Reply
Bibliographic record
Abstract
TO THE EDITOR: We thank Soyama et al.1 for their comments on our study that examined the incidence and predictors of acute and chronic postsurgical pain after living liver donation.2 We agree that these issues as well as other scar‐related complaints, such as numbness and sensory abnormalities, that arise after living liver donation merit further study. As to date they have received little attention in the literature. Paresthesias, numbness, and other sensory abnormalities are common complications of other major surgeries. In particular, sensory abnormalities have been reported to be more prevalent than moderate to severe chronic pain following thoracotomy,3 radial artery and saphenous vein graft harvest for coronary artery bypass surgery,4 and hernia repair.5 The prevalence and impact of these issues after living liver donation remain poorly understood. We hypothesize that there are important associations between the nature and prevalence of pain and other scar‐related complaints, donor quality of life, and satisfaction with the donation process. It is important to understand these issues so that donors can be fully informed before making a decision to donate. Further information will soon be forthcoming from the Adult‐to‐Adult Living Donor Liver Transplantation Cohort Study, a 9‐center consortium funded by the National Institutes of Health, which is examining the prevalence of somatic complaints, including persistent numbness, tension, and pain around the surgical site, as well as risk and protective factors for these poor outcomes. Moving forward, our work demonstrates that it is critical to follow donors closely from a pain perspective.2 This includes identifying patients with increased acute hospital needs, as well as creating a consistent recourse for the substantial proportion of patients who continue to struggle after discharge, with a focus on modifying their long‐term trajectory.6 At the University Health Network, we have developed a unique Transitional Pain Service to support this effort.7
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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 | 0.004 | 0.048 |
| 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 | 0.003 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.018 | 0.027 |
| Insufficient payload (model declined to judge) | 0.028 | 0.022 |
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".