Serum surfactant protein D is steroid sensitive and associated with exacerbations of COPD
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Surfactant protein (SP)-D is a lung-derived protein that has been proposed as a biomarker for inflammatory lung disease. Serum SP-D was evaluated as a biomarker for components of chronic obstructive pulmonary disease (COPD) in the Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints (ECLIPSE) cohort and its response assessed to the administration of the anti-inflammatory agent prednisolone. The median level of serum SP-D was significantly elevated in 1,888 individuals with COPD compared to 296 current and former smokers without airflow obstruction (121.1 and 114.3 ng x mL(-1), respectively; p = 0.021) and 201 nonsmokers (82.2 ng x ml(-1); p<0.001). There was no correlation with the severity of COPD. Individuals with COPD who had a serum SP-D concentration that was greater than the 95th percentile of nonsmokers (175.4 ng x mL(-1)) showed an increased risk of exacerbations over the following 12 months (adjusted OR 1.30; 95% CI 1.03-1.63). Treatment with 20 mg x day(-1) prednisolone for 4 weeks resulted in a fall in serum SP-D levels (126.0 to 82.1 ng x mL(-1); p<0.001) but no significant change in post-bronchodilator forced expiratory volume in 1 s. Serum SP-D concentration is raised in smokers and may be useful in identifying individuals who are at increased risk of exacerbations of COPD. It may represent an intermediate measure for the development of novel anti-inflammatory agents.
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.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it