Prenatal thoraco-amniotic chest drain insertion to manage a case of fetal hydrops secondary to <i>FOXC2</i>
Dossier post-publication
Source : Retraction Watch, jointe par DOI. OpenAlex consigne la rétractation dans is_retracted, un booléen sur un espace d'états à au moins quatre valeurs ; il ne peut donc exprimer ni une expression de préoccupation, ni une correction, ni un rétablissement, et les rapporte comme false, ce qui se lit comme « rien à signaler ».
Notice bibliographique
Résumé
Background Adherence to therapy is critical to achieve and sustain management targets and optimal outcomes in treating patients (pts) with immune-mediated inflammatory disease (IMID). Pts9 beliefs about the necessity of treatment and concerns about potential adverse effects could strongly influence adherence. However, knowledge about such beliefs and concerns in pts with IMIDs is quite limited. Objectives Conduct a multi-country cross-sectional study exploring pts9 beliefs, concerns, attitudes and adherence toward TNF inhibitors (TNFi) and selected conventional therapies used either alone or in combination across multiple IMIDs. Methods In the ALIGN study, adults age ≥18 y diagnosed with rheumatoid arthritis (RA), ankylosing spondylitis (AS), psoriatic arthritis (PsA), Crohn9s disease (CD), ulcerative colitis (UC) or psoriasis (PsO) who were receiving conventional therapy and/or disease-modifying antirheumatic drugs (including TNFi) were recruited by specialists at different disease stages. Pts completed validated questionnaires such as the Beliefs about Medicines Questionnaire (BMQ) and short Morisky Medication Adherence Scale (MMAS-4) at a single visit. Analyses of BMQ specific scores, MMAS-4 scores and pts9 attitudes toward their medications are presented. Results 7328 pts were recruited, including 7197 in 33 countries (Western Europe/Canada, 56.8%; Eastern Europe/Middle East, 19.8%; Latin America, 12.8%; Asia Pacific, 10.6%) who met eligibility criteria. Eligible pts had RA (27.5%), AS (11.3%), PsA (8.9%), CD (17.3%), UC (8.8%) or PsO (26.2%). Mean age was 47.5 y (range, 38.0 in CD to 54.8 in RA). Mean disease duration was 11.7 y (range, 8.1 in UC to 18.7 in PsO). The largest proportion of pts received conventional therapies (40.3%), followed by TNFi mono- (32.0%) and combination therapy (27.7%). An attitudinal analysis combining BMQ necessity and concern scores revealed that most pts were either “accepting” (high necessity/low concern) or “ambivalent” (high necessity/high concern) toward their medication irrespective of disease or treatment type. Adherence across disease types was generally higher in pts receiving TNFi with or without conventional therapy (range of mean MMAS-4 scores, 3.4–3.7; 0–1 = low adherence, 2–3 = medium adherence, 4 = high adherence), vs pts receiving conventional mono- (2.6–3.3) or combination therapy (2.8–3.4). Across all treatment types, high adherence according to MMAS-4 analysis was consistently lower among “ambivalent” pts (46.1–69.0%) vs “accepting” pts (55.8%−77.6%) according to combined BMQ scores (Table). Conclusions Compared with “accepting” pts, “ambivalent” pts appeared to be less often highly adherent (MMAS-4 score=4), which could negatively affect treatment efficacy. The high percentage of “ambivalent” pts across disease types reveals the need to better explore pts9 concerns about medication during routine consultations and to address any erroneous beliefs regarding benefit-risk of treatments to avoid potential nonadherence. Acknowledgements AbbVie funded the study and the analysis, and approved the abstract for submission. Jennifer Han, MS, of Complete Publication Solutions, Horsham, PA, provided writing assistance. Disclosure of Interest P. Michetti Grant/research support: MSD AG Switzerland, Consultant for: MSD, AbbVie, Abbott, UCB, Delenex, Vifor, Speakers bureau: MSD, UCB, Abbott, J. Weinman Employee of: Atlantis Healthcare, U. Mrowietz Grant/research support: Abbott/AbbVie, Almirall-Hermal, Amgen, BASF, Biogen Idec, Celgene, Centocor, Eli Lilly, Forward Pharma, Galderma, Janssen, Leo Pharma, Medac, MSD, Miltenyi Biotech, Novartis, Pfizer, Teva, VBL, Xenoport., Consultant for: Abbott/AbbVie, Almirall-Hermal, Amgen, BASF, Biogen Idec, Celgene, Centocor, Eli Lilly, Forward Pharma, Galderma, Janssen, Leo Pharma, Medac, MSD, Miltenyi Biotech, Novartis, Pfizer, Teva, VBL, Xenoport., Speakers bureau: Abbott/AbbVie, Almirall-Hermal, Amgen, BASF, Biogen Idec, Celgene, Centocor, Eli Lilly, Forward Pharma, Galderma, Janssen, Leo Pharma, Medac, MSD, Miltenyi Biotech, Novartis, Pfizer, Teva, VBL, Xenoport., J. Smolen Grant/research support: Abbott/AbbVie, Consultant for: Abbott/AbbVie, D. Schremmer Employee of: GKM Gesellschaft fuer Therapieforschung mbH, N. Tundia Shareholder of: AbbVie, Employee of: AbbVie, F. Gillas Shareholder of: AbbVie, Employee of: AbbVie, N. Selenko-Gebauer Shareholder of: AbbVie, Employee of: AbbVie DOI 10.1136/annrheumdis-2014-eular.2030
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 | 0,000 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 ».