by Pushpa Larsen, ND

Twenty years and more ago, when many of the practitioners reading this article were in medical school, we were taught that a fasting blood glucose measurement was an adequate screen for blood sugar issues. As long as it was below 100, it was considered normal and therefore of no consequence. Even those who practiced more proactively often considered fasting glucose a reliable indicator of glucose regulation, although perhaps levels above 90 would raise red flags. Glucose levels higher than 100 might trigger further evaluation with an oral glucose tolerance test (OGTT). Hemoglobin A1c (glycosylated hemoglobin) was then considered only for use in patients already diagnosed as diabetic. The focus was entirely on blood glucose. Insulin was rarely measured.

The limitation of relying entirely on these measurements is that, in the insulin-resistant individual, rising insulin levels may well keep blood sugar at normal, even optimal, levels for years, while elevated circulating insulin damages blood vessels and contributes to central weight gain. By the time the overworked pancreatic cells begin to decrease production of insulin and blood glucose levels skyrocket, the damage has been done. The road back to optimal blood sugar control is much more difficult at this point. Typically, patients go on blood–sugar lowering pharmaceuticals and remain on them the rest of their lives, even if they make changes in their dietary and exercise habits.

Today, of course, the phenomenon of insulin resistance is widely recognized, but the tests commonly used for screening may be missing a great number of patients that could benefit earlier detection and intervention. Let’s look at the available tests.

Fasting Glucose

Fasting glucose, as noted above, doesn’t really test for insulin resistance, but is important because it is commonly included in a comprehensive metabolic panel or other health screening panel and therefore may be the first sign that there is a problem. Optimal for fasting glucose is probably in the mid-80s, but this level should not be interpreted as a sign that insulin resistance is absent.

Oral Glucose Tolerance Test (OGTT)

The classic OGTT was done over a period of 2 to 3 hours with draws done at fasting, and 30, 60, 90, and 120 minutes after a 75 to 100 gram glucose challenge. Sometimes a 3-hour (180 minute) draw was also done. Over time, the number of draws was reduced and the glucose challenge was standardized. The current recommendation of the World Health Organization is a 75gm glucose challenge for adults.¹ A standard OGTT now consists of a baseline (fasting) draw and a two-hour post-challenge draw (Table 1).²

The shortcoming of the standard OGTT is that it is entirely possible to have fasting and 2-hour glucose levels in the normal range and still have elevated insulin values, a sign that insulin sensitivity is diminishing and that ever-increasing levels of insulin are required to maintain glucose regulation.

Hemoglobin A1c/Fructosamine

Hemoglobin A1c (also known as glycosylated or glycated hemoglobin) measures the degree to which hemoglobin molecules in red blood cells have been glycated or have had sugar molecules attached to them. Because red blood cells have a life span of around 120 days, this measurement allows us to assess average blood sugar levels over the past 3 to 4 months. Once used only for monitoring blood sugar in diabetics, HgbA1c is now routinely used by integrative and mainstream practitioners as a screening and monitoring tool (Table 2). The optimal level for HgbA1c used by many functional medicine practitioners is ≤5.4%

Fructosamine measures glycated serum proteins, particularly albumin, which suggests average blood sugar over the previous 2 to 3 weeks. It has much more limited utility, and values between labs can vary due to differences in methodology. Patient age, gender, and other factors can also affect fructosamine values. It is most useful for monitoring efficacy of treatment that might be expected to show results rather quickly. It is also used in place of HcbA1c in individuals with disorders that effect red blood cells, such as sickle cell disease and hemolytic anemia.

Fasting Insulin

Fasting insulin measurements started being used about 15 years ago by practitioners looking for a way of assessing insulin resistance. Normal values for fasting insulin are anywhere from <30 to <20, depending on the laboratory. However, optimal fasting insulin is considerably lower, usually considered to be ≤10. Many practitioners consider optimal to be closer to ≤6. Using fasting insulin to assess insulin resistance can be misleading as it is quite possible to have a fasting insulin of <10 and still have insulin resistance. This can be seen clearly in the graphs of patient results later in this article.

In short, we have very well-established methods for assessing glucose regulation, allowing us to easily diagnose patients as nondiabetic, prediabetic, or diabetic. What has been missing is a reliable way to detect insulin resistance in those years when insulin levels are rising but still keeping blood sugar levels down. This need is answered by the glucose tolerance/insulin response test.

