A Latin American consensus meeting on the essentials of mixed pain
Bibliographic record
Abstract
OBJECTIVES: The term "mixed pain" has been established when a mixture of different pain components (e.g. nociceptive, neuropathic, and nociplastic) are present. It has gained more and more acceptance amongst pain experts worldwide, but many questions around the concept of mixed pain are still unsolved. The sensation of pain is very personal. Cultural, social, personal experiences, idiomatic, and taxonomic differences should be taken into account during pain assessment. Therefore, a Latin American consensus committee was formed to further elaborate the essentials of mixed pain, focusing on the specific characteristics of the Latin American population. METHODS: The current approach was based on a systematic literature search and review carried out in Medline. Eight topics about the definition, diagnosis, and treatment of mixed pain were discussed and voted for by a Latin American consensus committee and recommendations were expressed. RESULTS: At the end of the meeting a total of 14 voting sheets were collected. The full consensus was obtained for 21 of 25 recommendations (15 strong agreement and 6 unanimous agreement) formulated for the above described 8 topics (7 of the 8 topics had for all questions at least a strong agreement - 1 topic had no agreement for all 4 questions). CONCLUSION: In a subject as complex as mixed pain, a consensus has been reached among Latin American specialists on points related to the definition and essence of this pain, its diagnosis and treatment. Recommendations for diagnosis and treatment of mixed pain in Latin America were raised.
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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 | 0.013 | 0.030 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".