Skip to main content
bioRxiv
  • Home
  • About
  • Submit
  • ALERTS / RSS
Advanced Search
New Results

Long-Term Effects of a Novel Continuous Remote Care Intervention Including Nutritional Ketosis for the Management of Type 2 Diabetes: A 2-year Non-randomized Clinical Trial

Shaminie J. Athinarayanan, Rebecca N. Adams, Sarah J. Hallberg, Amy L. McKenzie, Nasir H. Bhanpuri, Wayne W. Campbell, Jeff S. Volek, Stephen D. Phinney, James P. McCarter
doi: https://doi.org/10.1101/476275
Shaminie J. Athinarayanan
1Virta Health, 501 Folsom Street, San Francisco, CA 94105, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Rebecca N. Adams
1Virta Health, 501 Folsom Street, San Francisco, CA 94105, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Sarah J. Hallberg
1Virta Health, 501 Folsom Street, San Francisco, CA 94105, USA
2Indiana University Health Arnett, Lafayette, IN, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Amy L. McKenzie
1Virta Health, 501 Folsom Street, San Francisco, CA 94105, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Nasir H. Bhanpuri
1Virta Health, 501 Folsom Street, San Francisco, CA 94105, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Wayne W. Campbell
3Department of Nutrition Science, Purdue University, West Lafayette, IN, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Jeff S. Volek
1Virta Health, 501 Folsom Street, San Francisco, CA 94105, USA
4Department of Human Sciences, The Ohio State University, Columbus, OH, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Stephen D. Phinney
1Virta Health, 501 Folsom Street, San Francisco, CA 94105, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
James P. McCarter
1Virta Health, 501 Folsom Street, San Francisco, CA 94105, USA
5Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • Abstract
  • Full Text
  • Info/History
  • Metrics
  • Preview PDF
Loading

ABSTRACT

OBJECTIVE Studies on long-term sustainability of low-carbohydrate approaches to treat diabetes are limited. We aim to assess the effects of a continuous care intervention (CCI) on retention, glycemic control, weight, body composition, cardiovascular, liver, kidney, thyroid, inflammatory markers, diabetes medication usage and disease outcomes at 2 years in adults with type 2 diabetes (T2D).

RESEARCH DESIGN AND METHODS An open label, non-randomized, controlled study with 262 and 87 participants with T2D were enrolled in the CCI and usual care (UC) groups, respectively.

RESULTS Significant changes from baseline to 2 years in the CCI group included: HbA1c (−12% from 7.7±0.1%); fasting glucose (−18% from 163.67±3.90 mg/dL); fasting insulin (−42% from 27.73±1.26 pmol L-1); weight (−10% from 114.56±0.60 kg); systolic blood pressure (−4% from 131.7±0.9 mmHg); diastolic blood pressure (−4% from 81.8±0.5 mmHg); triglycerides (−22% from 197.2±9.1 mg/dL); HDL-C (+19% from 41.8±0.9 mg/dL), and liver alanine transaminase (−21% from 29.16±0.97 U/L). Spine bone mineral density in the CCI group was unchanged. Glycemic control medication use (excluding metformin) among CCI participants declined (from 56.9% to 26.8%, P=1.3×10-11) including prescribed insulin (−62%) and sulfonylureas (−100%). The UC group had no significant changes in these parameters (except uric acid and anion gap) or diabetes medication use. There was also significant resolution of diabetes (reversal, 53.5%; remission, 17.6%) in the CCI group but not in UC. All the reported improvements had p-values <0.00012.

CONCLUSIONS The CCI sustained long-term beneficial effects on multiple clinical markers of diabetes and cardiometabolic health at 2 years while utilizing less medication. The intervention was also effective in the resolution of diabetes and visceral obesity, with no adverse effect on bone health.

TRIAL REGISTRATION Clinicaltrials.gov NCT02519309

Author contributions

S.J.A, R.N.A, and J.P.M drafted the manuscript. S.J.A, R.N.A, A.L.M, N.H.B, and S.J.H participated in data acquisition and compiling. R.N.A and S.J.A analyzed the data. J.P.M, A.L.M, N.H.B, W.W.C, R.N.A, S.J.A, S.J.H, S.D.P and J.S.V edited the manuscript. All authors approved the final version of the manuscript.

Abbreviations
CCI
continuous care intervention;
UC
usual care;
T2D
type 2 diabetes;
HbA1c
hemoglobin A1c;
CVD
cardiovascular disease;
VLCD
very low calorie diet;
BMI
body mass index;
BHB
beta-hydroxybutryrate;
BMD
bone mineral density;
CAF
central abdominal fat;
A/G
android:gynoid ratio;
LELM
lower extremities lean mass;
HDL
high density lipoprotein;
LDL
low density lipoprotein;
ALT
alanine aminotransferase;
AST
aspartate aminotransferase;
ALP
alkaline phosphatase;
NAFLD
nonalcoholic fatty liver disease;
NLF
NAFLD liver fat score;
NFS
NAFLD fibrosis score;
TSH
thyroid stimulating hormone;
BUN
blood urea nitrogen;
eGFR
estimated glomerular filtration rate;
hsCRP
high sensitive C-reactive protein;
WBC
white blood cells;
HOMA-IR
Homeostatic Model Assessment of Insulin Resistance;
SGLT-2
sodium-glucose cotransporter-2 inhibitors;
DPP-4
dipeptidyl peptidase-4 inhibitors;
GLP-1
glucagon-like-peptide 1 receptor agonists;
FFM
fat-free mass;
VAT
visceral adipose tissue;
GLM
generalized linear model;
LMM
linear mixed-effect model;
ADA
American Diabetes Association;
CLIA
Clinical Laboratory Improvement Amendments;
IRB
Institutional Review Board;
DXA
dual-energy X-ray absorptiometry

Introduction

Type 2 diabetes (T2D), obesity, and metabolic disease impact over one billion people and present a challenge to public health and economic growth(1,S34). In the United States, over 30 million people have diabetes and it is a leading cause of morbidity and mortality, especially through increased cardiovascular disease (CVD)(2). The remission rate under usual care is 0.5 – 2%(3) while intensive lifestyle intervention resulted in remission rates (both partial and complete) of 11.5% and 9.2% at 1 and 2 years(4). When lifestyle intervention is insufficient, medications are indicated to manage the disease and slow progression.

