Chronic Persistent Pain After Severe Burns: A Survey of 358 Burn Survivors
Bibliographic record
Abstract
OBJECTIVE: To determine the prevalence, characteristics, and effects of chronic persistent pain on burn survivors. DESIGN: Mail survey. SETTING: Respondents' homes. PATIENTS: All members of the Phoenix Society for Burn Survivors. INTERVENTIONS: None. OUTCOME MEASURES: Twenty-three questions on the prevalence of pain and its characteristics, including the short form of the McGill-Melzack Pain Questionnaire. RESULTS: Of 1,500 members who received the survey, 358 (24%) responded. Respondents had burns covering an average of 59% of their bodies. Time between the injury and the survey averaged 12 years. On the survey, 52% of respondents reported ongoing burn-related pain, and 46% were able to characterize their pain with one or more of 15 characteristics. Two-thirds (66%) reported that pain interfered with their rehabilitation, and 55% reported that pain interfered with their daily lives. Asked "what makes the pain worse now?," the most frequent reply (15%) was "the weather" (including "hot" or "cold"). Various physical activities (e.g., walking, bicycling) were also mentioned, along with nerve regrowth, contractures, remembering the accident, and depression. "Things that make your pain better now" included "nothing," a variety of over-the-counter analgesics, "rest,""exercise,""yoga,""acupuncture,""family and friends," and "God." In coping with their pain, most respondents found family the most helpful, although nurse(s) received almost as high a rating. CONCLUSIONS: Pain associated with burn trauma continues to be of considerable significance in the lives of burn victims long after the initial injury and hospitalization. Little research has been done on this population.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".