Diabetes / CVD in HIV+ / Inaccuracy of A1C
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4 reports contained in this, pdfs attached
Once diabetes is diagnosed, HbA1c, the percentage of glycated hemoglobin (Hgb), is considered the best marker of glycemic control
The accuracy of HbA1c in predicting glycemia in patients with HIV and diabetes has been challenged. Published studies report inappropriately low HbA1c, underestimating glycemia in HIV patients with diabetes.4,5,18 We found only a moderate correlation between HbA1c and aAG and between fructosamine and aAG. Both correlations were weaker than expected and neither was superior to the other. Contrary to previously published findings, we found variability in the direction of the discrepancy between HbA1c and aAG, with both overestimation and underestimation of degree of glycemia. see full study report below
HIV-positive individuals have been thought to be in a chronic low-level hemolytic state from viral infection17 or ART,4 affecting the accuracy of HbA1c. Given the retrospective design of the current study, peripheral blood smear, haptoglobin, and lactate dehydrogenase levels were unavailable to evaluate hemolysis. The RDW and Hgb levels were extracted as surrogate markers, because hemolytic anemia frequently presents with elevated RDW and low Hgb levels.
A1C Underestimates Glycemia in HIV Infection
2009 Diabetes Care Peter Kim
Inaccuracy of haemoglobin A1c among HIV-infected men: effects of CD4 cell count, antiretroviral therapies andhematologicalparameters
2014 -Laurence Slama1,2 *, Frank J. Palella Jr2 , Alison G. Abraham3 , Xiuhong Li3 , Corinne Vigouroux1,4-7 , Gilles Pialoux1 ,
Lawrence Kingsley8 , Jordan E. Lake9 and Todd T. Brown3 on behalf of the Multicenter AIDS Cohort Study (MACS)
One very strong risk factor for hemoglobin A1c/ glycemia discordance that has been seen in multiple studies, including our work in the MACS,10 is a high mean corpuscular volume (MCV). The higher the MCV is over 90 or so, the greater the hemoglobin A1c/glycemia discordance. This is useful clinically since MCV is routinely measured on a complete blood count (CBC). In my practice, if I see an MCV in the high 90s or over 100 in an HIV-infected patient, I know not to trust the HbA1c too much. The reasons underlying this association are unclear, but we hypothesize that these larger red cells are taken out of circulation more quickly than normal-size cells.
Conclusion HbA1c underestimates glycaemia in HIV-infected patients and its use in patients with risk factors for HbA1c discordance may lead to under-diagnosis and to under-treatment of established diabetes mellitus.
Background There is limited evidence that among HIV-infected patients haemoglobin A1c (HbA1c) values may not accurately reflect glycaemia. We assessed HbA1c discordance (observed HbA1c - expected HbA1c) and associated factors among HIV-infected participants in the Multicenter AIDS Cohort Study (MACS).
Results Over 13 years, 1500 HIV-uninfected and 1357 HIV-infected men were included, with a median of 11 visits for each participant. At an FG of 125 mg/dL, the median HbA1c among HIV-infected men was 0.21% lower than among HIV-uninfected men and the magnitude of this effect increased with FG >126 mg/dL. Sixty-three percent of HIV-infected men had at least one visit with clinically significant HbA1c discordance, which was independently associated with: low CD4 cell count (<500 cells/mm3); a regimen containing a protease inhibitor, a non-nucleoside reverse transcriptase inhibitor or zidovudine; high mean corpuscular volume; and abnormal corpuscular haemoglobin.
INTRODUCTION:Among HIV-infected persons, HbA1c values may not accurately reflect glycaemia. Two recent studies have suggested that HbA1c underestimates mean fasting glucose (FG) among HIV-infected patients, possibly as a result of low-grade haemolysis,11,12 although the clinical significance of this effect is uncertain.13 In these studies, factors associated with HbA1c inaccuracy were higher mean corpuscular volume (MCV) as well as low serum haptoglobin, use of certain antiretroviral drugs (especially zidovudine or abacavir) or medication to treat diabetes.
