Assessment of Vascular Endothelial Dysfunction in Septic Patients Using Brachial Flow-Mediated Dilation: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Background/Objective: Sepsis remains a major cause of morbidity and mortality worldwide, making early risk stratification and prognosis critical. Vascular endothelial dysfunction is a hallmark of sepsis pathogenesis, with evidence suggesting that endothelial injury may occur early, preceding organ failure. Brachial flow-mediated dilation (FMD), a validated noninvasive ultrasound technique measuring endothelium-dependent vasodilation, serves as a surrogate marker of endothelial function, where lower FMD values reflect impaired function. This systematic review and meta-analysis aimed to evaluate the validity and quality of evidence on using FMD to measure vascular endothelial dysfunction in septic patients by comparing FMD (i) between septic patients and non-septic controls and (ii) between sepsis non-survivors and survivors. Methods: PubMed, Embase, Scopus, and Web of Science were searched until November 2024 for clinical studies assessing FMD in septic patients. A random-effects model was used for the meta-analysis, and quality of studies was assessed using the Newcastle–Ottawa Scale. Results: Eight studies were included, and seven underwent quantitative synthesis (385 septic patients, 106 non-survivors and 217 survivors). Compared with non-septic controls, septic patients demonstrated significantly lower FMD (pooled standardized mean difference (SMD) = −2.1617; 95% CI −3.8349 to −0.4885; p = 0.0113; I2 = 98.2939%). Within the sepsis cohort, non-survivors showed significantly attenuated FMD compared to survivors (pooled SMD = −0.7003; 95% CI −1.1133 to −0.2873; p = 0.001; I2 = 60.5593%). Conclusions: FMD shows potential as a surrogate marker of endothelial dysfunction for sepsis risk assessment, as evident by lower FMD in septic patients, particularly non-survivors.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.007 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".