)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEXTEM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCoagulation time (s)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e49.0 (44.0,52.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e48.0 (38.0,54.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.452\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eClot formation time (s)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e60.5 (44.3,77.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e54.0 (42.3,77.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.575\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eα angle (degree)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e80.0 (75.3,82.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e80.0 (76.0,82.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.824\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAmplitude 10 min after CT (mm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e61.0 (55.3,67.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e65.0 (55.8,69.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.444\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAmplitude 20 min after CT (mm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e66.5 (59.3,70.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e69.0 (61.0,73.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.209\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMaximum clot firmness (mm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e68.0 (61.3,72.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e69.5 (62.8,75.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.252\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMaximum lysis within 60 min (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e9.0 (5.0,12.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6.0 (3.0,11.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.049\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eINTEM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCoagulation time (s)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e175.5 (146.2,206.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e173.5 (136.8,221.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.797\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eClot formation time (s)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e64.0 (51.3,82.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e63.0 (49.0,84.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.717\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eα angle (degree)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e78.0 (75.0,79.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e78.0 (74.8,81.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.590\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAmplitude 10 min after CT (mm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e58.0 (53.3,64.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e62.0 (55.0,66.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.391\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAmplitude 20 min after CT (mm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e64.0 (60.0,70.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e67.0 (60.8,71.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.366\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMaximum clot firmness (mm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e64.5 (61.0,71.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e67.0 (60.8,72.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.554\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMaximum lysis within 60 min (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4.0 (3.0,7.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.0 (3.0,7.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.861\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAPTEM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMaximum clot firmness (mm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8.0 (4.0,49.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5.5 (4.0,64.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.898\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFIBTEM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAmplitude 10 min after CT (mm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e21.0 (16.0,26.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e24.0 (18.8,31.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.080\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAmplitude 20 min after CT (mm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e22.5 (17.0,28.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e25.0 (19.0,32.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.167\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMaximum clot firmness (mm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e23.0 (17.0,31.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e26.0 (20.0,33.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.142\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eCT, coagulation time; mm, millimeters; s, seconds.\u003c/p\u003e\n\u003ch3\u003eBleeding complications\u003c/h3\u003e\n\u003cp\u003eAmong the 119 patients who underwent kidney biopsy, 66 (55.5%) experienced bleeding complications. Major bleeding occurred in approximately 10.1% of patients. Specifically, four patients required therapeutic intervention, two patients experienced a significant decline in Hct, and four patients required blood transfusion. Minor bleeding occurred in 54 patients (45.4%), including 52 cases of perinephric hematoma and 2 cases of gross hematuria. No deaths occurred during the study period.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eFactors associated with bleeding complications\u003c/h2\u003e \u003cp\u003eIn the univariate analysis, body weight, NLR, fibrinogen, serum creatinine, time to maximum aggregation for ADP, collagen, epinephrine, and ristocetin, primary and secondary slopes of epinephrine, coagulation time, and ML60 in EXTEM were associated with bleeding complications.