Limits...
The true value of HbA1c as a predictor of diabetic complications: simulations of HbA1c variables.

Lind M, Odén A, Fahlén M, Eliasson B - PLoS ONE (2009)

Bottom Line: Continuous HbA1c curves for 10,000 hypothetical diabetes patients were simulated over an average of 7 years.We tested several different HbA1c variables including various profiles, e.g. different duration, of such a long-lasting effect.The predictive power of these variables was compared with that of the updated mean HbA1c.

View Article: PubMed Central - PubMed

Affiliation: Department of Medicine, Uddevalla Hospital, Uddevalla, Sweden. lind.marcus@telia.com

ABSTRACT

Aim: The updated mean HbA1c has been used in risk estimates of diabetic complications, but it does not take into account the temporal relationship between HbA1c and diabetic complications. We studied whether the updated mean HbA1c underestimated the risk of diabetic complications.

Method: Continuous HbA1c curves for 10,000 hypothetical diabetes patients were simulated over an average of 7 years. Simulations were based on HbA1c values encountered in clinical practice. We assumed that each short time interval of the continuous HbA1c curves had a long-lasting effect on diabetic complications, as evidenced by earlier studies. We tested several different HbA1c variables including various profiles, e.g. different duration, of such a long-lasting effect. The predictive power of these variables was compared with that of the updated mean HbA1c.

Results: The predictive power of the constructed HbA1c variables differed considerably compared to that of the updated mean HbA1c. The risk increase per standard deviation could be almost 100% higher for a constructed predictor than the updated mean HbA1c.

Conclusions: The importance of good glycemic control in preventing diabetic complications could have been underestimated in earlier hallmark studies by not taking the time-dependent effect of HbA1c into account.

Show MeSH

Related in: MedlinePlus

Gradients of risk.Gradient of risk for the updated mean HbA1c and the corresponding estimated gradient for an assumed optimal HbA1c variable. The correlation coefficient between the constructed variables versus the updated mean ranged from 0.53–0.78 and the figure illustrates the cases 0.5, 0.6, 0.7 and 0.8.
© Copyright Policy
Related In: Results  -  Collection


getmorefigures.php?uid=PMC2636883&req=5

pone-0004412-g004: Gradients of risk.Gradient of risk for the updated mean HbA1c and the corresponding estimated gradient for an assumed optimal HbA1c variable. The correlation coefficient between the constructed variables versus the updated mean ranged from 0.53–0.78 and the figure illustrates the cases 0.5, 0.6, 0.7 and 0.8.

Mentions: The correlation coefficient between the predictive power of the updated mean HbA1c and the constructed variables, which take the time-dependent effect of HbA1c into account, ranged from 0.53 to 0.78 (Table 1). Figure 4 shows the corresponding gradient of risk per SD increase in the constructed HbA1c variables for the correlation coefficients 0.5, 0.6, 0.7 and 0.8, in relation to the gradient of risk per SD for the updated mean HbA1c.


The true value of HbA1c as a predictor of diabetic complications: simulations of HbA1c variables.

Lind M, Odén A, Fahlén M, Eliasson B - PLoS ONE (2009)

Gradients of risk.Gradient of risk for the updated mean HbA1c and the corresponding estimated gradient for an assumed optimal HbA1c variable. The correlation coefficient between the constructed variables versus the updated mean ranged from 0.53–0.78 and the figure illustrates the cases 0.5, 0.6, 0.7 and 0.8.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC2636883&req=5

pone-0004412-g004: Gradients of risk.Gradient of risk for the updated mean HbA1c and the corresponding estimated gradient for an assumed optimal HbA1c variable. The correlation coefficient between the constructed variables versus the updated mean ranged from 0.53–0.78 and the figure illustrates the cases 0.5, 0.6, 0.7 and 0.8.
Mentions: The correlation coefficient between the predictive power of the updated mean HbA1c and the constructed variables, which take the time-dependent effect of HbA1c into account, ranged from 0.53 to 0.78 (Table 1). Figure 4 shows the corresponding gradient of risk per SD increase in the constructed HbA1c variables for the correlation coefficients 0.5, 0.6, 0.7 and 0.8, in relation to the gradient of risk per SD for the updated mean HbA1c.

Bottom Line: Continuous HbA1c curves for 10,000 hypothetical diabetes patients were simulated over an average of 7 years.We tested several different HbA1c variables including various profiles, e.g. different duration, of such a long-lasting effect.The predictive power of these variables was compared with that of the updated mean HbA1c.

View Article: PubMed Central - PubMed

Affiliation: Department of Medicine, Uddevalla Hospital, Uddevalla, Sweden. lind.marcus@telia.com

ABSTRACT

Aim: The updated mean HbA1c has been used in risk estimates of diabetic complications, but it does not take into account the temporal relationship between HbA1c and diabetic complications. We studied whether the updated mean HbA1c underestimated the risk of diabetic complications.

Method: Continuous HbA1c curves for 10,000 hypothetical diabetes patients were simulated over an average of 7 years. Simulations were based on HbA1c values encountered in clinical practice. We assumed that each short time interval of the continuous HbA1c curves had a long-lasting effect on diabetic complications, as evidenced by earlier studies. We tested several different HbA1c variables including various profiles, e.g. different duration, of such a long-lasting effect. The predictive power of these variables was compared with that of the updated mean HbA1c.

Results: The predictive power of the constructed HbA1c variables differed considerably compared to that of the updated mean HbA1c. The risk increase per standard deviation could be almost 100% higher for a constructed predictor than the updated mean HbA1c.

Conclusions: The importance of good glycemic control in preventing diabetic complications could have been underestimated in earlier hallmark studies by not taking the time-dependent effect of HbA1c into account.

Show MeSH
Related in: MedlinePlus