Smoking, season, and detection of chlamydia pneumoniaeDNA in clinically stable COPD patients
Bibliographic record
Abstract
BACKGROUND: The prevalence and role of Chlamydia pneumoniae in chronic obstructive pulmonary disease (COPD) remain unclear, and molecular methods of detection may help clarify this relationship. METHODS: Consecutive clinically stable patients with smoking-related COPD attending a tertiary care outpatient clinic were enrolled in this cross-sectional study. Peripheral blood mononuclear cells were obtained from 100 patients, and induced sputum was obtained in 62 patients. C. pneumoniae DNA was detected in blood or sputum by nested polymerase chain reaction (PCR). RESULTS: Patients had mean age (standard deviation) of 65.8 (10.7) years, mean forced expiratory volume in one second (SD) of 1.34 (0.61) L, and 61 (61.0%) were male. C. pneumoniae nucleic acids were detected in 27 (27.0%) patients. Among 62 patients with both blood and sputum available, blood specimens were superior to induced sputum for detection of C. pneumoniae DNA (21 versus 7 detected, P=0.003). Current smoking (odds ratio [OR]=2.6, 95 % confidence interval [CI]: 1.1, 6.6, P=0.04), season (November to April) (OR=3.6, 95% CI: 1.4, 9.2, P=0.007), and chronic sputum production (OR=6.4, 95% CI: 1.8, 23.2, P=0.005) were associated with detection of C. pneumoniae DNA. CONCLUSIONS: C. pneumoniae DNA prevalence was higher among current smokers, and during winter/spring months. Prospective molecular studies are needed to examine the role of C. pneumoniae detection in COPD disease symptoms and progression.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".