Skip to main content
NCBI home page
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2018 Apr 3.
Published in final edited form as: Obes Surg. 2018 Jan;28(1):25–30. doi: 10.1007/s11695-017-2804-5

The Role of Laboratory Testing in Differentiating Type 1 Diabetes from Type 2 Diabetes in Patients Undergoing Bariatric Surgery

Scott J Pilla 1,✉, Nisa M Maruthur 1,2, Michael A Schweitzer 3, Thomas H Magnuson 3, James J Potter 4, Jeanne M Clark 1,2, Clare J Lee 5
PMCID: PMC5881120  NIHMSID: NIHMS951657  PMID: 28695457

Abstract

Background

It may be difficult to distinguish between adults with type 1 diabetes and type 2 diabetes by clinical assessment. In patients undergoing bariatric surgery, it is critical to correctly classify diabetes subtype to prevent adverse perioperative outcomes including diabetic ketoacidosis. This study aimed to determine whether testing for C-peptide and islet cell antibodies during preoperative evaluation for bariatric surgery could improve the classification of type 1 versus type 2 diabetes compared to clinical assessment alone.

Methods

This is a retrospective analysis of the Improving Diabetes through Lifestyle and Surgery trial, which randomized patients with clinically diagnosed type 2 diabetes and BMI 30–40 kg/m2 to medical weight loss or bariatric surgery; one participant was discovered to have type 1 diabetes after experiencing postoperative diabetic ketoacidosis. Using blood samples collected prior to study interventions, we measured islet cell antibodies and fasting/meal-stimulated C-peptide in all participants.

Results

The participant with type 1 diabetes was similar to the 11 participants with type 2 diabetes in age at diagnosis, adiposity, and glycemic control but had the lowest C-peptide levels. Among insulin-treated participants, fasting and stimulated C-peptide correlated strongly with the C-peptide area-under-the-curve on mixed meal tolerance testing (R = 0.86 and 0.88, respectively). Three participants, including the one with type 1 diabetes, were islet cell antibody positive.

Conclusions

Clinical characteristics did not correctly identify type 1 diabetes in this study. Preoperative C-peptide testing may improve diabetes classification in patients undergoing bariatric surgery; further research is needed to define the optimal C-peptide thresholds.

Keywords: Bariatric surgery, Type 1 diabetes mellitus, Type 2 diabetes mellitus, Perioperative care, C-peptide, beta-cell

Introduction

Bariatric surgery improves outcomes in patients with type 2 diabetes, including achieving diabetes remission [1]. Thus, there is advocacy to perform bariatric surgery in patients with type 2 diabetes at body mass index (BMI) as low as 30 kg/m2 [2], and prospective studies have begun to evaluate patients with even lower BMI [3]. Performing bariatric surgery in patients at a lower BMI increases the likelihood that surgical candidates may include patients with type 1 diabetes who have been misdiagnosed as having type 2 diabetes [4].

Typically patients with type 1 diabetes are diagnosed at a young age and have low adiposity compared to patients with type 2 diabetes [5]. However, more than 25% of type 1 diabetes presents in adulthood [6], and the rate of obesity in type 1 diabetes is high and rising [7]. As such, patients with type 1 diabetes can have or develop insulin resistance in addition to absolute insulin deficiency, and features of type 1 and type 2 diabetes can overlap [7]. Additionally, approximately 10% of patients diagnosed with type 2 diabetes are thought to have latent autoimmune diabetes in adults (LADA), a subset of adult-onset diabetes who have an accelerated progression to insulin deficiency as a result of autoimmunity [8]. Such patients may have clinical features of type 2 diabetes, particularly with regard to age at onset and BMI, yet have absolute insulin deficiency [8]. Therefore, the clinical features of type 1 diabetes may not identify all patients who have absolute insulin deficiency.

Correct classification of diabetes prior to bariatric surgery is critical as patients with absolute insulin deficiency require close inpatient monitoring and continued administration of insulin in the postoperative period [9]. High rates of hypoglycemia and diabetic ketoacidosis occur in patients with type 1 diabetes after bariatric surgery [10–13]. Despite these important considerations for perioperative care, there is no consensus on how patients with diabetes should be evaluated preoperatively to avoid misclassification [2].

