Quality‐of‐life of people with keloids and its correlation with clinical severity and demographic profiles
Bibliographic record
Abstract
Although the impairment of quality of life (QoL) in individuals with keloids is profound, it has neither been well quantified nor correlated with severity in people with skin of colour. This cross-sectional, questionnaire-based study comprised 110 patients with keloid(s). A physician measured the severity of keloids using the Vancouver Scar scale and impairment of QoL using the patient-filled Hindi version of Dermatology Life Quality Index questionnaire. The relationship among QoL and severity score as well as with components of demographic data was analysed using SPSS. Our study found the severity of keloid(s) to be moderately but significantly correlated with the QoL of its sufferers. Individuals with multiple keloids were found to be significantly younger than those with solitary ones. Itching, pain, along with restricted mobility significantly impacted the QoL as well as severity of keloids. Individuals who had undergone prior treatment were found to have a worse QoL than the treatment naive. Recurrence was found to be associated with lower scar severity, multiple keloids, and younger age. Increasing age, though associated with greater scar severity, lacked any relationship with the QoL. Our study also found that individuals with bigger keloids sought treatment earlier and more often. Hyperpigmented keloid(s), more common in individuals with skin of colour, were associated with a significantly worse QoL and a higher scar severity.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| 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".