title: The H.U.G.E. Formula (Hematocrit, Urea, Sex) for Screening Chronic Kidney Disease (CKD) in an Age-Stratified General Population.
abstract: OBJECTIVE
  
  
  
  OBJECTIVE
  To evaluate the screening power of the HUGE formula for the detection of chronic kidney disease (CKD) in a Spanish population sample obtained from the HERMEX study, a survey of cardiovascular risk factors carried out in the region of Extremadura, stratified by age.
  
  
  METHODS
  This was an observational, cross-sectional, population-based study. The final sample included 2,813 subjects selected from Health Care System records. Anthropometric data and cardiovascular risk factors were recorded. Hematocrit, urea, creatinine and microalbuminuria were analyzed, after which the HUGE formula was applied. Renal function, assessed as eGFR based on serum creatinine, was estimated following the MDRD-4 formula.
  
  
  RESULTS
  Using the HUGE formula, the estimated prevalence of CKD was 2.2% (men 2.2%, women 2.1%). The prevalence of CKD increased with age (5.0% in persons aged 60- 70 years and 9.6% in individuals over 70 years of age, p < 0.001) whereas with the MDRD formula the prevalence values were 9.8% and 15.5% respectively. The HUGE formula was seen to be highly specific (0.99). CKD was more common in persons >70 years, obese subjects, hypertensive patients, dyslipidemic subjects and those with microalbuminuria. Multivariate analysis revealed an independent negative association of CKD as the dependent variable with SBP, serum triglyceride levels and microalbuminuria.
  
  
  CONCLUSIONS
  The HUGE formula allows the prediction of CKD in the general population to be honed without relying on serum creatinine levels. This method was found to have a higher specificity than the MDRD-4 formula. Moreover, it could reduce the excessively extensive diagnostic suspicion of CKD in women.
authors.affiliation: Dr. N. Roberto Robles Perez-Monteoliva. Unidad de Hipertensión Arterial. Hospital Infanta Cristina. Carretera de Portugal s/n. 06080. Badajoz. SPAIN. E-mail: nrrobles@yahoo.es.
authors.forename: N R
authors.initials: NR
authors.lastname: Robles
authors.forename: F J
authors.initials: FJ
authors.lastname: Felix
authors.forename: L
authors.initials: L
authors.lastname: Lozano
authors.forename: I
authors.initials: I
authors.lastname: Miranda
authors.forename: D
authors.initials: D
authors.lastname: Fernandez-Berges
authors.forename: J F
authors.initials: JF
authors.lastname: Macías
mesh_terms: D000328:Adult; D017677:Age Distribution; D000367:Age Factors; D000368:Aged; D000375:Aging; D000419:Albuminuria / Q000175:diagnosis / Q000453:epidemiology; D000886:Anthropometry; D002318:Cardiovascular Diseases / Q000209:etiology; D003404:Creatinine / Q000097:blood; D003430:Cross-Sectional Studies; D050171:Dyslipidemias / Q000453:epidemiology; D005260:Female; D005919:Glomerular Filtration Rate; D006400:Hematocrit; D006801:Humans; D006973:Hypertension / Q000453:epidemiology; D008297:Male; D008403:Mass Screening; D008875:Middle Aged; D015999:Multivariate Analysis; D009765:Obesity / Q000453:epidemiology; D015995:Prevalence; D051436:Renal Insufficiency, Chronic / Q000097:blood* / Q000175:diagnosis* / Q000453:epidemiology; D012307:Risk Factors; D012727:Sex Characteristics; D012737:Sex Factors; D013030:Spain / Q000453:epidemiology; D014280:Triglycerides / Q000097:blood; D014508:Urea / Q000097:blood*
chemical_list: D014280:Triglycerides; D014508:Urea; D003404:Creatinine