Of the 3244 men with a visit between 1 April 1999 and 31 March 2012, 2857 (1500 HIV-uninfected and 1357 HIV-infected participants) had at least one visit with both FG and HbA1c measurements (Table1). The mean of number of visits for each participant was 11 (range 1-26). Compared with the HIV-uninfected men, HIV-infected men were younger, were more likely to be Caucasian and have a lower level of education and BMI and were more likely to have DM.
The median FG was higher in the HIV-infected group at the index visit than in the HIV-uninfected group (91 and 90 mg/dL, respectively; P = 0.013), whereas the HbA1c level was lower (5.0% and 5.2%, respectively; P < 0.001). The HIV-infected men had a higher median MCV (P < 0.001), higher median MCH (P < 0.001) and lower median haemoglobin (P < 0.001) than the HIV-uninfected men.
Relationship between HbA1c and FG in HIV-infected and HIV-uninfected men
The median HbA1c at FG = 125 mg/dL was 5.82% in the HIV-uninfected group compared with 5.61% in the HIV-infected group (median HbA1c discordance -0.21; P < 0.001) (Figure1). The magnitude of the difference in the slopes of HbA1c versus FG in HIV-infected and uninfected men was statistically significant for FG ≥ 126 mg/dL (difference in slope -0.0044% for each additional mg/dL; P = 0.018). The slopes, however, were not significantly different for FG < 125 mg/dL (P = 0.094).
Factors associated with HbA1c discordance among HIV-infected men
Among the HIV-infected men, the median HbA1c discordance (difference between observed and expected HbA1c values) was -0.17%, with the 25th percentile of -0.49 and the 75th percentile of 0.11. Of these person-visits (n = 14 860), 24.5% had an HbA1c discordance ≤-0.5%, occurring in 871/1378 (63%) men.
In univariate models (Table2), a lower than expected HbA1c value (observed - expected <0) was associated with a CD4 cell count <500 cells/mm3, use of a PI, zidovudine and/or a lamivudine-containing regimen and higher MCV and MCH. Older age, non-Caucasian race and obesity were associated with a higher than expected HbA1c (observed - expected >0).
We used a series of nested multivariable models to determine the independence of each of these factors in their relationship with HbA1c discordance. In a model that contained demographic and HIV-related parameters (Table2, Model 2), lower CD4 cell count, ART treatment (with or without a suppressed HIV-1 RNA level) and HCV co-infection were each independently associated with a lower observed than expected HbA1c value. After the addition of haematological parameters (Model 3), lower CD4 cell count, but not current ART or HCV co-infection, remained associated with HbA1c discordance. In addition, HbA1c discordance was associated with abnormal MCH (either above or below the normal range) and higher MCV, with each 5 fL increase in MCV associated with a progressively greater degree of HbA1c discordance. In a final model (Model 4), which included ART variables, we found that ART regimens in the previous 6 months containing a PI, an NNRTI or zidovudine were associated with a lower observed than expected HbA1c value. In contrast, abacavir and emtricitabine were associated with a higher observed HbA1c than expected.
Figure2 shows the relationship between demographic, HIV-related and haematological factors and the presence of clinically significant HbA1c discordance defined as observed - expected HbA1c ≤-0.5%. In the multivariable logistic model, the odds ratios for the CD4 cell count were similar at 1.57 (95% CI 1.20, 2.07) for CD4 cell count <200 cells/mm3, 1.61 (95% CI 1.31, 1.97) for CD4 209-349 cells/mm3 and 1.45 (95% CI 1.23, 1.70) for CD4 350-499 cells/mm3 versus CD4 >500 cells/mm3 (P < 0.001). Current ART (with or without HIV-1 RNA viral suppression) was not associated with clinically significant HbA1c discordance. The HbA1c discordance increased markedly with each 5 fL increase in MCV, from 2.09 (95% CI 1.31, 3.36 for MCV 85-89 fL) to 15.39 (95% CI 9.19, 25.79 for MCV >105 fL) and was also related to abnormal MCH [1.95 (95% CI 0.95, 4.0) for MCH <27 pg (P = 0.086) versus 1.32 (95% CI 1.05, 1.65) for MCH >31 pg; P = 0.018].
