Evidence map›Paper›PMID 41924458›Full record

ArticleJournal of emergencies, trauma, and shock

Diagnostic Accuracy of AST and ALT for Detecting Liver Injury in Blunt Abdominal Trauma.

Jurjai Ravipol, Duongthong Patcharee, Wittayachamnankul Borwon

Abstract read
In one paragraph

Article in Journal of emergencies, trauma, and shock. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Jurjai RavipolEmergency Department, Saraburi Hospital, Saraburi, Thailand.
Duongthong PatchareeEmergency Department, Saraburi Hospital, Saraburi, Thailand.
Wittayachamnankul BorwonDepartment of Emergency Medicine, Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Liver injury from blunt abdominal trauma (BAT) is typically diagnosed using computed tomography (CT); however, access to CT imaging is limited in some hospitals. Liver function tests may serve as adjuncts to improve diagnostic accuracy and reduce unnecessary CT scans. This study evaluates whether thresholds of aspartate aminotransferase (AST) and alanine aminotransferase (ALT) can assist in diagnosing liver injury in BAT patients and support clinical decision-making. Methods: A retrospective and observational study was conducted at Saraburi Hospital from 2020 to 2023, including patients over 15 years old with BAT. Exclusion criteria included penetrating injuries, pregnancy, and laboratory testing delayed beyond 24 h after admission. Diagnostic performance of AST and ALT was assessed using receiver operating characteristic (ROC) curves and Youden's J statistic to determine the optimal cutoff values. Sensitivity, specificity, positive predictive value, and negative predictive value were calculated. Results: Of 565 patients, 160 (28.3%) were diagnosed with liver injuries confirmed by CT scan or laparotomy. AST and ALT demonstrated good discriminatory power, with area under the curve (AUC)-ROC values of 0.80 and 0.82. Using cutoff values of AST ≥120 U/L and ALT ≥105 U/L, sensitivity was 88.1% and 82.5%, while specificity was 71.4% and 81.0%. Incorporating these markers into the diagnostic model improved AUC-ROC from 0.762 to 0.891. Conclusions: AST and ALT significantly improved liver injury detection in BAT patients. Incorporating these biomarkers into early clinical assessment may reduce reliance on CT imaging, especially in the resource-limited settings.

Indexed as

Abdominal injuriesbiomarkersliver function testsROC curvesensitivity and specificitytriage

Identifiers

PMID41924458
PMCPMC13037908

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.