Introduction

The prevalence of diabetes has reached epidemic proportions globally, with 424.9 million affected adults (20–79 y), representing 8.8% of the global adult population. Current projections indicate that this figure will rise to 628.6 million by the year 2045, affecting almost 10% of the worldwide adult population [1]. Type 2 diabetes (T2DM) accounts for the vast majority (90–95%) of diabetes cases and is commonly characterized by the inability of pancreatic beta cells to meet the demand for insulin secretion due to a relative deficit of functional beta cells in a setting of peripheral insulin resistance. There has been much debate over the years as to how T2DM should be diagnosed; what should be measured, and the diagnostic targets have changed, being refined as our understanding of the disease has improved along with improvement in analytical methods. The diagnostic criteria for T2DM are established [2], but it is clear that a continuum in blood glucose level exists from normoglycemia to frank diabetes. As such, in 1997 and 2003, the Expert Committee on Diagnosis and Classification of diabetes mellitus recognized a cohort of subjects whose glucose levels did not meet the criteria for diabetes but were too high to be considered as normal [3, 4]; this “prediabetic” group exhibited impaired fasting glucose (IFG) [fasting plasma glucose (FPG) levels of 100–125 mg/dL (5.6–6.9 mmol/L) and/or impaired glucose tolerance (IGT)] defined as a 2-h plasma glucose following a 75 g oral glucose tolerance test (OGTT) of 140–199 mg/dL (7.8–11.0 mmol/L)] and represents individuals at high risk for development of T2DM.

Hemoglobin A1c (HbA1c) is considered key for assessing glycemic control in patients known to have diabetes, and several prospective studies using HbA1c have shown a strong, continuous association between HbA1c and the development of diabetes and complications [5,6,7]. An International Expert Committee (IEC) recommended an HbA1c level of 6.5% (48 mmol/mol) as the diagnostic threshold for T2DM diagnosis [8], purporting that individuals with HbA1c levels above this cutoff have a much higher probability of having retinopathy than those below. Both the American Diabetes Association (ADA) and, subsequently, the World Health Organization (WHO) endorsed this opinion, which was entirely based upon the risk of observing diabetic retinopathy, without consideration for other diabetic microvascular complications; however, the subject has to have had diabetes for a period of time for microvascular complications to develop that may occur at a lower HbA1c than 6.5%.

Key studies contributing to the IEC/ADA/WHO diagnostic threshold decision were the results of the cross-sectional Evaluation of Screening and Early Detection Strategies for Type 2 Diabetes and Impaired Glucose Tolerance (DETECT-2) study [9] and three epidemiological studies undertaken in the 1990s on Pima Indians, Egyptians and US subjects enrolled in the National Health and Nutrition Examination Survey (NHANES) study [3, 10, 11].

The current HbA1c threshold was based on data available at the time of these groups’ reports and, even at the time, there was debate as to whether a level of 6.5% (48 mmol/mol) may be too high since, in many studies, it identified fewer patients as having diabetes than the traditional blood glucose criteria [12]. Since then, a number of studies have been performed with the aim of better characterizing the HbA1c threshold for prevalent or incident retinopathy. The studies prior to 2013 were summarized in a publication by Kowall and Rathmann who looked at retinopathy, nephropathy and neuropathy [13]; since this time, there have been a number of relevant publications which can now be considered.

The key aims of this study were to perform a contemporary systematic review and meta-analysis to verify the HbA1c cutpoint of 6.5% (48 mmol/mol) for the diagnosis of T2DM using currently available retinopathy data and, secondly, to extend the analysis to establish the prevalence of nephropathy and neuropathy at differing levels of HbA1c.

Methods

Data sources and search strategy

This systematic review was guided by the Cochrane Collaboration Handbook [14], and followed the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines [15]. The PRISMA checklist is shown in Supplementary Table 1. A comprehensive systematic search for literature was conducted in the academic databases PubMed, Embase, Cochrane, Scopus, CINAHL and in sources for grey literature in October 2019 (Supplementary Table 2).

Table 1 Studies included for assessment of HbA1c level and incidence of retinopathy
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Table 2 Studies included for assessment of HbA1c level and incidence of nephropathy
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Pre-searches to identify relevant search terms, search strategies and information sources were performed in May–October 2019. PubMed’s MeSH was used to systematically identify search terms that encompass the variations in terminology for glycated hemoglobin, including thresholds or cutpoints, as well as terms that describe diabetic microvascular complications (Tables 1, 2, 3). The search strategy developed in PubMed was replicated in all databases with eventual search terms or technical variations documented (Supplementary Table 2). The PRESS peer review of electronic search strategies: 2015 guideline statement was used to peer review the search string [16].

