POCUS in perioperative medicine: a North American perspective
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Ultrasound (US) performed at the point of care has found fertile ground in perioperative medicine. In the hands of anesthesiologists, transesophageal echocardiography (TEE) has become established as a powerful diagnostic and monitoring tool in the perioperative care of cardiac and non-cardiac patients. A number of point-of-care US (POCUS) applications are relevant to perioperative care, including airway, cardiac, lung and gastric US. Although guidelines exist to define the scope of practice for basic and advanced TEE, there remains a lack of such guidelines for perioperative point-of-care ultrasound (POCUS), despite a number of recent calls for action in the academic anesthesia community. POCUS training has been integrated into anesthesia residency curricula in Canada and the United States of America (USA). However, a nation-wide curriculum is still lacking. Many limitations to the development of perioperative POCUS curricula exist, including the need to define the scope of practice and design integrated longitudinal learning approaches. The main anesthesiologist societies in both the USA and Canada are promoting the development of guidelines and have introduced POCUS courses into their national conferences. Although bedside US imaging has been integrated into the curricula of many medical schools in North America, the need for specific national guidelines for the training and practice of POCUS in the perioperative setting by anesthesiologists is crucial to the further development of POCUS in perioperative medicine.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.040 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 it