DELAYED ULTRASOUND-GUIDED REGIONAL ANESTHESIA (USGRA) IN HIP FRACTURE PATIENTS
Bibliographic record
Abstract
Background: Delirium develop in 30- 63% of hip fracture patients. Severe pain increases delirium nine fold. A recent meta-analysis showed patients who received Ultrasound-Guided Regional Anesthesia (USGRA) had a lower incidence, severity and duration of delirium. However, no studies describe the time to USGRA are effects of delays on outcomes in hip fracture patients. Objectives: To describe the time to administration of USGRA and any impact on delirium in hip fracture patients. Methodology This is a secondary data analysis of a clinical trial where ED MDs were randomized to training in use of USGRA vs. standard of care opioid analgesics. We reviewed medical charts for all hip fracture patients from January 2014 to October 2016 and collected the estimated time of injury. The primary outcome was the delay from triage to receiving USGRA. Secondary outcomes included ED length of stay, hospital length of stay, delays to surgery and delirium rates. Results: We enrolled 130 patients of which 97 were female (74%). The average age was 79 and 45 received USGRA. The average time to USGRA was 4:39 hours (h), with a range of 1:27 h to 11:11 h. Block time was not recorded. in 9 (20%) - 33 (64%) patients received the block in < 4:39 h, and 2/33 (6.1%) developed delirium. Blocks occurred after 4:39 h in 13 (34%), with delirium in 1/13 (7.7%). χ2=0.035, df=1, p=0.85). The average ED length of stay was 12:17 h, the average time to OR from block was 35:00 hours, and the average hospital length of stay was 8.56 days. 88/130 patients waited > 24 hours before surgery (66.2%). Of the total 130 patients, 17 developed delirium overall. Of the 17, three received USGRA (18%) and fourteen did not (82%, χ2=2.469, df=1, p=0.116). Conclusions: The average time from triage to block of 4:39h represents a significant delay in the provision of analgesia in hip fracture patients, although this was not associated with increased delirium in our small sample. Given that delays to OR of > 24 h occurred in 2/3rd of patients, ED USGRA would ideally be followed up by reassessment and potential top-up blocks by in-patient acute pain services. Future larger multi-center trials should test the impact of USGRA and time to block on delirium
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".