Glucose Tolerance/Insulin Response (GTIR)

The glucose tolerance/insulin response test is based on a classic OGTT, with measurements made at baseline (fasting) and at multiple points after a glucose challenge. At each point, both glucose and insulin are measured. The results are graphed and the insulin response is classified according to patterns. These patterns describe a progression of insulin response from completely normal to the flat curve seen with islet cell exhaustion. Patterns early in the progression can detect insulin resistance even when fasting and 2-hour glucose and fasting insulin are at optimal levels. This allows for much earlier intervention which can halt the progression of insulin resistance.

The GTIR test is based on the research of Dr. Joseph Kraft, a clinical pathologist, who has been studying insulin response and diabetes since the 1970s. Kraft (MD, MS, FCAP) was chairman of the Department of Pathology and Nuclear Medicine at St. Joseph Hospital in Chicago from 1972 to 1998. His paper, “Detection of Diabetes Mellitus In Situ (Occult Diabetes)”, was originally published in Laboratory Medicine in 1975.³ This study included 3650 patients who had been referred for a glucose tolerance test to rule out (or in) diabetes mellitus. Patients had a fasting blood draw and then received a 100 gram glucose challenge, followed by blood draws at 30 minutes, and at hours 1 through 4 after consumption of the glucose drink.

Based on the glucose tolerance test alone, 1937 patients (53%) were diagnosed as having DM; 1713 patients (47%) were determined to be normal (Figure 1). But Dr. Kraft had tested insulin for these patients at the same time, and analysis of the insulin values revealed a different story for the “normal” group. Of the normal group, 565 patients (33%) were still deemed normal after analyzing insulin response. 862 patients (50%) were determined to have what Dr. Kraft characterized as “diabetes in situ,” a term that he adopted “because it embodies the concept of disease detection at its earliest identifiable point.” Another 240 patients (14% of the “normal” group) were found to be borderline. 43 patients (~3%) had a flat insulin curve suggestive of islet cells that were no longer producing adequate insulin (Figure 2).

Looking at it another way, we could say that of the original 3650 patients who were administered the OGTT, only 15% (not 53%) were truly normal. Nearly one-third of these patients had an abnormal insulin response that went undetected when looking only at glucose values (Figure 3). If this seems high, we should remember that these were patients referred for OGTT because of a suspicion of DM. Since this original study, Kraft has continued to investigate insulin response as a marker for early detection of developing diabetes. His evaluations of more than 14,000 OGTTs with insulin assays have substantiated his early findings.⁴

GTIR Insulin Response Patterns

Kraft distinguished five patterns of insulin response. One of these, Pattern III, has two variations. The progression of these patterns depicts the progression of glucose/insulin dysregulation from its earliest stages to full-blown diabetes and insulin dependence. The graphs illustrating these patterns are drawn from actual patient results.

Pattern I

Pattern I represents normal glucose tolerance and insulin response (Figure 4). Fasting insulin is normal at between 0 and 10. Insulin peaks at 30 minutes or 1 hour and is <50 by the second hour. Third-hour insulin is lower than the second hour, and second plus third hour total is <60. Subsequent hour insulin values are back at the fasting range (0–10).

Pattern II

Pattern II starts out looking normal but shows evidence of beginning insulin resistance as the test progresses (Figure 5). As in Pattern I, fasting insulin is between 0 and 10 and insulin peaks at 30 minutes or 1 hour. The second hour plus third hour total is more than 60. If the total is between 60 and 100, the test is considered borderline for insulin resistance. If the total is more than 100, the test is considered confirmatory for insulin resistance.

Patte

rn III

Pattern III shows a delayed insulin peak and a much greater area under the curve. Fasting insulin is between 0 and 10. Pattern III-A insulin peaks at 2 hours. Two-hour glucose levels may be within normal limits, as can be seen in the example in Figure 6. Pattern III-B insulin peaks at 3 hours. (Figure 7) Two-hour glucose levels are generally higher although may fall within normal limits. The area under the curve for both insulin and glucose is much greater. Both variants are diagnostic for insulin resistance.

Pattern IV

Pattern IV is characterized by fasting insulin >10 (Figure 8). Elevated fasting insulin is diagnostic for insulin resistance regardless of other values. Glucose values are often in diabetic ranges and insulin levels are dramatically high, typically peaking at the third hour. The area under the curve is quite large. The example in Figure 8 shows a Pattern IV result in which extremely high insulin levels functioned to keep all blood glucose levels within normal levels. This would have been completely missed on a standard OGTT.

