The Impact of Point-of-Care Ultrasound-Guided Resuscitation on Clinical Outcomes in Patients With Shock: A Systematic Review and Meta-Analysis*
Bibliographic record
Abstract
OBJECTIVE: To determine the impact of point-of-care ultrasound (POCUS)-guided resuscitation on clinical outcomes in adult patients with shock. DATA SOURCE: We searched MEDLINE, Embase, and unpublished sources from inception to December 2023. STUDY SELECTION: We included randomized controlled trials (RCTs) that examined the use of POCUS to guide resuscitation in patients with shock. DATA EXTRACTION: We collected data regarding study and patient characteristics, POCUS protocol, control group interventions, and outcomes. DATA SYNTHESIS: We identified 18 eligible RCTs. POCUS slightly influences physicians' plans for IV fluid (IVF) and vasoactive medication prescription (moderate certainty), but results in little to no changes in the administration of IVF (low to high certainty) or inotropes (high certainty). POCUS may result in no change in the number of CT scans performed (low certainty) but probably reduces the number of diagnostic echocardiograms performed (moderate certainty). POCUS-guided resuscitation probably reduces 28-day mortality (relative risk [RR] 0.88; 95% CI, 0.78-0.99), the duration of vasoactive medication (mean difference -0.73 d; 95% CI, -1.16 to -0.30), and the need for renal replacement therapy (RRT) (RR 0.80; 95% CI, 0.63-1.02) (low to moderate certainty evidence), and lactate clearance (high certainty evidence). POCUS-guided resuscitation may results in little to no difference in ICU or hospital admissions, ICU and hospital length of stay, and the need for mechanical ventilation (MV) (low to moderate certainty evidence). There is an uncertain effect on the risk of acute kidney injury and the duration of MV or RRT (very low certainty evidence). CONCLUSIONS: POCUS-guided resuscitation in shock may yield important patient and health system benefits. Due to lack of sufficient evidence, we were unable to explore how the thresholds of operator competency, frequency, and timing of POCUS scans impact patient outcomes.
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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 | 0.016 | 0.050 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.020 | 0.036 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 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".