When T2D care directed at disease reversal is successful, this includes achievement of restored metabolic health, glycemic control with reduced dependence on medication, and in some cases disease remission. Three non-pharmaceutical approaches have demonstrated high rates of at least temporary T2D diabetes reversal or remission: bariatric surgery, very low calorie diets (VLCD), and nutritional ketosis achieved through carbohydrate restriction(5,6,7). In controlled clinical trials, each approach has demonstrated improved glycemic control and CVD risk factors, reduced pharmaceutical dependence, and weight loss. The three approaches show a similar time-course with glycemic control preceding weight loss by weeks or months, suggesting potential overlap of mechanisms(8,S35,S36).

With bariatric surgery, up to 60% of patients demonstrate T2D remission at 1 year(9). Outcomes at two years and beyond indicate ~50% of patients can achieve ongoing diabetes remission(10,S37). The second Diabetes Surgery Summit recommended using bariatric surgery to treat T2D with support from worldwide medical and scientific societies(10), but both complications and cost limit its widespread use(11,S38). VLCDs providing <900 kcal/day allow rapid discontinuation of most medications, improved glycemic control, and weight loss. This approach is necessarily temporary, however, with weight regain and impaired glucose control typically occurring within 3-6 months of reintroduction of substantial proportions of dietary carbohydrate (6,12,S39,S40).

A third approach to diabetes reversal is sustained dietary carbohydrate restriction. Low-carbohydrate diets have consistently elicited improvements in T2D, metabolic disease, and obesity up to one year(13,S41); however, longer-term studies and studies including patients prescribed insulin are limited. A low carbohydrate Mediterranean diet caused remission in 14.7% of newly diagnosed diabetes patients at 1 year versus 4.1% with a low-fat diet (14), and a small randomized trial utilizing a ketogenic diet demonstrated improved weight and diabetes control at one year (15). Systematic reviews also corroborate the effectiveness of a low-carbohydrate diet for T2D(16,S42) and it has recently become a consensus recommended dietary option(17). Nonetheless, sustained adherence is considered challenging(17), and an LDL-C increase is sometimes observed(18,S43,S44) with carbohydrate restriction. Given that total LDL-P, small LDL-P, and ApoB tend to improve or remain unchanged, the impact of an isolated increase in LDL-C on CVD risk in the context of this dietary pattern is unknown.

We have previously reported 1 year outcomes of an open-label, non-randomized, controlled, longitudinal study with 262 continuous care intervention (CCI) and 87 usual care (UC) participants with T2D(7). The CCI included telemedicine, health coaching, and guidance in nutritional ketosis using an individualized whole foods diet. Eighty-three percent of CCI participants remained enrolled 1 year and 60% of completers achieved an HbA1c <6.5% while prescribed metformin or no diabetes medication. Weight was reduced and most CVD risk factors improved(19). Here we report the results of this study at 2 years. The primary aims were to investigate the effect of the CCI on retention, glycemic control, and weight. Secondary aims included: (1) investigating the effect of the CCI on bone mineral density, visceral fat composition, cardiovascular risk factors, liver, kidney, thyroid and inflammatory markers; diabetes medication use, and disease outcomes (e.g. diabetes remission, metabolic syndrome); and (2) comparing 2-year outcomes between the CCI and UC groups.

Materials and methods

Study design and participants

The comprehensive study design has been published previously (7,25), and the results presented here are the follow-up 2-year results (Clinical trials.gov identifier: NCT02519309). This is an open-label, non-randomized, outpatient study and results presented here include data collected between August, 2015 and May, 2018. Participants aged 21 to 65 years with a confirmed diagnosis of T2D and a body mass index (BMI) > 25 kg/m2. Participants in the CCI accessed a remote care team consisting of a health coach and medical provider and reported routine biomarkers (weight, blood glucose and beta-hydroxybutyrate [BHB]) through a web-based application (app). Participants self-selected between two different CCI educational modes: on-site (n=136, CCI-onsite) or web-based (n=126, CCI-virtual). We also recruited another cohort of participants with T2D (n=87) who were categorized as usual care (UC). Exclusion criteria have been published previously (7,25). A brief description of the study participants and interventions (CCI and UC) are listed in the supplementary data (Methods section). All study participants provided written informed consent and the study was approved by the Franciscan Health Lafayette Institutional Review Board.

Outcomes

Primary Outcomes

The primary outcomes were retention, HbA1c, HOMA-IR-insulin and c-peptide derived (scores, equations in supplemental material A), fasting glucose, fasting insulin, c-peptide and weight.

Secondary Outcomes

Long-term body composition changes assessed in CCI participants included bone mineral density (BMD), abdominal fat content (CAF and A/G ratio), and lower extremities lean mss (LELM). Body composition was not assessed in UC participants. Cardiovascular-, liver-, kidney-, thyroid-related and inflammatory markers were analyzed (Table 1 and Supplementary Table 1). Changes in overall diabetes medication use, use by class, and insulin dose were tracked over the two years of the trial.

View this table:
  • View inline
  • View popup
Table 1.

Baseline characteristics

The prevalence of T2D (diabetes reversal, partial and complete remission), metabolic syndrome, suspected steatosis and absence of fibrosis were evaluated at 2 years in the CCI and UC groups using the criteria provided in Supplementary Table 2 (assignment references listed in the supplementary). Assignment of metabolic syndrome was based on the presence of three of the five defined criteria according to measured laboratory and anthropometric variables; pharmacological treatment for any of the conditions was not considered.

