Association of circulating Chlamydia pneumoniaeDNA with cardiovascular disease: a systematic review
Bibliographic record
Abstract
BACKGROUND: Chlamydia pneumoniae antigens, nucleic acids, or intact organisms have been detected in human atheroma. However, the presence of antibody does not predict subsequent cardiovascular (CV) events. We performed a systematic review to determine whether the detection of C. pneumoniae DNA in peripheral blood mononuclear cells (PBMC) was associated with CV disease. METHODS: We sought studies of C. pneumoniae DNA detection in PBMC by polymerase chain reaction (PCR) among patients with CV disease or other clinical conditions. We pooled studies in which CV patients were compared with non-diseased controls. We analyzed differences between studies by meta-regression, to determine which epidemiological and technical characteristics were associated with higher prevalence. RESULTS: Eighteen relevant studies were identified. In nine CV studies with control subjects, the prevalence of circulating C. pneumoniae DNA was 252 of 1763 (14.3%) CV patients and 74 of 874 (8.5%) controls, for a pooled odds ratio of 2.03 (95% CI: 1.34, 3.08, P < 0.001). Prevalence was not adjusted for CV risk factors. Current smoking status, season, and age were associated with C. pneumoniae DNA detection. High prevalence (>40%) was found in patients with cardiac, vascular, chronic respiratory, or renal disease, and in blood donors. Substantial differences between studies were identified in methods of sampling, extraction, and PCR targets. CONCLUSIONS: C. pneumoniae DNA detection was associated with CV disease in unadjusted case-control studies. However, adjustment for potentially confounding measures such as smoking or season, and standardization of laboratory methods, are needed to confirm this association.
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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 | 0.005 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.008 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".