Dataset Information

Validation of the IMPROVE bleeding risk score in Chinese medical patients during hospitalization: Findings from the dissolve-2 study.

ABSTRACT:

Background

Venous thromboembolism (VTE) prophylaxis remains suboptimal in China due to the bleeding risk associated with pharmacologic prophylaxis. We used data from the DissolVE-2 study to report the risk factors for bleeding and validated the International Medical Prevention Registry on Venous Thromboembolism (IMPROVE) bleeding risk score (BRS).

Methods

In-hospital major bleeding incidence in medical patients from the DissolVE-2 study were assessed by Kaplan-Meier method. Risk factors associated with clinically relevant bleeding (CRB) were analysed using Cox regression model. Sensitivity, specificity, positive predictive value, negative predictive value and receiver-operating characteristic (ROC) curve was used to compute the diagnostic accuracy of IMPROVE BRS in the study cohort.

Findings

Of the 6623 medical patients, 5076 patients with all relevant clinical details were included for the validation cohort. Overall, 127 CRB events (38 major and 89 clinically relevant non-major bleeding events) occurred in this cohort, with a cumulative incidence rate of 2.6% (95% confidence interval [CI], 2.3-3.4). Application of IMPROVE BRS revealed significantly higher hazards of CRB (hazard ratio [HR]: 7.17, 95% CI, 5.05-10.18) and major bleeding (HR: 13.95, 95% CI, 7.28-26.73) in patients with IMPROVE BRS ≥7. Comparison of predictive parameters revealed higher sensitivity (44.1 vs 35.9) and positive predictive value (10.9 vs 2.6) for CRB in our study than the IMPROVE study, which was substantiated by the area under the curve (0.73, p<0.0001) from the ROC curve analysis.

Interpretation

IMPROVE BRS is a simple model for estimating bleeding risk in Chinese medical patients and could be used in conjunction with VTE risk assessment models to decide prophylactic treatment for VTE.

Funding

This study and the additional data analysis were funded by Sanofi (Beijing) Pharmaceutical Co, Ltd by the Fund of The National Key Research and Development Program of China [Grant 2016YFC0905600] and by CAMS Innovation Fund for Medical Sciences (CIFMS) (No.2018-I2M-1-003).

SUBMITTER: Zhang Z

PROVIDER: S-EPMC8315610 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:BackgroundThe International Medical Prevention Registry for Venous Thromboembolism (IMPROVE) Bleeding Risk Score is the recommended risk assessment model (RAM) for predicting bleeding risk in acutely ill medical inpatients in Western countries. However, few studies have assessed its predictive performance in local Asian settings.MethodsWe retrospectively identified acutely ill adolescents and adults (aged ≥ 15 years) who were admitted to our general internal medicine department between July 5, 2016 and July 5, 2021, and extracted data from their electronic medical records. The outcome of interest was the cumulative incidence of major and nonmajor but clinically relevant bleeding 14 days after admission. For the two-risk-group model, we estimated sensitivity, specificity, and positive and negative predictive values (PPV and NPV, respectively). For the 11-risk-group model, we estimated C statistic, expected and observed event ratio (E/O), calibration-in-the-large (CITL), and calibration slope. In addition, we recalibrated the intercept using local data to update the RAM.ResultsAmong the 3,876 included patients, 998 (26%) were aged ≥ 85 years, while 656 (17%) were hospitalized in the intensive care unit. The median length of hospital stay was 14 days. Clinically relevant bleeding occurred in 58 patients (1.5%), 49 (1.3%) of whom experienced major bleeding. Sensitivity, specificity, NPV, and PPV were 26.1% (95% confidence interval [CI]: 15.8-40.0%), 84.8% (83.6-85.9%), 98.7% (98.2-99.0%), and 2.5% (1.5-4.3%) for any bleeding and 30.9% (95% CI: 18.8-46.3%), 84.9% (83.7-86.0%), 99.0% (98.5-99.3%), and 2.5% (1.5-4.3%) for major bleeding, respectively. The C statistic, E/O, CITL, and calibration slope were 0.64 (95% CI: 0.58-0.71), 1.69 (1.45-2.05), - 0.55 (- 0.81 to - 0.29), and 0.58 (0.29-0.87) for any bleeding and 0.67 (95% CI: 0.60-0.74), 0.76 (0.61-0.87), 0.29 (0.00-0.58), and 0.42 (0.19-0.64) for major bleeding, respectively. Updating the model substantially corrected the poor calibration observed.ConclusionsIn our Japanese cohort, the IMPROVE bleeding RAM retained the reported moderate discriminative performance. Model recalibration substantially improved the poor calibration obtained using the original RAM. Before its introduction into clinical practice, the updated RAM needs further validation studies and an optimized threshold.