Adverse events encountered in the study were reported to the Principal Investigator and reviewed by the Institutional Review Board (IRB).

Laboratory and body composition measures

Clinical anthropometrics and laboratory blood analytes measurements were obtained at baseline, 1 year, and 2 years from the CCI and UC participants. Details of the methods were previously published(7,19). All blood analytes were measured at a Clinical Laboratory Improvement Amendments (CLIA) certified laboratory. The CCI participants were also assessed for total body composition changes at baseline, 1 and 2 years using dual X-ray absorptiometry (DXA) (Lunar GE Prodigy, Madison, WI) and analyzed using GE Encore software(v11.10, Madison, WI). The details of the DXA procedure and analyses are listed in the supplementary data (Methods section).

Statistical analyses

All analyses were conducted using SPSS statistical software (Version 25.0, Armonk, NY). A detailed description of the statistical method is included in the supplementary data (Methods section). Briefly, we conducted intent-to-treat analyses to assess study outcomes. For continuous study outcomes, linear mixed-effects (LMM) models were used to assess within-group changes from baseline to 2 years and between-group differences at 2 years. For dichotomous disease outcomes, generalized estimating equation models were used. Changes in diabetes medication use and insulin dosage from baseline to 2 years were assessed using McNemar’s tests with continuity correction when appropriate and paired t-tests. Available data only was used to assess changes in medication use, which was routinely adjusted as part of the intervention protocol. Data from the two CCI educational groups were combined because no group differences were found, as in our prior time points(7,S45). Completers-only analyses were also conducted for all outcomes and results appear in the supplementary material. For all study analyses, nominal significance levels (P) are presented in the tables. A significance level of P<0.0012 ensures overall simultaneous significance of P<0.05 over the 43 variables using Bonferroni correction.

Results

Participant characteristics

Table 1 presents baseline characteristics of the 262 CCI and 87 UC participants. Participants did not differ between groups in demographic characteristics, except the proportion of African Americans was higher in the CCI group. Baseline characteristics were well-matched between the groups, except for mean weight and BMI, which were higher in the CCI group. There were no significant differences between completers and dropouts on baseline characteristics for either group.

Retention and long-term dietary adherence

One hundred ninety four participants (of 262; 74%) remained enrolled in the CCI at 2 years (Figure 1), as did 78% of the UC group participants (68 of 87). CCI participant-reported reasons for dropout included: intervening life events (e.g. family emergencies), difficulty attending or completing laboratory and clinic visits associated with the trial, and insufficient motivation for participation in the intervention. At both 1 and 2 years, laboratory measured blood BHB was 0.3 ± 0.0 mmol L-1, about 1.5 fold higher than the baseline value (0.2 ± 0.0 mmol L-1). The mean laboratory BHB level was stable from 1 to 2 years, and 61.5% (n=161) of participants reported a blood BHB measurement ≥0.5mmol L-1 in the app at least once between 1 and 2 years.

Figure 1.
  • Download figure
  • Open in new tab
Figure 1.

Flow chart of participants in each stage of the study from recruitment to 2 years post-enrollment and analysis.

All adjusted within and between group changes in study outcomes for the CCI and UC groups appear in Table 2.

View this table:
  • View inline
  • View popup
Table 2.

Adjusted mean changes over time

Glycemic outcomes

From baseline to 2 years (Table 2), significant reductions in HbA1c (0.9% unit decrease, −12% relative to baseline, P=1.8×10-17; Figure 2A), C-peptide (−27%, P=2.2×10-16), fasting glucose (−18%, P=6.8×10-9), fasting insulin (−42%, P=2.2×10-18, Figure 2B), insulin-derived HOMA-IR excluding exogenous insulin users (−42%, P=2.7×10-13), and C-peptide-derived HOMA-IR (−30%, P=1.1×10-15) were observed in the CCI group, whereas no changes occurred in the UC group (Supplementary Figures 1A and 1B) (Table 2). There were also significant between-group (CCI vs. UC) differences observed at 2 years in HbA1c, fasting glucose, fasting insulin, insulin-derived HOMA-IR excluding exogenous users, and C-peptide-derived HOMA-IR, with the CCI group having lower glycemic marker means (Table 2).

Figure 2.
  • Download figure
  • Open in new tab
Figure 2.
  • Download figure
  • Open in new tab
Figure 2.

Adjusted mean changes from baseline to 2-years in the CCI group for (A) HbA1c, (B) Fasting insulin, (C) Weight, (D) Central Abdominal Fat [CAF], (E) Systolic Blood Pressure, (F) Diastolic Blood Pressure (G) Alanine aminotransferase (ALT), and (H) High sensitive C-reactive protein (hsCRP).

Metabolic and body composition outcomes

At 2 years, mean weight change from baseline was −10% (P=8.8×10-28; Figure 2C) in the CCI group, whereas no change was observed in the UC group (Supplementary Figure 1C). Among CCI patients, 74% had ≥ 5% weight loss compared to only 14% of UC patients (Supplementary Figure 2; completers analysis). Consistent with the weight loss observed, the CCI group had reductions in abdominal fat content, with decreases in CAF (−15%, P=1.6×10-21, Figure 2D) and the A/G ratio (−6%, P=4.7×10-8) from baseline to 2 years (Table 2). The CCI group’s total spine BMD remained unchanged from baseline to 2 years after correction for multiple comparisons (Table 2). The changes in the average LELM in the CCI are included in the Table 2, and further elaborated in the supplementary data (Discussion section).

Cardiovascular risk factor outcomes

Decreases in systolic (−4%, P= 2.4×10-6, Figure 2E) and diastolic (−4%, P= 3.3×10-5, Figure 2F) blood pressures and triglycerides (−22%, P=6.2×10-9) were observed in the CCI but not UC group at 2 years (Table 2, Supplementary Figures 3A and 3B). The CCI group’s HDL-cholesterol (+19%, P= 2.7×10- 16) and LDL-cholesterol (+11%, P=1.1×10-4) both increased from baseline to two years, whereas no changes were observed in the UC group (Table 2). No changes in total cholesterol were observed in either the CCI or UC group. At 2 years, the CCI group had higher HDL-cholesterol, higher LDL-cholesterol, and lower triglycerides than UC. No between-group differences were observed at 2 years for systolic or diastolic blood pressure or total cholesterol (Table 2).

