FC 113UTILITY OF A SINGLE ITCH-RELATED QUESTION AND THE SKINDEX-10 QUESTIONNAIRE FOR ASSESSING PRURITUS AND PREDICTING HEALTH RELATED QUALITY OF LIFE IN HEMODIALYSIS PATIENTS
Bibliographic record
Abstract
Abstract Background and Aims Chronic kidney disease-associated pruritus (CKD-aP) has been linked with comorbid conditions, and poorer mental and physical health-related quality-of-life (HR-QOL) in hemodialysis (HD) patients. The Skindex-10 questionnaire and a single itch-related question from the KDQOL-36 have been used to evaluate the impact of pruritus in HD patients. In this analysis, we investigated the performance of the single question and the Skindex-10 as predictors of HR-QOL in HD patients. Method We analyzed data from 4940 HD patients from 17 countries enrolled during year 2 of phase 5 of the Dialysis Outcomes and Practice Patterns Study (DOPPS, 2013): Belgium, Canada, Germany, the Gulf Cooperation Council (GCC) (Bahrain, Kuwait, Oman, Qatar, Saudi Arabia, United Arab Emirates), Italy, Japan, Russia, Spain, Sweden, Turkey, the UK, and the US. The Skindex-10 scores were calculated as per Mathur et al. (2010): responses to each of the 10 questions (0-6 scale), pertaining to how often patients were bothered by itchy skin in the past week, were summed to create a total summary score (range 0-60, with 0 indicating not at all bothered) and 3 subdomain scores [i.e., itching (disease) and its impact on mood/emotional and social functioning]. The itch-related single question from the KDQOL-36 asked: “During the past 4 weeks, to what extent were you bothered by itchy skin?” with response options including “not at all, somewhat, moderately, very much, extremely”. Itch-related measures were collected concurrently with HR-QOL measures: Physical (PCS) and Mental (MCS) Component Summary scores, derived from the SF-12. We calculated the Spearman correlation coefficient between the Skindex-10 (total score and for each of its 3 domains) and the single question. We used separate linear regression models to evaluate the predictive power of 1) the Skindex-10 score, 2) the single itch question, and 3) both, on PCS and MCS outcomes, based on R-squared values. Results Skindex-10 scores varied across countries; the proportion of patients with a very high Skindex-10 score (≥50) ranged from 12% in the GCC to only 2% in Italy, Russia and Sweden. Across all countries, 55% had a Skindex-10 score=0. For the single pruritus question, 37% answered that they were not at all bothered while 16% were very much or extremely bothered by itchy skin. The correlation between the single question and Skindex-10 was 0.71 overall, 0.72 for the disease domain, 0.62 for the social domain, and 0.70 for the emotional domain. Patient characteristics were similar across categories of both pruritus measures. Regression analyses showed that every 10 points higher in the Skindex-10 score was associated with 1.2 point lower PCS (95% CI: -1.4, -0.9) and 1.5 point lower MCS (95% CI: -1.7, -1.3) scores. Similarly, the single question showed increasingly poorer PCS and MCS scores with a greater degree of being bothered by pruritus: compared with patients not at all bothered by itchy skin, patients who were moderately bothered had 4.8 point lower PCS (-5.7, -3.9) and 4.3 point lower MCS (-5.3, -3.3) scores. The R-squared for PCS was 0.065 when using the single question and only 0.033 when using the Skindex-10 as the predictor. R-squared was also higher for MCS when using the single question (0.056) vs. Skindex-10 (0.052). When including both pruritus measures, the predictive power for PCS did not improve compared to the single question (R2=0.065), while increasing only slightly (R2=0.063) for MCS. Conclusion The single KDQOL-36 question about the extent bothered by itchy skin over the past 4 weeks was highly correlated with the Skindex-10 score and at least as predictive – if not more – of key HR-QOL measures as the Skindex-10. In daily clinical practice, utilizing 1 simple question about the extent patients are bothered by itchy skin can be a feasible and efficient way for routine assessment of pruritus to better identify HD patients with not only CKD-aP but also poorer HR-QoL.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".