Predictive value of pregnancy-associated plasma protein-A in relation to fetal loss: A systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: For a woman with bleeding and threatened abortion, ultrasound scan is done to confirm the viability of the fetus; however, 10-15% of the embryos are eventually aborted. Distinguishing between women with good and poor prognosis can be a helpful approach. OBJECTIVE: This study aimed to review the predictive value of Pregnancy-associated Plasma Protein A (PAPP-A) in relation to the diagnosis of fetal loss. MATERIALS AND METHODS: The articles published in multiple databases including Web of Science, PubMed, MEDLINE, Scopus, and Persian databases such as ISC, Magiran, and IranMedx were searched for articles published until May 2019. MeSH terms was used for searching the databases including fetal loss OR pregnancy loss OR abortion OR miscarriage with the following word using AND; Pregnancy-Associated Plasma Protein-A OR PAPP-A. Two reviewers extracted data and recorded them in a pre-defined form and assessed the quality of articles using the Newcastle-Ottawa tool. Meta-analysis was done using the Comprehensive Meta-Analysis/2.0 software and MetaDisc. RESULTS: A total number of 16 studies were eligible for the qualitative data synthesis, out of which 8 studies were included in the meta-analysis. All studies had high and medium quality. The forest plot analysis showed a sensitivity of 57% (95% CI: 53-63%), a specificity of 83% (95% CI: 80-85%), a positive likelihood ratio of 3.52 (95% CI: 2.44-5.07), a negative likelihood ratio of 0.54 (95% CI: 0.37-0.79), and a diagnostic odds ratio of 6.95 (95% CI: 3.58-13.50). CONCLUSION: PAPP-A cannot be recommended on a routine basis for predicting fetal loss and still further research with a combination of other biomarkers is required.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.008 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".