Figure 3.
  • Download figure
  • Open in new tab
Figure 3.

Medication and insulin dose changes from baseline to 2 years for CCI and UC group completers. (A) Percent of completers taking diabetes medications, excluding metformin. (B) Mean + SE prescribed insulin dose among baseline users. (C) Frequency of medication dosage and use change among prescribed users by diabetes medication class.

Liver-related outcomes

From baseline to 2 years, the CCI group’s ALT (−21%, P=4.0×10-10; Table 2, Figure 2G), AST (12%, P=5.1×10-5), ALP (−13%, P=1.8×10-14), NLF (−78%, P=2.9×10-25) and NFS (−60%, P=2.3×10-9) were reduced, whereas no changes were observed in UC (e.g. ALT; Supplementary Figure 3C; Table 2). No bonferroni-corrected group differences were observed for bilirubin,ALT, nor AST at 2 years (Table 2).

Kidney, thyroid, and inflammation outcomes

The eGFR increased in the CCI (+3%, P=1.6×10-4, Table 2) but not UC group at 2 years. The UC but not CCI group had increased anion gap and decreased uric acid (Table 2). No bonferroni-corrected within-group changes in BUN, serum creatinine, TSH, or Free T4 were observed in either the CCI or UC group from baseline to 2 years. No between-group differences were observed for any thyroid- or kidney-related markers at 2 years (Table 2).

From baseline to 2 years, decreases in the CCI group’s hsCRP (−37%, P=6.9×10-13, Table 2, Figure 2H) and white blood cell count (−7%, P=4.3×10-5) were observed. No changes were observed in the UC group (Supplementary Figure 3D). At 2 years, both markers of inflammation were lower in the CCI group compared to the UC group (Table 2).

Diabetes Medication

All within-group changes in diabetes medication use among study completers appear in eTable 3 (ns are listed in the table). The proportion of CCI completers taking any diabetes medication (excluding metformin) decreased from 55.7% at baseline to 26.8% at 2 years (P=1.3×10-11, Figure 3A). Reductions in the use of diabetes medication classes included insulin (29.8% at baseline to 11.3% at 2 years, P=9.1×10-9) and sulfonylureas (23.7% at baseline and 0% at 2 years, P=4.2×10-12). At 2 years, no changes in the proportions of CCI completers taking SGLT-2 inhibitors (10.3% to 3.1%, P=0.01), DPP-4 (9.9% to 6.7%, P=0.42), GLP-1 agonists (13.4% to 10.8%, P=0.42), thiazolidinediones (1.5% to 2.6%, P=0.73), or metformin (71.4% to 63.9%, P=0.05) were observed after correction for multiple comparisons. No changes in use of any diabetes medication (excluding metformin) or individual diabetes medication classes were observed in the UC completers from baseline to 2 years. The mean dose for insulin-using participants at baseline decreased among CCI participants by 81% (P= 2.6×10-12) at 2 years, but not in UC participants (+13%, P=0.45) (see Figure 3B). For participants who remained insulin-users at 2 years, the mean dose also decreased in the CCI group by 61% (P=9.2×10-5) but not UC group (+19%, P=0.29). Among participants prescribed each diabetes medication class, the proportion with each dosage change (eliminated, reduced, unchanged, increased, or newly added) at 2 years in each group appears in Figure 3C.

Disease Outcomes

All within-group changes and between-group differences in disease outcomes among the CCI and UC group participants appear in supplementary Table 4 (intent-to-treat analyses were conducted; all below n=262). The proportion of participants meeting the defined criteria for diabetes reversal at 2 years increased 41.4% (from 12.1% at baseline to 53.5% at 2 years, P<0.0×10-36) in the CCI group, whereas no Bonferroni-corrected change was observed in the UC group (7.1% absolute decrease, P=0.04). In addition, diabetes remission (partial or complete) was observed in 46 (17.6%) participants in the CCI group and two (2.4%) of the UC participants at 2 years. Complete remission was observed in 17 (6.7%) CCI participants and none (0%) of the UC participants at 2 years.

At 2 years, 27.2% of CCI participants and 6.5% of UC patients showed resolution of metabolic syndrome. The proportion of participants with metabolic syndrome decreased from baseline to 2 years in the CCI (from 89.1% to 61.9%, P= 4.9×10-15) but not UC group. The two years improvements of suspected steatosis and fibrosis status are included in the supplementary Tables 4 and 5.

Safety and adverse events

In the CCI group, there were no reported serious adverse events between one and two years attributed to the intervention or that resulted in discontinuation, including no reported episodes of ketoacidosis or severe hypoglycemia requiring assistance. Adverse events occurring in the first year of intervention (n=6) were previously reported[10]. Details of the adverse events are included in the supplementary data (Results section).

Discussion

Following 2 years of a remote continuous care intervention supporting medical and lifestyle changes, the CCI participants demonstrated improved HbA1c, fasting glucose and insulin, and HOMA-IR. Pharmaceutical interventions of 1.5 to 3 years duration report HbA1c reductions of 0.2 to 1.0% with DPP-4 inhibitors, SGLT-2 inhibitors and GLP-1 agonists(20,21,S46–S48). The HbA1c reduction of 0.9% with this CCI is comparable to that observed in pharmaceutical trials, but is achieved while discontinuing 67.0% of diabetes-specific prescriptions including most insulin and all sulfonylureas that engender risks for weight gain and hypoglycemia(22,23). Comparable improvements in glycemic control and reduced medication were not observed in UC participants recruited from the same healthcare system, suggesting that the CCI improves diabetes management relative to usual care. Other interventions using carbohydrate restriction reported variable long-term glycemic improvement outcomes(24–26,S49–S51). The 0.9% absolute (12% relative) HbA1c reduction observed at 2 years is consistent with low carbohydrate studies reporting HbA1c reductions of 8-15% at 2 to 3.5 years (25,26,S49,S51) with medication reduction. Two others studies reported no changes in HbA1c from baseline to 2 years, even though the low carbohydrate arm reduced HbA1c in the first 6 months(24,S50). This study observed a modest increase in HbA1c and weight between 1 and 2 years in CCI participants suggesting some reduction in long-term effectiveness. Interestingly, insulin-levels show no regression toward baseline from 1 to 2 years indicating long-term improvement in hyperinsulinemia, an important component of diabetes pathology(8,27).

