IMPACT OF PROGESTOGEN-CONTAINING HORMONAL THERAPY ON SOFT-TISSUE AND BONE HEALING AFTER ORAL SURGERY: AN INTEGRATED COMPUTATIONAL AND STATISTICAL FRAMEWORK FOR SYSTEMATIC REVIEW AND META-ANALYSIS
DOI:
https://doi.org/10.4238/4bhvz961Keywords:
Progesterone, hormone replacement therapy, oral contraceptives, alveolar osteitis, wound healing, dental extractionAbstract
Background: Sex steroid hormones influence oral wound healing, yet postoperative outcomes differ across progestogen-containing hormonal states. Therapeutic progesterone and hormone replacement therapy (HRT) aim to restore physiological balance, whereas combined oral contraceptives (OCPs) maintain constant synthetic hormone levels, potentially producing distinct surgical effects.
Aim: To compare the impact of therapeutic progesterone/HRT versus OCP exposure on soft-tissue healing, bone regeneration, and alveolar osteitis (AO) risk after surgery.
Methods: Following PRISMA 2020 guidelines (PROSPERO: CRD420251238949), PubMed, Embase, Scopus, and Cochrane Library searches (2000–2025) identified randomized and observational studies assessing postoperative outcomes in women using progesterone, HRT or OCPs. Two reviewers independently screened and extracted data; risk of bias was assessed using RoB 2 and the Newcastle–Ottawa Scale. Random effects computational meta-analytic models generated pooled standardized mean differences (SMDs) and risk ratios (RRs).
Results: Eighteen studies met the inclusion criteria. Therapeutic progesterone/HRT improved periodontal indices, soft-tissue healing and bone outcomes (pooled SMD = 0.72). In contrast, OCP users showed a significantly higher AO incidence after third molar surgery (RR = 2.35; 95% CI: 1.58–3.48). No meaningful publication bias was detected.
Conclusion: Progesterone and HRT support favourable postoperative healing, whereas OCPs markedly increase AO risk. Understanding these divergent hormonal states is essential for preoperative counselling, surgical timing and targeted prevention. The integrated computational and statistical framework employed in this study highlights the value of advanced evidence-synthesis methodologies in biomedical and clinical decision-making.
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