Project description:Background Bleeding risk stratification in acute coronary syndrome is of highest clinical interest but current risk scores have limitations. We sought to develop and validate a new in-hospital bleeding risk score for patients with acute myocardial infarction. Methods and Results From the nationwide SWEDEHEART (Swedish Web-System for Enhancement and Development of Evidence-Based Care in Heart Disease Evaluated According to Recommended Therapies) register, 97,597 patients with acute myocardial infarction enrolled from 2009 until 2014 were selected. A full model with 23 predictor variables and 8 interaction terms was fitted using logistic regression. The full model was approximated by a model with 5 predictors and 1 interaction term. Calibration, discrimination, and clinical utility was evaluated and compared with the ACTION (Acute Coronary Treatment and Intervention Outcomes Network) and CRUSADE (Can Rapid Risk Stratification of Unstable Angina Patients Suppress Ad verse Outcomes With Early Implementation of the ACC /AHA Guidelines) scores. Internal and temporal validity was assessed. In-hospital major bleeding, defined as fatal, intracranial, or requiring surgery or blood transfusion, occurred in 1356 patients (1.4%). The 5 predictors in the approximate model that constituted the SWEDEHEART score were hemoglobin, age, sex, creatinine, and C-reactive protein. The ACTION and CRUSADE scores were poorly calibrated in the derivation cohort and therefore were recalibrated. The SWEDEHEART score showed higher discriminative ability than both recalibrated scores, overall ( C-index 0.80 versus 0.73/0.72) and in all predefined subgroups. Decision curve analysis demonstrated consistently positive and higher net benefit for the SWEDEHEART score compared with both recalibrated scores across all clinically relevant decision thresholds. The original ACTION and CRUSADE scores showed negative net benefit. Conclusions The 5-item SWEDEHEART score discriminates in-hospital major bleeding in patients with acute myocardial infarction and has superior model performance compared with the recalibrated ACTION and CRUSADE scores.