Criticisms of low-carbohydrate diets relate to poor adherence and long-term sustainability(16,28). In this CCI, self-monitoring combined with continuous remote-monitoring and feedback from the care team, including behavioral support and nutrition advice via the app, may have improved accountability and engagement(S52). In addition to glucose and weight tracking, dietary adherence was monitored by blood ketones. The 2 year BHB increase above baseline demonstrates sustained dietary modification. While laboratory BHB levels were increased from baseline, nutritional ketosis (≥0.5 mM) was observed in only a minority (14.1%) of participants at 2 years. On average, patient-measured BHB was ≥0.5 mM for 32.8% of measurements over the 2 years (eFigure 4). This reveals an opportunity to increase adherence to nutritional ketosis for patients not achieving their desired health outcomes while prompting future research investigating the association between dietary adherence and health improvements.

A majority of the CCI participants (53.5%) met criteria for diabetes reversal at 2 years while 17.6% achieved diabetes remission (i.e. glycemic control without medication use) based on intent-to-treat with multiple imputation. The percentage of all CCI enrollees (N=262) with verified reversal and remission requiring both completion of two years of the trial and an obtained laboratory value for HbA1c were 37.8% and 14.9%, respectively. CCI diabetes reversal exceeds remission as metformin prescriptions were usually continued given its role in preventing disease progression(7,29), preserving β-cell function(29) and in treatment of pre-diabetes per guidelines (28). Partial and complete remission rates of 2.4% and 0. 2% per year, respectively, have been reported in 122,781 T2D patients receiving standard diabetes care(3). The two-year remission rate (both partial and complete) in the CCI (17.6%) is higher than that achieved through intensive lifestyle intervention (ILI) in the Look AHEAD trial (9.2%)(4). Greater diabetes remission in the CCI versus Look AHEAD ILI could result from differences in the dietary intervention(14), patients’ ability to self-select their lifestyle or effectiveness of continuous remote care. Length of time with a T2D diagnosis is a factor in remission, with longer time since diagnosis resulting in lower remission(3,4,6,S53). Despite a mean of 8.4 years since diagnosis among CCI participants, the remission rate was higher than the Look AHEAD trial where its participants had a median of 5 years(4) since diabetes diagnosis.

Participants in the CCI achieved 10% mean weight loss (−11.9kg) at 2 years. CCI weight loss was comparable to observed weight loss following surgical gastric banding (−10.7kg) at 2 years(29). Previous studies consistently report that weight loss increases the likelihood of T2D remission(3,4,6). CCI participants also improved blood pressure, triglycerides, and HDL-cholesterol. Total cholesterol was unchanged and calculated LDL-cholesterol was increased at 2 years, but was not different from the LDL-cholesterol level observed at one year (+0.51, P=0.85). Despite the rise in LDL-cholesterol, the CCI cohort improved in 22 out of 26 CVD markers at one year(19). This includes a decrease in small LDL-particles and large VLDL-P and an increase in LDL-particle size with no changes in ApoB(19), a marker considered a better predictor of CVD risk than LDL-cholesterol(19,30,S54). Non-elevated LDL cholesterol values together with higher triglycerides and lower HDL-cholesterol are common in patients with abdominal obesity, T2D, and metabolic syndrome(31,S55,S56); these individuals often still have elevated atherogenic lipoproteins such as non-HDL(32,S57), small LDL particles(31,S58), and VLDL(31,S58). In the CCI group, non-HDL cholesterol did not change significantly from baseline to 2 years and several cardiovascular risk factors across various physiological systems improved, suggesting that the rise in LDL-cholesterol may not be associated with increased atherogenic risk(33).

The CCI group had a reduction in visceral fat content, CAF and A/G ratio. This is consistent with other low-carbohydrate interventions reporting visceral fat reduction as a component of weight loss(18,24,34,35,S59). Anatomical distribution of fat around the abdominal area (“android” obesity) is associated with T2D(36,S60) and other comorbidities such as metabolic syndrome(37) and NAFLD(38,S61). The alleviation of visceral fat in the CCI group was concurrent with resolution of metabolic syndrome at 2 years, while sustaining one-year improvements of liver enzymes(7), steatosis and fibrosis (39 in press, S62-S67). While studies in animal models(40,S68,S69) and children treated with ketogenic diets(41,S70) have suggested retardation in skeletal development and reduction in BMD, in this study of T2D adults the CCI group had no change in total spine BMD over two years. Our results are consistent with other adult ketogenic dietary studies that reported no bone mass loss in short-term(34,S71) or long-term follow-up of 2(35,S72) and 5(S73) years. The differing findings of ketogenic diet on bone mass between adults and children could be due to differential effects on developed and mineralized versus developing bones(42).

Strengths and limitations

This study’s strengths include its size and prospective, longitudinal data collection from two participant groups (CCI and UC) which allowed statistical analysis by LMMs to investigate intervention time and treatment effects. While not randomized, the participants’ self-selection of intervention may contribute to the observed high retention and predicts real-life clinical management of chronic disease. The study also included patients prescribed insulin and with long-standing disease, groups often excluded from prior studies. The multi-component aspect of the intervention involving regular biomarker monitoring and access to a a remote care team may have improved the patients’ long-term dietary adherence and engagement. The dietary advice including encouraging participants to restrict carbohydrates, moderate protein intake, and eat to satiety may also help in maintaining long-term effectiveness. Weaknesses of this study include the lack of randomization and limited racial diversity. Interpretation of DXA body composition was limited to subregion analyses due to to the scanner not accomodating the patients’ complete body.