It has been proposed that all patients with diabetes should be screened prior to bariatric surgery with a C-peptide level and islet cell antibody tests [14, 15]. C-peptide reflects endogenous insulin secretion by pancreatic β-cells which can be measured fasting or with a stimulation test, which is considered to be more accurate [16]. Islet cell antibodies are auto-antibodies directed at the pancreas found in >95% of patients with type 1 diabetes at diagnosis and are usually persistent [17, 18]. Studies of bariatric surgery in patients with type 1 diabetes have required the presence of islet cell antibodies or a low C-peptide level for inclusion [11, 12, 19, 20]. In contrast, bariatric surgery trials enrolling patients with type 2 diabetes use varying criteria to exclude patients with type 1 diabetes [21–25] with two major studies using clinical assessment alone [21, 22].

Here, we present data from the Improving Diabetes through Lifestyle and Surgery (IDeaLS) clinical trial relevant to preoperative diabetes classification. IDeaLS randomized patients with clinically diagnosed type 2 diabetes to medical weight loss, laparoscopic adjustable gastric banding (LAGB), or laparoscopic Roux-en-Y gastric bypass (LRYGB). One participant, referred to as Patient X, was initially thought to have type 2 diabetes by clinical assessment but was discovered to have type 1 diabetes after being readmitted with diabetic ketoacidosis within 72 h of uncomplicated LRYGB. On subsequent evaluation, Patient X was found to have positive islet cell antibodies, a low fasting C-peptide level, and a persistent insulin requirement after LRYGB.

We performed a secondary analysis of participants in the IDeaLS trial to determine whether preoperative testing for pancreatic β-cell function and islet cell antibodies could have prevented diabetes misclassification in our study and could inform protocols to prevent adverse perioperative outcomes in patients undergoing bariatric surgery.

Methods

Participants

The IDeaLS trial enrolled ambulatory adults from July 2013 to June 2014. Inclusion criteria were type 2 diabetes determined by clinical assessment by trial staff, BMI 30–40 kg/m2, hemoglobin A1c (HbA1c) 6.5–10%, and insured by a single health insurer. Exclusion criteria included prior bariatric surgery, significant recent weight loss, severe kidney disease, active cancer, HIV, substance abuse, and use of thiazolidinediones. Fifteen participants were enrolled, and three withdrew prior to initial evaluation; this analysis includes the 12 remaining participants.

Study Interventions

The primary objective of IDeaLS was to evaluate the differential effects of surgical and medical weight loss interventions on type 2 diabetes. Participants were randomized to medical weight loss, LAGB, or LRYGB. All surgical procedures were performed at a single academic medical center using standardized protocols [26]. Follow-up continued until participants had lost 10% of initial body weight or for 9 months.

Study Measures

Weight, height, waist circumference, and blood pressure were measured by trained staff using standard protocols. Percent body fat was determined by dual energy x-ray absorptiometry (DXA) using the Lunar Prodigy densitometer. All C-peptide measurements were derived from C-peptide mixed meal tolerance testing (MMT) which was performed as part of the IDeaLS trial prior to study interventions. Additionally, for this study, we retrospectively tested preoperative stored blood for islet cell antibodies. C-peptide was measured in plasma using the Milliplex MAP Human Metabolic Hormone Magnetic Bead Panel Kit (EMD Millipore, Billerica, MA). The mean minimum detectible concentration was 27 pg/ml and the intra- and inter-assay coefficients of variation were <10 and <15%, respectively. MMT was conducted after an overnight fast, with antihyperglycemic medications held except long-acting insulins which were reduced by 50%; after drinking two cans of Ensure Plus (474 mL), C-peptide was measured at 10 time points over 5 h. Islet cell antibodies tested were glutamic acid decarboxylase 65 antibody (GADA), insulinoma antigen-2 antibody (IA2A), and zinc transporter 8 antibody (ZnT8A). GADA and IA2A were measured by radiobinding assays using the NIDDK standardized protocol at the Northwest Lipid Research Laboratories in Seattle, Washington [27]. Znt8A was measured by radioimmunoassay at the Barbara Davis Center for Diabetes in Aurora, Colorado [28].