Table 3 Studies included for assessment of HbA1c level and incidence of neuropathy
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All selected search terms were searched in a combination of “Abstract” and “Article Title” (alternatively “Topic” or “Title, Abstract and Keyword”) and in MeSH/Subject Headings/Thesaurus when available. A publication year filter to include studies from 1990 up to the search date was applied to account for the predominant lack of standardized/harmonized HbA1c measurement before this time. In order to ensure literature saturation and inclusion of pre-indexed materials, no additional filters or limitations were included.

In addition to the search in academic databases, Open Grey, Clinical Trials.gov, The New York Academy of Medicine-Grey Literature Report and ProQuest Dissertation and Theses were searched for grey literature. Hand screening of the references lists of all studies selected to be included in the review was also conducted.

A full search log including search technical details, results and notes about search term variations/translations for all databases can be found in Supplementary Table 2.

A review protocol for this study was registered in the Prospero international prospective register of systematic reviews: https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=99410PROSPERO2018CRD42018099410.

Study selection

Search results were imported into the Covidence systematic review tool where duplicate publications were identified and duplicates excluded. Study eligibility was independently determined by two investigators (AEB and SLA). Where there was a discrepancy, both investigators revisited the publication in question, discussed the results with the group and re-entered their decision into the database.

The criterion for inclusion was for a publication to report the prevalence of microvascular complications by levels of HbA1c. More specifically, studies were only considered if they provided a prevalence measure for a microvascular complication stratified by HbA1c of < 6% (< 42 mmol/mol), 6–6.4% (42–47 mmol/mol) and ≥ 6.5% (48 mmol/mol) in the same study. The reason for that is to ensure rigor in the association with microvascular complications. Exclusion criteria were studies that did not report microvascular complications by different HbA1c level and those published before 1990.

For terminology, a “publication” is a document containing a relevant outcome measure, while a “study” indicates all details pertaining to a specific outcome measure—one publication may contribute multiple studies. A study, such as “prevalence of retinopathy,” could include multiple stratified “measures,” such as prevalence by age group.

Data extraction and quality assessment

Following screening of records for eligibility, eligible studies had full-text screening (Supplementary Figure 1). Extracted variables included: author(s), publication title, year(s) of data collection, publication year, country of origin, country of survey, study design, study sampling procedure, study population and its characteristics (e.g., sex, age and ethnicity), sample size, HbA1c measurement method, HbA1c stratification outcome measures, complications, retinal photography method, number of eyes photographed, determination of albumin creatinine ratio, measure of peripheral neuropathy. Two investigators (AEB and SLA) independently assessed the full-text articles and determined the eligibility of studies for inclusion in the systematic review.

Quality assessment

Risk of bias (ROB) and precision assessments were performed for all studies included in the review. Guided by the Cochrane approach [17], studies were classified as having “low” vs. “high” ROB on two quality domains assessing (1) consistency in HbA1c diagnostic measurement across all study participants (consistent vs. not consistent) and (2) rigor of sampling methodology (probability-based vs. non-probability-based). Studies with unavailable information for any given domain were classified as having “unclear” ROB for that domain. Studies including at least 100 participants were considered as having higher precision. For a prevalence of microvascular complications of 1% (see prevalence by HbA1c in Table 1) and a sample size of 100, the 95% confidence interval (95% CI) is 0–5%, an acceptable CI for the prevalence of microvascular complications (a lower sample size is needed to detect a higher prevalence). Results of the quality assessment are shown in Supplementary Tables 3 and 4.

Table 4 Results of meta-analyses of studies reporting complications of diabetes in patients with different HbA1c (%)
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Data synthesis and analysis

Statistical analysis

Meta-analysis methodology

Meta-analyses were conducted to estimate the pooled mean of diabetes complications in relation to the stratified HbA1c values (extracted overall outcome measures for a specific HbA1c category, such as 6.0–6.4, were substituted with stratified measures such as by sub-levels of HbA1c, that is 6.0, 6.1, 6.2…, or population characteristics). Forest plots were constructed to visualize prevalence measures and 95% confidence intervals (CIs) associated with each of the three outcomes of interest (retinopathy, nephropathy and neuropathy). Estimates for the pooled mean prevalence and 95% CIs were then calculated using random-effects meta-analyses. Here, variances of prevalence measures were first stabilized using a Freeman–Tukey-type arcsine square-root transformation [18, 19]. Inverse variance weighting [19, 20] was subsequently applied prior to pooling estimates using a DerSimonian–Laird random-effects model [21]. This model assumes a normal distribution for true effect sizes (prevalence) across studies and thus factors in sampling variation and true heterogeneity in effect size [22].

