Cell-Free Placental mRNA in Maternal Plasma to Predict Placental Invasion in Patients With Placenta Accreta
Bibliographic record
Abstract
The first-line methods used to diagnose placenta accreta are ultrasound and Doppler. A large number of studies have shown that their diagnostic accuracy is variable. Some investigators have suggested that placental messenger RNA (mRNA) may be a useful predictive marker for hysterectomy among patients with placenta previa associated with placenta accreta. This prospective study investigated whether the concentration of cell-free placental mRNA was a useful predictive marker for detection of placental invasion in women with placenta accreta and whether knowledge of the concentration could improve the diagnostic accuracy of ultrasound and color Doppler. The participants were 35 singleton pregnant women of more than 28 weeks' gestation who were at risk for placenta accreta. All study subjects underwent ultrasound and color Doppler assessment. The study was conducted at an antenatal care clinic at a university hospital in Egypt between 2007 and 2009. Maternal plasma concentrations of cell-free mRNA were measured using a one-step quantitative real-time reverse transcription polymerase chain reaction assay. Based on the cesarean and/or histological diagnosis, the study subjects were divided into 2 following groups: women with (n = 28) and without (n = 7) placenta accreta. The median MoM (multiples of the median) value of cell-free placental mRNA was calculated in both groups. Compared to women without placenta accreta, those with accreta had a significantly higher median MoM value of cell-free placental mRNA (6.50 vs. 2.60, P < 0.001). In addition, cell-free placental mRNA values were significantly higher among patients with placenta increta or percreta compared to those with simple accreta diagnosed at cesarean delivery (P < 0.002). Insignificant increases in cell-free placental mRNA levels were observed in 6 women with a false-positive diagnosis of placenta accreta on ultrasound. These findings suggest that measurement of cell-free placental mRNA in maternal plasma may increase the predictive diagnostic accuracy of ultrasound and color Doppler for placental invasion in pregnant women with suspected placenta accreta. However, the small sample size makes it difficult to draw a definite conclusion from this study.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".