title: A new tool to detect kidney disease in Chinese type 2 diabetes patients: comparison of EZSCAN with standard screening methods.
abstract: BACKGROUND
  EZSCAN(®) (Impeto Medical, Paris, France), a noninvasive device that assesses sweat gland dysfunction using reverse iontophoresis, also detects early dysglycemia. Given the interrelationships among dysglycemia, vasculopathy, and neuropathy, EZSCAN may detect kidney disease in diabetes (DKD).
  
  
  METHODS
  An EZSCAN score (0-100) was calculated using a proprietary algorithm based on the chronoamperometry analysis. We measured the score in 50 Chinese type 2 diabetes patients without DKD (urinary albumin-creatinine ratio [ACR] <2.5 mg/mmol in men or ACR <3.5 mg/mmol in women and estimated glomerular filtration rate [eGFR] >90 mL/min/1.73 m(2)) and 50 with DKD (ACR ≥25 mg/mmol and eGFR <60 mL/min/1.73 m(2)). We used spline analysis to determine the threshold value of the score in detecting DKD and its sensitivity and specificity.
  
  
  RESULTS
  EZSCAN scores were highly correlated with log values of eGFR (r=0.67, P<0.0001) and ACR (r=-0.66, P<0.0001). Using a cutoff value of 55, the score had 94% sensitivity, 78% specificity, and a likelihood ratio of 4.2 to detect DKD with a positive predictive value of 81% and a negative predictive value of 93%. On multivariable analysis, DKD was independently associated with EZSCAN score (β=-0.72, P=0.02), smoking status (1=never, 0=current/former) (β=-2.37, P=0.02), retinopathy (1=yes, 0=no) (β=3.019, P=0.01), triglycerides (β=2.56, P=0.013), and blood hemoglobin (β=-0.613, P=0.04). Patients without DKD but low EZSCAN score (n=10) had longer duration of disease (median [interquartile range], 13 [9-17] vs. 8 [4-16] years; P=0.017) and were more likely to have retinopathy (36.7% vs. 5.1%, P=0.02), lower eGFR (98 [95.00-103] vs. 106 [98.5-115], P=0.036), and treatment with renin-angiotensin system blockers (81.8% vs. 25.6%, P=0.002) than those with a normal score.
  
  
  CONCLUSIONS
  EZSCAN may detect high-risk subjects for DKD in Chinese populations.
authors.affiliation: Department of Medicine & Therapeutics and Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, The Prince of Wales Hospital, Hong Kong SAR, China.
authors.forename: Risa
authors.initials: R
authors.lastname: Ozaki
authors.forename: Kitty K T
authors.initials: KK
authors.lastname: Cheung
authors.forename: Enoch
authors.initials: E
authors.lastname: Wu
authors.forename: Alice
authors.initials: A
authors.lastname: Kong
authors.forename: Xilin
authors.initials: X
authors.lastname: Yang
authors.forename: Eric
authors.initials: E
authors.lastname: Lau
authors.forename: Philippe
authors.initials: P
authors.lastname: Brunswick
authors.forename: Jean-Henri
authors.initials: JH
authors.lastname: Calvet
authors.forename: Jean-Paul
authors.initials: JP
authors.lastname: Deslypere
authors.forename: Juliana C N
authors.initials: JC
authors.lastname: Chan
mesh_terms: D000328:Adult; D000368:Aged; D000465:Algorithms; D002681:China / Q000453:epidemiology; D003404:Creatinine / Q000652:urine; D003924:Diabetes Mellitus, Type 2 / Q000150:complications* / Q000503:physiopathology / Q000652:urine; D003928:Diabetic Nephropathies / Q000453:epidemiology*; D003930:Diabetic Retinopathy / Q000453:epidemiology; D005260:Female; D005919:Glomerular Filtration Rate; D006801:Humans; D006943:Hyperglycemia / Q000175:diagnosis; D007003:Hypoglycemia / Q000175:diagnosis; D007478:Iontophoresis / Q000295:instrumentation; D008297:Male; D008403:Mass Screening / Q000295:instrumentation*; D008422:Materials Testing; D008875:Middle Aged; D012307:Risk Factors; D012680:Sensitivity and Specificity; D013545:Sweat Glands / Q000503:physiopathology
chemical_list: D003404:Creatinine