Evidence map›Paper›PMID 42277722›Full record

SynthesisBMC pregnancy and childbirth2026

AI-guided meta-analysis of non-invasive prenatal testing platforms for trisomy 21 screening: comparative evaluation of cffDNA and fetal cell-based approaches.

Alaa Elmetwalli, Fuad Ameen, Najwa Magrashi, Eman Saad Alamri, Aisha Nawaf Albalawi, Othman R Alzahrani, Ali H El-Far

Abstract readMeta-AnalysisComparative StudySystematic Review
PubMed Full text at PMC Publisher
In one paragraph

Synthesis in BMC pregnancy and childbirth, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Alaa ElmetwalliPrince Fahad bin Sultan Chair for Biomedical Research, University of Tabuk, Tabuk, Saudi Arabia. aelmetwalli@ut.edu.sa.ORCID http://orcid.org/0000-0001-5372-4297
Fuad AmeenDepartment of Botany and Microbiology, College of Science, King Saud University, Riyadh, 11451, Saudi Arabia.
Najwa MagrashiDepartment of Botany and Microbiology, College of Science, King Saud University, Riyadh, 11451, Saudi Arabia.
Eman Saad AlamriFood Science and Nutrition Department, University of Tabuk, Tabuk, 71491, Saudi Arabia.
Aisha Nawaf AlbalawiBiology Department, University College of Haqel, University of Tabuk, Tabuk, 71491, Saudi Arabia.
Othman R AlzahraniDepartment of Biology, Faculty of Science, University of Tabuk, Tabuk, 47512, Saudi Arabia.
Ali H El-FarKey Laboratory of Epigenetics and Oncology, The Research Center for Preclinical Medicine, Southwest Medical University, Luzhou, 646000, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTrisomy 21 (Down syndrome) remains the most prevalent autosomal aneuploidy, necessitating accurate prenatal diagnosis. While cell-free fetal DNA (cffDNA)-based non-invasive prenatal testing (NIPT) has transformed screening, challenges persist in low fetal fraction cases and confined placental mosaicism. Integrating artificial intelligence (AI), multi-omics, and fetal cell-based approaches represents a paradigm shift toward comprehensive prenatal diagnostics.

objectiveThis AI-assisted meta-analysis evaluates NIPT platforms for Trisomy 21 detection, comparing cffDNA-based, SNP-based, digital PCR, and emerging fetal cell-based approaches.

methodsFollowing PRISMA guidelines, we systematically searched PubMed, Web of Science, and Scopus (2010-2023). Ten high-quality studies were analyzed for diagnostic accuracy metrics across multiple NIPT platforms.

resultsMPS-based cffDNA NIPT demonstrated pooled sensitivity of 99.3% (95% CI: 98.7-99.7%) and specificity of 99.9% (95% CI: 99.8-100%). Alternative platforms, including fetal cell-based NIPT, showed promising but moderately lower accuracy. AI-driven risk stratification models demonstrated enhanced diagnostic precision in complex cases.

conclusionMPS-based NIPT remains the gold standard for Trisomy 21 screening. Future integration of AI-enhanced fetal cell isolation and multi-omics profiling may expand diagnostic capabilities beyond aneuploidy detection.

Indexed as

Artificial IntelligenceCell-Free Nucleic AcidsDown SyndromeNoninvasive Prenatal TestingFemaleHumansPregnancySensitivity and SpecificityCell-Free Nucleic AcidsAI-driven diagnosticsFetal cell-based NIPTNon-invasive prenatal testing (NIPT)Prenatal genomicsTrisomy 21 screening

Identifiers

PMID42277722
PMCPMC13488287

What Socratic holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.