人工智能辅助口腔环境管理模式在颈动脉狭窄合并牙周炎患者中的应用研究  

Application of artificial intelligence-assisted oral environment management model in patients with carotid stenosis and periodontitis

作　　者：周艳[1] 赵梦扬 乔彤[1] 蔡颖[1] Zhou Yan;Zhao Mengyang;Qiao Tong;Cai Ying(Department of Vascular Surgery,the Affiliated Drum Tower Hospital of Nanjing University Medical School,Nanjing 210008,China)

机构地区：[1]南京大学医学院附属鼓楼医院血管外科,210008

出　　处：《中华脑血管病杂志(电子版)》2024年第6期528-534,共7页Chinese Journal of Cerebrovascular Diseases(Electronic Edition)

基　　金：国家自然科学基金资助项目(81870348)。

摘　　要：目的探讨利用人工智能辅助口腔环境管理模式在颈动脉狭窄合并牙周炎患者中的应用价值。方法选取2022年1月至2023年5月在南京鼓楼医院血管外科住院的颈动脉狭窄合并牙周炎的患者,利用人工智能识别斑块不稳定患者共80例,随机分为干预组和对照组,每组各40例。对照组实施健康教育模式,干预组在健康教育模式基础上实施口腔环境管理模式。采用重复测量方差分析比较不同时间点2组入院时,出院前,出院后3、6个月口腔健康素养量表得分、Beck口腔评分、牙菌斑指数;采用秩和检验比较2组术后3 d炎症指标变化;采用连续矫正χ^(2)检验比较2组出院后3、6个月再狭窄及卒中发生率的差异。结果经重复测量方差分析,干预组和对照组口腔健康素养量表得分在不同时间点、组别与时间点的交互作用比较差异有统计学意义(P<0.05),出院后6个月组间比较差异具有统计学意义[(172.35±27.73)分vs(160.17±23.36)分;t=-2.124,P=0.037]。2组患者Beck口腔评分不同时间点、组别与时间点的交互作用比较差异有统计学意义(P<0.05),出院后3、6个月组间比较差异具有统计学意义[(7.58±1.32)分vs(8.43±1.50)分,t=-2.692、P=0.009;(6.43±1.28)vs(7.28±1.36)分,t=-2.881、P=0.005]。2组患者牙菌斑指数在不同组别、不同时间点比较差异有统计学意义(P<0.05),出院后6个月组间比较差异有统计学意义(1.60±0.67 vs 1.95±0.50,t=-2.636,P=0.010)。口腔健康素养量表得分、Beck口腔评分及牙菌斑指数的组内比较:出院后6个月与入院时、出院时、出院后3个月比较,差异均有统计学意义(P均<0.05)。术后3 d,2组白细胞介素-6、中性粒细胞计数比较[3.24(2.09,5.60)pg/ml vs 6.65(4.70,8.50)pg/ml;3.60(3.20,4.00)×10^(9)/L vs 5.25(4.40,7.50)×10^(9)/L],差异具有统计学意义(Z=2.990、P=0.003;Z=-4.266、P=0.001)。出院后6个月2组并发症发生率比较[0(0.00%)vs 6(15.00%)],差异具有统计学意Objective To explore the application value of artificial intelligence-assisted oral environment management mode in patients with carotid artery stenosis and periodontitis.Methods 80 patients were enrolled with carotid artery stenosis and periodontitis hospitalized in the vascular surgery department of Nanjing Drum Tower Hospital from January 2022 to May 2023.Using artificial intelligence to identify unstable plaques,they were randomly assigned to either an intervention group or a control group,each with 40 cases.The control group implemented a standard health education model,while the intervention group implemented an oral environment management model based on the health education model.We employed repeated measures ANOVA to compare the scores of the Oral Health Literacy Scale,Beck Oral Score,and Plaque Index between the two groups at different time points:admission,pre-discharge,and at 3 and 6 months post-discharge;The rank sum test was used to compare the changes in inflammatory markers between the two groups 3 days post-surgery,and theχ^(2)test was used to compare the incidence of restenosis and stroke between the two groups at 3 and 6 months post-discharge.Results Repeated measures ANOVA revealed statistically significant difference in the Oral Health Literacy Scale scores between the intervention group and the control group at various time points,groups,and time points(P<0.05).The difference between the groups at 6 months post-discharge was statistically significant[(172.35±27.73)points vs(160.17±23.36)points;t=-2.124,P=0.037].Beck Oral Score also showed significant differences at different time points,groups,and time points(P<0.05),with significant differences at 3 and 6 months post-discharge[(7.58±1.32)points vs(8.43±1.50)points],t=-2.692,P=0.009;(6.43±1.28)points vs(7.28±1.36)points,t=-2.881,P=0.005].Plaque Index differences were significant at various groups and time points(P<0.05),with a significant difference at 6 months post-discharge(1.60±0.67 vs 1.95±0.50,t=-2.636,P=0.010).Intragroup compar

关 键 词：颈动脉狭窄 牙周炎 人工智能 口腔环境管理 护理干预 

分 类 号：R743.3[医药卫生—神经病学与精神病学]