Emergency Physician Performed Ultrasound-Guided Abdominal Paracentesis: A Retrospective Analysis
Bibliographic record
Abstract
BACKGROUND: Emergency physicians commonly perform ultrasound-assisted abdominal paracentesis, using point of care ultrasound (POCUS) to identify ascites and select a site for needle insertion. However, ultrasound-guided paracentesis has the benefit of real-time needle visualization during the entire procedure. Our objective was to characterize the performance of emergency physician-performed ultrasound-guided paracentesis using POCUS, their ability to achieve good in-plane needle visualization, and factors associated with procedural success. METHODS: A POCUS database was retrospectively reviewed for examinations where abdominal paracentesis was performed by an emergency physician at two academic urban emergency departments over a six-year period. Medical records were reviewed for demographics, presenting history, complications, and hospital course. Descriptive statistics were used to summarize the data. RESULTS: 131 patients were included in the final analysis. The success rate for ultrasound-guided paracentesis was 97.7% (84/86 [95% CI: 92-100%]) compared to 95.6% (43/45 [95% CI: 85-99%]) for ultrasound-assisted paracentesis (p=0.503). 58% (50/86) demonstrated good in-plane needle visualization; 17% (15/86) had partial or out-of-plane visualization; and 24% (21/86) did not demonstrate needle visibility on their saved POCUS images. All four procedural failures were performed by first- or second-year residents using a curvilinear transducer, while all procedures using a linear transducer were successful. The most common complications were ascites leak, infection at the site, and minor bleeding. CONCLUSIONS: Emergency physicians with training in real-time needle guidance with ultrasound were able to use POCUS to perform ultrasound-guided paracentesis in the emergency department with a high success rate and no fatal complications. Based on our experience, we recommend performing ultrasound-guided paracentesis using a linear transducer, with attention to identifying vessels near the procedure site and maintaining sterile 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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".