\u003c/p\u003e \u003cp\u003eIn the multivariate analysis, NLR\u0026thinsp;\u0026ge;\u0026thinsp;15, fibrinogen\u0026thinsp;\u0026ge;\u0026thinsp;500 mg/dL, time to maximum aggregation of epinephrine\u0026thinsp;\u0026ge;\u0026thinsp;450 s, and time to maximum aggregation of ristocetin\u0026thinsp;\u0026ge;\u0026thinsp;420 s were identified as protective factors against bleeding complications. In contrast, ML60 in EXTEM\u0026thinsp;\u0026ge;\u0026thinsp;5% was independently associated with an increased risk of bleeding complications in patients undergoing kidney biopsy (Supplementary Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003ePrediction model generation for bleeding complications\u003c/h2\u003e \u003cp\u003eA prediction model (BENREEF model) was developed using backward stepwise regression to estimate the risk of bleeding complications in patients undergoing kidney biopsy (Supplementary Table S2). The model included \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eB\u003c/span\u003eody weight, time to maximum aggregation of \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eE\u003c/span\u003epinephrine, \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eN\u003c/span\u003eeutrophil-to-lymphocyte ratio, time to maximum aggregation of \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eR\u003c/span\u003eistocetin, coagulation time in \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eE\u003c/span\u003eXTEM, ML60 in \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eE\u003c/span\u003eXTEM, and \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eF\u003c/span\u003eibrinogen level.\u003c/p\u003e \u003cp\u003eA nomogram of the prediction model is presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The model demonstrated good discriminative ability, with an AUC of 0.88 (95% CI: 0.81\u0026ndash;0.95) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The calibration plot indicated good agreement between predicted and observed outcomes (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eInternal validation of prediction model\u003c/h2\u003e \u003cp\u003eInternal validation was performed using bootstrap resampling with 1,000 iterations. The validated model showed an AUC of 0.88 (95% CI: 0.80\u0026ndash;0.94). The calibration plot also demonstrated good calibration (Supplementary Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this study, approximately 10.1% of patients who underwent kidney biopsy experienced major bleeding. NLR\u0026thinsp;\u0026ge;\u0026thinsp;15, fibrinogen\u0026thinsp;\u0026ge;\u0026thinsp;500 mg/dL, time to maximum aggregation of epinephrine\u0026thinsp;\u0026ge;\u0026thinsp;450 s, and time to maximum aggregation of ristocetin\u0026thinsp;\u0026ge;\u0026thinsp;420 s were associated with a decreased risk of bleeding complications. In contrast, ML60 in EXTEM\u0026thinsp;\u0026ge;\u0026thinsp;5% was associated with an increased risk of bleeding complications in patients undergoing kidney biopsy. The BENREEF model demonstrated good performance in predicting the probability of bleeding in these patients.\u003c/p\u003e \u003cp\u003eThe incidence of major bleeding complications for kidney biopsy in this study was higher than that reported in previous studies (10.1% vs. 0.9\u0026ndash;7.2%) (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). All kidney biopsies were performed by experienced radiologists or supervised trainees according to standard protocols. The higher incidence observed in this study may reflect a population with a greater baseline bleeding risk. Additionally, variations in the definition of major bleeding across studies may contribute to differences in reported incidence. Minor bleeding occurred in 45.4% of patients, predominantly as asymptomatic perinephric hematoma, which is higher than the 8.9\u0026ndash;17.2% reported previously (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). This increased incidence may be explained by routine post-kidney biopsy ultrasonography, enabling detection of otherwise asymptomatic hematomas.\u003c/p\u003e \u003cp\u003eThis study identified seven predictors associated with bleeding risk following kidney biopsy. NLR reflects the balance between innate and adaptive immune responses (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). Interestingly, a high NLR was associated with a reduced risk of bleeding complications. Elevated NLR indicates increased systemic inflammation, which promotes a procoagulant state through cytokine-mediated upregulation of tissue factor, resulting in increased thrombin generation and fibrin formation. It may also enhance platelet activation, suppress natural anticoagulant pathways, and inhibit fibrinolysis (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). These mechanisms may reduce bleeding risk but may also increase the risk of thrombosis. Previous studies have not evaluated the association between elevated NLR and bleeding risk in kidney biopsy. However, elevated NLR has been associated with increased bleeding complications in other clinical settings, including gastrointestinal bleeding in acute ischemic stroke, Henoch\u0026ndash;Sch\u0026ouml;nlen purpura, major bleeding in atrial fibrillation, and rebleeding in aneurysmal subarachnoid hemorrhage (\u003cspan additionalcitationids=\"CR22 CR23\" citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e). The underlying mechanisms of hemostasis in patients with elevated NLR undergoing kidney biopsy remain unclear and warrant further investigation.\u003c/p\u003e \u003cp\u003eBody weight was not significantly associated with bleeding risk in this study, consistent with previous reports (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e), but it remained an important component of the prediction model. This highlights that predictors in multivariable models do not necessarily represent independent risk factors. Fibrinogen plays a central role in the coagulation cascade and is essential for maintaining hemostasis (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e). Patients with afibrinogenemia, hypofibrinogenemia, or dysfibrinogenemia are at increased risk of spontaneous and perioperative bleeding (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e). Low fibrinogen levels have also been associated with bleeding during medical interventions (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e). In this study, higher fibrinogen levels (\u0026ge;\u0026thinsp;500 mg/dL) were associated with a reduced risk of bleeding following kidney biopsy. However, prophylactic elevation of fibrinogen to this threshold is not recommended, as excessively high levels may increase thrombotic risk. Instead, patients with fibrinogen levels\u0026thinsp;\u0026lt;\u0026thinsp;500 mg/dL should be closely monitored.