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Record W4288045606 · doi:10.1136/bmjresp-2022-001254

Rationale and design of the SARCoidosis Outcomes in all respiratory Viral Infectious Diseases (SARCOVID) Study

2022· article· en· W4288045606 on OpenAlexfundno aff
Rachel K Strykowski, Divya Patel, Manny Ribeiro Neto, Kerry Hena, Mridu Gulati, Lisa A. Maier, Karen Patterson

Bibliographic record

VenueBMJ Open Respiratory Research · 2022
Typearticle
Languageen
FieldMedicine
TopicSarcoidosis and Beryllium Toxicity Research
Canadian institutionsnot available
FundersNational Center for Advancing Translational SciencesUniversity of Illinois at ChicagoUniversity of California, San DiegoUniversity of Illinois at Urbana-ChampaignYale UniversityVirginia Commonwealth UniversityUniversity of South FloridaCleveland ClinicCleveland Clinic FoundationUniversity of MiamiYork UniversityUniversity of PennsylvaniaEast Carolina University
KeywordsMedicineSarcoidosisCohortRespiratory systemObservational studyPopulationCohort studyIntensive care medicineInternal medicineImmunologyEnvironmental health

Abstract

fetched live from OpenAlex

INTRODUCTION: Respiratory infections are ubiquitous. The COVID-19 pandemic has refocused our attention on how morbid and potentially fatal they can be, and how host factors have an impact on the clinical course and outcomes. Due to a range of vulnerabilities, patients with sarcoidosis may be at higher risk of poor outcomes from respiratory infections. The objective of the SARCoidosis Outcomes in all respiratory Viral Infectious Diseases (SARCOVID) Study is to determine the short-term and long-term impacts of respiratory viral illnesses (COVID-19 and non-COVID-19) in sarcoidosis. METHODS AND ANALYSIS: Up to 20 clinical sites across the USA are participating in the recruitment of 2000 patients for this observational, prospective study. To ensure that the study cohort is representative of the general population with sarcoidosis, participating sites include those dedicated to reaching under-represented minorities or patients from non-urban areas. Baseline data on demographic features, comorbidities, sarcoidosis characteristics and pre-enrolment lung function will be captured at study entry. During this 3-year study, all acute respiratory infectious events (from SARS-CoV-2 and any other respiratory pathogen) will be assessed and recorded at quarterly intervals. The level of required medical care and survival outcomes determine infection severity, and the impact of infection on quality of life measures will be recorded. Post-infection lung function and imaging results will measure the long-term impact on the trajectory of sarcoidosis. Patients will be analysed according to the clinical phenotypes of cardiac and fibrotic pulmonary sarcoidosis. Control groups include non-infected patients with sarcoidosis and patients with non-sarcoidosis interstitial lung disease. ETHICS AND DISSEMINATION: Each site received local institutional review board approval prior to enrolling patients, with the consent process determined by local institution standards. Data will be published in a timely manner (goal <12 months) at the conclusion of the 3-year follow-up period and will be made available upon request.

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)0.042
metaresearch head score (Gemma)0.022
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.042
Threshold uncertainty score0.223

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0420.022
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0020.002
Science and technology studies0.0020.003
Scholarly communication0.0030.002
Open science0.0030.002
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0150.005

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 head0.342
GPT teacher head0.496
Teacher spread0.153 · 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 designNot applicable
Domainnot available
GenreProtocol

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

Citations3
Published2022
Admission routes1
Has abstractyes

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