Conclusions

At 2 years, the CCI, including remote medical management with instruction in nutritional ketosis, led to improvements in blood glucose, insulin, HbA1c, weight, blood pressure, triglycerides, liver function, and inflammation and reduced dependence upon medication. These long-term benefits were achieved concurrent with reduced prevalence of metabolic syndrome and visceral adiposity. The CCI had no adverse effect on bone mineral density. The CCI group also had higher prevalence of diabetes reversal and remission compared to the UC group following a standard diabetes care program. These results provide strong evidence that sustained improvement in diabetes status can be achieved through the continuous remote monitoring and accountability mechanisms provided by this multi-component CCI including recommendations for low carbohydrate nutrition.

Footnotes

  • DATA SHARING: The complete data and statistical codes are available upon reasonable request.

  • Conflicts of Interests: SJA, RNA, SJH, ALM, NHB, SDP and JPM are employed by Virta Health Corp and were offered stock options. SDP and JSV are founders of Virta Health Corp. WWC has no conflict of interest to declare.

  • Financial support: Virta Health Corp. is the study sponsor.

Author contributions

S.J.A, R.N.A, and J.P.M drafted the manuscript. S.J.A, R.N.A, A.L.M, N.H.B, and S.J.H participated in data acquisition and compiling. R.N.A and S.J.A analyzed the data. J.P.M, A.L.M, N.H.B, W.W.C, R.N.A, S.J.A, S.J.H, S.D.P and J.S.V edited the manuscript. All authors approved the final version of the manuscript.