\u003c/p\u003e \u003cp\u003ePatients with renal failure are at risk of uremia-related platelet dysfunction, which contributes to bleeding. Platelet function analyzers are commonly used to assess platelet-related bleeding risk in kidney biopsy. Prolonged closure time has been associated with increased bleeding risk in some studies (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e), although others have reported no significant association (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e). In this study, light transmission aggregometry, the gold standard for assessing platelet function (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e), was used. Maximum platelet aggregation was not associated with bleeding risk. Shorter time to maximum aggregation of epinephrine and ristocetin was associated with an increased risk of bleeding complications. This may reflect dysregulated platelet activation kinetics and impaired clot stability, leading to unstable thrombus formation and premature disaggregation. However, clinical evidence supporting this association remains limited and requires further validation.\u003c/p\u003e \u003cp\u003eTEG assesses the viscoelastic properties of clot formation in real time and is widely used to evaluate bleeding risk and guide transfusion strategies (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e). EXTEM reflects the extrinsic coagulation pathway and may be particularly useful in this context. Evidence for the use of TEG in predicting bleeding during kidney biopsy remains limited and inconsistent. Davis et al. reported an association between abnormal TEG findings and bleeding in transplant kidney biopsies, whereas Gal-Oz et al. found no such association in native kidney biopsies (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e). In the present study, prolonged coagulation time (CT) and increased ML60 in EXTEM were associated with an increased risk of bleeding complications. These findings suggest delayed clot formation and enhanced fibrinolysis, respectively, both of which contribute to clot instability and increased bleeding risk.\u003c/p\u003e \u003cp\u003eWe developed a BENREEF model to predict bleeding risk in patients undergoing kidney biopsy. This model incorporates seven predictors, including parameters from platelet aggregation testing and TEG, and represents the first model to integrate these two hemostatic assessments in this clinical setting. The model demonstrated strong predictive performance across a wide range of bleeding probabilities ranging from 5% to 99%. However, no specific cutoff was established to guide clinical decision-making. We suggest that patients with a bleeding probability\u0026thinsp;\u0026ge;\u0026thinsp;20% should undergo careful evaluation before proceeding with kidney biopsy. Modifiable risk factors should be optimized prior to the procedure, and patients should be closely monitored during the perioperative and postoperative periods. Early detection and management of bleeding may reduce complications. The model was internally validated using bootstrap resampling and demonstrated good discrimination and calibration. However, external validation is necessary to confirm its generalizability.\u003c/p\u003e \u003cp\u003eThis study has several limitations. First, it was conducted at a single center, which may limit generalizability and introduce the risk of model overfitting. Although internal validation demonstrated good performance, external validation is required. Second, the incidence of bleeding complications was higher than that reported in previous studies, which may reflect higher baseline risk or increased detection due to routine ultrasonography. Third, the study population consisted exclusively of Asian patients, and the applicability of the model to other populations requires further investigation.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eNeutrophil-to-lymphocyte ratio\u0026thinsp;\u0026ge;\u0026thinsp;15, fibrinogen\u0026thinsp;\u0026ge;\u0026thinsp;500 mg/dL, time to maximum aggregation of epinephrine\u0026thinsp;\u0026ge;\u0026thinsp;450 s, and time to maximum aggregation of ristocetin\u0026thinsp;\u0026ge;\u0026thinsp;420 s were associated with a reduced risk of bleeding complications following kidney biopsy, whereas ML60 in EXTEM\u0026thinsp;\u0026ge;\u0026thinsp;5% was associated with an increased risk. The BENREEF model demonstrated good predictive performance for estimating bleeding risk in this population. However, external validation is required before routine clinical implementation.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eADP\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAdenosine diphosphate\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eAIC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAkaike Information Criterion\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eaPTT\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eActivated partial thromboplastin time\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eAUC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eArea under the curve\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eBENREEF\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003e(Model name; expand if defined by authors)\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eConfidence interval\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCT\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCoagulation time\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eEXTEM\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eExtrinsic pathway thromboelastometry\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eFIBTEM\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eFibrin-based thromboelastometry\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHct\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eHematocrit\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eINTEM\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eIntrinsic pathway thromboelastometry\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eIQR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eInterquartile