P147 Lupus damage index revision: item generation and reduction phase
Notice bibliographique
Résumé
Abstract Background/Aims The Systemic Lupus International Collaborating Clinics (SLICC), the American College of Rheumatology (ACR) and the Lupus Foundation of America (LFA) collaboratively embarked on a project to develop a revised Systemic Lupus Erythematosus (SLE) Damage Index (SDI), employing a structured methodology including five key phases: updating the construct of damage(I), item generation(II), item reduction(III), item weighting and threshold determination(IV), and the assessment of validation and reliability(V). This initiative aims to address limitations of the current SDI, notably incomplete items, restricted applicability in paediatric patients, and outdated item definitions, through a data- and expert/patient-driven approach. Methods Item generation began with a comprehensive literature review and an initial Delphi round. Item reduction involved conducting two additional Delphi rounds, where items with a median score of ≤ 4 out of 9 were excluded. Following this, a 14-member steering committee assessed the remaining items and removed those that did not reflect the damage construct, were excessively rare, or were not feasible to assess. The expert organ domain groups then refined the remaining items, suggesting severity gradations for relevant items. Results A cohort of 146 individuals from 35 countries, broadly reflecting the lupus research and patient community, was established. Our literature review identified 4 (1.8%) unique items, while 103 (46.8%) were unique to the Delphi process, and 113 (51.4%) items overlapped both processes. After the second Delphi round, Delphi participants suggested an additional 6 unique items. As a result, we had 226 items for review by our third Delphi round where 36 items scoring ≤4 out of 9 were removed. Our steering committee removed 126 items due to redundancy, limited feasibility for assessment, overlap, inadequate reflection of damage construct, or association with lupus disease activity, and rarity. This included all items in a proposed ‘reproduction and pregnancy’ domain reducing the number of organ domains to 13. Subsequently, the expert organ domain groups reviewed the candidate items, leading to a final total of 38 items. Eleven items from the previous SDI, including chronic peritonitis, muscle atrophy, and osteomyelitis, were removed. Additionally, several new items were proposed, such as growth failure/reduced final height and adrenal insufficiency. Moreover, 12 items had proposed gradings of severity, including cardiomyopathy and chronic kidney disease. Conclusion The item generation and reduction phases resulted in 38 candidate items to be taken forward to the next stages. Grading damage items is possible for 32% of proposed items in a new revised damage index. This offers a more detailed and clinically relevant assessment of organ damage in SLE patients. It reflects current evidence based medical practice and is likely to improve sensitivity of the index in SLE populations. Further validation in cohorts and consideration of weighting of grades across clinical organ systems is now underway. Disclosure B. Kundakci: None. M.R.W. Barber: None. A.E. Clarke: None. S.R. Johnson: None. I. Bruce: None.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
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 | 0,080 | 0,173 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,003 |
| Bibliométrie | 0,005 | 0,005 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,002 | 0,003 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,017 | 0,005 |
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 ».