Evidence map›Paper›PMID 30300541›Full record

ArticleEndocrine connections2018

Serum anti-Mullerian hormone predicts ovarian response in (Macaca fascicularis) monkeys

Hui Long, Yanhong Nie, Li Wang, Yong Lu, Yan Wang, Yijun Cai, Zhen Liu, Miaomiao Jia, Qifeng Lyu, Yanping Qifeng and 1 more

Open access · goldAbstract read
In one paragraph

Article in Endocrine connections, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact, top 89% of its field
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

2 citing papers in PubMed, 3 citations in OpenAlex.

  1. Article
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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

11 authors at 4 institutions in 1 country.

Hui Long
Yanhong Nie
Li Wang
Yong Lu
Yan Wang
Yijun Cai
Zhen Liu
Miaomiao Jia
Qifeng Lyu
Yanping Qifeng
Qiang Sun
Shanghai Ninth People's Hospital · CNShanghai Institutes for Biological Sciences · CNChinese Academy of Sciences · CNCenter for Excellence in Brain Science and Intelligence Technology · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

AMH as a promising predictor of ovarian response has been studied extensively in women undergoing assisted reproductive technology treatment, but little is known about its prediction value in monkeys undergoing ovarian stimulation. In the current study, a total of 380 cynomolgus monkeys ranging from 5 to 12 years received 699 ovarian stimulation cycles. Serum samples were collected for AMH measure with enzyme-linked immunosorbent assay. It was found that serum AMH levels were positive correlated with the number of retrieved oocytes (P < 0.01) in the first, second and third stimulation cycles. In the first cycles, area under the curve (ROCAUC) of AMH is 0.688 for low response and 0.612 for high response respectively, indicating the significant prediction values (P = 0.000 and P = 0.005). The optimal AMH cutoff value was 9.68 ng/mL for low ovarian response and 15.88 ng/mL for high ovarian response prediction. In the second stimulation cycles, the significance of ROCAUC of AMH for high response rather than the low response was observed (P = 0.001 and P = 0.468). The optimal AMH cutoff value for high ovarian response was 15.61 ng/mL. In the third stimulation cycles, AMH lost the prediction value with no significant ROCAUC. Our data demonstrated that AMH, not age, is a cycle-dependent predictor for ovarian response in form of oocyte yields, which would promote the application of AMH in assisted reproductive treatment (ART) of female cynomolgus monkeys. AMH evaluation would optimize candidate selection for ART and individualize the ovarian stimulation strategies, and consequentially improve the efficiency in monkeys.

Identifiers

PMID30300541
PMCPMC6176281
OpenAlexW2886330093

What OpenQuestion holds

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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.