Neighbourhood disadvantage impacts on pulmonary function in patients with sarcoidosis
Bibliographic record
Abstract
Background This multicentre, international, prospective cohort study evaluated whether patients with pulmonary sarcoidosis living in neighbourhoods with greater material and social disadvantage experience worse clinical outcomes. Methods The area deprivation index and the Canadian Index of Multiple Deprivation evaluate neighbourhood-level disadvantage in the US and Canada, with higher scores reflecting greater disadvantage. Multivariable linear regression evaluated associations of disadvantage with baseline forced vital capacity (FVC) or diffusing capacity of the lung for carbon monoxide ( D LCO ) and linear mixed effects models for associations with rate of FVC or D LCO decline, and competing hazards models were used for survival analyses in the US cohort, evaluating competing outcomes of death or lung transplantation. Adjustments were made for age at diagnosis, sex, race and smoking history. Results We included 477 US and 122 Canadian patients with sarcoidosis. Higher disadvantage was not associated with survival or baseline FVC. The highest disadvantage quartile was associated with lower baseline D LCO in the US cohort (β = −6.80, 95% CI −13.16 to −0.44, p=0.04), with similar findings in the Canadian cohort (β = −7.47, 95% CI −20.28 to 5.33, p=0.25); with more rapid decline in FVC and D LCO in the US cohort (FVC β = −0.40, 95% CI −0.70 to −0.11, p=0.007; D LCO β = −0.59, 95% CI −0.95 to −0.23, p=0.001); and with more rapid FVC decline in the Canadian cohort (FVC β = −0.80, 95% CI −1.37 to −0.24, p=0.003). Conclusion Patients with sarcoidosis living in high disadvantage neighbourhoods experience worse baseline lung function and more rapid lung function decline, highlighting the need for better understanding of how neighbourhood-level factors impact individual patient outcomes.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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 teacher head, 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".