Analysis

Non-parametric summary statistics were used to describe participant characteristics given the small sample size. Stimulated C-peptide was the value at 90-min elapsed time on MMT to align with other studies [16]. C-peptide area under the curve (AUC) was calculated using the trapezoidal method, then converted to mean C-peptide by dividing by time. The homeostatic model assessment calculatorV2.2.4was used to estimate β-cell function (HOMA-B) and insulin resistance (HOMA-IR) from fasting C-peptide and fasting glucose values collected concurrently [29, 30]. Analyses were performed using STATA version 14 (StataCorp LP, College Station, TX).

Results

Median follow up for the 12 study participants was 7.9, 2.3, and 1.8 months in the medical weight loss arm, LAGB arm, and LRYGB arms, respectively. Only Patient X experienced diabetic ketoacidosis or developed signs suggestive of type 1 diabetes during follow-up, so the remaining 11 participants were considered to have been correctly classified as having type 2 diabetes.

Table 1 shows baseline characteristics of the study population. Among the 11 participants with type 2 diabetes, all were female, the median age was 52 years, and the median BMI was 37.3 kg/m2. Participants with type 2 diabetes were diagnosed with diabetes at a median age of 42 years, and three were using insulin. Patient X was 59 years old and was diagnosed with diabetes 6 years prior. Her BMI (31.3 kg/m2) was the second lowest of all participants, and her body fat percentage (55%) was the highest. Her fasting glucose and HbA1c were within the range of other participants. Her diabetes medications were metformin, liraglutide, and basal and prandial insulin totaling 25 units daily.

Table 1.

Baseline characteristics of Patient X (type 1 diabetes) and other participants (type 2 diabetes)

Characteristica Patient X Participants with type
2 diabetes
Number of participants, n 1 11
Age (years) 59 52 (32–62)
Female sex Yes 11 (100)
Race
  White Yes 2 (18.2)
  Black No 9 (81.8)
Weight (kg) 80.0 99.9 (85.9–112.3)
BMI (kg/m2) 31.3 37.3 (31.0–40.5)
Waist circumference (cm) 80.0 114.3 (103.5–131.0)
Body fat by DXA (%) 55 45 (38–50)
Fasting glucose (mg/dL) 175 146 (92–256)
Hemoglobin A1c (%) 9.4 8.0 (6.3–10.0)
Age at diabetes diagnosis (years) 53 42 (27–57)
Diabetes duration (years) 6 6 (1–16)
Use of insulin—any type Yes 3 (27.3)
Use of insulin—long acting Yes 2 (18.2)
Use of insulin—rapid acting Yes 3 (27.3)
Open in a new tab

BMI body mass index, DXA dual energy x-ray absorptiometry

a

Values expressed as median (range) or n (% of column)

Table 2 shows the results of baseline testing of glucose homeostasis and islet cell antibodies. Participants with type 2 diabetes had a median fasting C-peptide of 1.70 ng/mL and a median stimulated C-peptide of 3.85 ng/mL. Patient X had the lowest C-peptide values of any participant: her fasting and stimulated C-peptide values were approximately one half and one third that of the next lowest participant, respectively. Patient X had the lowest pancreatic β-cell function and the lowest insulin resistance of any participant by HOMA analysis. In addition, Patient X had a C-peptide response to MMT that was qualitatively different from that of other participants, exhibiting very little augmentation of C-peptide with no clear peak (Fig. 1). Patient X was positive for all three islet cell antibodies: GADA, IA2A, and Znt8A. Among participants with type 2 diabetes, two were positive for GADA; none were positive for other antibodies.

Table 2.

Results of glucose homeostasis and islet cell antibody testing of Patient X (type 1 diabetes) and other participants (type 2 diabetes), stratified by insulin use

Characteristica Patient X Participants with
type 2 diabetes		 Type 2 diabetes—insulin
users		 Type 2 diabetes—insulin
non-users
Number of participants, n 1 11 3 8
Fasting C-peptide (ng/mL) 0.37 1.70 (0.69–3.08) 1.74 (0.69–2.15) 1.70 (1.10–3.08)
Stimulated C-peptide (ng/mL)b 0.38 3.85 (1.25–7.09) 1.81 (1.59–4.74) 3.86 (1.25–7.09)
Peak C-peptide (ng/mL)c 0.43 4.80 (2.34–18.29) 3.99 (2.34–4.80) 6.37 (2.56–18.29)
Mean C-peptide (ng/mL)d 0.41 3.85 (1.69–7.59) 2.82 (1.69–3.85) 4.29 (2.12–7.59)
HOMA % beta cell function 10.5 30.3 (21.4–129.0) 28.1 (21.4–30.3) 51.0 (25.4–129.0)
HOMA insulin resistance 0.3 1.6 (0.6–2.4) 1.6 (0.6–2.4) 1.6 (0.8–2.4)
GADA positive Yes 2 (18.2) 1 (33.3) 1 (12.5)
IA2A positive Yes 0 0 0
ZnT8A positive Yes 0 0 0
Open in a new tab