References

  1. 1.↵
    World Health Organization. (2016). Global report on diabetes. World Health Organization. http://www.who.int/iris/handle/10665/204871.
  2. 2.↵
    Centers for Disease Control and Prevention. National Diabetes Statistics Report, 2017. Atlanta, GA: Centers for Disease Control and Prevention, US. Dept of Health and Human Services; 2017.
  3. 3.↵
    Karter AJ, Nundy S, Parker MM, Moffet HH, Huang ES. Incidence of remission in adults with type 2 diabetes: The diabetes & aging study. Diabetes Care 2014; 37: 3188–3195.
    OpenUrlAbstract/FREE Full Text
  4. 4.↵
    Gregg EW, Chen H, Wagenknecht LE, et al. Association of an intensive lifestyle intervention with remission of type 2 diabetes. JAMA 2012; 308: 2489–2496.
    OpenUrlCrossRefPubMedWeb of Science
  5. 5.↵
    Sjostrom L, Peltonen M, Jacobson P, et al. Association of bariatric surgery with long-term remission of type 2 diabetes and with microvascular and macrovascular complications. JAMA 2014; 311: 2297–2304.
    OpenUrlCrossRefPubMedWeb of Science
  6. 6.↵
    Lean MEJ, Leslie WS, Barnes AC, et al. Primary care-led weight management for remission of type 2 diabetes (DiRECT): an open-label, cluster-randomised trial. The Lancet 2018; 391: 541–551.
    OpenUrl
  7. 7.↵
    Hallberg SJ, McKenzie AL, Williams PT, et al. Effectiveness and safety of a novel care model for the management of type 2 diabetes at 1 year: an open-label, non-randomized, controlled study. Diabetes Ther 2018; 9: 583–612.
    OpenUrlCrossRefPubMed
  8. 8.↵
    Taylor R. Type 2 Diabetes: Etiology and reversibility. Diabetes Care 2013: 36: 1047–1055.
    OpenUrlFREE Full Text
  9. 9.↵
    Dicker D, Yahalom R, Comaneshter DS, Vinker S. Long-term outcomes of three types of bariatric surgery on obesity and type 2 diabetes control and remission. Obesity Surg 2016; 26: 1814–1820.
    OpenUrl
  10. 10.↵
    Rubino F, Nathan DM, Eckel RH, et al. Metabolic surgery in the treatment algorithm for type 2 diabetes: A joint statement by International Diabetes Organizations. Diabetes Care 2016; 39: 861–867.
    OpenUrlAbstract/FREE Full Text
  11. 11.↵
    Berger ER, Huffman KM, Fraker T, et al. Prevalence and risk factors for bariatric surgery readmissions: Findings from 130,007 admissions in the metabolic and bariatric surgery accreditation and quality improvement program. Ann Surg 2018; 267: 122–131.
    OpenUrl
  12. 12.↵
    Snel M, Jonker JT, Hammer S, et al. Long-term beneficial effect of a 16-week very low calorie diet on pericardial fat in obese type 2 diabetes mellitus patients. Obesity 2012; 20: 1572–1576.
    OpenUrl
  13. 13.↵
    Yamada Y, Uchida J, Izumi H, et al. A non-calorie-restricted low-carbohydrate diet is effective as an alternative therapy for patients with type 2 diabetes. Intern Med 2014; 53: 13–19.
    OpenUrlPubMed
  14. 14.↵
    Esposito K, Maiorino MI, Petrizzo M, Bellastella G, Giugliano D. The effects of a Mediterranean diet on the need for diabetes drugs and remission of newly diagnosed type 2 diabetes: follow-up of a randomized trial. Diabetes Care 2014; 37: 1824–1830
    OpenUrlAbstract/FREE Full Text
  15. 15.↵
    Saslow LR, Daubenmier JJ, Moskowitz JT, et al. Twelve-month outcomes of a randomized trial of a moderate-carbohydrate versus very low-carbohydrate diet in overweight adults with type 2 diabetes mellitus or prediabetes. Nutrition and Diabetes 2017; 304: doi 10.1038/s41387-017-0006-9.
    OpenUrlCrossRef
  16. 16.↵
    Wheeler ML, Dunbar SA, Jaacks LM, et al. Macronutrients, food groups, and eating patterns in the management of diabetes: a systematic review of the literature, 2010. Diabetes Care 2012; 35: 434–455.
    OpenUrlFREE Full Text
  17. 17.↵
    Davies MJ, D’Alessio DA, Fradkin J, et al. Management of hyperglycemia in type 2 diabetes, 2018. A consensus report by the American Diabetes Association (ADA) and the European Association for the Study of Diabetes (EASD). Diabetes Care 2018;https://doi.org/10.2337/dci18-0033.
  18. 18.↵
    Volek JS, Phinney SD, Forsythe CE, et al. Carbohydrate restriction has a more favorable impact on the metabolic syndrome than a low fat diet. Lipids 2009; 44: 297–309.
    OpenUrlCrossRefPubMedWeb of Science
  19. 19.↵
    Bhanpuri NH, Hallberg SJ, Williams PT, et al. Cardiovascular disease risk factor responses to a type 2 diabetes care model including nutritional ketosis induced by sustained carbohydrate restriction at 1 year: an open label, non-randomized, controlled study. Cardiovasc Diabetol 2018; 17: 56 https://doi.org/10.1186/s12933-018-0698-8.
    OpenUrlCrossRefPubMed
  20. 20.↵
    Scirica BM, Bhatt DL, Braunwald E, et al. Saxagliptin and cardiovascular outcomes in patients with type 2 diabetes mellitus. N Engl J Med 2013; 369: 1317–1326.
    OpenUrlCrossRefPubMedWeb of Science
  21. 21.↵
    Marso SP, Bain SC, Consoli A, et al. Semaglutide and cardiovascular outcomes in patients with type 2 diabetes. N Engl J Med 2016; 375: 1834–1844.
    OpenUrlCrossRefPubMed
  22. 22.↵
    Action to Control Cardiovascular Risk in Diabetes Study Group, Gerstein HC, Miller ME, Byington RP, et al. Effects of intensive glucose lowering in type 2 diabetes. N Engl J Med 2008; 358: 2545–2559.
    OpenUrlCrossRefPubMedWeb of Science
  23. 23.↵
    Henry RR, Gumbiner B, Ditzler T, Wallace P, Lyon R, Glauber HS. Intensive conventional insulin therapy for type II diabetes. Metabolic effects during a 6-mo outpatient trial. Diabetes Care 1993; 16:21–31.
    OpenUrlAbstract/FREE Full Text
  24. 24.↵
    Guldbrand H, Dizdar B, Bunjaku B, et al. In type 2 diabetes, randomisation to advice to follow a low-carbohydrate diet transiently improves glycaemic control compared with advice to follow a low-fat diet producing a similar weight loss. Diabetologia 2012; 55: 2118–2127.
    OpenUrlCrossRefPubMedWeb of Science
  25. 25.↵
    Nielsen JV, Joensson EA. Low carbohydrate diet in type 2 diabetes: stable improvement of bodyweight and glycemic control during 44 months follow-up. Nutr Metab 2008; 5: 14 doi: 10.1186/1743-7075-5-14
    OpenUrlCrossRefPubMed
  26. 26.↵
    Tay J, Thompson CH, Luscombe-Marsh ND, et al. Effects of an energy-restricted low-carbohydrate, high unsaturated fat/low saturated fat diet versus a high-carbohydrate, low-fat diet in type 2 diabetes: A 2-year randomized clinical trial. Diabetes Obes Metab 2018; 20: 858–871.
    OpenUrlCrossRefPubMed
  27. 27.↵
    Pories WJ and Dohm GL. Diabetes: Have we got it all wrong? Hyperinsulinism as the culprit: surgery provides the evidence. Diabetes Care 2012; 35: 2438–2442.
    OpenUrlFREE Full Text
  28. 28.↵
    Standards of Medical Care in Diabetes-2018: Summary of Revisions. Diabetes Care 2018; 41: S1–S1.
    OpenUrlFREE Full Text
  29. 29.↵
    Xiang AH, Trigo E, Martinez M, et al. Impact of gastric banding versus metformin on □-cell function in adults with impaired glucose tolerance or mild type 2 diabetes. Diabetes Care 2018; https://doi.org/10.2337/dc18-1662.
  30. 30.↵
    Sniderman AD, Toth PP, Thanassoulis G, Furberg CD. An evidence-based analysis of the National Lipid Association recommendations concerning non-HDL-C and apoB. J Clin Lipidol 2016;10:248–258.
    OpenUrl
  31. 31.↵
    Welthy FK. How do elevated triglycerides and low HDL-cholesterol affect inflammation and atherothrombosis? Curr Cardiol Rep 2013; 15: 400.doi:10.1007/s11886-013-0400-4.
    OpenUrlCrossRefPubMed
  32. 32.↵
    Lu W, Resnick HE, Jablonski KA, et al. Non-HDL cholesterol as a predictor of cardiovascular disease in type 2 diabetes. Diabetes Care 2003; 26: 16–23.
    OpenUrlAbstract/FREE Full Text
  33. 33.↵
    Creighton BC, Hyde PN, Maresh CM, Kraemer WJ, Phinney SD, Volek JS. Paradox of hypercholesterolaemia in highly trained, keto-adapted athletes. BMJ Open Sport Exerc Med 2008;4: e000429.doi:10.1136/bmjsem-2018-00429.
    OpenUrlCrossRef
  34. 34.↵
    Gomez-Arbelaez D, Bellido D, Castro AI, et al. Body composition changes after very low-calorie-ketogenic diet in obesity evaluated by three standardized methods. J Clin Endocrinol Metab 2016; doi: 10.1210/jc.2016-2385
    OpenUrlCrossRef
  35. 35.↵
    Moreno B, Crujeiras AB, Bellido D, Sajoux I, Casanueva FF. Obesity treatment by very low-calorie-ketogenic diet at two years: reduction in visceral fat and on the burden of disease. Endocrine 2016; 54: 681–690.
    OpenUrl
  36. 36.↵
    Levelt E, Pavlides M, Banerjee R, et al. Ectopic and visceral fat deposition in lean and obese patients with type 2 diabetes. J Am Coll Cardiol 2016; 68: 53–63.
    OpenUrlFREE Full Text
  37. 37.↵
    Shah RV, Murthy VL, Abbasi SA, et al. Visceral adiposity and the risk of metabolic syndrome across of body mass index. JACC Cardiovasc Imaging 2014; 7: 1221–1235.
    OpenUrlAbstract/FREE Full Text
  38. 38.↵
    Mirza MS. Obesity, visceral fat, and NAFLD: Querying the role of adipokines in the progression of nonalcoholic fatty liver disease.
  39. 39.↵
    Vilar-Gomez E, Athinarayanan SJ, Adams RN, et al. Post-hoc analyses of surrogate markers of non-alcoholic fatty liver disease (NAFLD) and liver fibrosis in patients with type 2 diabetes in a digitally-supported continuous care intervention: an open label, non-randomized, controlled study (in press).
  40. 40.↵
    Bielohuby M, Matsuura M, Herbach N, et al. Short-term exposure to low-carbohydrate, high-fat diets induces low bone mineral density and reduces bone formation in rats. J Bone Miner Res. 2010;25:275–284.
    OpenUrlCrossRefPubMedWeb of Science
  41. 41.↵
    Simm PJ, Bicknell-Royle J, Lawrie J, et al. The effect of the ketogenic diet on the developing skeleton. Epilepsy Res 2017; 136: 62–66
    OpenUrl
  42. 42.↵
    Stagi S, Cavalli L, lurato C, Seminara S, Brandi ML, de Martino M. Bone metabolism in children and adolescents: main characteristics of the determinants of peak bone mass. Clin Cases Miner Bone Metab 2013; 10:172–179.
    OpenUrl

