Discovering medical conditions associated with periodontitis using linked electronic health records. (15th March 2013)

• Record Type: Journal Article
• Authors: Boland, Mary Regina; Hripcsak, George; Albers, David J.; Wei, Ying; Wilcox, Adam B.; Wei, Jin; Li, Jianhua; Lin, Steven; Breene, Michael; Myers, Ronnie; Zimmerman, John; Papapanou, Panos N.; Weng, Chunhua
• Is Part Of: Journal of clinical periodontology. Volume 40:Number 5(2013:May)
• Page Start: 474
• Page End: 482
• Publication Date: 2013-03-15
• Subjects: data linkage -- dental records -- electronic health records -- medical informatics -- periodontal diseases; Periodontics -- Periodicals; 617.6
• DOI: 10.1111/jcpe.12086
• Languages: English
• ISSNs: 0303-6979

Abstract

Abstract: Aim: To use linked electronic medical and dental records to discover associations between periodontitis and medical conditions independent of a priori hypotheses. Materials and Methods: This case‐control study included 2475 patients who underwent dental treatment at the College of Dental Medicine at Columbia University and medical treatment at NewYork‐Presbyterian Hospital. Our cases are patients who received periodontal treatment and our controls are patients who received dental maintenance but no periodontal treatment. Chi‐square analysis was performed for medical treatment codes and logistic regression was used to adjust for confounders. Results: Our method replicated several important periodontitis associations in a largely Hispanic population, including diabetes mellitus type I (OR = 1.6, 95% CI 1.30–1.99, p < 0.001) and type II (OR = 1.4, 95% CI 1.22–1.67, p < 0.001), hypertension (OR = 1.2, 95% CI 1.10–1.37, p < 0.001), hypercholesterolaemia (OR = 1.2, 95% CI 1.07–1.38, p = 0.004), hyperlipidaemia (OR = 1.2, 95% CI 1.06–1.43, p = 0.008) and conditions pertaining to pregnancy and childbirth (OR = 2.9, 95% CI: 1.32–7.21, p = 0.014). We also found a previously unreported association with benign prostatic hyperplasia (OR = 1.5, 95% CI 1.05–2.10, p = 0.026) after adjusting for age, gender, ethnicity, hypertension, diabetes, obesity, lipid and circulatory system conditions, alcohol and tobacco abuse. Conclusions: This study contributes a high‐throughput method for associating periodontitis with systemic diseases using linked electronic records.