Pattern V

Pattern V displays a flattened insulin curve, with all insulin values being less than 30 (Figure 9). This is considered to be an inadequate insulin response to the glucose challenge and suggests exhaustion of pancreatic islet cells. This might be seen in someone who has been hyperinsulinemic for an extended period of time and now has a decreased capacity to respond. Typically, glucose values will be in diabetic ranges if not otherwise controlled.

In a few cases, Pattern V insulin response will be seen in conjunction with normal glucose levels. This may be due to a low-carbohydrate diet that has resulted in a downregulated insulin response.

GTIR Pattern Progression

Putting the insulin curves for the different patterns into a single graph illustrates a distinct progression of insulin resistance from normal to insulinopenic (Figure 10). With this test, nascent insulin resistance can be detected long before blood glucose values might start to sound alarm bells. The import of this is magnified when one considers that diabetes has both individual and societal costs, and that it can largely be prevented or reversed with earlier detection, lifestyle changes, and treatment.

Case Study

The value of the GTIR for early detection and treatment cannot be overstated. The case of G. J. is a compelling example of this. G. J. is a 38-year-old woman who came into our clinic with a chief complaint of easy weight gain and fatigue. She is 5’4” tall and weighed 174 pounds at the initial visit. BMI was 29.9. Her pulse and respirations were normal and her BP was 107/76. She had a history of gestational diabetes and a family history of type 2 diabetes. Fasting blood sugar was elevated at 111, but HgbA1c was only 5.3. Because of the family and personal history, a 4-hour GTIR test was run. On the test, fasting and 2 hour glucose were 83 and 113, respectively, both well within the limits of normal based on American Diabetes Association criteria. Fasting insulin was above 10 (11.80) and peaked in the second hour at 93.20. This is a Pattern IV insulin response (Figure 11A).

GJ was put on berberine, 500mg t.i.d., and counseled about diet and exercise. She was highly motivated because of her Pattern IV GTIR result. At her 6-month follow-up visit, she had lost 9 pounds and her BMI had decreased to 28.3. Her HgbA1c was also improved at 5.1. Her GTIR test demonstrated a dramatic reversal from the original Pattern IV result to a completely normal Pattern I result (Figure 11B).

A New Method of GTIR Testing

Up until now, the GTIR test has required the capacity to do multiple venipunctures over an extended period of time, whether in the practitioner’s office or at a lab draw station. Now a new finger-stick version of the test is being introduced, making early detection of insulin resistance accessible to those practitioners who do not draw blood in their offices. Finger-stick blood sugar measurements have been around for decades, of course, and finger-stick testing of insulin is not new. However, inherent differences between venous blood and capillary blood in both sugar and insulin levels require careful calibration of references ranges to allow accurate identification of the Kraft patterns of insulin response. The new blood-spot GTIR test is the result of extended testing and verification to authenticate these patterns.

The Cost of Ignorance

It is indisputable that rising costs have the US health-care system teetering on the edge of catastrophe. It can certainly be argued that this is in large part because of the focus on “disease management” rather than actual “health care” or prevention. With any condition, early detection allows for early intervention. The earlier the intervention, the fewer drastic measures are needed and the better the chances for a return to health. In the US, 21.0 million adults have been diagnosed with diabetes and another 8.1 million have diabetes and are undiagnosed. In addition, it is estimated that 86 million Americans over age 20 have prediabetes, based on fasting glucose or HgbA1c levels.⁵ Yet as we have seen in the case of G. J. and other examples presented in the above graphs, these parameters miss people who show signs of growing glucose/insulin dysregulation if the insulin response is taken into account. What is the price of this ignorance?

The total estimated cost of diabetes in the US in 2012 was $245 billion. That figure includes direct medical costs as well as indirect costs such as disability and loss of income due to missed work.⁵ If we extend those costs to the 86 million with prediabetes, we are looking at more than $700 billion in additional future costs. This does not include those with insulin resistance who slip under the ADA radar.

After adjusting for age and sex differences, the average medical expenses among people diagnosed with diabetes was 2.3 times higher than those without diabetes.⁵ If we could prevent only those 86 million with prediabetes from progressing to diabetes (and perhaps even reverse their condition), that would translate into nearly half a billion additional dollars that these individuals could use in more productive ways. These numbers also do not account for the more human costs, in decreased function, enjoyment of life, and ability to contribute to one’s community that accompany chronic disease.

