Physician perspectives on complementary and alternative medicine in hidradenitis suppurativa
Bibliographic record
Abstract
Hidradenitis suppurativa (HS) is a chronic and often debilitating inflammatory condition characterized by frequent nodules, abscesses, sinus tracts, and scars impacting the intertriginous areas. Many patients with HS often report limited treatment success and symptom coverage with conventional therapies. Recent studies have reported the widespread use of complementary and alternative medicine (CAM) among patients with HS. In this study, our aim was to examine current physician practice patterns, opinions, and comfort with recommending CAM. Our results indicate that provider comfort and opinions on CAM varied based on the provider's experiences, demographics, and the CAM modality itself. Overall, nearly two-thirds (n = 30, 61.2%) of respondents agreed that CAM and conventional medicine were more effective together than either alone. Meanwhile, 44.9% (n = 22) of respondents routinely recommend CAM while 64.6% (n = 31) of respondents reported that they are routinely asked about CAM. The majority (n = 41, 83.7%) of respondents indicated a lack of scientific evidence in the medical literature as a barrier to recommending CAM along with efficacy concerns (n = 34, 69.4%) and ability to recommend reputable CAM products (n = 32, 65.3%) and practitioners (n = 32, 65.3%). Future investigations are warranted to establish a better understanding of the efficacy and benefit of CAM methods in conjunction with conventional methods.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".