Assessment of bleeding in chronic liver disease and coagulopathy using the IMPROVE bleeding criteria

A scale conjugate neural network approach for the fractional schistosomiasis disease system

This study presents the numerical solutions of the fractional schistosomiasis disease model (SDM) using the supervised neural networks (SNNs) and the computational scaled conjugate gradient (SCG), i.e. SNNs-SCG. The fractional derivatives are used for the precise outcomes of the fractional SDM. The preliminary fractional SDM is categorized as: uninfected, infected with schistosomiasis, recovered through infection, expose and susceptible to this virus. The accurateness of the SNNs-SCG is performed to solve three different scenarios based on the fractional SDM with synthetic data obtained with fractional Adams scheme (FAS). The generated data of FAS is used to execute SNNs-SCG scheme with 81% for training samples, 12% for testing and 7% for validation or authorization. The correctness of SNNs-SCG approach is perceived by the comparison with reference FAS results. The performances based on the error histograms (EHs), absolute error, MSE, regression, state transitions (STs) and correlation accomplish the accuracy, competence, and finesse of the SNNs-SCG scheme.

External Validation of the IMPROVE Risk Score for Predicting Bleeding in Hospitalized COVID-19 Patients

BACKGROUND

COVID-19 patients are at increased risk of thrombosis and bleeding, but no standardized bleeding risk assessment tool has been recommended.

OBJECTIVE

This study evaluates the predictive value of the IMPROVE Bleeding Risk Score (BRS) in hospitalized COVID-19 patients.

DESIGN

A multicenter, prospective cohort of 3,886 hospitalized COVID-19 patients across six tertiary hospitals in China between December 1, 2022, and January 31, 2023.

PARTICIPANTS

Patients were objectively diagnosed with COVID-19 by pathogen or antibody detection and followed for 90 days.

MAIN MEASURES

The primary outcomes were major bleeding (MB) and clinically relevant non-major bleeding (CRNMB). We evaluated the IMPROVE BRS predictive performance using hazard ratios (HRs), positive and negative predictive values, the area under the receiver operating characteristic curve (AUC), and calibration.

KEY RESULTS

Among 3,886 hospitalized COVID-19 patients (median age 74, IQR 62-84), 42 MB (1.1%) and 47 CRNMB (1.2%) events occurred within 90 days. The IMPROVE BRS performed well in predicting MB events, with an AUC of 0.84 (95% CI, 0.77-0.91) at 90 days. Calibration plots indicated good calibration. High-risk patients had a significantly higher bleeding risk than low-risk patients, even after adjusting for low molecular weight heparin (LMWH) thromboprophylaxis (MB: adjusted HR 6.63, 95% CI 3.62-12.15; CRNMB: adjusted HR 3.69, 95% CI 2.04-6.71). Subgroup analysis indicated that LMWH thromboprophylaxis significantly increased MB risk in elderly patients with high bleeding risk (14 days: adjusted HR 5.45, 95% CI 1.15-25.94; 30 days: adjusted HR 4.16, 95% CI 1.11-15.53).

CONCLUSIONS

The IMPROVE BRS effectively predicted MB risk in COVID-19 patients and provided valuable guidance for LMWH thromboprophylaxis in elderly patients. Further research is needed to validate its applicability in different populations and refine threshold values for improved predictive accuracy.

Prediction of bleeding in patients being considered for venous thromboembolism prophylaxis

BACKGROUND

Venous thromboembolism (pulmonary embolism and deep vein thrombosis) is an important preventable cause of in-hospital death. Prophylaxis with low doses of anticoagulants reduces the incidence of venous thromboembolism but can also cause bleeding. It is, therefore, important to stratify the risk of bleeding for hospitalized patients when considering pharmacologic prophylaxis. The IMPROVE (international medical prevention registry on venous thromboembolism) and Consensus risk assessment models (RAMs) are the two tools available for such patients. Few studies have evaluated their ability to predict bleeding in a large, unselected cohort of patients. We assessed the ability of the IMPROVE and Consensus bleeding RAMs to predict bleeding within 90 days of hospitalization in a comprehensive analysis encompassing all hospitalized patients, regardless of surgical vs nonsurgical status.

