Continuous Interscalene Block for Open Shoulder Surgery
Bibliographic record
Abstract
To the Editor: Hofmann-Kiefer et al.1 recently confirmed that continuous patient controlled interscalene block (PCISB) can reduce pain after open shoulder surgery compared with IV patient controlled analgesia. In contrast, however, to previous work by Ilfeld2 and Capdevila,3 functional ability was not improved. Admittedly, the types of shoulder surgery and outcome measures were different between the studies, but we question whether the quality of the block in Hofmann-Kiefer’s study contributed to their equivocal result. Despite reporting a zero incidence of incomplete blocks preoperatively, the mean dose of intraoperative fentanyl required in the PCISB group was curiously large (260 μg). In addition, a significant proportion of patients in the PCISB group were not analyzed either because of catheter dislocation or removal, or postoperative dyspnea. Combined with the fact that certain investigators were unblinded, the lack of “intention to treat” analysis may have skewed results in favor of the PCISB group. The rate of catheter dislodgement reported in Hofmann-Kiefer’s study (approximately 20%) is unacceptably high and could likely have been reduced by tunneling4 or using glue.5 Further investigation is required to confirm whether or not PCISB can confer early functional improvement and, importantly, whether this actually translates into long-term benefit. Alan J. R. Macfarlane, BSc, MB ChB, MRCP, FRCA Richard Brull, MD, FRCPC Department of Anesthesia and Pain Management Toronto Western Hospital University of Toronto Toronto, Canada [email protected]
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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 | 0.015 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.010 | 0.014 |
| Insufficient payload (model declined to judge) | 0.004 | 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".