Ultrasound guidance compared to anatomic landmark approach for thoracentesis: A systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: Although thoracentesis has traditionally been performed with anatomic landmarking, ultrasound guidance is increasingly used. The primary objective of this systematic review and meta-analysis is to determine the difference in success rates between ultrasound guidance versus anatomic landmark technique. Secondary outcomes include assessing the effects of ultrasound guidance on complication rates. METHODS: MEDLINE, Embase, CINAHL, Scopus, Cochrane Central Register of Controlled Trials, LILACS, Web of Science Core Collection, Google Scholar, and the grey literature were searched for prospective randomized trials or cluster randomized trials comparing the success rate of ultrasound-guided to anatomic landmark thoracentesis in patients of all ages from inception to February 2024. Two investigators independently completed study screening, data extraction, and quality evaluations using the Cochrane Risk of Bias and GRADE tools. Outcomes were analyzed using random effects meta-analysis using generalized linear mixed effects models and corresponding 95 % confidence intervals (CI). RESULTS: Three papers met inclusion criteria (n = 417 patients). Overall, ultrasound-guided thoracentesis was successful in 195 of 202 patients (96.5 %), and anatomic landmark thoracentesis was successful in 189 of 215 patients (87.9 %). Ultrasound-guidance trended towards higher success rates (OR 3.99, 95 % CI 0.60-26.50) and lower complication rates (OR 0.18, 95 % CI 0.01-3.07). Only two of the three studies evaluated post-procedure pneumothorax: in sum, 1/99 of the ultrasound group versus 20/113 in the anatomic landmark group were complicated by pneumothorax. CONCLUSIONS: This systematic review and meta-analysis of randomized trials found that ultrasound guidance for thoracentesis trended towards increased success and lower complication rates compared to anatomic landmark technique.
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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 | 0.005 | 0.017 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.025 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".