Kumari Ranjana, Suhagia Bansariben, Maheshwari R, Singh Mamta
BDS, Kothiwal Dental College and Research Centre, Moradabad, Uttar Pradesh, India.
BDS, Ahmedabad Dental College and Hospital, Ahmedabad, Gujarat, India.
J Pharm Bioallied Sci. 2025 May;17(Suppl 1):S339-S341. doi: 10.4103/jpbs.jpbs_533_25. Epub 2025 Apr 9.
Endo-perio lesions are complex pathological conditions involving concurrent infections in endodontic and periodontal tissues. These lesions often present diagnostic and therapeutic challenges due to overlapping microbial etiologies and anatomical intercommunications.
To investigate the microbiological composition and evaluate diagnostic methods for effective differentiation and management of endo-perio lesions.
A cross-sectional study was conducted, enrolling 120 patients diagnosed with endo-perio lesions. Samples from root canals and periodontal pockets were analyzed using conventional culturing, polymerase chain reaction (PCR), and next-generation sequencing (NGS). Diagnostic tools such as radiographic imaging, clinical parameters, and microbial tests were assessed. Baseline and final data were statistically analyzed using paired -tests and logistic regression models.
Microbial analysis revealed distinct profiles in primary endodontic (, ), primary periodontal (, ), and combined lesions, with significant microbial diversity in the latter. PCR and NGS demonstrated higher diagnostic sensitivity (90%) and specificity (85%) compared with conventional methods. Statistical analysis showed significant differences in microbial abundance and diagnostic accuracy across lesion types ( < 0.05).
Endo-perio lesions exhibit unique microbial ecosystems that necessitate precise diagnostic approaches. Integration of advanced microbial diagnostics with clinical findings enhances lesion classification and treatment outcomes.
牙髓-牙周联合病变是一种复杂的病理状况,涉及牙髓组织和牙周组织的同时感染。由于微生物病因重叠和解剖学上的相互连通,这些病变常常带来诊断和治疗方面的挑战。
研究牙髓-牙周联合病变的微生物组成,并评估有效鉴别和管理此类病变的诊断方法。
进行了一项横断面研究,纳入120例被诊断为牙髓-牙周联合病变的患者。使用传统培养法、聚合酶链反应(PCR)和新一代测序(NGS)对根管和牙周袋样本进行分析。对诸如影像学检查、临床参数和微生物检测等诊断工具进行评估。使用配对t检验和逻辑回归模型对基线数据和最终数据进行统计学分析。
微生物分析揭示了原发性牙髓病变( , )、原发性牙周病变( , )和联合病变中不同的微生物谱,联合病变中微生物多样性显著。与传统方法相比,PCR和NGS显示出更高的诊断敏感性(90%)和特异性(85%)。统计学分析表明,不同病变类型之间微生物丰度和诊断准确性存在显著差异( < 0.05)。
牙髓-牙周联合病变呈现出独特的微生物生态系统,需要精确的诊断方法。将先进的微生物诊断与临床发现相结合可提高病变分类和治疗效果。