A heterogeneity assessment was further conducted using Cochran’s Q statistic to confirm existence of heterogeneity across studies and I2 to quantify magnitude of between-study variation that is due to true differences in effect size rather than chance [22, 23].

Meta-analyses were implemented in R version 3.4.2 [24].

Meta-regression methodology

Associations with prevalence and sources of between-study heterogeneity were identified using random-effects univariable and multivariable meta-regression analyses. Predictors considered a priori included: HbA1c levels, age and race. Factors associated with prevalence at p value ≤ 0.10 in univariable analysis were eligible for inclusion in the multivariable model. In the latter, a p value ≤ 0.10 but > 0.05 was considered as showing “good evidence” for an association with prevalence, while a p value ≤ 0.05 indicated strong evidence for an association with prevalence.

The magnitude of the association between these predictors and prevalence was determined by calculating, in the univariable analysis, odds ratios (ORs) and their associated 95% CIs, and in the multivariable analysis, by calculating adjusted odds ratios (AORs) and their associated 95% CIs.

Meta-regressions were conducted in Stata/SE version 13 [25] using the metareg package [26].

Results

Literature search

A total of 12,845 references were identified through the literature search and uploaded to the systematic review software Covidence for de-duplication and screening. 9370 references (9324 from the database search and 46 from the grey literature search) qualified for title and abstract screening after de-duplication. The screening process in Covidence software was blinded. Of the 9370 references, 9206 records were excluded. 164 full-text articles were then assessed for eligibility; of those 135 were excluded because of insufficient details of the relationship of the microvascular complication to the HbA1c values less than 6.5% (48 mmol/mol). Twenty nine publications remained eligible for inclusion in the systematic review, 22 relating to retinopathy (Table 1) [6, 9, 11, 27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46]; 4 relating to nephropathy (Table 2) [28, 38, 47, 48] and 3 relating to neuropathy (Table 3) [38, 49, 50]. No additional relevant references were identified in the hand searching of the reference lists of the 29 included studies. The retinopathy studies contributed 74 stratified measures for the quantitative meta-analysis according to HbA1c as detailed above.

Study characteristics

The definitions of retinopathy, nephropathy and neuropathy used in each study are shown in Tables 1, 2 and 3, respectively.

Diabetic retinopathy, defined as diabetes-related damage to the retina, is classified into early stage non-proliferative diabetic retinopathy (NPDR, comprising microaneurysms and macular edema) and second-stage proliferative diabetic retinopathy (PDR, comprising neovascularization and vitreous hemorrhages) and fundal photography is required for diagnosis [51]. HbA1c was stratified into the following categories in each study: < 6% (< 42 mmol/mol),  = 6–6.4% (42–47 mmol/mol) and  ≥ 6.5% (≥ 48 mmol/mol).

The forest plot for retinopathy is shown in Fig. 1. The median prevalence of retinopathy was overall 4.0% (range: 0–48.3%), but varied according to HbA1c levels (Table 4). It was 2.7% (range: 0–15.9%) for HbA1c < 6.0% (< 42 mmol/mol), 1.2% (range: 0.2–14.8%) for HbA1c 6.0–6.4% 42–47 mmol/mol) and 5.6% (range: 0.4–48.3%) for HbA1c ≥ 6.5% (≥ 48 mmol/mol).

Fig. 1
figure 1

Forest plot showing results of the meta-analysis for retinopathy prevalence. Retinopathy prevalence stratified by HbA1c levels

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The forest plot for nephropathy is shown in Fig. 2. The median prevalence of nephropathy was assessed at 11.2% (range: 0.9–32.6%). However, there was also variability based on HbA1c value, with a median of 7.3% (range: 1.0–19.7%) for HbA1c < 6.0% (< 42 mmol/mol), 12.4% (range: 0.9–18.5%) for HbA1c 6.0–6.4% (42–47 mmol/mol) and 26.0% (range: 1.9–32.6%) for HbA1c ≥ 6.5% (≥ 48 mmol/mol) (Table 4).

