title: Discovering medical conditions associated with periodontitis using linked electronic health records.
abstract: OBJECTIVE
  To use linked electronic medical and dental records to discover associations between periodontitis and medical conditions independent of a priori hypotheses.
  
  
  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.
authors.affiliation: Department of Biomedical Informatics, Columbia University, New York, NY 10032, USA. mab7036@dbmi.columbia.edu
authors.forename: Mary Regina
authors.initials: MR
authors.lastname: Boland
authors.forename: George
authors.initials: G
authors.lastname: Hripcsak
authors.forename: David J
authors.initials: DJ
authors.lastname: Albers
authors.forename: Ying
authors.initials: Y
authors.lastname: Wei
authors.forename: Adam B
authors.initials: AB
authors.lastname: Wilcox
authors.forename: Jin
authors.initials: J
authors.lastname: Wei
authors.forename: Jianhua
authors.initials: J
authors.lastname: Li
authors.forename: Steven
authors.initials: S
authors.lastname: Lin
authors.forename: Michael
authors.initials: M
authors.lastname: Breene
authors.forename: Ronnie
authors.initials: R
authors.lastname: Myers
authors.forename: John
authors.initials: J
authors.lastname: Zimmerman
authors.forename: Panos N
authors.initials: PN
authors.lastname: Papapanou
authors.forename: Chunhua
authors.initials: C
authors.lastname: Weng
mesh_terms: D000328:Adult; D000368:Aged; D000437:Alcoholism / Q000453:epidemiology; D016022:Case-Control Studies; D059019:Clinical Coding; D015986:Confounding Factors, Epidemiologic; D003625:Data Collection; D057225:Data Mining; D003792:Dental Records; D003922:Diabetes Mellitus, Type 1 / Q000453:epidemiology; D003924:Diabetes Mellitus, Type 2 / Q000453:epidemiology; D057286:Electronic Health Records; D004813:Epidemiology; D005260:Female; D006630:Hispanic or Latino / Q000706:statistics & numerical data; D006801:Humans; D006937:Hypercholesterolemia / Q000453:epidemiology; D006949:Hyperlipidemias / Q000453:epidemiology; D006973:Hypertension / Q000453:epidemiology; D008297:Male; D008875:Middle Aged; D009518:New York / Q000453:epidemiology; D009765:Obesity / Q000453:epidemiology; D036801:Parturition; D010518:Periodontitis / Q000453:epidemiology*; D011247:Pregnancy; D011470:Prostatic Hyperplasia / Q000453:epidemiology; D014029:Tobacco Use Disorder / Q000453:epidemiology