<i>Chlamydia Pneumoniae</i> DNA in Peripheral Blood Mononuclear Cells in Peritoneal Dialysis Patients
Bibliographic record
Abstract
OBJECTIVE: The aim of the present study was to examine the association between infection with Chlamydia pneumoniae and symptomatic atherosclerosis in peritoneal dialysis (PD) patients. DESIGN: Cross-sectional study. SETTING: Peritoneal Dialysis Unit of Kingston General Hospital. PATIENTS: Fifty-five prevalent PD patients. OUTCOME MEASURES: (1) Infection with C. pneumoniae diagnosed by detection of DNA in peripheral blood mononuclear cells (PBMCs) using polymerase chain reaction. (2) Symptomatic atherosclerosis involving the coronary, cerebral, or peripheral circulation. RESULTS: The DNA of C. pneumoniae was detected in PBMCs in 33 patients (60.0%). Atherosclerosis was present in 16 of 33 (48%) PBMC C. pneumoniae DNA-positive patients, and in 10 of 22 (45%) PBMC C. pneumoniae DNA-negative patients (p = 0.83). Using multiple logistic regression and controlling for a number of known cardiovascular risk factors, PBMC C. pneumoniae DNA status was not predictive of atherosclerosis. The only significant independent predictors of atherosclerosis were diabetes and age. CONCLUSIONS: In prevalent PD patients, a high prevalence of symptomatic atherosclerosis and of Chlamydia pneumoniae DNA in PBMCs were seen; however, the results of the present study do not support the presence of an association between infection with C. pneumoniae and atherosclerosis.
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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 | 0.000 | 0.002 |
| 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 | 0.000 |
| 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".