Low bone mineral density and its predictors in type 1 diabetic patients evaluated by the classic statistics and artificial neural network analysis

Cristina Eller-Vainicher, Volha V. Zhukouskaya, Yury V. Tolkachev, Sergei S. Koritko, Elisa Cairoli, Enzo Grossi, Paolo Beck-Peccoz, Iacopo Chiodini, Alla P. Shepelkevich

Research output: Contribution to journalArticlepeer-review

Abstract

OBJECTIVE - To investigate factors associated with bone mineral density (BMD) in type 1 diabetes by classic statistic and artificial neural networks. RESEARCH DESIGN AND METHODS - A total of 175 eugonadal type 1 diabetic patients (age 32.8 ± 8.4 years) and 151 age- and BMI-matched control subjects (age 32.6 ± 4.5 years) were studied. In all subjects, BMI and BMD (as Z score) at the lumbar spine (LS-BMD) and femur (F-BMD) were measured. Daily insulin dose (DID), age at diagnosis, presence of complications, creatinine clearance (ClCr), and HbA 1c were determined. RESULTS - LS- and F-BMD levels were lower in patients (20.11 ± 1.2 and 20.32 ± 1.4, respectively) than in control subjects (0.59 ± 1, P <0.0001, and 0.63 ± 1, P <0.0001, respectively). LS-BMD was independently associated with BMI and DID, whereas F-BMD was associated with BMI and ClCr. The cutoffs for predicting low BMD were as follows: BMI 2, DID >0.67 units/kg, and ClCr

Original languageEnglish
Pages (from-to)2186-2191
Number of pages6
JournalDiabetes Care
Volume34
Issue number10
DOIs
Publication statusPublished - Oct 2011

ASJC Scopus subject areas

  • Internal Medicine
  • Endocrinology, Diabetes and Metabolism
  • Advanced and Specialised Nursing

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