Effect Of Scaling And Root Planning In Reducing The Risk Of Preterm Birth Among Pregnant Women - A Systematic Review And Meta-Analysis

Abstract

Background: Preterm birth is a major public health issue in India, one of the top five contributors to the 13.4 million global cases in 2020. Maternal periodontal disease is linked to increased risk of preterm birth and low birth weight. However, the impact of treating periodontal disease during pregnancy remains unclear. This systematic review and meta-analysisaimed to assess the effect of scaling and root planning (SRP) in reducing the risk of preterm birth among pregnant women.

Methods: A systematic review with meta-analysis was conducted following PRISMA guidelines. PROSPERO registration was done (ID: CRD42024518915). A comprehensive search strategy was employed across electronic databases, including PubMed/Medline, Embase, Scopus, and Web of Science. The systematic review was conducted using CADIMA software, with critical appraisal of included studies performed using the JBI tool. The certainty of evidence for the outcomes was evaluated using the GRADE approach by the GRADEpro GDT tool. Meta-analysis was performed in RevMan, calculating pooled risk ratios (RRs) with 95% confidence intervals (CIs) using a random-effects model.

Results: Out of109 initially identified reports, 7 RCTs met the inclusion criteria. Out of the included studies, 5 RCTs involving 1,458 pregnant women were analyzed to evaluate the effect of scaling and root planning (SRP) during pregnancy on the risk of preterm birth (PTB). Meta-analysis using a random-effects model showed that SRP was associated with a lower risk of PTB (pooled estimate [OR] = 0.59, 95% CI: 0.34–1.02). However, the result did not reach statistical significance (P = 0.06). Moderate heterogeneity was observed across studies (I² = 68%).

Conclusion: SRP during pregnancy was associated with a lower risk of preterm birth, though the effect did not reach statistical significance. The included RCTs were limited by moderate heterogeneity and variation in study design. Larger, well-conducted trials are needed to confirm these findings and inform clinical practice.