Current thinking about reducing health-care costs in the US focuses on reducing testing (deemed “unnecessary” testing). There is evidence that this may also be the case in Canada. This is a penny-wise, pound-foolish approach. It saves money now, but at the cost of billions of dollars of future health-care expenses. To truly reduce health-care costs requires preventing chronic diseases from developing in the first place. Diabetes is one such disease wherein the natural progression of the disease is clear enough to make early detection too valuable a tool to omit.

Who Should Be Tested?

The National Diabetes Education Program recommends that anyone with risk factors be evaluated for diabetes. Besides the obvious risk factors, such as family history, gestational diabetes, lipid abnormalities, or elevated blood pressure, the NDEP also recommends including African American, Hispanic/Latino, American Indian, Asian American, or Pacific Islander ethnicity as triggers for increased vigilance. A BMI of >25 (>23 for Asian, >26 for Pacific Islander) is also a reason for further evaluation. Simply being 45 years or older warrants increased surveillance. Also on the NDEP risk factor list are PCOS, acanthosis nigricans, history of giving birth to a baby of 9 pounds or more, and being physically active less than 3 times a week.⁶

Not on the NDEP list, but worthy of consideration in this context are tinnitus, sugar cravings, symptoms of hypoglycemia, sleep disturbances (including in those who are shift workers and others with disrupted sleep patterns), skin tags, osteoarthritis prior to age 50, Peyronie’s disease, DuPuytren’s contracture, recurrent yeast/fungal infections, changes in vision, gum disease, and low testosterone in men. All of these conditions or symptoms have been associated with changes in blood sugar and insulin regulation.^7–19

It is also worth noting that patients with an optimal BMI may still exhibit central weight gain. Thin patients who also have a “love handles” or a “muffin top” may be showing signs of insulin resistance (which may be well disguised by their clothing). Certainly any weight gain beyond normal growth in a child or adolescent should raise red flags.

Beyond the more familiar laboratory markers discussed earlier, a number of other less than optimal results point to insulin resistance. In a 24-hour urine hormone profile, elevated 5α-reductase, a testosterone:estrogen ratio of <4 (in men), an elevated cortisol/cortisone ratio, and elevated cortisol metabolites all suggest further evaluation for insulin resistance. Hyperviscosity on a blood viscosity panel may also have insulin resistance as an underlying etiology.

For an individual with a healthful lifestyle and no other risk factors, a baseline GTIR at 45 years of age would be prudent, with follow-up testing every 3 to 5 years if no signs of insulin resistance become apparent.

There is no question that the problem of type 2 diabetes has reached epidemic proportions. This disease takes a great toll, both personal and societal, and reducing the incidence of diabetes would provide wide-ranging benefits. The best way to do this is by preventing the development of the disease in its earliest stages, long before it actually becomes diabetes. Traditional methods of detection are good but miss many people in the early stages of insulin resistance. The glucose tolerance/insulin response test offers a way to improve our ability to intervene earlier, when it can make the most difference.

Notes

1. About diabetes [Web page]. World Health Organization. http://www.who.int/diabetes/action_online/basics/en. Oct. 6, 2014.

2. American diabetes association: diagnosing diabetes and learning about pre-diabetes [Web page]. Sept. 22, 2104. www.diabetes.org/diabetes-basics/diagnosis/?loc=db-slabnav Accessed Oct. 6, 2014.

3. Kraft JR. Detection of diabetes mellitus in situ (occult diabetes). Lab Med. 1975;6(2):10–22.

4. Kraft JR. Diabetes Epidemic and You. Bloomington, IN: Trafford; 2009.

5. National diabetes statistical report, 2014 [online document]. CDC. www.cdc.gov/diabetes/pubs/statsreport14/national-diabetes-report-web.pdf. Accessed Oct. 6, 2014.

6. Diabetes risk factors [Web page]. National Diabetes Education Program. http://ndep.nih.gov/am-i-at-risk/DiabetesRiskFactors.aspx. Accessed Oct. 1, 2014.

7. Kraft JR. Hyperinsulinemia: a merging history with idiopathic tinnitus, vertigo, and hearing loss. Int Tinnitus J. 1998;4(2):127–130.

