Evidence map›Paper›PMID 40993563›Full record

ArticleBMC pregnancy and childbirth2025

An analytical pipeline for dose-response effect: laboratory tests assessment and early pregnancy preeclampsia risk.

Yinyao Ma, Xiao Wang, Jinjiang Mao, Hanlin Lv, Yanhua Ma, Hua Wu, Chun Zhang, Lei Wang, Xuxia Liang

Abstract read
In one paragraph

Article in BMC pregnancy and childbirth, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

9 authors.

Yinyao Ma *Department of Obstetrics, People's Hospital of Guangxi Zhuang Autonomous Region, Taoyuan Road No. 6, Qingxiu District, Nanning, 530016, China.
Xiao Wang *BGI Research, Wuhan, 430074, China.
Jinjiang Mao *Department of Obstetrics, People's Hospital of Guigang, Zhongshan Zhong Road No. 1, Gangbei District, Guigang, 537100, China.
Hanlin LvBGI Research, Wuhan, 430074, China.
Yanhua MaDepartment of Obstetrics, People's Hospital of Guangxi Zhuang Autonomous Region, Taoyuan Road No. 6, Qingxiu District, Nanning, 530016, China.
Hua WuDepartment of Obstetrics, People's Hospital of Guangxi Zhuang Autonomous Region, Taoyuan Road No. 6, Qingxiu District, Nanning, 530016, China.
Chun ZhangDepartment of Obstetrics, People's Hospital of Guangxi Zhuang Autonomous Region, Taoyuan Road No. 6, Qingxiu District, Nanning, 530016, China.
Lei WangBGI Research, Wuhan, 430074, China. wanglei12@genomics.cn.
Xuxia LiangDepartment of Obstetrics, People's Hospital of Guangxi Zhuang Autonomous Region, Taoyuan Road No. 6, Qingxiu District, Nanning, 530016, China. lxx1968131@163.com.

Funding

Guangxi Key Research and Development Program AB22035018Guangxi Key Research and Development Program AB25069059National Natural Science Foundation of China 82060805
6 · The paper itself

Abstract

backgroundFew studies have explored the associations between early pregnancy laboratory tests and preeclampsia, leaving rich first-trimester data underutilized. This study introduces a pipeline, integrating Generalized Additive Models with dose-response analysis, to elucidate the complex associations.

methodsOur pipeline includes identifying turning points (pathway A) and risk/protective intervals (pathway B). We used Generalized Additive Models with cubic regression splines. For pathway A, turning points were identified at the second derivative extrema of nonlinear monotonic fitted probability curves. For pathway B, risk/protective intervals were determined where the Odds Ratios equaled 1. Propensity score matching and the risk ratios were used for evaluation. This pipeline was applied to a retrospective GZ cohort of 12,474 pregnancies and evaluated in an external GG cohort.

resultsThrough analyzing 99 unique laboratory tests within GZ cohort, our pipeline highlighted 16 exhibiting optimal turning points via pathway A and 4 showing risk/protective intervals through pathway B. The turning points from pathway A were comparable to those from traditional piecewise logistic regression. Evaluation within GG cohort confirmed the statistical robustness. Additionally, our experiments demonstrated that hyperparameter fine-tuning of Generalized Additive Models fitting had minimal effect, and pathway output metrics are sensitive to pregnancy stages, leading to considerable variability in conclusions.

conclusionsThe proposed pipeline was rigorously validated for its efficacy across two independent cohorts, achieving consistent outcomes. Furthermore, the laboratory tests identified mostly align with conclusions from prior studies. We believe it both advances our understanding of the mechanisms during early pregnancy disorder and offers vital insights for early preeclampsia detection and preventive interventions. TRAIL REGISTRATION: NA.

Indexed as

Pre-EclampsiaPregnancy Trimester, FirstAdultFemaleHumansPregnancyPropensity ScoreRetrospective StudiesRisk AssessmentRisk FactorsDose-response effectGeneralized additive modelsPreeclampsiaRisk/protective intervalsTurning points

Identifiers

PMID40993563
PMCPMC12462207

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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.