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Table 1 Characteristics of SSc cases and non-cases in the training set

From: Rule-based and machine learning algorithms identify patients with systemic sclerosis accurately in the electronic health record

CharacteristicsSSc cases (n = 86)Non-cases (n = 94)p value1
Age, years, mean ± standard deviation68 ± 1459 ± 20< 0.01
Female, n (%)71 (83%)84 (89%)0.19
White, n (%)65 (76%)70 (75%)0.86
Number of counts of the SSc ICD-92 code (710.1), mean ± standard deviation10 ± 162 ± 5< 0.01
Number of counts of the SSc ICD-10-CM3 codes (M34*), mean ± standard deviation6 ± 72 ± 8< 0.01
Years of follow-up4, mean ± standard deviation7 ± 610 ± 7< 0.01
  1. 1Mann-Whitney U test for continuous variables and chi-square test for categorical variables
  2. 2ICD-9 International Classification of Diseases, Ninth Revision
  3. 3ICD-10-CM International Classification of Diseases, Tenth Revision, Clinical Modification
  4. 4Years of data available in the electronic health record from first to last ICD-9 and/or ICD-10-CM codes for any conditions