HOMA homeostatic model assessment, GADA glutamic acid decarboxylase 65 antibody, IA2A insulinoma antigen-2 antibody, ZnT8A zinc transporter 8 antibody

a

Values expressed as median (range) or n (% of column)

b

Value at 90 min from C-peptide 5-h mixed meal tolerance test

c

Highest value from C-peptide 5-h mixed meal tolerance test

d

Calculated from C-peptide 5-h mixed meal tolerance test as the area under the curve (trapezoidal method) divided by time

Fig. 1.

Fig. 1

Open in a new tab

Results of C-peptide mixed meal tolerance testing in Patient X (type 1 diabetes) and other participants with type 2 diabetes using insulin (n = 3)

Pancreatic β-cell function measured by mean C-peptide area-under-the-curve from MMT was compared to measures requiring only a single blood draw: fasting C-peptide, stimulated C-peptide, and HOMA-B (Fig. 2). HOMA-B had the highest linear correlation with mean C-peptide (R = 0.85). Restricting to participants using insulin, stimulated C-peptide had the highest linear correlation with mean C-peptide (R = 0.88); fasting C-peptide and HOMA-B had correlation coefficients of 0.86 and 0.66, respectively.

Fig. 2.

Fig. 2

Open in a new tab

Scatterplots of mean C-peptide from mixed meal tolerance testing versus pancreatic function tests requiring only a single blood draw, with linear regression lines. Mean C-peptide (the gold standard) was calculated from C-peptide 5-h mixed meal tolerance test as the area-under-the-curve divided by time, and compared to fasting C-peptide (a), stimulated C-peptide (level at 90 min on mixed meal tolerance test) (b), and HOMA % β-cell function (c). Black lines are results of linear regression for all participants; red dashed lines are results of linear regression for insulin users; blue dash-dot lines are results of linear regression for insulin non-users. The correlation coefficient (R) is shown for each linear regression function. HOMA homeostatic model assessment

Discussion

Diabetes classification prior to bariatric surgery is a high-stakes evaluation, as misclassifying a patient who has type 1 diabetes could result in significant adverse perioperative outcomes. In this study, we found that clinical assessment alone misclassified a patient with type 1 diabetes, and that laboratory testing for pancreatic β-cell function could have aided in determining this patient’s diabetes subtype.

Pancreatic β-cell function testing has been proposed to be used for diabetes classification prior to bariatric surgery [14, 15]; here, we evaluated several methods. MMT for C-peptide provided detailed data that clearly distinguished Patient X as having lower β-cell function than other participants. However, MMT is not always feasible due to high cost and requirement for multiple blood draws. We compared the mean C-peptide on MMT, a gold standard measure of β-cell function [16], to tests that require only a single blood draw: fasting C-peptide, stimulated C-peptide, and HOMA-B. The performance of these tests in insulin-treated patients is the most relevant, as patients who are not using insulin are unlikely to have type 1 diabetes. Among insulin-treated participants, stimulated C-peptide had the highest correlation with mean C-peptide. Fasting C-peptide performed slightly less well in our study, though it may be falsely low in insulin-treated patients which could require confirmatory testing [16]. HOMA-B had the worst performance and has not been validated in insulin-treated patients [30]. Overall, either fasting or stimulated C-peptide may be a useful and efficient measure of β-cell function prior to bariatric surgery.

