Association between Levels of Total Cell-Free DNA and Development of Preeclampsia—A Literature Review
Bibliographic record
Abstract
Abstract Objectives The aim of the study is to synthesize the evidence and evaluate the total cell-free deoxyribonucleic (cfDNA) associated with the prediction of preeclampsia (PE). Total cfDNA is constituted by both cell-free fetal DNA (cffDNA) originated mainly from the placenta, and maternal cfDNA derived from maternal leukocytes. Methods A systematic review was conducted by searching PubMed and Medline. Literature reporting levels of total cfDNA in the development of PE was included. Studies that only reported cffDNA, but no cfDNA concentrations were not included in this review. Results Eight studies were included. Seven reported values of cfDNA in PE patients, regardless of early or late onset PE, six of which demonstrated a significant increase of cfDNA in patients who subsequently developed PE. Seven studies evaluated cfDNA levels in the first trimester, six of which showed significant increase of cfDNA concentrations in women who later developed PE. Five studies investigated cfDNA levels in the second trimester, all presenting increased total cfDNA levels in the PE group compared with normal controls. Conclusion Total cfDNA may play a role as a biochemical marker of PE, compared with fetal cfDNA. Large prospective studies with homogeneous populations and standardized methodology are needed to further confirm its predictive value.
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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 | 0.003 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.015 | 0.014 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 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".