title: Predicting the risk of diabetic retinopathy in type 2 diabetic patients.
abstract: OBJECTIVE
  Diabetic retinopathy (DR) is often asymptomatic even in its more advanced stages. Timely and repeated screening for DR avoids a late diagnosis of DR, but the high number of diabetic patients precludes a frequent screening; thus, the need for a method to identify patients at higher risk for DR becomes crucial.
  
  
  METHODS
  A prospective analysis of 5034 type 2 diabetic patients followed from 1996 to 2007 and not affected by retinopathy at the time of the recruitment was performed. Patients were randomly divided (ratio 2:1) into two groups: the train data set and the test set (3327 and 1707 patients, respectively). Factors associated with the occurrence of DR were assessed by the Cox's proportional hazard model.
  
  
  RESULTS
  Duration of diabetes, glycosylated hemoglobin, systolic blood Pressure, male gender, albuminuria and diabetes therapy other than diet were all significantly associated with the occurrence of DR.
  
  
  CONCLUSIONS
  The nomogram could help in ranking the type 2 diabetic patients at higher risk to develop DR and thus with a need for more frequent ophthalmologic checks, without enhancing neither the time nor the costs.
authors.affiliation: Section of Ophthalmology, Department of Surgical Specialities and Forensic Medicine, University of Brescia, Brescia, Italy.
authors.forename: Francesco
authors.initials: F
authors.lastname: Semeraro
authors.forename: Giovanni
authors.initials: G
authors.lastname: Parrinello
authors.forename: Anna
authors.initials: A
authors.lastname: Cancarini
authors.forename: Luisa
authors.initials: L
authors.lastname: Pasquini
authors.forename: Emanuela
authors.initials: E
authors.lastname: Zarra
authors.forename: Antonio
authors.initials: A
authors.lastname: Cimino
authors.forename: Giovanni
authors.initials: G
authors.lastname: Cancarini
authors.forename: Umberto
authors.initials: U
authors.lastname: Valentini
authors.forename: Ciro
authors.initials: C
authors.lastname: Costagliola
mesh_terms: D000368:Aged; D000419:Albuminuria / Q000150:complications; D001185:Artificial Intelligence; D003663:Decision Trees; D003924:Diabetes Mellitus, Type 2 / Q000097:blood / Q000150:complications* / Q000188:drug therapy / Q000652:urine; D003930:Diabetic Retinopathy / Q000453:epidemiology*; D005260:Female; D005500:Follow-Up Studies; D006442:Glycated Hemoglobin / Q000032:analysis; D006801:Humans; D006973:Hypertension / Q000150:complications; D007558:Italy / Q000453:epidemiology; D008297:Male; D008875:Middle Aged; D049451:Nomograms; D016016:Proportional Hazards Models; D011446:Prospective Studies; D012189:Retrospective Studies; D012307:Risk Factors; D012737:Sex Factors; D015351:Vision Screening
chemical_list: D006442:Glycated Hemoglobin; C517652:hemoglobin A1c protein, human