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Record W4295761925 · doi:10.1136/rmdopen-2022-002508

Factors associated with severe COVID-19 in people with idiopathic inflammatory myopathy: results from the COVID-19 Global Rheumatology Alliance physician-reported registry

2022· article· en· W4295761925 on OpenAlexaff
Su‐Ann Yeoh, Milena Gianfrancesco, Saskia Lawson‐Tovey, Kimme L Hyrich, Anja Strangfeld, Laure Gossec, Loreto Carmona, Elsa F Mateus, Martin Schäfer, Christophe Richez, É. Hachulla, Marie Holmqvist, Carlo Alberto Scirè, Hanns‐Martin Lorenz, Reinhard Voll, Rebecca Hasseli, Arundathi Jayatilleke, Tiffany Hsu, Kristin M. D’Silva, Víctor R. Pimentel-Quiroz, Mónica Vázquez-Del Mercado, Samuel Katsuyuki Shinjo, Edgard Torres dos Reis Neto, Laurindo Ferreira da Rocha, Ana Carolina de Oliveira e Silva Montandon, Guillermo Pons‐Estel, Sofía Ornella, Maria Eugenia D’Angelo Exeni, E. Velozo, Paula Jordan, Emily Sirotich, Jonathan S. Hausmann, Jean W. Liew, Lindsay Jacobsohn, Monique Gore‐Massy, Paul Sufka, Rebecca Grainger, Suleman Bhana, Zachary S. Wallace, Philip C. Robinson, Jinoos Yazdany, Pedro Machado

Bibliographic record

VenueRMD Open · 2022
Typearticle
Languageen
FieldMedicine
TopicInflammatory Myopathies and Dermatomyositis
Canadian institutionsMcMaster UniversityImpactCanadian Arthritis Patient Alliance
FundersEuropean League Against Rheumatism
KeywordsMedicineInternal medicineRheumatologyLogistic regressionCoronavirus disease 2019 (COVID-19)PrednisoloneSeverity of illnessDiseaseInfectious disease (medical specialty)

Abstract

fetched live from OpenAlex

OBJECTIVES: To investigate factors associated with severe COVID-19 in people with idiopathic inflammatory myopathy (IIM). METHODS: Demographic data, clinical characteristics and COVID-19 outcome severity of adults with IIM were obtained from the COVID-19 Global Rheumatology Alliance physician-reported registry. A 3-point ordinal COVID-19 severity scale was defined: (1) no hospitalisation, (2) hospitalisation (and no death) and (3) death. ORs were estimated using multivariable ordinal logistic regression. Sensitivity analyses were performed using a 4-point ordinal scale: (1) no hospitalisation, (2) hospitalisation with no oxygen (and no death), (3) hospitalisation with oxygen/ventilation (and no death) and 4) death. RESULTS: Of 348 patients, 48% were not hospitalised, 39% were hospitalised (and did not die) and 13% died. Older age (OR=1.59/decade, 95% CI 1.31 to 1.91), high disease activity (OR=3.50, 95% CI 1.25 to 9.83; vs remission), ≥2 comorbidities (OR=2.63, 95% CI 1.39 to 4.98; vs none), prednisolone-equivalent dose >7.5 mg/day (OR=2.40, 95% CI 1.09 to 5.28; vs no intake) and exposure to rituximab (OR=2.71, 95% CI 1.28 to 5.72; vs conventional synthetic disease-modifying antirheumatic drugs only) were independently associated with severe COVID-19. In addition to these variables, in the sensitivity analyses, male sex (OR range: 1.65-1.83; vs female) was also significantly associated with severe outcomes, while COVID-19 diagnosis after 1 October 2020 (OR range: 0.51-0.59; vs on/before 15 June 2020) was significantly associated with less severe outcomes, but these associations were not significant in the main model (OR=1.57, 95% CI 0.95 to 2.59; and OR=0.61, 95% CI 0.37 to 1.00; respectively). CONCLUSIONS: This is the first large registry data on outcomes of COVID-19 in people with IIM. Older age, male sex, higher comorbidity burden, high disease activity, prednisolone-equivalent dose >7.5 mg/day and rituximab exposure were associated with severe COVID-19. These findings will enable risk stratification and inform management decisions for patients with IIM.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.044
GPT teacher head0.298
Teacher spread0.254 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations13
Published2022
Admission routes1
Has abstractyes

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