Evidence map›Paper›PMID 41034727›Full record

ArticleBMC pregnancy and childbirth2025

Association of Inflammatory markers with pregnancy loss: Global Burden (1990-2021) and NHANES survey (2005-2016).

Saisai Yang, Huirong Shi, Shumin Ren, Yibing Chen, Xiaoqing Jin, Liping Han, Qinghua Wu

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 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

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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

7 authors.

Saisai YangDepartment of Obstetrics and Gynecology, Center of Genetics and Prenatal Diagnosis, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, 450052, China.
Huirong ShiDepartment of Obstetrics and Gynecology, Center of Gynecology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, 450052, China.
Shumin RenDepartment of Obstetrics and Gynecology, Center of Genetics and Prenatal Diagnosis, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, 450052, China.
Yibing ChenDepartment of Obstetrics and Gynecology, Center of Genetics and Prenatal Diagnosis, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, 450052, China.
Xiaoqing JinThe Emergency Center, Zhongnan Hospital of Wuhan University, Wuhan, Hubei, 430071, China.
Liping HanDepartment of Obstetrics and Gynecology, Center of Gynecology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, 450052, China.
Qinghua WuDepartment of Obstetrics and Gynecology, Center of Genetics and Prenatal Diagnosis, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, 450052, China. qh_wu77@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveThis study systematically characterized the global burden of pregnancy loss from 1990 to 2021 and evaluated the association between inflammatory markers and pregnancy loss, aiming to reduce the risk of pregnancy loss.

methodsA comprehensive analysis was conducted, encompassing the incidence, deaths, disability-adjusted life years (DALYs), and years lived with disability (YLDs), across a total of 204 countries. This analysis was complemented by the implementation of joinpoint regression and ARIMA models, which were utilized to assess trends and projections. Additionally, inflammatory markers were analyzed in a cohort of 5,517 U.S. women. The association between inflammatory markers and pregnancy loss was assessed using survey-weighted multivariate logistic regression. Subsequently, restricted cubic spline (RCS) plots were utilized to explore the non-linear association between inflammatory markers and pregnancy loss. Subgroup analyses were conducted to further elucidate the effects of other covariates on the association between inflammatory markers and pregnancy loss.

resultsGlobally, the incidence of pregnancy loss has been observed to decline at a rate of 1.5% per annum, with a concomitant decrease in mortality of 64.8% from 1990 to 2021. The regions exhibiting the highest-burden were those with a low socio-demographic index (SDI), with an average age-standardized incidence rate (ASIR) of 1,715.1 per 100,000. In contrast, High SDI regions demonstrated rates below 500 per 100,000. Projections indicate a continued global decline to 725.2 cases/100,000 by 2032, though High SDI regions may face rising rates (3.66% annually). A U-shaped association between neutrophil-to-lymphocyte ratio (NLR) and miscarriage risk was revealed by NHANES analysis, with moderate NLR levels (the third quartile-the fourth quartile) linked to reduced odds (OR: 0.75-0.76, p < 0.05). Subgroup analyses revealed stronger associations in women aged ≤ 35 years and those with a Body Mass Index (BMI) of 25-30 kg/m

conclusionsThese findings challenge the notion of linear inflammatory risk, emphasizing immune homeostasis's role in pregnancy maintenance. The study underscores persistent disparities in low-resource settings and advocates for integrating inflammatory markers into clinical risk stratification. Public health strategies must address inequities through targeted antenatal care, while high-income regions require interventions targeting delayed childbearing and metabolic health. This dual approach may mitigate the evolving global burden of pregnancy loss.

Indexed as

Abortion, SpontaneousInflammationAdultBiomarkersDisability-Adjusted Life YearsFemaleGlobal Burden of DiseaseGlobal HealthHumansIncidenceNutrition SurveysPregnancyRisk FactorsUnited StatesYoung AdultBiomarkersGlobal Burden of Disease (GBD 2021, 1990–2021)Inflammatory markersNational Health and Nutrition Examination Survey (NHANES)Pregnancy loss

Identifiers

PMID41034727
PMCPMC12486506

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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.