Prediction of in-hospital mortality after acute upper gastrointestinal bleeding: cross-validation of several risk scoring systems

Diagnostic value of liver stiffness measurement combined with risk scores for esophagogastric variceal bleeding in patients with hepatitis B cirrhosis

PURPOSE

To assess the predictive value of liver stiffness measurement (LSM) and three bleeding risk scoring systems for esophagogastric varices bleeding (EGVB) in patients with hepatitis B cirrhosis during hospitalization.

METHODS

In this study, 210 patients who had hepatitis B cirrhosis were selected as the subjects. They were categorized into two groups based on whether EGVB occurred during hospitalization: a bleeding group (70 cases) and a non-bleeding group (140 cases). Logistic regression was used to analyze the factors related to the occurrence of EGVB, and the diagnostic performance was evaluated using a receiver operating characteristic (ROC) curve.

RESULTS

Significant differences were observed between the two groups in systolic blood pressure, platelet count, albumin, urea nitrogen, LSM, pre-endoscopic Rockall score (PRS), Glasgow-Blatchford score (GBS), and AIMS65 score (P < 0.05). The correlation analysis showed that LSM had significant positive relationship with PRS, GBS and AIMS65 score. Logistic regression analysis revealed that LSM and GBS score were independent risk factors for EGVB occurrence during hospitalization. ROC curve analysis showed that the combined prediction model of LSM and GBS score had the best prediction performance for EGVB occurrence, with an ROC curve area of 0.811, which was significantly better than the three risk scoring systems (P < 0.05), but similar to the predicted value of LSM (P = 0.335).

CONCLUSIONS

The combination of LSM and GBS score can significantly improve the predictive efficacy of EGVB occurrence in patients with hepatitis B cirrhosis during hospitalization, which has important clinical significance for patients' prognosis.

Lactate level as a predictor of outcomes in patients with acute upper gastrointestinal bleeding: A systematic review and meta‑analysis

There remains no consensus on the prognostic value of lactate in predicting adverse outcomes such as mortality, rebleeding and higher intensive care unit (ICU) admission rates in patients with upper gastrointestinal bleeding (UGIB). The present study aimed to determine the prognostic accuracy of lactate level in predicting adverse clinical outcomes in patients with acute UGIB. Systematic literature search was conducted in PubMed Central, SCOPUS, EMBASE, MEDLINE, Google Scholar and ScienceDirect databases for studies published up to February 2023. Random-effects model was used for the meta-analysis and the results were presented as pooled standardized mean differences or odds ratio (OR) with 95% confidence interval (CIs). A total of 11 studies were included in the present review. Most of the studies had a high risk of bias. Pooled OR were as follows: 1.39 (95% CI: 1.29-1.51; I2=85%) for the prediction of mortality; 1.29 (95% CI: 1.17-1.42; I2=85.9%) for prediction of ICU admission, 1.14 (95% CI: 1.06-1.23; I2=42.4%) for rebleeding and 2.84 (95% CI: 2.14-3.77; I2=8.1%) for the need of packed red blood cell (pRBC) transfusion. Sensitivity and specificity for the mortality prediction were 72% (95% CI: 57-83%) and 75% (95% CI: 61-85%), respectively, with the area under the curve of 0.79 (95% CI: 0.72-0.85). In conclusion, the results showed that lactate level is a moderately accurate early prediction marker of most adverse clinical outcomes such as mortality, rebleeding, ICU admission and the need for pRBC transfusion in acute UGIB patients.

Progress in research of risk prediction models for upper gastrointestinal bleeding

Upper gastrointestinal bleeding is a common gastrointes-tinal condition with a high incidence rate and great harm to the body. This paper reviews the rebleeding, endos-copic intervention, and death risk prediction models for upper gastrointestinal bleeding, including the study population, research methods, related risk factors, and model performance, in order to provide reference for clinicians to conduct risk assessment as soon as possible, formulate effective prevention and management plans, and improve patient survival outcomes.