Project description:ObjectiveTo evaluate performance of the ABC (Age, Biomarkers, Clinical history)-bleeding risk score in estimating major bleeding risk in Chinese patients with atrial fibrillation (AF) on oral anticoagulation (OAC) therapy in real-world practice.MethodsData were collected from the Chinese Atrial Fibrillation Registry study (CAFR). Patients were stratified into low-, medium-, and high-risk groups based on ABC-bleeding risk score with 1-year major bleeding risk (<1%, 1-2%, and > 2%) and modified HAS-BLED score (≤1, 2, and > 2 points). Cox proportional-hazards (Cox-PH) models were used to determine the association of major bleeding incidence with bleeding scores. Harrell's C-index of the two scores were compared. Net reclassification improvement (NRI) and integrated discrimination improvement (IDI) at 1 year were employed to evaluate the reclassification capacity. The calibration curve was plotted to compare the predicted major bleeding risk using ABC-bleeding risk score with the observed annualized event rate. The decision analysis curves (DCA) were performed to show the clinical utilization of two scores in identifying major bleeding events.ResultsThe study included 2,892 AF patients on OAC therapy. After the follow-up of 3.0 years, 48 patients had major bleeding events; the incidence of a bleeding event in the low-, medium-, and high-risk groups according to ABC-bleeding risk score was 0.31% (reference group, HR = 1.00),0.51% (HR = 1.83, 95%CI: 0.91-3.69, P = 0.09), and 1.49% (HR = 4.92, 95%CI: 2.34-10.30, P < 0.001), respectively. Major bleeding incidence had an independent association with growth differentiation factor 15 (GDF-15) level (HR = 2.16, 95%CI: 1.27-3.68, P = 0.005) after adjusting components of the HAS-BLED score and cTnT-hs level. The ABC-bleeding score showed a Harrell's C-index of 0.67 (95%CI: 0.60-0.75) in estimating major bleeding risk, which was non-significant compared to the modified HAS-BLED score (0.67 vs. 0.63; P = 0.38). NRI and IDI also revealed comparable reclassification capacity of ABC-bleeding risk score compared with HAS-BLED score (14.6%, 95%CI: -10.2%, 39.4%, P = 0.25; 0.2%, 95%CI -0.1 to 0.9%, P = 0.64). Cross-tabulation of the two scores showed that the ABC-bleeding score outperformed the HAS-BLED score in identifying patients with a high risk of major bleeding. The calibration curve showed that the ABC-bleeding risk score overestimated the observed major bleeding risk. DCA did not show any difference in net benefit when using either of the scores.ConclusionThis study verified the value of the ABC-bleeding risk score in assessing major bleeding risk in Chinese patients with AF on OAC therapy in real-world practice. Despite the overestimation of major bleeding risk, ABC-bleeding score performed better in stratifying patients with a high risk than the modified HAS-BLED score. Combining the two scores could be a clinically practical strategy for precisely stratifying AF patients, especially those at a high risk of major bleeding, and further supporting the optimization of OAC treatment.

Project description:BackgroundGastrointestinal bleeding (GIB) is a common and often serious complication after stroke. Although several risk factors for post-stroke GIB have been identified, no reliable or validated scoring system is currently available to predict GIB after acute stroke in routine clinical practice or clinical trials. In the present study, we aimed to develop and validate a risk model (acute ischemic stroke associated gastrointestinal bleeding score, the AIS-GIB score) to predict in-hospital GIB after acute ischemic stroke.MethodsThe AIS-GIB score was developed from data in the China National Stroke Registry (CNSR). Eligible patients in the CNSR were randomly divided into derivation (60%) and internal validation (40%) cohorts. External validation was performed using data from the prospective Chinese Intracranial Atherosclerosis Study (CICAS). Independent predictors of in-hospital GIB were obtained using multivariable logistic regression in the derivation cohort, and ?-coefficients were used to generate point scoring system for the AIS-GIB. The area under the receiver operating characteristic curve (AUROC) and the Hosmer-Lemeshow goodness-of-fit test were used to assess model discrimination and calibration, respectively.ResultsA total of 8,820, 5,882, and 2,938 patients were enrolled in the derivation, internal validation and external validation cohorts. The overall in-hospital GIB after AIS was 2.6%, 2.3%, and 1.5% in the derivation, internal, and external validation cohort, respectively. An 18-point AIS-GIB score was developed from the set of independent predictors of GIB including age, gender, history of hypertension, hepatic cirrhosis, peptic ulcer or previous GIB, pre-stroke dependence, admission National Institutes of Health stroke scale score, Glasgow Coma Scale score and stroke subtype (Oxfordshire). The AIS-GIB score showed good discrimination in the derivation (0.79; 95% CI, 0.764-0.825), internal (0.78; 95% CI, 0.74-0.82) and external (0.76; 95% CI, 0.71-0.82) validation cohorts. The AIS-GIB score was well calibrated in the derivation (P = 0.42), internal (P = 0.45) and external (P = 0.86) validation cohorts.ConclusionThe AIS-GIB score is a valid clinical grading scale to predict in-hospital GIB after AIS. Further studies on the effect of the AIS-GIB score on reducing GIB and improving outcome after AIS are warranted.