MétaCan
Menu
Back to cohort

Does Systemic Sclerosis–Associated Interstitial Lung Disease Burn Out? Specific Phenotypes of Disease Progression

2018· article· en· W2890199186 on OpenAlexaff
Sabina A. Guler, Tiffany A. Winstone, Darra Murphy, Cameron Hague, Jeanette Soon, Nada Sulaiman, Kathy H. Li, James V. Dunne, Pearce Wilcox, Christopher J. Ryerson

Bibliographic record

VenueAnnals of the American Thoracic Society · 2018
Typearticle
Languageen
FieldMedicine
TopicSystemic Sclerosis and Related Diseases
Canadian institutionsCentre for Advancing Health OutcomesSt. Paul's HospitalUniversity of British ColumbiaProvidence Health Care
Fundersnot available
KeywordsMedicineDLCOInterstitial lung diseaseVital capacityInternal medicineDiffusing capacityPulmonary function testingCohortConfidence intervalLungLung function

Abstract

fetched live from OpenAlex

Abstract Rationale Previous studies have suggested that interstitial lung disease (ILD) progresses most rapidly early in the course of systemic sclerosis–associated (SSc)-ILD, and that SSc-ILD is often more stable or even “burned out” after the first 4 years following diagnosis. Objectives Our objectives were to determine whether an apparent plateau in pulmonary function decline is due to survival bias and to identify distinct prognostic phenotypes of ILD progression. Methods Consecutive patients with SSc-ILD from a single center were included. Pulmonary function measurements were typically performed every 6 months. Study participants were categorized into long-term survivors (>8 yr survival from diagnosis), and those with medium-term and short-term mortality (4–8 and <4 yr survival, respectively). We excluded those censored with less than 8 years of follow-up. Subject-specific slopes for change in forced vital capacity (FVC) and diffusing capacity of the lung for carbon monoxide (DlCO) were calculated using generalized linear models with mixed effects. The rate of decline in FVC was compared across prognostic groups. Results The cohort included 171 study participants with SSc-ILD. A plateau in the progression of FVC was apparent in the full cohort analysis but disappeared with stratification into prognostic subgroups to account for survival bias. Those with short-term mortality had a higher annual rate of decline in FVC (−4.10 [95% confidence interval (CI), −7.92 to −0.28] vs. −2.14 [95% CI, −3.31 to −0.97] and −0.94 [−1.46 to −0.42]; P = 0.003) and DlCO (−5.28 [95% CI, −9.58 to −0.99] vs. −3.13 [95% CI, −4.35 to −1.92] and −1.32 [95% CI, −2.01 to −0.63]; P < 0.001) than those with medium-term mortality and long-term survival with adjustment for age, sex, and pack-years. Change in FVC in the previous year did not predict FVC change in the subsequent year. Conclusions Adults with SSc-ILD have distinct patterns of physiological progression that remain relatively consistent during long-term follow-up; however, recent change in FVC cannot be used to predict future change in FVC within shorter follow-up intervals. The findings of this study provide important information on the course of disease in SSc-ILD and identify specific phenotypes of progression that may improve clinical decision-making and design of future therapeutic trials.

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)0.006
metaresearch head score (Gemma)0.013
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 score0.006
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.070
GPT teacher head0.371
Teacher spread0.301 · 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

Citations107
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueAnnals of the American Thoracic SocietySame topicSystemic Sclerosis and Related DiseasesFrench-language works237,207