Comorbidity study on type 2 diabetes mellitus using data mining.
OBJECTIVE
The aim of this study was to analyze comorbidity in patients with type 2 diabetes mellitus (T2DM) by using association rule mining (ARM).


METHODS
We used data from patients who visited Keimyung University Dongsan Medical Center from 1996 to 2007. Of 411,414 total patients, T2DM was present in 20,314. The Dx Analyze Tool was developed for data cleansing and data mart construction, and to reveal associations of comorbidity.


RESULTS
Eighteen associations reached threshold (support, ≥ 3%; confidence, ≥ 5%). The highest association was found between T2DM and essential hypertension (support, 17.43%; confidence, 34.86%). Six association rules were found among three comorbid diseases. Among them, essential hypertension was an important node between T2DM and stroke (support, 4.06%; confidence, 8.12%) as well as between T2DM and dyslipidemia (support, 3.44%; confidence, 6.88%).


CONCLUSIONS
Essential hypertension plays an important role in the association between T2DM and its comorbid diseases. The Dx Analyze Tool is practical for comorbidity studies that have an enormous clinical database.
Department of Internal Medicine, Keimyung University School of Medicine, Daegu, Korea.
Hye Soon
HS
Kim
A Mi
AM
Shin
Mi Kyung
MK
Kim
Yoon Nyun
YN
Kim
D000046:Academic Medical Centers / Q000706:statistics & numerical data; D000465:Algorithms; D016022:Case-Control Studies; D016009:Chi-Square Distribution; D015897:Comorbidity; D057225:Data Mining / Q000706:statistics & numerical data*; D016208:Databases, Factual / Q000706:statistics & numerical data; D003924:Diabetes Mellitus, Type 2 / Q000453:epidemiology*; D050171:Dyslipidemias / Q000453:epidemiology; D006801:Humans; D006973:Hypertension / Q000453:epidemiology; D056910:Republic of Korea / Q000453:epidemiology; D020521:Stroke / Q000453:epidemiology