Prenatal thoraco-amniotic chest drain insertion to manage a case of fetal hydrops secondary to <i>FOXC2</i>
Post-publication record
Source: Retraction Watch, joined by DOI. OpenAlex records retraction as is_retracted, a boolean over a state space with at least four values, so it cannot express an expression of concern, a correction or a reinstatement; it reports them as false, which reads as “fine”.
Bibliographic record
Abstract
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
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".