range\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eML60\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eMaximum lysis at 60 minutes\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eNLR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eNeutrophil-to-lymphocyte ratio\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePRP\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ePlatelet-rich plasma\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePPP\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ePlatelet-poor plasma\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePT\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eProthrombin time\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePT/INR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eProthrombin time/International normalized ratio\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eROC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eReceiver operating characteristic\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eTEG\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eThromboelastography\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e \u003cp\u003e This study was approved by the institutional review board of Songklanagarind Hospital and conducted in accordance with the Declaration of Helsinki (approval number: REC. 63-131-14-1). Written informed consent was obtained from all participants prior to enrollment.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eConsent for publication\u003c/strong\u003e \u003cp\u003eNot applicable.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eCompeting interests\u003c/h2\u003e \u003cp\u003eThe authors declare no conflict of interest.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThis study was supported by the Faculty of Medicine, Prince of Songkla University (grant number REC. 63-131-14-1).\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eN.W. and P.S. designed the study. All authors collected the data. PS analyzed the data, interpreted the results, and drafted the manuscript. All authors critically revised the manuscript for intellectual content, approved the final version for publication, and agreed to be accountable for all aspects of the study.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eWe would like to thank the Division of Information Technology at Songklanagarind Hospital and Prince of Songkla University for their support.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe datasets are available from the corresponding author upon request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eHaarhaus, M. et al. Early referral to nephrological care improves long-term survival and hospitalization after dialysis initiation, independent of optimal dialysis start \u0026ndash; a call for harmonization of reimbursement policies. \u003cem\u003eRen. 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Fail.\u003c/em\u003e \u003cb\u003e42\u003c/b\u003e(1):10\u0026ndash;18. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1080/0886022X.2019.1700805\u003c/span\u003e\u003cspan address=\"10.1080/0886022X.2019.1700805\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"prediction model, thromboelastography, platelet aggregation, kidney biopsy, bleeding complications","lastPublishedDoi":"10.21203/rs.3.rs-9347196/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9347196/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eKidney biopsy is an essential procedure for diagnosing kidney diseases. However, bleeding remains a major complication. This study aimed to evaluate predictive factors, including platelet aggregation testing and thromboelastography, and to develop a prediction model to estimate the probability of bleeding complications in patients undergoing kidney biopsy.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eIn this prospective cohort study, adult patients (aged\u0026thinsp;\u0026ge;\u0026thinsp;18 years) with renal failure were enrolled. Platelet aggregation testing and thromboelastography were performed within 24 h prior to kidney biopsy. A prediction model was developed using backward stepwise regression. Model performance was assessed using discrimination and calibration, and internal validation was performed using bootstrap resampling.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eA total of 119 patients were included. Bleeding complications occurred in 66 patients. Neutrophil-to-lymphocyte ratio\u0026thinsp;\u0026ge;\u0026thinsp;15, fibrinogen\u0026thinsp;\u0026ge;\u0026thinsp;500 mg/dL, time to maximum aggregation of epinephrine\u0026thinsp;\u0026ge;\u0026thinsp;450 s, and time to maximum aggregation of ristocetin\u0026thinsp;\u0026ge;\u0026thinsp;420 s were associated with a reduced risk of bleeding complications. In contrast, maximum lysis at 60 min (ML60) in extrinsic pathway thromboelastometry (EXTEM)\u0026thinsp;\u0026ge;\u0026thinsp;5% was associated with an increased risk of bleeding. The BENREEF model demonstrated good performance, with strong discrimination and calibration, including in internal validation.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eBoth protective and risk factors for bleeding complications following kidney biopsy were identified. The BENREEF model showed good predictive performance for estimating bleeding risk. However, external validation is required before clinical application.\u003c/p\u003e","manuscriptTitle":"Prediction of bleeding complications using platelet aggregation testing and thromboelastography in patients undergoing kidney biopsy: a prospective cohort study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-23 09:08:41","doi":"10.21203/rs.3.rs-9347196/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"eef9be22-942b-469a-8721-36df01cf0c69","owner":[],"postedDate":"April 23rd, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":66602470,"name":"Health sciences/Biomarkers"},{"id":66602471,"name":"Health sciences/Diseases"},{"id":66602472,"name":"Health sciences/Medical research"},{"id":66602473,"name":"Health sciences/Nephrology"},{"id":66602474,"name":"Health sciences/Risk factors"}],"tags":[],"updatedAt":"2026-04-24T04:54:38+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-23 09:08:41","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9347196","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9347196","identity":"rs-9347196","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}