Canadian Internal Medicine Ultrasound (CIMUS) consensus statement: recommendations for mandatory ultrasound competencies for ultrasound-guided thoracentesis, paracentesis, and central venous catheterization
Bibliographic record
Abstract
OBJECTIVES: To develop a Canadian Internal Medicine Ultrasound (CIMUS) consensus statement on recommended mandatory point-of-care ultrasound (POCUS) competencies for ultrasound-guided thoracentesis, paracentesis, and central venous catheterizations (CVC) for internal medicine physicians. METHODS: The 2022 CIMUS group consists of 27 voting members, with representations from all 17 Canadian academic institutions across 8 provinces. Members voted in 3 rounds on 46 procedural competencies as "mandatory, must include", "optional, could include" or "superfluous, do not include". These 46 competencies included 6 general competencies that apply to all POCUS-guided procedures, 11 competencies for thoracentesis, 10 competencies for paracentesis, and 19 competencies for CVC. RESULTS: In the first round, members reached consensus on 27 competencies (5 general, 6 thoracentesis, 8 paracentesis, 8 CVC). In the second round, 10 competencies (1 general, 2 thoracentesis, 1 paracentesis, 6 CVC) reached consensus. In the third round, 2 additional competencies (1 paracentesis, 1 CVC) reached consensus for being mandatory and 3 as optional (1 thoracentesis and 2 CVC). Overall, a total of 28 competencies reached consensus as mandatory, 3 as optional, while 11 competencies reached consensus as superfluous. Four competencies did not reach consensus for either inclusion or exclusion. CONCLUSIONS: The CIMUS group recommends 28 competencies be considered mandatory and 3 as optional for internal medicine physicians performing POCUS guided thoracentesis, paracentesis, and CVC placement. National curriculum development and implementation efforts should include training these mandatory competencies.
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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 | 0.042 | 0.075 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.008 | 0.005 |
| Science and technology studies | 0.009 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.008 | 0.005 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.010 | 0.003 |
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".