Systemic corticosteroids for outpatient respiratory viral infections in lung transplant recipients
Bibliographic record
Abstract
INTRODUCTION: Respiratory viral infections (RVI) in lung transplant recipients (LTR) have variably been associated with rejection and chronic lung allograft dysfunction. Our center has used systemic corticosteroids to treat outpatient RVI in some cases, but evidence is limited. We reviewed all adult LTR diagnosed with outpatient RVI January 2017 to December 2019. The primary outcome was recovery of lung function (forced expiratory volume in 1 s [FEV1]) at next stable visit between 1 and 12 months postinfection, expressed as a ratio over stable preinfection FEV1 (FEV1 recovery ratio). METHODS: We identified 100 adult LTR with outpatient RVI diagnoses eligible for study, 36% of whom received corticosteroids. We modelled the adjusted association between corticosteroid use and FEV1 recovery ratio using linear regression. RESULTS: Steroid-treated patients had a lower FEV1 presentation ratio (0.92 vs. 1.04, p = .0070) and were more likely to have chronic lung allograft dysfunction at time of infection (25% vs. 5%, p = .0077). Mean FEV1 recovery ratio was 1.02 (SD 0.19) with no association with corticosteroid therapy via multivariable linear regression (p = .5888). CONCLUSIONS: Steroid treatment was not associated with FEV1 recovery. This suggests corticosteroids may not have a role in the management of RVI in this population.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".