Application of Antithrombotic Drugs in Different Age-Group Patients with Upper Gastrointestinal Bleeding

Objective

This study aimed at exploring the safety and timing of antithrombotic drugs in different age-group patients with UGIB.

Methods

An observational study retrospectively based on the single-center database with 713 patients with UGIB.

Result

Among the 713 patients, 62.13% were elderly patients (aged > 60 years) and the mortality was 2.9%. In elderly patients with UGIB, we found that previous medication history, resumption of medication, and time of resumption did not affect the in-hospital mortality. The resumption of anticoagulants increased the risk of rebleeding. The independent risk factors of mortality were CHF, cirrhosis, creatine kinase, and albumin. The independent risk factors of rebleeding were the application of anticoagulants during hospitalization, variceal bleeding, black stool, red blood cells (lab), platelets (lab), and heart rate.

Conclusions

In UGIB patients, a history of antiplatelet or antithrombotic drugs and the use of antiplatelet drugs after UGIB did not affect the patient's prognosis. In elderly UGIB patients, although antithrombotic drugs did not increase the risk of death, the increased risk of rebleeding after resumption of use deserved careful treatment. It was safe to recover anticoagulant drugs as soon as possible in young UGIB patients.

Big data and variceal rebleeding prediction in cirrhosis patients

Big data has convincing merits in developing risk stratification strategies for diseases. The 6 “V”s of big data, namely, volume, velocity, variety, veracity, value, and variability, have shown promise for real-world scenarios. Big data can be applied to analyze health data and advance research in preclinical biology, medicine, and especially disease initiation, development, and control. A study design comprises data selection, inclusion and exclusion criteria, standard confirmation and cohort establishment, follow-up strategy, and events of interest. The development and efficiency verification of a prognosis model consists of deciding the data source, taking previous models as references while selecting candidate predictors, assessing model performance, choosing appropriate statistical methods, and model optimization. The model should be able to inform disease development and outcomes, such as predicting variceal rebleeding in patients with cirrhosis. Our work has merits beyond those of other colleagues with respect to cirrhosis patient screening and data source regarding variceal bleeding.

MAP(ASH): A new scoring system for the prediction of intervention and mortality in upper gastrointestinal bleeding

BACKGROUND AND AIM

Risk stratification for upper gastrointestinal bleeding (UGIB) is recommended. However, scoring system accuracy is suboptimal, and score calculation can be complex. Our aim was to develop a new score, the MAP(ASH) score, with information available in the emergency room and to validate it.

METHODS

The score was built from a prospective database of patients with UGIB and validated in an international database of 3012 patients from six hospitals. Outcomes were 30-day mortality, endoscopic intervention, any intervention (red blood transfusion, endoscopic treatment, interventional radiology, surgery, or death), and rebleeding. Accuracy to predict outcomes was assessed by the area under the receiver operating characteristic curve (AUROC).

RESULTS

Five hundred forty-seven patients were included in the development cohort. Impaired mental status, albumin < 2.5 g/dL, pulse > 100, American Society of Anesthesiologists score > 2, systolic blood pressure < 90 mmHg, and hemoglobin < 10 g/dL were included in the score. The model had a good predictive accuracy for intervention (AUROC = 0.83; 95% confidence interval [CI]: 0.79-0.88) and fair for mortality (AUROC = 0.74; 95% CI: 0.68-0.81). Regarding endoscopic intervention, AUROC was 0.61 (95% CI: 0.56-0.66) in the original cohort and 0.69 (95% CI: 0.66-0.71) in the validation cohort, showing a poor performance, similar to other scores. For rebleeding, the MAP(ASH) (AUROC 0.73; 95% CI: 0.69-0.77) was similar to Glasgow Blatchford score (AUROC = 0.72; 95% CI: 0.67-0.76) but superior to AIMS65 (AUROC = 0.64; 95% CI: 0.59-0.68).

CONCLUSION

MAP(ASH) is a simple pre-endoscopy risk score to predict intervention after UGIB, with fair discrimination at predicting mortality. Because of its applicability, it could be an option in clinical practice.