Fig. 2
figure 2

Forest plot showing results of the meta-analysis for nephropathy prevalence. Nephropathy prevalence stratified by HbA1c levels

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The forest plot for neuropathy is shown in Fig. 3. The median prevalence for neuropathy was 3.9% (range: 0.2–8.5%). It was 2.8% (range: 0.2–5.0%) for HbA1c < 6.0% (< 42 mmol/mol), 5.6% (range: 0.2–8.5%) for HbA1c 6.0–6.4% (42–47 mmol/mol) and 3.8% (range: 0.2–8.5%) for HbA1c ≥ 6.5% (≥ 48 mmol/mol) (Table 4).

Fig. 3
figure 3

Forest plot showing results of the meta-analysis for neuropathy prevalence. Neuropathy prevalence stratified by HbA1c levels

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Quality assessment

Supplementary Tables 3 and 4 show the results of the summarized and study-specific quality assessments. In sum, 72.7% (n = 16 out of 22) of retinopathy studies, 50.0% (n = 2 out of 4) of nephropathy studies and 66.7% (n = 2 out of 3) of neuropathy studies included at least 100 participants and therefore were considered as having higher precision.

Low risk of bias, assessed as consistency in measuring HbA1c across study participants, was found in 81.8% of studies assessing retinopathy, all studies assessing nephropathy, and 66.7% of studies assessing neuropathy. The majority of studies assessing retinopathy (95.5%) and all studies assessing nephropathy and neuropathy used probability-based sampling and hence were also classified as having low ROB on that quality domain.

Overall, studies reporting the prevalence of microvascular complications of T2DM were of acceptable quality: 81.8% of retinopathy studies, all nephropathy studies and 66.7% of neuropathy studies had low ROB on both quality domains. High ROB on both domains was found in only 4.5% of retinopathy studies and none of nephropathy or neuropathy studies.

Meta-analysis results

The pooled mean prevalence was estimated at 4.1% (95% CI: 3.2–5.0%) for retinopathy, 10.5% (95% CI: 4.4–18.8%) for nephropathy and 2.5% (95% CI: 1.1–4.3%) for neuropathy (Table 4 and Figs. 1, 2, 3).

There was evidence for heterogeneity in prevalence estimates across all meta-analyses (Table 4). P value for Cochran’s Q statistic was almost always < 0.0001. I2 was > 90% indicating that most variability is due to true differences in prevalence across studies rather than chance.

HbA1c Level and risk of retinopathy

For retinopathy, when the prevalence of complications was stratified according to HbA1c, using categories of < 6.0% (< 42 mmol/mol), 6.0–6.4% (42–46 mmol/mol) and ≥ 6.5% (≥ 48 mmol/mol), there was a distinct increase in retinopathy prevalence from a pooled mean of 3.41% (95% CI: 1.84–5.42) in the < 6.0% (< 42 mmol/mol) stratum and a pooled mean of 2.40% (95% CI: 1.65–3.29) in the 6–6.4% 42–47 mmol/mol) stratum to a pooled mean of 7.97% (95% CI: 5.70–10.57) in the ≥ 6.5% (≥ 48 mmol/mol) stratum. The J-shaped curve describing this association can be found in Fig. 4. The prevalence of retinopathy stratified in 0.1% increments is shown in Fig. 5. The latter analysis showed no trend of increasing retinopathy for HbA1c ranging from 6.0 to 6.4%, but a marked increase in prevalence at HbA1c of 6.5% and greater.

Fig. 4
figure 4

Pooled mean prevalence and adjusted odds ratio of retinopathy according to HbA1c. a Prevalence of retinopathy (%) stratified by HbA1c levels of < 6.0%, 6.1–6.4% and 6.5% or greater, showing marked increase in retinopathy prevalence in the 6.5% or greater group. b Adjusted odds ratio for retinopathy prevalence (for age, sex and ethnicity) stratified by HbA1c levels of < 6.0%, 6.1–6.4% and 6.5% or greater, showing marked increase in the odds ratio in the 6.5% or greater group

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Fig. 5
figure 5

Pooled mean prevalence of retinopathy stratified in 0.1% increments of HbA1c. The prevalence of retinopathy stratified in 0.1% increments showed no trend of increasing retinopathy for HbA1c ranging from 6.0 to 6.4%, but a marked increase in prevalence at HbA1c of 6.5% and greater

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HbA1c Level and risk of nephropathy

