Classification and scoring systems used in diagnostics, prognosis and the treatment of proximal digestive tract bleeding

Benedeto-Stojanov, Daniela; Nagorni, Aleksandar; Bjelaković, Goran; Petrović, Gordana; Stojanov, Dragan; Djenic, Nebojsa

doi:10.2298/vsp1110872b

Cited by 2 publications

(1 citation statement)

References 35 publications

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“…Risk scoring systems, which take into consideration the specific combination of admission clinical, biochemical, and endoscopic features, are of great importance as risk adjusters for prognostication and risk assessment of the poor outcome after AUGIB. [18][19][20][21][22] The clinical use of risk scoring systems may lead to improved patient risk stratification, triage, and management, thus providing more accurate guidance for emergency physicians for making final decisions (hospital admission, intensive care unit admission, discharge from the emergency department). Unfortunately, no specific scoring system has been adopted in routine clinical practice for patients presenting to the emergency department.…”

Section: Discussionmentioning

confidence: 99%

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

2022

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Objective We aimed to identify the clinical, biochemical, and endoscopic features associated with in-hospital mortality after acute upper gastrointestinal bleeding (AUGIB), focusing on cross-validation of the Glasgow-Blatchford score (GBS), full Rockall score (RS), and Cedars-Sinai Medical Center Predictive Index (CSMCPI) scoring systems. Methods Our prospective cross-sectional study included 156 patients with AUGIB. Several statistical approaches were used to assess the predictive accuracy of the scoring systems. Results All three scoring systems were able to accurately predict in-hospital mortality (area under the receiver operating characteristic curve [AUC] > 0.9); however, the multiple logistic model separated the presence of hemodynamic instability (state of shock) and the CSMCPI as the only significant predictive risk factors. In compliance with the overall results, the CSMCPI was consistently found to be superior to the other two systems (highest AUC, highest sensitivity and specificity, highest positive and negative predictive values, highest positive likelihood ratio, lowest negative likelihood ratio, and 1-unit increase in CSMCPI associated with 6.3 times higher odds of mortality), outperforming the GBS and full RS. Conclusions We suggest consideration of the CSMCPI as a readily available and reliable tool for accurately predicting in-hospital mortality after AUGIB, thus providing an essential backbone in clinical decision-making.

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Section: Discussionmentioning

confidence: 99%