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Prevalence and Predictors of Depression and Anxiety in Patients With Fibrotic Interstitial Lung Disease: A Prospective Cohort Study

2025· article· en· W4410268201 on OpenAlexaffabout
N. Avitzur, Deborah Assayag, Jolene H. Fisher, Kerri A. Johannson, Nasreen Khalil, Martin Kolb, H. Manganas, Veronica Marcoux, C.J. Ryerson

Bibliographic record

VenueAmerican Journal of Respiratory and Critical Care Medicine · 2025
Typearticle
Languageen
FieldMedicine
TopicInterstitial Lung Diseases and Idiopathic Pulmonary Fibrosis
Canadian institutionsUniversity of SaskatchewanMcMaster UniversityCentre Hospitalier de l’Université de MontréalMcGill UniversityUniversity of CalgaryUniversity Health NetworkUniversity of British Columbia
Fundersnot available
KeywordsMedicineAnxietyDepression (economics)Prospective cohort studyInterstitial lung diseaseCohortInternal medicineCohort studyDiseaseLung diseaseLungPhysical therapyPsychiatry

Abstract

fetched live from OpenAlex

Abstract Background Interstitial lung disease (ILD) consists of a large group of lung diseases with high mortality and reduced quality of life. Previous small studies have reported depression and anxiety in up to 60% of patients, but their prevalence in specific subgroups is unknown and there is little understanding of what drives these disorders. Methods Patients with ILD were identified from the Canadian Registry for Pulmonary Fibrosis. Patient reported history of depression, anxiety, and other comorbidities were recorded based on a standardized review of the clinical record at the time of ILD diagnosis. Medications used to treat depression and/or anxiety were recorded and categorized by class (selective serotonin reuptake inhibitor, serotonin and norepinephrine reuptake inhibitor, tricyclic antidepressant, antipsychotic, and benzodiazepine). Presence of a self-reported diagnosis or medication use were used to classify patients as having depression and/or anxiety. Multivariable logistic regression models tested association of presence of depression and/or anxiety with age, sex, smoking pack-years, forced vital capacity (FVC%), and diffusion capacity of the lung for carbon monoxide (DLCO%). Results The study population consisted of 3,988 patients, including 31% with idiopathic pulmonary fibrosis (IPF), 41% with connective tissue disease-associated ILD (CTD-ILD), 9% with fibrotic hypersensitivity pneumonitis (fHP), and 19% with unclassifiable ILD. Mean age was 65±12 years, 2,002 (50%) were female, mean smoking pack years was 25±22, and 649 (16%) used oxygen. Depression and/or anxiety was present in 701 (18%) patients in the total cohort, including 17% with IPF, 15% with CTD-ILD, 23% with fHP, and 22% with unclassifiable ILD. In unadjusted analysis, the presence of depression and/or anxiety was associated with female sex (OR 1.79, 95% CI 1.51 to 2.12, p<0.001) and oxygen use (OR 1.45, 95% CI 1.16 to 1.79, p<0.001). Female sex was an independent predictor of depression and/or anxiety in all ILD diagnosis subgroups (Table), with increased smoking pack-years also independently associated with presence of depression and/or anxiety in CTD-ILD and unclassifiable ILD. Conclusions Depression and/or anxiety is present in 18% of patients with fibrotic ILD and is more common in females. These findings highlight the importance of a comprehensive approach to patient care that specifically addresses the possible presence of mood disorders.

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)0.002
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 score0.013
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
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 head0.003
GPT teacher head0.266
Teacher spread0.263 · 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

Citations0
Published2025
Admission routes2
Has abstractyes

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