When use of specific ARTs was added to the model, PI use [OR 1.39 (95% CI 1.08, 1.78); P = 0.01] and zidovudine use [OR 1.38 (95% CI 1.06, 1.81); P = 0.019] were independently associated with clinically significant discordance (data not shown). In contrast, abacavir [OR 0.73 (95% CI 0.58, 0.91); P = 0.002], emtricitabine [OR 0.36 (95% CI 0.26, 0.49); P < 0.001] and lamivudine [OR 0.74 (95% CI 0.56, 0.99); P = 0.041] appeared to be protective against clinically significant HbA1c discordance.
This analysis of MACS data that span a 13 year period and include 1357 HIV-infected men constitutes the largest study to date that has evaluated whether HbA1c accurately predicts glycaemia among HIV-infected persons. We found that, at an FG of 125mg/dL, median HbA1c values were 0.21% lower in HIV-infected men than in HIV-uninfected men and that the magnitude of this difference increased at higher glucose values. We also found that HbA1c discordance (observed - expected HbA1c) was associated with lower CD4 cell counts, haematological parameters including high MCV and MCH, and exposure to certain ART agents including PIs, NNRTIs and zidovudine. Our findings suggest that HbA1c may not be an adequate marker of glycaemic control in certain HIV-infected persons and that its use may lead to under-treatment of established DM or under-diagnosis of DM when used as a diagnostic criterion.
Following an initial case report,19 three controlled studies have been published to date that addressed the relationship between glycaemia and HbA1c levels in HIV-infected persons. In a retrospective cross-sectional study, Diop et al.11 found that HbA1c underestimated mean FG in HIV-infected patients (n = 112) by ∼12% compared with HIV-uninfected persons. A prospective cross-sectional study12 compared observed and expected HbA1c levels in 100 HIV-infected patients with DM (77% of patients) or fasting hyperglycaemia (23%) and 200 matched HIV-uninfected participants and found that HbA1c underestimated glycaemia (mean of one fasting and one non-fasting sample) among HIV-infected persons by an average of 29 mg/dL. Most recently, Glesby et al.13 compared FG values and HbA1c values among 315 HIV-infected and 109 HIV-uninfected women with DM and found that HbA1c values were modestly lower among HIV-infected women compared with HIV-uninfected women (6.4% and 6.8%, respectively, P = 0.023) at the same level of FG. In our study, we found that, at a glucose level of 125 mg/dL, HbA1c values were a median of 0.21% lower in HIV-infected than in HIV-uninfected men and that the magnitude of this difference increased at higher glucose values. When we examined the HbA1c discordance as a categorical variable we found that 63.2% of men (24.5% observations) had an HbA1c discordance ≤-0.5%, defined as clinically significant.
The mechanisms underlying the underestimation of glycaemia by HbA1c among HIV-infected persons are unclear. Previous reports have suggested that HIV infection and/or its treatment is associated with a low-grade haemolysis,11 thereby leading to a shorter period of time during which haemoglobin within erythrocytes can become glycated. This hypothesis was supported by Diop,11 who found that the difference between measured and predicted HbA1c based on FG was correlated with low serum levels of haptoglobin, a plasma protein that binds to free haemoglobin and decreases during haemolysis.20 In contrast, Kim et al.12showed no association between haptoglobin and HbA1c discordance in HIV-infected persons. It should be noted that haptoglobin levels might be less reliable indicators of haemolytic anaemia in the setting of inflammation or low-grade extravascular haemolysis. In the current study we did not have measurements of serum haptoglobin, but plan to assess this in future MACS investigations.
