Evidence map›Paper›PMID 28083776›Full record

ArticleJournal of assisted reproduction and genetics2017

Serum progesterone trend after day of transfer predicts live birth in fresh IVF cycles.

Jennifer K Blakemore, Jason D Kofinas, David H McCulloh, Jamie Grifo

Abstract read
In one paragraph

Article in Journal of assisted reproduction and genetics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
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

4 authors.

Jennifer K BlakemoreDivision of Reproductive Endocrinology and Infertility, NYU Langone Medical Center, 660 1st Avenue, New York, NY, 10016, USA. Jennifer.blakemore@nyumc.org.
Jason D KofinasDivision of Reproductive Endocrinology and Infertility, NYU Langone Medical Center, 660 1st Avenue, New York, NY, 10016, USA.
David H McCullohDivision of Reproductive Endocrinology and Infertility, NYU Langone Medical Center, 660 1st Avenue, New York, NY, 10016, USA.
Jamie GrifoDivision of Reproductive Endocrinology and Infertility, NYU Langone Medical Center, 660 1st Avenue, New York, NY, 10016, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeOur objective was to determine if a change in serum P4 from day of transfer (defined as day 19) to day 28 could predict live birth outcome in patients undergoing IVF.

methodsThis study was a retrospective analysis of fresh IVF cycles from 2010 to 2013 at a single center. Primary outcomes include raw and percent change in serum P4, live birth rate, missed abortion, and biochemical pregnancies.

resultsOur results showed an association between live birth rate and percent change in P4. Patients with a 10% or greater drop in serum P4 from day 19 to day 28 had a lower live birth rate, at 26 versus 63%. Interestingly, both groups had "normal" serum P4 levels on day 19, but patients with a 10% or greater drop had lower P4 levels than their counterparts. There was no association between percent P4 change and spontaneous abortion or biochemical pregnancy.

conclusionsThis is the first study to show that percent drop in serum P4 from day of transfer to day 28 is associated with decreased rates of live birth and ongoing pregnancy in fresh IVF cycles, even despite "high or normal" P4 levels on day of transfer.

Indexed as

Embryo TransferFertilization in VitroAbortion, SpontaneousAdultBirth RateFemaleHumansLive BirthPregnancyProgesteroneProgesteroneART outcome predictorsEmbryo transferIn vitro fertilizationLuteal support

Identifiers

PMID28083776
PMCPMC5360684

What OpenQuestion 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 OpenQuestion graph.