A survey of emergency medicine and orthopaedic physicians’ knowledge, attitude, and practice towards the use of peripheral nerve blocks
Bibliographic record
Abstract
INTRODUCTION: Peripheral nerve blocks (also known as regional anaesthesia) are currently used by many anaesthesiologists and emergency physicians for perioperative and procedural pain management. METHODS: This is a cross sectional descriptive study conducted to evaluate knowledge, attitudes, and current practice towards use of peripheral nerve blocks for lower extremity injuries at Black Lion Hospital, a tertiary trauma centre in Addis Ababa. RESULTS: A standardised survey was conducted with 64 participants working in emergency medicine [30/64 (46.9%)] and orthopaedics [34/64 (53.1%)]. Twenty-three of 64 (35.9%) respondents had received formal training. Knowledge was acquired from didactic/workshop format for 15/23 (65.2%), followed by peer training 6/23 (39.1%). The majority, 62/64 (96.9%), believed that knowledge of general anatomy and nerve blocks are very important. Thirty-one of 64 (48%) of the respondents did not routinely perform peripheral nerve blocks. A majority, 27/31 (87.1%) stated they lacked the required skills. Ultrasound guidance of the femoral nerve 16/33 (48.5%) was the most commonly performed peripheral nerve block, followed by ankle block using anatomic landmarks 15/33 (45.5%). Almost all (15/16) ultrasound-guided nerve blocks were done by emergency medicine providers, while all anatomic land mark guided blocks were done by orthopaedic teams. A majority of the respondents (93.8%) (n = 60) were optimistic that their practice on peripheral nerve blocks would increase in future. A highly significant association was found between previous training on peripheral nerve blocks and the number of peripheral nerve blocks performed in a month; p value - 0.006. DISCUSSION: This study indicates peripheral nerve blocks are likely underutilised due to lack of training. There was a positive attitude towards peripheral nerve blocks but gaps on knowledge and practice.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".