<i>Chlamydia pneumoniae</i>Infection in Preeclampsia
Bibliographic record
Abstract
OBJECTIVE: The maternal syndrome of preeclampsia results from systemic endothelial activation by a number of factors that primarily derive from the intervillous space, so-called intervillous soup. Co-precipitants, such as innate immune activators, may lower the threshold to develop the maternal syndrome in preeclampsia. We examined whether, like atherosclerosis, preeclampsia is associated with infection with Chlamydia pneumoniae (C. pneumoniae). STUDY DESIGN: A case-control study was performed on 50 women with preeclampsia, 57 women with normal pregnancies at term, and 25 non-pregnant controls. Anti-C. pneumoniae antibodies were examined by enzyme-linked immunosorbent assay and C. pneumoniae genomic DNA (gDNA) loads were measured by real-time PCR. We also performed a data synthesis of the relationship between anti-C. pneumoniae seroprevalence and preeclampsia risk. RESULTS: Neither the number of women with measurable copy numbers of C. pneumoniae gDNA, the anti-C. pneumoniae seroprevalence, nor antibody indices of IgG, IgM, or IgA to C. pneumonia varied between groups. However, when measurable, gDNA copy numbers of C. pneumoniae were increased in women with preeclampsia compared with the normal pregnant (p < 0.05) and non-pregnant controls (p < 0.05). For women with measurable C. pneumoniae gDNA, their copy numbers were correlated with anti-C. pneumoniae IgG concentrations (r2 = 0.49; p < 0.0001). Data synthesis reveals that anti-C. pneumoniae IgG seroprevalence is associated with preeclampsia risk. CONCLUSION: Our data suggest an association between C. pneumoniae infection and preeclampsia. While not a uniform and singular precipitant of the maternal syndrome of preeclampsia, C. pneumoniae infection may be a co-precipitant with other components of the intervillous soup. Further investigations appear warranted.
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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 | 0.001 | 0.001 |
| 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) | 0.002 | 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".