The albumin/creatinine ratio (expressed as mg albumin: mmol creatinine; ACR) is a sensitive indicator of kidney disease, and patients are classified according to the 2012 guidelines developed by the Kidney Disease: Improving Global Outcomes organization (KDIGO) [52] as: normal < 3 mg/mmol (A1), moderate 3–30 mg/mmol (A2), severe > 30 mg/mmol (A3; nephropathy). Notably, for nephropathy, the prevalence of this complication overall tended to be higher than that for retinopathy. Again, there was a distinct increase in nephropathy prevalence from a pooled mean of 7.12% (95% CI: 1.68–15.85) in the < 6.0% (< 42 mmol/mol) stratum and a pooled mean of 9.56% (95% CI: 0.75–26.41) in the 6–6.4% (42–47 mmol/mol) stratum to a pooled mean of 17.10% (95% CI: 0.96–46.85) in the ≥ 6.5% (≥ 48 mmol/mol) stratum.

HbA1c Level and risk of neuropathy

Diabetic neuropathy, defined as the signs and symptoms of neuropathy wherein diabetes is the underlying cause, most frequently manifests as a distal, symmetric deficit [53]. For neuropathy, no trend in the pooled mean was seen when stratified according to HbA1c: < 6.0% (< 42 mmol/mol) (pooled mean of 2.06%; 95% CI: 0.02–6.76), 6–6.4% (42–47 mmol/mol) (pooled mean 3.39%; 95% CI: 0.00–11.55) and ≥ 6.5% (≥ 48 mmol/mol) (pooled mean 2.81%; 95% CI: 0.00–12.77). This may, however, be due to the paucity of studies available.

Subgroup Analysis

As a higher prevalence of complications may be anticipated with increasing age, the meta-analysis data of studies reporting retinopathy were stratified by age using both two strata (age ≤ 55 years and > 55 years) and three strata (age ≤ 55 years, age 55–59 years and > 60 years) with levels of HbA1c (Table 5). As anticipated, the pooled means did tend to increase with age, though this trend did not differ substantially from the original analysis.

Table 5 Results of meta-analyses of studies reporting retinopathy in patients with different HbA1C stratified by age
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Certain ethnic populations are also known to develop diabetes complications more frequently, notably African-Americans [46]. A sensitivity analysis was therefore performed on the results of the meta-analysis for studies reporting retinopathy separately for African-Americans and non-Black populations (Table 6). The results showed the same upward trend for retinopathy with increasing levels of HbA1c in both the Black and non-Black populations, though the African-Americans populations had a notably higher prevalence of retinopathy at every level of HbA1c; the prevalence of retinopathy in non-African-Americans in those studies did not differ to the overall non-African American prevalence.

Table 6 Sensitivity analysis showing results of meta-analyses of studies reporting retinopathy in patients with different HbA1C excluding African-American patients
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There were insufficient studies for both nephropathy and neuropathy to perform subgroup analyses.

Meta-regression results

Only retinopathy prevalence had a sufficient number of studies to warrant conduct of meta-regression analysis (Table 7).

Table 7 Results of univariable meta-regression analyses for the prevalence of retinopathy by key factors
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The univariable analysis showed an association with prevalence for HbA1c levels, age and race; these were therefore included in the multivariable model. Here, HbA1c stratification showed a marked and significant increase of retinopathy prevalence at ≥ 6.5% with an AOR of 4.0 (95% CI: 1.9–8.5; p < 0.001) after controlling for the confounding effect of age and race. The model also showed that individuals > 55 years of age had threefold higher odds for retinopathy than younger individuals (AOR: 3.3; 95% CI: 1.8–6.0; p < 0.001). African-Americans also had significantly higher odds for retinopathy prevalence than those of other race (AOR: 11.0; 95% CI: 4.4–27.5; p < 0.001). This model explained 44.8% of the variation in retinopathy prevalence.

Discussion

The meta-analysis relating stratified HbA1c to the prevalence of retinopathy, nephropathy and neuropathy showed clearly that for moderate retinopathy, the recent data are in accord with a HbA1c diagnostic cutoff of 6.5% (48 mmol/mol and above) for T2DM, with the inflection point for the increase in diabetic retinopathy prevalence being at 6.5% (48 mmol/mol), as also shown by the stratified analysis using the J-shaped curve. Pooled mean retinopathy prevalence by 0.1% HbA1c changes showed no obvious signal of a rising retinopathy prevalence for HbA1c 6.0 to 6.4%, with the inflection point being at 6.5% or greater. This being said, there were too few studies assessing retinopathy prevalence at HbA1c increments of 6.3% and 6.4% for evidence to be conclusive. The latter analysis also showed considerable retinopathy prevalence at below 6.0% (42 mmol/mol) HbA1c. It should be also emphasized that the stratification of HbA1c and retinopathy was based on the detection of moderate retinopathy and it is unknown whether the diagnostic cutpoint for T2DM may be altered by prevalence studies on minimal diabetic retinopathy. These results differ from that reported in a previous meta-analysis that concluded that HbA1c thresholds could not be identified from the studies on microvascular complications, though the threshold of HbA1c of 6.5% was strong for severe retinopathy [13].

