Evidence map›Paper›PMID 26247944›Full record

ReviewInternational journal of molecular sciences2015

Combined Screening for Early Detection of Pre-Eclampsia.

Hee Jin Park, Sung Shin Shim, Dong Hyun Cha

Abstract readReview
In one paragraph

Review in International journal of molecular sciences, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

15 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Cell journal · 2023
    Article
  5. Review
  6. Diagnostic biomolecules and combination therapy for pre-eclampsia.Reproductive biology and endocrinology : RB&E · 2022
    Review
  7. Review
  8. Article
  9. Review
  10. Article
  11. Review
  12. Review
  13. Article
  14. Long Non-Coding RNAs Serve as Diagnostic Biomarkers of Preeclampsia and Modulate Migration and Invasiveness of Trophoblast Cells.Medical science monitor : international medical journal of experimental and clinical research · 2018
    Article
  15. Article
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

3 authors.

Hee Jin ParkDepartment of Obstetrics and Gynecology, CHA Gangnam Medical Center, CHA University, Seoul 135-081, Korea. coolsome72@chamc.co.kr.
Sung Shin ShimDepartment of Obstetrics and Gynecology, CHA Gangnam Medical Center, CHA University, Seoul 135-081, Korea. ogshinyss@chamc.co.kr.
Dong Hyun ChaDepartment of Obstetrics and Gynecology, CHA Gangnam Medical Center, CHA University, Seoul 135-081, Korea. chadh001@chamc.co.kr.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Although the precise pathophysiology of pre-eclampsia remains unknown, this condition continues to be a major cause of maternal and fetal mortality. Early prediction of pre-eclampsia would allow for timely initiation of preventive therapy. A combination of biophysical and biochemical markers are superior to other tests for early prediction of the development of pre-eclampsia. Apart from the use of parameters in first-trimester aneuploidy screening, cell-free fetal DNA quantification is emerging as a promising marker for prediction of pre-eclampsia. This article reviews the current research of the most important strategies for prediction of pre-eclampsia, including the use of maternal risk factors, mean maternal arterial pressure, ultrasound parameters, and biomarkers.

Indexed as

Early DiagnosisBiomarkersDNAFemaleFetusGestational AgeHumansPre-EclampsiaPregnancyBiomarkersDNAbiomarkercell-free fetal DNAearly predictionmaternal risk factorsmean maternal arterial pressurepre-eclampsiapregnancy-associated plasma protein-A (PAPP-A)ultrasound parameters

Identifiers

PMID26247944
PMCPMC4581230

What OpenQuestion holds

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LicenceCC BY
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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 OpenQuestion graph.