As in previous studies, we found that higher MCV was a strong predictor of HbA1c discordance among HIV-infected persons.11,12 Macrocytosis is common among HIV-infected persons and has been attributed to certain antiretroviral agents, including zidovudine, stavudine and lamivudine. Macrocytosis has also been associated with lower HIV-1 RNA levels, independently of specific ART.21-23 Our data suggest that clinicians should be particularly cautious about using HbA1c in the management or diagnosis of DM among HIV-infected persons who have an MCV ≥95 fL, for whom the odds of HbA1c discordance is 4-15-fold higher than among persons with MCV <95 fL.
MCH, defined as the average mass of haemoglobin per erythrocyte, was also an important predictor of HbA1c discordance in our study. Low levels are characteristic of iron deficiency anaemia and may also be related to HbA1c. In a study involving 423 women without DM in the general population,15 an increase of 1 pg in MCH corresponded to a decrease of ∼0.03% in HbA1c, independently of haemoglobin levels or other red cell parameters. Since MCH values are readily available from complete blood cell count reports, identification of an HIV-infected person with a high MCH (>31 pg) might serve as an alert that HbA1c levels need to be interpreted with caution.
As in prior studies, we also found that use of certain ART drugs was associated with HbA1c discordance. Many of these effects, including those associated with zidovudine and PI use, remained significantly associated with HbA1c discordance in models adjusted for MCV and other haematological variables, suggesting that ART effects are not fully mediated by their impact upon erythrocyte parameters. In contrast to the study of Kim et al.,12 we did not detect an association between abacavir use and HbA1c discordance.
A novel finding in our analysis is that HbA1c discordance was strongly associated with CD4 counts <500 cells/mm3. We hypothesize that lower CD4 cell counts among HIV-infected patients are associated with chronic monocyte activation, leading to increased activation of the reticulo-endothelial system, erythrocyte phagocytosis, decreased red cell lifespan and consequent lowering of HbA1c levels.24 Of note, the monocyte activation marker sCD163, which is commonly evaluated in studies of HIV-related immune activation, is a haemoglobin-haptoglobin scavenger receptor and a marker specific for the reactive haemophagocytic syndrome.25 Future work in the MACS will investigate associations between HbA1c discordance and sCD163 levels.
We also found that several demographic factors were related to differences between observed and expected HbA1c, including older age and higher BMI. The finding regarding age has also been observed in NHANES III, in which HbA1c rose by ∼0.10% with each decade after age 40,26 which has been attributed to the acceleration of haemoglobin glycation with advancing age.27 In addition, in our study we used FG as our primary measure of glycaemia and hence did not capture post-prandial fluctuations in blood glucose. Since glucose intolerance increases with ageing, older individuals may have greater post-prandial glucose excursions, which would not impact the expected HbA1c levels that we calculated using FG values. Similarly, obese individuals may also experience larger post-prandial glucose excursions, which could lead to higher observed HbA1c levels than expected. Lastly, as in previous studies in the general population, the observed HbA1c was greater than expected among black and Hispanic compared with white participants.26,28,29 Whether these differences are due to differences in glycaemia or non-glycaemic genetic factors is debated.28
Our study has several limitations. We used FG to assess glycaemia rather than seven-point glucose monitoring or glycaemia as assessed by a continuous glucose monitor, which is the gold standard.30 Our study population included relatively few persons with impaired FG or overt diabetes, for whom inaccuracy of HbA1c would have the highest clinical relevance. In addition, without measurements of other indices of haemolysis we were unable to assess the mechanism(s) accounting for HbA1c discordance. Similarly, we did not have other laboratory-based methods to assess glycaemia, including fructosamine or 1,5-anhydroglucitol, which have been proposed as alternatives to HbA1c among HIV-infected persons.12 Finally, our study included only men and cannot be extrapolated to women.
In conclusion, we found that HbA1c underestimated glycaemia in certain HIV-infected men. This effect was particularly pronounced in men with a CD4 cell count <500 cells/mm3, a higher MCV and a high MCH, and in persons receiving ART regimens that included PIs, NNRTIs or zidovudine. In these sub-populations, it would be prudent for clinicians to use direct measures of glycaemia (i.e. fasting glucose or an oral glucose tolerance test) to diagnose diabetes and, for persons with diabetes, to consider a lower HbA1c level treatment target in order to prevent long-term diabetes complications.
