摘要
目的 系统评价慢性牙周炎与绝经后骨质疏松(PMOP)的相关性.方法 电子检索Cochrane Library、Pubmed、Embase、Ovid、CNKI、CBM、VIP和WF数据库,收集慢性牙周炎与PMOP相关性的研究文献.采用Newcastle-Ottawa Scale(NOS)标准对纳入文献进行质量评价,采用RevMan 5.3软件进行meta分析,结局指标为临床附着丧失(CAL)、探诊深度(PD)、菌斑指数(PI)、牙石指数(GI)、探诊出血(BOP)以及简化口腔卫生指数(OHI-S).结果 共纳入16篇文献,共1 587例患者.与绝经后非骨质疏松组相比,骨质疏松组存在显著的CAL[标准化均数差(SMD)=1.09,95％CI:0.62～1.57,P＜0.001]、PD(SMD=0.71,95％CI:0.28～1.14,P＜0.001)、PI(SMD=0.43,95％CI:0.29～0.56,P＜0.001)及 OHI-S(SMD=0.28,95％CI:0.22～0.35,P＜0.001)指标异常,在 BOP(SMD=0.01,95％CI:-0.48～0.49,P=0.97)、GI(SMD=0.24,95％CI:-0.34～0.81,P=0.42)水平上,差异无统计学意义.结论 PMOP女性存在更显著的CAL、PD、PI、OHI-S等指标改变,提示绝经后骨质疏松女性更可能罹患牙周炎.
Abstract
Objective To systematically evaluate the correlation between chronic periodontitis and postmenopausal osteoporosis(PMOP).Methods Electronic searches were conducted on Cochrane Library,Pubmed,Embase,Ovid,CNKI,CBM,VIP,and WF databases to collect research literature on the correlation between chronic periodontitis and PMOP.The Newcastle Ottawa Scale(NOS)criteria were used to evaluate the quality of the included literature,and RevMan 5.3 software was used for meta-analysis.The outcome measures were clinical attachment loss(CAL),probing depth(PD),plaque index(PI),calculus index(CI),bleeding on probing(BOP),and simplified oral hygiene index(OHI-S).Results A total of 16 articles were included,with a total of 1587 patients.Compared with the postmenopausal non osteoporosis group,the osteoporosis group showed significant abnormalities in CAL[standardized mean difference(SMD)=1.09,95％CI:0.62-1.57,P＜0.001],PD(SMD=0.71,95％CI:0.28-1.14,P＜0.001),PI(SMD=0.43,95％CI:0.29-0.56,P＜0.001),and OHI-S(SMD=0.28,95％CI:0.22-0.35,P＜0.001)indicators,as well as in BOP(SMD=0.01,95％CI:-0.48-0.49,P=0.97)and GI(SMD=0.01,95％CI:-0.48-0.49,P=0.97).At the level of 0.24 and 95％CI:-0.34 to 0.81,P=0.42,there was no statistically significant difference.Conclusions Women with PMOP exhibit more significant changes in indicators such as CAL,PD,PI,and OHI-S,suggesting that postmenopausal women with osteoporosis are more likely to suffer from periodontitis.
维普
万方数据