8. Lavinsky L et al. Hyperinsulinemia and tinnitus: a historical cohort. Int Tinnitus J. 2004;10(1):24–30

9. Spiegel K et al. Sleep loss: a novel risk factor for insulin resistance and Type 2 diabetes. J Appl Physiol. 2005;99(5):2008–2019.

10. Buxton O et al. Sleep restriction for 1 week reduces insulin sensitivity in healthy men. Diabetes. 2010;59(9):2126–2133.

11. Spiegel K et al. Impact of sleep debt on metabolic and endocrine function. Lancet. 1999;354(9188):1435–1439.

12. Schilling W, Crook M .Cutaneous stigmata associated with insulin resistance and increased cardiovascular risk. Int J Dermatol. 2014;53(9):1062–1069.

13. Sellam J, Berenbaum F. Is osteoarthritis a metabolic disease? Joint Bone Spine. 2013;80(6):568–573.

14. Han CD et al. Correlation between metabolic syndrome and knee osteoarthritis: data from the Korean National Health and Nutrition Examination Survey (KNHANES). BMC Pub Health. 2013;13:603.

15. Deveci S et al. Defining the clinical characteristics of Peyronie’s disease in young men. J Sex Med. 2007;4(2):485–490.

16. Papanas N et al. The diabetic hand: a forgotten complication? J Diabetes Complications. 2010;24(3):154–162.

17. Kolar P. Risk factors for central and branch retinal veign occlusion: a meta-analysis of published clinical data. J Ophthalmology. 2014.

18. Demmer R et al. Periodontal infection, systemic inflammation, and insulin resistance: results from the continuous National Health and Nutrition Examination Survey (NHANES) 1999–2004. Diabetes Care. 2012;35(11):2235–2242.

19. Kapoor D et al. Androgens insulin resistance and vascular disease in men. Clin Endocrinol. 2005;63(3):239–250.

Captions for GTIR Figures

Figure

1

: Out of a total of 3650 patients referred for an oral glucose tolerance test because of suspected diabetes mellitus, 1713 (47%) were determined to be normal based on the results of the OGTT.

Figure

2

: Of the 1713 determined to be normal based on OGTT alone, two-thirds were determined to have an abnormal insulin response.

Figure

3

: In looking again at the 3650 patients referred for OGTT, only 15% were considered normal after taking into account insulin response.

Figure

4: Pattern I.

37-year-old female patient with normal insulin and glucose response on glucose tolerance/insulin response test (GTIR)

Figure

5:

Pattern II.

19-year-old female patient with normal fasting insulin and glucose and normal 2-hour glucose. 2nd-hour insulin >50. 2nd- and 3rd-hour insulin total >60 but <100. This is considered borderline insulin resistance.

Figure

6: Pattern III-A.

70-year-old female patient. Fasting insulin and glucose and 2-hour glucose are all within normal limits and she would be classified as normal on OGTT alone. Insulin peak at 147 in the 2nd hour reveals well-established insulin resistance. Scale is changed from Figures 4 and 5 to accommodate higher blood sugar levels.

Figure

7: Pattern III-B.

76-year-old female patient with abnormal fasting and 2-hour glucose. Insulin peak is at 3 hours, indicating a prolonged rise in insulin as the body tries to deal with the glucose challenge. Insulin is still elevated at 4 hours postchallenge.

Figure

8: Pattern IV.

67-year-old female patient with normal fasting and 2-hour glucose. Fasting insulin is >10 but still within most standard lab references ranges. Notice how high her insulin rises in order to keep blood sugar normal. Scale is changed from Figures 6 and 7 to accommodate higher insulin and blood sugar levels.

Figure

9: Pattern V.

63-year-old male patient with diabetes. Suppressed insulin response explains why his antiglycemic drugs were not keeping his blood sugar levels under control. This patient needed to go on insulin.

Figure

10: Progression of Insulin Resistance.

Insulin peak is delayed further into the testing period as insulin response becomes more abnormal (Patterns I through III-B). Pattern IV demonstrates prolonged exposure to very high insulin levels. Pattern V demonstrates flattened insulin response.

Figure

11A: Case Study.

Insulin resistance in a 38-year-old female, as evidenced by Pattern IV GTIR test results. Fasting insulin is >10, peaks at 2 hours, and remains >10 by the 4-hour measurement.

Figure

11B:

A second test in the same patient 6 months later shows a complete reversal of insulin insensitivity. This test had a normal Pattern I result.