HbA1c Underestimates Plasma Glucose in People Taking
Monitoring HIV-infected Patients with Diabetes: Hemoglobin A1c, Fructosamine, or Glucose?
So-Young Kim1, Patricia Friedmann2, Amit Seth3 and Adrienne M. Fleckman3
1Department of Medicine, Beth Israel Medical Center, New York, NY, USA. 2Office of Grants and Research Administration, Beth Israel Medical Center, New York, NY, USA. 3Division of Endocrinology and Friedman Diabetes Institute, Albert Einstein College of Medicine/Beth Israel Medical Center, New York, NY, USA.
Published studies report inappropriately low hemoglobin A1C (HbA1c) values that underestimate glycemia in HIV patients.
We reviewed the charts of all HIV patients with diabetes mellitus (DM) at our clinic. Fifty-nine patients had HbA1c data, of whom 26 patients also had fructosamine data. We compared the most recent HbA1c to finger-stick (FS) glucose averaged over three months, and fructosamine to FS averaged over six weeks. Predicted average glucose (pAG) was calculated as reported by Nathan et al: pAG (mg/dL) = 28.7 × A1C% - 46.7. Data were analyzed using the Statistical Analysis System (SAS) and Kruskal-Wallis test.
average glucose (aAG), and between HbA1c and aAG. We also examined the proportion of patients whose pAG and aAG values differed by more than 29 mg/dL. Data were further analyzed using non-parametric Kruskal-Wallis test to evaluate differences in age, red cell distribution width (RDW), and Hgb between patients with underestimated (UE), overestimated (OE), and accurately estimated (AE) average glucose.
HbA1c values underestimated (UE) actual average glucose (aAG) in 19% of these patients and overestimated (OE) aAG in 27%. HbA1c estimated aAG within the established range in only 54% of the patients. There were no statistical differences in the types of HIV medication used in patients with UE, OE, or accurately estimated (AE) glycemia. A Spearman correlation coefficient between HbA1c and aAG was r = 0.53 (P < 0.0001). Correlation between fructosamine and aAG was r = 0.47 (P = 0.016).
The correlations between HbA1c and aAG and between fructosamine and aAG were weaker than expected, and fructosamine was not more accurate than HbA1c.
Abnormal glucose metabolism in HIV-infected patients has increased with antiretroviral therapy (ART) and improved longevity. More than 35% of HIV patients have impaired glucose tolerance, compared to 5% in the general population,1 with 4.6 times the prevalence of diabetes mellitus (DM) in HIV patients.2 Diabetes diagnosis and management in HIV patients follow general guidelines, which rely on hemoglobin A1c (HbA1c).3 However, published studies report inappropriately low HbA1c values that underestimate glycemia in HIV patients.4,5
Current guidelines stipulate HbA1c ≥6.5% to diagnose DM based on analysis showing increased prevalence of retinal abnormalities around this value,6 without a requirement to measure plasma glucose.
Once diabetes is diagnosed, HbA1c, the percentage of glycated hemoglobin (Hgb), is considered the best marker of glycemic control,4 with treatment often adjusted solely on HbA1c values. However, HbA1c can be affected by many factors,7 including age, increasing 0.4% from age 40 to age 70;8 and ethnicity.9-12 Non-Hispanic blacks have a 2.4-fold likelihood of having HbA1c >6% among individuals with fasting glucose <100 mg/dL.13
Abnormal Hgb or shortened RBC life span,14 cirrhosis, and renal failure15 may also alter HbA1c.4,5,16 HIV-positive individuals are hypothesized to be in a chronic low-level hemolytic state from viral infection17 or ART,4 affecting the accuracy and consistency of HbA1c, with falsely low values resulting in overoptimistic estimates of glucose control. This has led to the suggestion that fructosamine (glycated serum protein) may be a better marker of glycemic control in HIV patients with diabetes than HbA1c.5,18
In our study, we aim to determine the association between HbA1c and actual glucose levels in HIV-positive patients with diabetes. We also compare the accuracy of HbA1c to fructosamine in assessing glycemic control in HIV patients with diabetes.
