AIMS: To evaluate various measures of haemoglobin (Hb) A1c variability, compared with average HbA1c, as independent predictors of mortality. MATERIALS AND METHODS: The Renal Insufficiency And Cardiovascular Events Italian multicentre study enroled 15 733 patients with type 2 diabetes from 19 diabetes clinics during 2006-2008. A total of 3 to 5 HbA1c measures, obtained during the 2-year period before enrolment, were available from 9 centres (8290 patients) and were used to calculate average HbA1c (HbA1c -MEAN) and HbA1c variability, measured as intra-individual standard deviation (HbA1c-SD), SD adjusted for the number of HbA1c assessments (HbA1c-AdjSD) and coefficient of variation (HbA1c-CV), that is, the HbA1c-SD to HbA1c-MEAN ratio. Vital status on October 31, 2015 was retrieved for 8252 patients (99.5%). RESULTS: The measures of HbA1c variability increased according to quartiles of HbA1c-MEAN and vice versa. HbA1c-MEAN and measures of HbA1c variability were associated with all-cause mortality; however, the strength of association of HbA1c-MEAN was lower than that of HbA1c -SD, HbA1c-CV or HbA1c-AdjSD, and disappeared after adjusting for confounders and any of the measures of HbA1c variability. Mortality increased with quartiles of HbA1c-MEAN, HbA1c -SD, HbA1c-CV and HbA1c-AdjSD, but only the association with HbA1c variability measures remained after adjustment for confounders and/or each other measure. In the fully adjusted model, mortality risk was lower for HbA1c-SD below the median and higher for HbA1c-SD above the median, regardless of whether HbA1c-MEAN was below or above the median. Conclusions HbA1c variability is a strong, independent predictor of all-cause mortality in type 2 diabetes and appears to be even more powerful than average HbA1c in predicting mortality.

Haemoglobin A1c variability is a strong, independent predictor of all-cause mortality in patients with type 2 diabetes

Gruden G.;
2018-01-01

Abstract

AIMS: To evaluate various measures of haemoglobin (Hb) A1c variability, compared with average HbA1c, as independent predictors of mortality. MATERIALS AND METHODS: The Renal Insufficiency And Cardiovascular Events Italian multicentre study enroled 15 733 patients with type 2 diabetes from 19 diabetes clinics during 2006-2008. A total of 3 to 5 HbA1c measures, obtained during the 2-year period before enrolment, were available from 9 centres (8290 patients) and were used to calculate average HbA1c (HbA1c -MEAN) and HbA1c variability, measured as intra-individual standard deviation (HbA1c-SD), SD adjusted for the number of HbA1c assessments (HbA1c-AdjSD) and coefficient of variation (HbA1c-CV), that is, the HbA1c-SD to HbA1c-MEAN ratio. Vital status on October 31, 2015 was retrieved for 8252 patients (99.5%). RESULTS: The measures of HbA1c variability increased according to quartiles of HbA1c-MEAN and vice versa. HbA1c-MEAN and measures of HbA1c variability were associated with all-cause mortality; however, the strength of association of HbA1c-MEAN was lower than that of HbA1c -SD, HbA1c-CV or HbA1c-AdjSD, and disappeared after adjusting for confounders and any of the measures of HbA1c variability. Mortality increased with quartiles of HbA1c-MEAN, HbA1c -SD, HbA1c-CV and HbA1c-AdjSD, but only the association with HbA1c variability measures remained after adjustment for confounders and/or each other measure. In the fully adjusted model, mortality risk was lower for HbA1c-SD below the median and higher for HbA1c-SD above the median, regardless of whether HbA1c-MEAN was below or above the median. Conclusions HbA1c variability is a strong, independent predictor of all-cause mortality in type 2 diabetes and appears to be even more powerful than average HbA1c in predicting mortality.
2018
20
8
1885
1893
http://onlinelibrary.wiley.com/journal/10.1111/(ISSN)1463-1326
all-cause mortality; cardiovascular risk factors; complications; HbA1c; type 2 diabetes; variability; Aged; Cardiovascular Diseases; Cohort Studies; Diabetes Mellitus, Type 2; Diabetic Angiopathies; Diabetic Cardiomyopathies; Diabetic Nephropathies; Follow-Up Studies; Glomerular Filtration Rate; Glycated Hemoglobin A; Humans; Hyperglycemia; Hypoglycemia; Italy; Kidney; Male; Middle Aged; Mortality; Prevalence; Prospective Studies; Renal Insufficiency; Risk Factors
Orsi E.; Solini A.; Bonora E.; Fondelli C.; Trevisan R.; Vedovato M.; Cavalot F.; Gruden G.; Morano S.; Nicolucci A.; Penno G.; Pugliese G.
File in questo prodotto:
File Dimensione Formato  
Orsi_et_al-2018-Diabetes,_Obesity_and_Metabolism.pdf

Accesso riservato

Descrizione: PDF editoriale
Tipo di file: PDF EDITORIALE
Dimensione 1.19 MB
Formato Adobe PDF
1.19 MB Adobe PDF   Visualizza/Apri   Richiedi una copia

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/1719145
Citazioni
  • ???jsp.display-item.citation.pmc??? 23
  • Scopus 49
  • ???jsp.display-item.citation.isi??? 44
social impact