Pericapsular nerve group (PENG) block for hip fracture in the emergency department: a case series
Bibliographic record
Abstract
Guidelines for the management of hip fractures recommend timely identification, analgesia and optimisation, in order to facilitate prompt surgical repair. In achieving these aims, multidisciplinary care is essential. In this case series, we present five patients who received bedside pericapsular nerve group (PENG) blocks by emergency physicians in collaboration with the anaesthesia team for pain management following hip fracture. The PENG block is a novel motor- and opioid-sparing technique, which offers long-lasting analgesia and requires less volume than other blocks. In all of the cases in this series, the blocks were performed successfully in a short period of time, without complication. All patients reported a clinically important reduction in pain scores. Patients with hip fracture are often medically complex, and while early surgery is not always possible, pain management should be addressed from an early point in their hospital admission. Multidisciplinary input into peri-operative pathways can enhance the provision of analgesia in the emergency department, by allowing anaesthetists and emergency physicians to work together for the benefit of these often-frail patients.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".