Genetic risk factors for chronic postsurgical pain in children
Bibliographic record
Abstract
Genetic risk factors for chronic postsurgical pain in adults have been established, but little is known whether the same associations exist in children. It is even less clear how much influence single nucleotide polymorphisms can exert on the phenotypic expression of chronic postsurgical pain in children in general. To this effect, a search was made for original articles which met the following criteria: evaluation of postsurgical pain in children with known genetic mutations or, conversely, evaluation of atypical pain trajectories of postsurgical children assessing for possible genetic mutations that may explain the phenotype. All titles and abstracts retrieved were reviewed for suitability for inclusion. The references of the selected articles were also checked for additional relevant papers. To assess the transparency and quality of the genetic studies both STrengthening the REporting of Genetic Association studies scores and Q-Genie scores were applied. Overall, there is a paucity of information regarding the link between genetic mutations and eventual chronic postsurgical pain development although there is some information on acute postoperative pain. Evidence has shown that the contribution of genetic risk factors to chronic postsurgical pain development appears to be minor, with its clinical relevance yet to be described. More advanced techniques in systems biology (proteomics, transcriptomics) suggest promising avenues for investigating the disease.
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 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) | 0.000 | 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".