Evidence mapPaperPMID 41670733Full record

ArticleArchives of gynecology and obstetrics2026

Inflammation at the crossroads of reproduction: SIRI as a prognostic signature of female infertility in hybrid regression-machine learning models.

Mohammad Ali Khaksar, Mostafa Hosseinpour, Mohammad-Navid Bastani, Reza Mohammadpour Fard, Mehdi Zahedian, Amir Hossein Mahdizade, Seyed Sobhan Bahreiny

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Article in Archives of gynecology and obstetrics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Mohammad Ali KhaksarLillehei Heart Institute, University of Minnesota, Minneapolis, MN, 55455, USA.
Mostafa HosseinpourStudent Research Committee, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran.
Mohammad-Navid BastaniStudent Research Committee, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran.
Reza Mohammadpour FardStudent Research Committee, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran.
Mehdi ZahedianStudent Research Committee, Iran University of Medical Sciences, Tehran, Iran.
Amir Hossein MahdizadeStudent Research Committee, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran.
Seyed Sobhan BahreinyDepartment of Physiology, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran. bahsobi@gmail.com.ORCID 0000-0003-2148-1205

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundFemale infertility is a critical global health concern, with a rising prevalence and significant psychosocial consequences. This study aimed to investigate the association between Systemic Inflammatory Response Index (SIRI) and female infertility.

methodsThis cross-sectional study enrolled 3059 reproductive-aged women (18-45 years) to examine the association between SIRI and female infertility using data from the National Health and Nutrition Examination Survey (NHANES) spanning from 2015 to 2020. Multivariable logistic regression generalized additive models (GAM), restricted cubic splines (RCS), and threshold effect analyses were leveraged. Machine learning approaches were also utilized to validate predictive performance and identify key features.

resultsElevated SIRI was independently associated with increased odds of infertility. In the fully adjusted logistic model, each unit increase in SIRI corresponded to a 34% increase in infertility risk (OR 1.34, p = 0.001). Women in the highest SIRI quartile had more than double the odds of infertility compared to those in the lowest quartile (OR 2.08, p < 0.001), with a significant dose-response trend (p trend < 0.001). GAM and RCS models confirmed a monotonic and curvilinear association, respectively. Threshold analysis revealed a critical inflection point at SIRI = 1.66. Machine learning validation identified SIRI as one of the most influential predictors, with XGBoost achieving the highest (AUC = 0.866).

conclusionThese findings support the role of chronic systemic inflammation in female infertility and highlight SIRI as a valuable biomarker for risk prediction and clinical assessment.

Indexed as

Infertility, FemaleInflammationMachine LearningAdolescentAdultBiomarkersCross-Sectional StudiesFemaleHumansLogistic ModelsMiddle AgedNutrition SurveysPredictive Learning ModelsPrognosisYoung AdultBiomarkersFemale infertilityInflammatory biomarkerMachine learningNHANESSystemic Inflammation Response Index (SIRI)

Identifiers

PMID41670733
PMCPMC12894131

What Socratic 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 Socratic graph.