The heterogeneity in the retinopathy data was controlled for in the meta-regression and showed, in both the univariate and multivariate analyses, the increased odds ratio of 3.2 and 4.05, respectively, with an HbA1c of 6.5% or greater; however, as noted the stratified HbA1c data revealed a J-shaped curve showing accountable retinopathy prevalence at below 6.0%. The meta-regression also revealed the increase in retinopathy prevalence with those aged over 55 years, with an OR of 3.23 and a striking increase in retinopathy prevalence for African-Americans with an OR of 10.73 on multivariate analysis. While this is in accord with the previous data [3, 9,10,11], retinopathy clearly occurs earlier than the cutoff of 6.5%. The magnitude of the association of retinopathy with race found here may not be representative as only 8 studies were available among African-Americans, though it raises the question whether a different diagnostic cutoff for T2DM for African-Americans aged greater than 55 years may be appropriate, as they would appear to be the group at greatest risk [54]. It should also be emphasized that the stratification of HbA1c and retinopathy was based on the detection of moderate retinopathy and it is unknown whether the diagnostic cutpoint for T2DM may be altered by prevalence studies on minimal diabetic retinopathy. Thus, the T2DM diagnostic cutpoint for HbA1c may not be a universal “one size fits all,” but may need to be stratified according to age and race.

The main limitations of the 22 studies of retinopathy included in the meta-analysis were that retinal photography was not standardized and that the degree of retinopathy was often reported as moderate or poorly specified [27, 38]. As different studies have measured the complications in different ways, this may have affected the outcome and we may therefore have underestimated the prevalence of the diabetic complications. There were few studies focusing specifically on the onset of minimal diabetes retinopathy. In addition, minimal retinopathy may be difficult to differentiate between diabetes and non-diabetes-related retinopathy and therefore only moderate diabetes changes were identified in all studies analyzed. This could suggest that with a standardized procedure specifically identifying minimal diabetic retinopathy, that the inflection point for the onset of retinopathy would be a HbA1c lower than 6.5% (48 mmol/mol), but this is clearly speculative as there is insufficient evidence to support this at present.

Four studies were evaluated which considered the onset of nephropathy, the data showing that the HbA1c cutoff of 6.5% (48 mmol/mol) was appropriate with a significant increase in the urine albumin/creatinine ratio. Again, it is evident that there were significant numbers of subjects with albuminuria in the range of “prediabetes” between 6.0–6.4% (42–47 mmol/mol); however, the main limitations were the small number of studies, heterogeneity of the population and lack of division of the HbA1c level into 0.1% ranges that prevented a more stringent determination. In addition, all of the studies were cross sectional with a need for longitudinal studies to be performed.

There were only three studies with sufficient data that could be evaluated for the onset of neuropathy, and these were inconclusive with no inflection point seen for the HbA1c cutoff, with a prevalence of neuropathy at an HbA1c of 6.0–6.4 (42–46 mmol/mol) being the same as that of 6.5% (48 mmol/mol) and above. The main limitations here include the limited amount of data in too few studies, heterogeneity of the population and poor division of the HbA1c range into 0.1% ranges; however, given the limited data, it is unlikely that division of HbA1c into 0.1% ranges would have allowed a more stringent determination.

Conclusions

In conclusion, based on the strongest data of moderate retinopathy, this systematic review and meta-analysis is in accord that the HbA1c diagnostic cutpoint of 6.5% (48 mmol/mol) is highly specific for diagnosing T2DM, though the increased prevalence of retinopathy in those aged 55 years or greater and in African-Americans may suggest a lower threshold is appropriate for those groups. However, this analysis highlights that diabetic microvascular complications commonly occur at lower HbA1c values, and the sensitivity of diagnosing T2DM may improve with a lower diagnostic cutpoint. There is a need for studies that standardize the definition of minimal diabetic retinopathy with more sensitive measures of nephropathy and neuropathy to determine if a lower threshold is appropriate.