METHODS

We analyzed consecutive first hospital admissions of 1,228,448 unique surgical and nonsurgical patients to 1298 Veterans Affairs facilities nationwide between January 2016 and December 2021. IMPROVE and Consensus scores were generated using data from a repository of their common electronic medical records. We assessed the ability of the two RAMs to predict bleeding within 90 days of admission. We used area under the receiver operating characteristic curves to determine the prediction of bleeding by each RAM.

RESULTS

Of 1,228,448 hospitalized patients, 324,959 (26.5%) were surgical and 903,489 (73.5%) were nonsurgical. Of these patients, 68,372 (5.6%) had a bleeding event within 90 days of admission. The Consensus RAM scores ranged from -5.60 to -1.21 (median, -4.93; interquartile range, -5.60 to -4.93). The IMPROVE RAM scores ranged from 0 to 22 (median, 3.5; interquartile range, 2.5-5). Both showed good calibration, with higher scores associated with higher bleeding rates. The ability of both RAMs to predict 90-day bleeding was low (area under the receiver operating characteristic curve 0.61 for the IMPROVE RAM and 0.59 for the Consensus RAM). The predictive ability was also low at 30 and 60 days for surgical and nonsurgical patients, patients receiving prophylactic, therapeutic, or no anticoagulation, and patients hospitalized for ≥72 hours. Prediction was also low across different bleeding outcomes (ie, any bleeding, gastrointestinal bleeding, nongastrointestinal bleeding, and bleeding or death).

CONCLUSIONS

In this large, unselected, nationwide cohort of surgical and nonsurgical hospital admissions, increasing IMPROVE and Consensus bleeding RAM scores were associated with increasing bleeding rates. However, both RAMs had low ability to predict bleeding at 0 to 90 days after admission. Thus, the currently available RAMs require modification and rigorous reevaluation before they can be applied universally.

Outcome of pharmacological thromboprophylaxis in hospitalized patients with cirrhosis - a systematic review and meta-analysis

BACKGROUND

Portal hypertension in cirrhosis brings about a complex interplay in the risks of bleeding and thrombosis. It is unclear whether hospitalized patients with cirrhosis need pharmacological prophylaxis for venous thromboembolism (VTE), as it may increase the risk of bleeding. We aimed to compare the outcome of hospitalized patients with cirrhosis with and without pharmacological thromboprophylaxis.

METHODS

A comprehensive search of three databases was conducted from inception to August 2022 for studies comparing the outcome of hospitalized patients with cirrhosis with and without pharmacological prophylaxis for VTE. Odds ratios (OR) with 95% confidence intervals (CIs) were calculated for the outcomes of VTE or bleeding.

RESULTS

Overall, 12 studies were included in the final analysis. The pooled incidence of VTE in patients with and without thromboprophylaxis was 1.9% (95% CI: 0.8-2.9) and 1.9% (95% CI: 0.9-2.9), respectively. The odds of VTE were comparable between the groups with OR 1.11 (95% CI: 0.76-1.62). The pooled incidence of bleeding events in patients with and without thromboprophylaxis was 6.7% (95% CI: 3.6-9.8) and 10.4% (95% CI: 6.6-14.1), respectively. There was no significant difference in the odds of overall bleeding (OR 0.68; 95% CI: 0.30-1.52) or major bleeding (OR 1.18; 95% CI: 0.55-2.56) between the groups. There was no significant difference in the relative effects on sensitivity analysis.

CONCLUSION

The present analysis could not demonstrate the benefit of pharmacological thromboprophylaxis in reducing in-hospital VTE in patients with cirrhosis. Future studies are required to assess the role of risk prediction models in hospitalized patients with cirrhosis.