We conducted a retrospective chart review of 65 consecutive patients with HIV and DM followed in our clinic during a single calendar year. Our study was granted exemption from review by the IRB of Beth Israel Medical Center, as subjects could not be identified directly or through identifiers linked to the subjects. A total of 59 patients had available HbA1c data, of whom 26 patients had fructosamine data (see flow chart). In all, 57 patients had type 2 diabetes and 2 had type 1 diabetes. Given a lack of evidence to suggest that accuracy of HbA1c or fructosamine is different between type 1 and 2 diabetic patients, all 59 patients were included in the study. We extracted the HbA1c and finger-stick (FS) glucose averaged over three months; and the proximate fructosamine and FS glucose averaged over four to six weeks. We chose the three-month time frame and six-week time frame within the 12-month review period that captured the greatest number of FS values for each patient.
All blood samples were sent to Beth Israel Central Laboratory. HbA1c was measured using high-performance liquid chromatography (HPLC). Fructosamine was analyzed using a colorimetric assay by Quest Diagnostics Laboratory.
Predicted average glucose (pAG) was calculated as reported by Nathan et al19: pAG (mg/dL) = 28.7 × A1C% - 46.7, which estimates a change of 29 mg/dL in plasma glucose for each 1% change in HbA1c,15 a clinically relevant magnitude. Data were analyzed using the Statistical Analysis System (SAS) v9.2 for the correlation between fructosamine and actual average glucose (aAG), and between HbA1c and aAG. We also examined the proportion of patients whose pAG and aAG values differed by more than 29 mg/dL. Data were further analyzed using non-parametric Kruskal-Wallis test to evaluate differences in age, red cell distribution width (RDW), and Hgb between patients with underestimated (UE), overestimated (OE), and accurately estimated (AE) average glucose.
pAG based on HbA1c estimated aAG within the established range for only 54% of the 59 patients examined. For the remaining patients, 19% had HbA1c values that UE aAG by more than 29 mg/dL, while the HbA1c value in 27% of the patients OE aAG by more than 29 mg/dL (Fig. 1). For the subgroup of patients with at least seven FS values (n = 23), HbA1c UE aAG in 29% of the cases and OE it in 18% of the cases. In this group, HbA1c-based pAG estimated aAG within the measured range for 53% of these patients (Fig. 2), a percentage similar to that for the whole group.
All patients analyzed in the study were taking highly active antiretroviral therapy (HAART) for their HIV infection (one patient did not have available HIV medication status). HAART was categorized into three different classes: nucleoside reverse transcriptase inhibitors (NRTIs), non-nucleoside reverse transcriptase inhibitors (NNRTIs), and protease inhibitors (PIs). In all, 100% of patients with UE glycemia, 93% of patients with OE glycemia, and 93% of patients with AE glycemia were on NRTIs. A total of 18% of UE group, 20% of OE group, and 29% of AE group were on NNRTs. Overall, 82% of UE group, 80% of OE group, and 61% of AE group were on PIs (Table 1). The percentage of patients taking NRTIs, NNRTIs, and PIs were similar in UE, OE, and AE glycemia groups. Further analysis was not performed because of limited statistical power, given small sample size in each group.
HIV-positive individuals have been thought to be in a chronic low-level hemolytic state from viral infection17 or ART,4 affecting the accuracy of HbA1c. Given the retrospective design of the current study, peripheral blood smear, haptoglobin, and lactate dehydrogenase levels were unavailable to evaluate hemolysis. The RDW and Hgb levels were extracted as surrogate markers, because hemolytic anemia frequently presents with elevated RDW and low Hgb levels. The mean RDW (nl 11-15%) was 14.1% in UE group, 14.6% in OE group, and 14.1% in AE group (Table 2). The mean Hgb (nl 13.2-17.1 g/dL) was 13.6 g/dL in UE group, 13.4 g/dL in OE group, and 13.8 g/dL in AE group (Table 2). A nonparametric Kruskal-Wallis test was performed. There were no statistically significant differences in mean RDW or Hgb in groups with UE, OE, or AE glycemic levels.
