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Association of periodontitis and gingivitis with stroke: A systematic review and meta-analysis
Meghna Dewan1, Awadh Kishor Pandit2, Lata Goyal3
1Private practice (former scientist at All India Institute of Medical Sciences (AIIMS), New Delhi, India).
Background:
Stroke is among the leading causes of morbidity and mortality. Chronic inflammatory conditions may lead to atherosclerosis and a subsequent stroke.
Objectives:
This systematic review and meta-analysis aimed to review the association of periodontitis and gingivitis with stroke.
Methods:
An electronic search of PubMed, Ovid EMBASE, Ovid MEDLINE, Web of Science, Cochrane Central Register of Controlled Trials (CENTRAL), Science Citation Index, Database of Abstracts and Reviews of Effects (DARE), and various clinical trial registries was conducted to include studies published up to February 2022. Data was retrieved by 2 independent reviewers. The Stata software, v. 13, was used to conduct a meta-analysis.
Results:
Thirteen studies stated an association between periodontitis, determined based on clinical attachment loss (CAL), and stroke. Meanwhile, 6 studies described an association between gingivitis, determined based on the gingival index (GI), and stroke. Out of the 6 studies on gingivitis, 5 also investigated CAL, which means the meta-analysis included 14 studies in total. The total number of participants from the included studies was 35,937, and they were all above 17 years of age. There was a significant association between periodontitis and gingivitis and stroke and its all types. There was a significant association between periodontitis and stroke and its all types in 13 studies (ES (effect size): 1.32; 95% CI (confidence interval): 1.04-1.60), and between gingivitis and all stroke types in 6 studies (ES: 1.17; 95% CI: 0.42-1.92).
Conclusions:
This systematic review indicated a significant association between stroke and periodontal disease in case-control, cohort and cross-sectional studies. The findings need to be further substantiated in prospective cohort studies with an optimal sample size.
