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
Notice bibliographique
Résumé
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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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,004 | 0,008 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,002 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».