A challenge with the use of C-peptide testing is that the optimal threshold to distinguish type 1 diabetes from type 2 diabetes has varied by population [16]. Data from patients with insulin-treated diabetes suggest that those with fasting C-peptide <0.75 ng/mL or stimulated C-peptide <1.80 ng/mL likely have type 1 diabetes [16]. In our study, these thresholds would have correctly classified Patient X but would have incorrectly classified three of 11 participants with type 2 diabetes. A recent trial of LRYGB for type 2 diabetes excluded those with stimulated C-peptide ≤1.0 ng/mL and documented one complication of diabetic ketoacidosis among 60 participants undergoing surgery [25]; this threshold would have correctly classified all participants in our study. Of note, C-peptide assays are not universally standardized at this time [16].

We also tested for the presence of three islet cell antibodies (GADA, IA2A, and Znt8A) for diabetes classification. While Patient X was positive for all three antibodies, two participants with type 2 diabetes were also GADA positive. In prior studies, approximately 6–10% of adults diagnosed with type 2 diabetes were GADA positive, and these patients had higher HbA1c, lower C-peptide, and a greater need for insulin longitudinally [8, 31, 32]. Given that islet cell antibody positivity is not highly specific to type 1 diabetes, it is not clear that islet cell antibody testing will add value to β-cell function testing for preoperative diabetes classification. However, it is possible that islet cell antibody positivity may have implications for the effects of bariatric surgery on diabetes outcomes. In patients with type 2 diabetes, lower preoperative C-peptide levels have been associated with a less favorable response to bariatric surgery in respect to glycemic control [33]. Further research is needed to determine whether the presence of islet cell antibodies impacts the efficacy of bariatric surgery.

This study was limited by a small sample size, with only one participant having type 1 diabetes. However, these data highlight the capacity for misclassifying diabetes by clinical assessment alone, supporting the use of objective testing prior to bariatric surgery in all patients on insulin. Routine testing of pancreatic β-cell function in future bariatric surgery trials could provide data to determine the C-peptide threshold that best identifies patients with absolute insulin deficiency. This study supports the use of a stimulated C-peptide threshold of 1.0 ng/mL.

In conclusion, it is important to correctly determine diabetes subtype prior to bariatric surgery to avoid perioperative complications and to identify individuals whose diabetes is unlikely to remit postoperatively. Pancreatic β-cell function testing, which may be done using fasting or stimulated C-peptide, can help to increase the accuracy of preoperative diabetes classification.

Acknowledgments

The authors would like to thank the Translational Research Enhancement Core of the Hopkins Conte Digestive Diseases Basic and Translational Research Development Center for the processing, preparation, storage, and shipment of the specimens for this study.

Funding Research reported in this publication was partially supported by the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) and the National Heart, Lung, and Blood Institute of the National Institutes of Health under award number 1R01DK089557–01 (PI: J. Clark) and the NIDDK under award number K23DK107921 (PI: C. Lee).

Footnotes

Compliance with Ethical Standards

Statement of Informed Consent Informed consent was obtained from all individual participants included in the study.

Statement of Human and Animal Rights This study was approved by the Johns Hopkins University School of Medicine Institutional Review Board. All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards.

Conflict of Interest The authors declare that they have no conflict of interest.

