CONTEXT: There are limited published data characterizing severe hypoglycemia complicating type 2 diabetes. OBJECTIVE: The objective of the study was to determine the incidence and predictors of severe hypoglycemia in community-dwelling type 2 patients. DESIGN: This was a longitudinal observational cohort study. SETTING: This was a community-based study. PATIENTS: There were 616 patients (mean age 67.0 yr, 52.3% males, median diabetes duration 7.7 yr) assessed in 1998 and followed up to the end of June 2006. MAIN OUTCOME MEASURES: Severe hypoglycemia defined as that requiring ambulance attendance, emergency department services, and/or hospitalization. Cox proportional hazards modeling was used to determine predictors of first episode, and Poisson, negative binomial, zero-inflated Poisson, and zero-inflated negative binomial regression models identified predictors of frequency. RESULTS: Fifty-two (8.4%) experienced 66 episodes during 3953 patient-years (incidence 1.7 per 100 patient-years). Those experiencing severe hypoglycemia had one to four episodes. Significant independent predictors of time to first episode were duration of insulin treatment, estimated glomerular filtration rate less than 60 ml/min per 1.73 m(2), peripheral neuropathy, education beyond primary level, and past severe hypoglycemia. The zero-inflated negative binomial provided the best model of severe hypoglycemia frequency. Lower fasting serum glucose and higher glycosylated hemoglobin were significantly associated with frequency, whereas patients at minimal risk of repeated severe hypoglycemia were unlikely to use insulin or to have short-duration insulin treatment, to have renal impairment or peripheral neuropathy, or to be educated beyond primary level. CONCLUSIONS: Duration of insulin treatment was confirmed as an independent risk factor for severe hypoglycemia. The novel association with educational attainment suggests knowledge-driven intensive glycemic self-management. The positive relationship between frequency and glycosylated hemoglobin may identify patients with unstable glycemic control.
CONTEXT: There are limited published data characterizing severe hypoglycemia complicating type 2 diabetes. OBJECTIVE: The objective of the study was to determine the incidence and predictors of severe hypoglycemia in community-dwelling type 2 patients. DESIGN: This was a longitudinal observational cohort study. SETTING: This was a community-based study. PATIENTS: There were 616 patients (mean age 67.0 yr, 52.3% males, median diabetes duration 7.7 yr) assessed in 1998 and followed up to the end of June 2006. MAIN OUTCOME MEASURES: Severe hypoglycemia defined as that requiring ambulance attendance, emergency department services, and/or hospitalization. Cox proportional hazards modeling was used to determine predictors of first episode, and Poisson, negative binomial, zero-inflated Poisson, and zero-inflated negative binomial regression models identified predictors of frequency. RESULTS: Fifty-two (8.4%) experienced 66 episodes during 3953 patient-years (incidence 1.7 per 100 patient-years). Those experiencing severe hypoglycemia had one to four episodes. Significant independent predictors of time to first episode were duration of insulin treatment, estimated glomerular filtration rate less than 60 ml/min per 1.73 m(2), peripheral neuropathy, education beyond primary level, and past severe hypoglycemia. The zero-inflated negative binomial provided the best model of severe hypoglycemia frequency. Lower fasting serum glucose and higher glycosylated hemoglobin were significantly associated with frequency, whereas patients at minimal risk of repeated severe hypoglycemia were unlikely to use insulin or to have short-duration insulin treatment, to have renal impairment or peripheral neuropathy, or to be educated beyond primary level. CONCLUSIONS: Duration of insulin treatment was confirmed as an independent risk factor for severe hypoglycemia. The novel association with educational attainment suggests knowledge-driven intensive glycemic self-management. The positive relationship between frequency and glycosylated hemoglobin may identify patients with unstable glycemic control.
Authors: Alexandra K Lee; Clare J Lee; Elbert S Huang; A Richey Sharrett; Josef Coresh; Elizabeth Selvin Journal: Diabetes Care Date: 2017-09-19 Impact factor: 19.112
Authors: J Hans DeVries; Luigi Meneghini; Anthony H Barnett; Timothy Reid; Marie-Paule Dain; Wolfgang Landgraf; Aleksandra Vlajnic; Louise Traylor; Richard M Bergenstal Journal: Eur Endocrinol Date: 2014-02-28
Authors: Wayne J Katon; Bessie A Young; Joan Russo; Elizabeth H B Lin; Paul Ciechanowski; Evette J Ludman; Michael R Von Korff Journal: Ann Fam Med Date: 2013 May-Jun Impact factor: 5.166