Venous excess ultrasound score association with acute kidney injury in critically ill patients: a systematic review and meta-analysis of observational studies
Bibliographic record
Abstract
Abstract Background Systemic venous congestion assessed by the venous excess ultrasound score (VExUS), has been associated with acute kidney injury (AKI) in patients undergoing cardiac surgery. However, there is a lack of evidence of this association in the general critically ill patients. Study Design and Methods PubMed, Embase, and Cochrane databases were searched for observational prospective studies that included critically ill patients and analyzed VExUS score on the first day of admission to the ICU. The main outcome was occurrence of AKI. Secondary outcome was all-cause mortality. Statistical analysis was performed using Review Manager 5.4.1. Odds ratios (OR) with 95% confidence interval were pooled using a random-effects model. The Quality in Prognosis Studies (QUIPS) tool was used to assess risk of bias. Publication bias was assessed via funnel plot and heterogeneity was examined with I 2 statistics. Results Our analysis included 1036 patients from nine studies, of whom 17.4% presented venous congestion according to VExUS definition. In critically ill patients presenting with venous congestion (VExUS score ≥ 2), the incidence of AKI was significantly higher as compared with those without congestion (OR 2.63, 95% CI 1.06–6.54; p = 0.04; I 2 = 74%). The association was notably stronger in cardiac surgery patients (OR 3.86, 95% CI 2.32–6.42; p < 0.00001; i 2 = 0%). There was no significant association between venous congestion and all-cause mortality (OR 1.25, 95% CI 0.71–2.19; p = 0.44; i 2 = 8%). Conclusions These findings suggest that VExUS score may correlate with an elevation in the incidence AKI in critically ill patients, with a more pronounced effect observed within the subgroup of patients undergoing cardiac surgery. There was no statistically significant association between VExUS score and all-cause mortality. Clinical Trial Registration : PROSPERO under protocol number CRD535513.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.035 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.024 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".