References

  • 1.Yu J, Zhou X, Li L, et al. The long-term effects of bariatric surgery for type 2 diabetes: systematic review and meta-analysis of randomized and non-randomized evidence. Obes Surg. 2015;25(1):143–58. doi: 10.1007/s11695-014-1460-2. [DOI] [PubMed] [Google Scholar]
  • 2.Mechanick JI, Youdim A, Jones DB, et al. Clinical practice guidelines for the perioperative nutritional, metabolic, and nonsurgical support of the bariatric surgery patient—2013 update: cosponsored by American Association of Clinical Endocrinologists, the Obesity Society, and American Society for Metabolic & Bariatric Surgery. Surg Obes Relat Dis. 2013;9(2):159–91. doi: 10.1016/j.soard.2012.12.010. [DOI] [PubMed] [Google Scholar]
  • 3.Baskota A, Li S, Dhakal N, et al. Bariatric surgery for type 2 diabetes mellitus in patients with BMI <30 kg/m2: a systematic review and meta-analysis. PLoS One. 2015;10(7):e0132335. doi: 10.1371/journal.pone.0132335. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 4.Shields BM, Peters JL, Cooper C, et al. Can clinical features be used to differentiate type 1 from type 2 diabetes? A systematic review of the literature. BMJ Open. 2015;5(11):e009088. doi: 10.1136/bmjopen-2015-009088. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5.American Diabetes Association. Diagnosis and classification of diabetes mellitus. Diabetes Care. 2014;37(Suppl 1):S81–90. doi: 10.2337/dc14-S081. [DOI] [PubMed] [Google Scholar]
  • 6.Maahs DM, West NA, Lawrence JM, et al. Epidemiology of type 1 diabetes. Endocrinol Metab Clin N Am. 2010;39(3):481–97. doi: 10.1016/j.ecl.2010.05.011. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7.Polsky S, Ellis SL. Obesity, insulin resistance, and type 1 diabetes mellitus. Curr Opin Endocrinol Diabetes Obes. 2015;22(4):277–82. doi: 10.1097/MED.0000000000000170. [DOI] [PubMed] [Google Scholar]
  • 8.Naik RG, Brooks-Worrell BM, Palmer JP. Latent autoimmune diabetes in adults. J Clin Endocrinol Metab. 2009;94(12):4635–44. doi: 10.1210/jc.2009-1120. [DOI] [PubMed] [Google Scholar]
  • 9.Tridgell DM, Tridgell AH, Hirsch IB. Inpatient management of adults and children with type 1 diabetes. Endocrinol Metab Clin N Am. 2010 Sep;39(3):595–608. doi: 10.1016/j.ecl.2010.05.014. [DOI] [PubMed] [Google Scholar]
  • 10.Brethauer SA, Aminian A, Rosenthal RJ, et al. Bariatric surgery improves the metabolic profile of morbidly obese patients with type-1 diabetes. Diabetes Care. 2014;37(3):e51–2. doi: 10.2337/dc13-1736. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11.Maraka S, Kudva YC, Kellogg TA, et al. Bariatric surgery and diabetes: implications of type 1 versus insulin-requiring type 2. Obesity (Silver Spring) 2015;23(3):552–7. doi: 10.1002/oby.20992. [DOI] [PubMed] [Google Scholar]
  • 12.Faucher P, Poitou C, Carette C, et al. Bariatric surgery in obese patients with type 1 diabetes: effects on weight loss and metabolic control. Obes Surg. 2016 doi: 10.1007/s11695-016-2106-3. [DOI] [PubMed] [Google Scholar]
  • 13.Rottenstreich A, Keidar A, Yuval JB, et al. Outcome of bariatric surgery in patients with type 1 diabetes mellitus: our experience and review of the literature. Surg Endosc. 2016;28 doi: 10.1007/s00464-016-4901-2. [DOI] [PubMed] [Google Scholar]
  • 14.Khanna V, Kashyap SR. Clinical management of type 2 diabetes mellitus after bariatric surgery. Curr Atheroscler Rep. 2015;17(10):59. doi: 10.1007/s11883-015-0537-2. [DOI] [PubMed] [Google Scholar]
  • 15.Deitel M. From bariatric to metabolic surgery in non-obese subjects: time for some caution. Arq Bras Endocrinol Metabol. 2009;53(2):246–51. doi: 10.1590/s0004-27302009000200016. [DOI] [PubMed] [Google Scholar]
  • 16.Jones AG, Hattersley AT. The clinical utility of C-peptide measurement in the care of patients with diabetes. Diabet Med. 2013;30(7):803–17. doi: 10.1111/dme.12159. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17.Bingley PJ. Clinical applications of diabetes antibody testing. J Clin Endocrinol Metab. 2010;95(1):25–33. doi: 10.1210/jc.2009-1365. [DOI] [PubMed] [Google Scholar]