Further data were analyzed to evaluate differences in gender or age in patients with UE, OE, or AE glycemia by HbA1c. In all, 61% of UE group, 38% of OE group, and 63% of AE group were male patients (Table 3). Mean age of patients was 53.45 years in UE group, 55 years in OE group, and 54.69 years in AE group (Table 4). A non-parametric Kruskal-Wallis test was performed. There were no statistically significant differences in mean age in groups with UE, OE, or AE glycemic levels.
Diabetes medication usage was evaluated in the study patients. Seventy-three percent of UE group, 38% of OE group, and 47% of AE group were on insulin. Twenty-seven percent of UE group, 50% of OE group, and 38% of AE group were on biguanides. Nine percent of UE group, 19% of OE group, and 19% of AE group were on sulfonylurea. Nine percent of UE group, 19% of OE group, and 13% of AE group were on dipeptidyl peptidase-4 inhibitor (DPP-4 inhibitor). Zero percent of UE group, 19% of OE group, and 22% of AE group were on thiazolidinediones (TZDs). Zero percent of UE group, 6% of OE group, and 3% of AE group were on glucagon-like peptide-1 agonists (Table 5). Further analysis was not performed because of limited statistical power, given small sample size in each group.
A Spearman correlation coefficient was computed between HbA1c and aAG (r = 0.53, P < 0.0001) and between fructosamine and aAG (r = 0.47, P = 0.016) (Figs. 3 and and4).4). Our findings suggest a moderate correlation between HbA1c and aAG as well as between fructosamine and aAG. Our analysis also revealed that HbA1c UE or OE average FS values in almost half of the patients studied (46% of our HIV-infected patients with diabetes).
Given the frequent comorbidities in individuals with diabetes, it is likely that factors that may alter HbA1c are under-recognized and widely overlooked,7,14,20,21 which makes our current reliance on HbA1c questionable.
The accuracy of HbA1c in predicting glycemia in patients with HIV and diabetes has been challenged. Published studies report inappropriately low HbA1c, underestimating glycemia in HIV patients with diabetes.4,5,18 We found only a moderate correlation between HbA1c and aAG and between fructosamine and aAG. Both correlations were weaker than expected and neither was superior to the other. Contrary to previously published findings, we found variability in the direction of the discrepancy between HbA1c and aAG, with both overestimation and underestimation of degree of glycemia.
All analyzed patients in the study were on HAART for HIV infection. There were no differences between the types of HIV medication used and the accuracy of HbA1c prediction of average glucose. It is possible that HIV medications contribute to inaccuracy of HbA1c in predicting glycemia, but pathogenesis is yet to be explained. Although the mean RDW and Hgb levels were within normal range and were similar between the patients who had UE, OE, or AE glycemia based on HbA1c, we cannot conclude that the patients were not in chronic hemolytic state as previously hypothesized. More definitive data, such as peripheral smears, haptoglobin, or LDH, would be needed.
Medications or conditions that affect RBC lifespan, glycation of RBC, and erythropoiesis can all contribute to inaccuracy of HbA1c. Although we know conditions, such as cirrhosis, renal failure, and sickle cell anemia; and medications, such as HAART and dapsone, can affect red cell survival, leading to inaccuracy of HbA1c, there are likely many other conditions and medications that may potentially affect RBC or interfere with HbA1c assays. The similar age, RDW, Hgb, and use of HAART in our study group underscore the importance of additional factors that may affect the accuracy of HbA1c.
Study limitations include retrospective data collection, the limited number of FS values, and lack of data on red cell survival. The sample size did not permit adjustment for gender, race, age, or renal function. While further study is needed, our patients are from a large urban center and reflect the comorbidity of any inner city population. Our findings clearly suggest that fructosamine does not have greater utility than HbA1c in predicting aAG in HIV-infected patients who have DM, and emphasize the importance of complementing HbA1c and fructosamine values with accurate FS reporting in this patient population.