Eligibility criteria in paravertebral block meta‐analysis
Bibliographic record
Abstract
Heesen et al. reported a meta-analysis of trials reporting the effect of pre-operative paravertebral block (PVB) on the risk of developing persistent post-surgical pain (PPP) following breast cancer surgery 1. We congratulate the authors on their effort to answer an important clinical and research question, and we applaud their use of sequential analysis. However, we have identified some serious methodological concerns about the eligibility criteria, which are likely to have influenced their findings, and which differ from the results of earlier meta-analyses 2, 3. Firstly, the meta-analysis included only randomised controlled trials comparing the effect of PVB to sham or no block on PPP. However, Ilfeld et al. 4 compared single-shot and continuous PVB, and reported that ‘all patients received a single injection of long-acting local anesthetic (15 ml of ropivacaine 0.5%, with epinephrine 5 μg.ml−1) administered through the catheter’ before randomisation to an infusion of local anesthetic or saline. This breaches Heesen et al.'s inclusion criteria. Heesen et al. considered single-shot and continuous PVB as equally important in preventing PPP, combining them into one group when any trial included both interventions. The Ilfled trial does not include a control group and should have been excluded from the analysis. Secondly, the trial by Chui et al. 5, who compared PVB with local infiltration analgesia, also lacked a control group, local infiltration itself being an effective intervention in preventing chronic pain following breast cancer surgery 6-8, and so should have also been excluded from the meta-analysis. These exclusions may affect the validity of Heesen et al.'s findings, particularly as the number of trials pooled for certain outcomes (e.g. PPP at 1 year) would be fewer than three, mitigating any justification for pooling the data. Could we invite the authors to re-analyse and report their results having excluded these ineligible trials?
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How this classification was reachedexpand
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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 teacher head, 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".