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Discovering medical conditions associated with periodontitis using linked electronic health records
Author(s) -
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
Publication year - 2013
Publication title -
journal of clinical periodontology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.456
H-Index - 151
eISSN - 1600-051X
pISSN - 0303-6979
DOI - 10.1111/jcpe.12086
Subject(s) - medicine , periodontitis , medical record , population , diabetes mellitus , odds ratio , confounding , logistic regression , environmental health , endocrinology
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.