ReviewCureus2026
Current Evidence on the Use of Biomarkers for the Diagnosis of Acute Mesenteric Ischemia: A Narrative Review.
Review in Cureus, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
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.
Who cites it
1 citing paper in PubMed.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Acute mesenteric ischemia (AMI) is a life-threatening vascular emergency associated with high morbidity and mortality, largely because diagnosis is frequently delayed by non-specific clinical manifestations. Although computed tomography angiography (CTA) remains the diagnostic gold standard, considerable research has focused on identifying laboratory biomarkers that may facilitate earlier recognition and improve clinical decision-making. This narrative review summarizes the current evidence regarding routinely available and emerging laboratory biomarkers for the diagnosis of AMI. A comprehensive literature search was performed using PubMed/Medical Literature Analysis and Retrieval System Online (MEDLINE), Scopus, Web of Science, and the Cochrane Library, supplemented by manual review of reference lists. Routine laboratory markers, including leukocyte count, C-reactive protein (CRP), serum lactate, metabolic acidosis, D-dimer, amylase, phosphate, and procalcitonin (PCT), were evaluated alongside investigational biomarkers, such as intestinal fatty acid-binding protein (I-FABP), D-lactate, citrulline, ischemia-modified albumin (IMA), alpha-glutathione S-transferase (α-GST), interleukin-6 (IL-6), and cell-count-derived inflammatory indices. Current evidence demonstrates that no single laboratory biomarker possesses sufficient sensitivity and specificity to independently confirm or exclude AMI. Serum lactate and metabolic acidosis primarily reflect advanced intestinal injury and systemic hypoperfusion, rather than early ischemia, whereas D-dimer offers relatively high sensitivity but poor specificity. Enterocyte-specific biomarkers, particularly I-FABP, remain biologically attractive because they may detect early mucosal injury; however, inconsistent diagnostic performance, limited assay availability, and methodological heterogeneity have prevented routine clinical implementation. Emerging multimarker strategies integrating indicators of enterocyte injury, coagulation activation, inflammation, and tissue hypoperfusion may improve diagnostic accuracy but require prospective validation. At present, laboratory investigations should be regarded as complementary tools that increase clinical suspicion, assist with risk stratification, and reinforce the need for urgent CTA. They should never delay definitive imaging or revascularization when AMI is suspected. Further high-quality prospective studies are required to establish standardized biomarker panels capable of facilitating earlier diagnosis and improving patient outcomes.
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Registered trials
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.