Abstract: Metabolic resilience in pregnancy refers to the paradoxical observation that subsets of women with thyroid or glucose dysregulation do not develop adverse maternal or neonatal outcomes. This systematic review and meta-analysis aimed to synthesize and critically appraise the evidence surrounding thyroid–glucose interactions and resilience mechanisms in pregnancy. Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines, we searched PubMed, Embase, Web of Science, and Scopus up to October 2025. Thirty-six eligible studies were identified from 1,154 screened records, of which 20 met criteria for “core evidence” with the lowest risk of bias. Studies encompassed prospective cohorts, retrospective analyses, randomized trial data, and systematic reviews spanning Asia, Europe, and North America. Risk of bias was assessed using the Newcastle–Ottawa Scale, Risk of Bias in Non-randomized Studies of Interventions, Risk of Bias tool for randomized trials, version 2, and A Measurement Tool to Assess Systematic Reviews, version 2 tools. Evidence demonstrates that elevated thyroid-stimulating hormone (TSH), low free thyroxine (FT4), or altered ratio of FT4 to TSH ratios increase gestational diabetes risk, but subgroups defined by adequate iodine intake, favorable body mass index phenotype, or fetal sex-specific placental modulation exhibit preserved outcomes. Mechanistic insights highlight nutriepigenomic buffering, immune-endocrine crosstalk, placental adaptation, and microbiome balance as resilience modifiers. Importantly, metabolically healthy obese women and treated thyroid dysfunction cohorts consistently demonstrated benign outcomes despite biochemical dysregulation. Synthesized findings converge on three domains of impact: Refinement of clinical prediction models for thyroid dysfunction and gestational diabetes, development of tailored interventions including sex-specific and iodine-sensitive strategies, and a forward research agenda emphasizing resilience biomarkers and artificial intelligence-assisted phenotyping. This review provides the first integrated evidence-to-impact framework for metabolic resilience in pregnancy, underscoring opportunities to redefine risk stratification and intervention strategies in perinatal medicine.
Andonotopo et al. (Thu,) studied this question.