  • 18.Decochez K, Tits J, Coolens JL, et al. High frequency of persisting or increasing islet-specific autoantibody levels after diagnosis of type 1 diabetes presenting before 40 years of age. The Belgian Diabetes Registry. Diabetes Care. 2000;23(6):838–44. doi: 10.2337/diacare.23.6.838. [DOI] [PubMed] [Google Scholar]
  • 19.Blanco J, Jimenez A, Casamitjana R, et al. Relevance of beta-cell function for improved glycemic control after gastric bypass surgery. Surg Obes Relat Dis. 2014;10(1):9–13. doi: 10.1016/j.soard.2013.07.020. quiz 189-90. [DOI] [PubMed] [Google Scholar]
  • 20.Robert M, Belanger P, Hould FS, et al. Should metabolic surgery be offered in morbidly obese patients with type I diabetes? Surg Obes Relat Dis. 2015;11(4):798–805. doi: 10.1016/j.soard.2014.12.016. [DOI] [PubMed] [Google Scholar]
  • 21.Schauer PR, Kashyap SR, Wolski K, et al. Bariatric surgery versus intensive medical therapy in obese patients with diabetes. N Engl J Med. 2012;366(17):1567–76. doi: 10.1056/NEJMoa1200225. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 22.Dixon JB, O'Brien PE, Playfair J, et al. Adjustable gastric banding and conventional therapy for type 2 diabetes: a randomized controlled trial. JAMA. 2008;299(3):316–23. doi: 10.1001/jama.299.3.316. [DOI] [PubMed] [Google Scholar]
  • 23.Lee WJ, Chong K, Lin YH, et al. Laparoscopic sleeve gastrectomy versus single anastomosis (mini-) gastric bypass for the treatment of type 2 diabetes mellitus: 5-year results of a randomized trial and study of incretin effect. Obes Surg. 2014;24(9):1552–62. doi: 10.1007/s11695-014-1344-5. [DOI] [PubMed] [Google Scholar]
  • 24.Mingrone G, Panunzi S, De Gaetano A, et al. Bariatric surgery versus conventional medical therapy for type 2 diabetes. N Engl J Med. 2012;366(17):1577–85. doi: 10.1056/NEJMoa1200111. [DOI] [PubMed] [Google Scholar]
  • 25.Ikramuddin S, Korner J, Lee WJ, et al. Durability of addition of roux-en-Y gastric bypass to lifestyle intervention and medical management in achieving primary treatment goals for uncontrolled type-2 diabetes in mild to moderate obesity: a randomized control trial. Diabetes Care. 2016;39(9):1510–8. doi: 10.2337/dc15-2481. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26.Schweitzer MA. Laparoscopic bariatric surgery. In: Cameron JL, editor. Atlas of gastrointestinal surgery. USA: PMPH-USA, Limited; 2005. pp. 95–132. [Google Scholar]
  • 27.Bonifacio E, Yu L, Williams AK, et al. Harmonization of glutamic acid decarboxylase and islet antigen-2 autoantibody assays for national institute of diabetes and digestive and kidney diseases consortia. J Clin Endocrinol Metab. 2010;95(7):3360–7. doi: 10.1210/jc.2010-0293. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 28.Yu L, Boulware DC, Beam CA, et al. Zinc transporter-8 autoantibodies improve prediction of type 1 diabetes in relatives positive for the standard biochemical autoantibodies. Diabetes Care. 2012;35(6):1213–8. doi: 10.2337/dc11-2081. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 29.Levy JC, Matthews DR, Hermans MP. Correct homeostasis model assessment (HOMA) evaluation uses the computer program. Diabetes Care. 1998;21(12):2191–2. doi: 10.2337/diacare.21.12.2191. [DOI] [PubMed] [Google Scholar]
  • 30.Wallace TM, Levy JC, Matthews DR. Use and abuse of HOMA modeling. Diabetes Care. 2004;27(6):1487–95. doi: 10.2337/diacare.27.6.1487. [DOI] [PubMed] [Google Scholar]
  • 31.Turner R, Stratton I, Horton V, et al. UKPDS 25: autoantibodies to islet-cell cytoplasm and glutamic acid decarboxylase for prediction of insulin requirement in type 2 diabetes. Lancet. 1997;350(9087):1288–93. doi: 10.1016/s0140-6736(97)03062-6. [DOI] [PubMed] [Google Scholar]
  • 32.Zhou Z, Xiang Y, Ji L, et al. Frequency, immunogenetics, and clinical characteristics of latent autoimmune diabetes in China (LADA China study): a nationwide, multicenter, clinic-based cross-sectional study. Diabetes. 2013;62(2):543–50. doi: 10.2337/db12-0207. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 33.Mallipedhi A, Min T, Prior SL, et al. Association between the preoperative fasting and postprandial C-peptide AUC with resolution of type 2 diabetes 6 months following bariatric surgery. Metabolism. 2015;64(11):1556–63. doi: 10.1016/j.metabol.2015.08.009. [DOI] [PubMed] [Google Scholar]

RESOURCES