The Contribution of Malodour in Quality of Life of Patients With Hidradenitis Suppurativa
Bibliographic record
Abstract
BACKGROUND: Malodourous discharge in patients with hidradenitis suppurativa (HS) has a strong psychosocial impact and is often reported as a source of embarrassment, low self-esteem, social stigma, and barriers to interpersonal relationships. Malodour is a maker of bacterial colonization, and its role in HS is understudied. OBJECTIVES: The aim of this study is to assess the relationship between severity of malodourous discharge and quality-of-life impairment in patients with HS. METHODS: This is a cross-sectional study of 51 patients recruited from the Women's College Hospital and the York Dermatology Centre. Quality of life was assessed using both the Dermatology Life Quality Index (DLQI) and the Skindex-29 instruments. RESULTS: = 0.17, F = 2.63, P = .064). There was no difference in mean DLQI scores for the low- vs high-odour groups, but patients with high odour had a greater quality of life impairment as measured by the Skindex tool ( t = -4.19, df = 43, P < .0001, mean difference = -18.87). CONCLUSION: Malodour is a common symptom that significantly impairs quality of life in patients with HS. The fact that this effect is captured in Skindex and not the DLQI may be attributed to the nonspecificity of the DLQI in terms of unique disease characteristics. It is important to address odour in the management of patients with HS.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".