Supplementary References (S)

  1. 1.↵
    Hallberg SJ, McKenzie AL, Williams PT, et al. Effectiveness and safety of a novel care model for the management of type 2 diabetes at 1 year: an open-label, non-randomized, controlled study. Diabetes Ther 2018; 9: 583–612.
    OpenUrlCrossRefPubMed
  2. 2.↵
    Bhanpuri NH, Hallberg SJ, Williams PT, et al. Cardiovascular disease risk factor responses to a type 2 diabetes care model including nutritional ketosis induced by sustained carbohydrate restriction at 1 year: an open label, non-randomized, controlled study. Cardiovasc Diabetol 2018; 17: 56 https://doi.org/10.1186/s12933-018-0698-8.
    OpenUrlCrossRefPubMed
  3. 3.↵
    Standards of Medical Care in Diabetes – 2018: Summary of Revisions. Diabetes Care 2018; 41: S1–S1
    OpenUrlFREE Full Text
  4. 4.↵
    Brownbill RA, and Ilich JZ. Measuring body composition in overweight individuals by dual energy x-ray absorptiometry. BMC Med Imaging 2005; 5: 1 doi:10.1186/1471-2342/5/I.
    OpenUrlCrossRefPubMed
  5. 5.↵
    Rothney MP, Brychta RJ, Schaefer EV, et al. Body composition measured by dual-energy X-ray absorptiometry half-body scans in obese adults. Obesity 2009; 17: 1281–1286.
    OpenUrl
  6. 6.↵
    Chun KJ. Bone densitometry. Semin Nucl Med 2011; 41: 220–228.
    OpenUrlCrossRefPubMed
  7. 7.↵
    Kamel EG, McNeill G, Van Wijk CWV. Usefulness of anthropometry and DXA in predicting intra-abdominal fat in obese men and women. Obes Res 2000; 8: 36–42.
    OpenUrlPubMedWeb of Science
  8. 8.↵
    Reid KF, Naumova EN, Carabello RJ, et al. Lower extremity muscle mass predicts functional performance in mobility-limited elders. J Nutr Health Aging 2008; 12: 493–498.
    OpenUrlCrossRefPubMedWeb of Science
  9. 9.↵
    Moon JJ, Park SG, Ryu SM, et al. New skeletal muscle mass index in diagnosis of sacropenia. J Bone Metab 2018; 25: 15–21.
    OpenUrl
  10. 10.↵
    Kline RB. Principles and practice of structural equation modeling (3rd ed.) 2011 New York: The Guilford Press.
  11. 11.↵
    John JA, Draper NR. An alternative family of transformations. Appl Statist 1980; 29: 190–197.
    OpenUrlCrossRef
  12. 12.↵
    Buse JB, Caprio S, Cefalu WT, et al. How do we define cure of diabetes? ADA Consensus Statement. Diabetes Care 2009; 32: 2133–2135.
    OpenUrlFREE Full Text
  13. 13.↵
    International Diabetes Federation (IDF). The IDF consensus worldwide definition of the metabolic syndrome. IDF Communications 2006; 1–24.
  14. 14.↵
    Huang PL. A comprehensive definition for metabolic syndrome. Dis Model Mech 2009; 2: 231–237.
    OpenUrlAbstract/FREE Full Text
  15. 15.↵
    Kotronen A, Peltonen M, Hakkarainen A, et al. Prediction of non-alcoholic fatty liver disease and liver fat using metabolic and genetic factors. Gastroenterology 2009; 137: 865–872.
    OpenUrlCrossRefPubMedWeb of Science
  16. 16.↵
    Angulo P, Hui JM, Marchesini G, et al. The NAFLD fibrosis score: a noninvasive system that identifies liver fibrosis in patients with NAFLD. Hepatology 2007;45: 846–854.
    OpenUrlCrossRefPubMedWeb of Science
  17. 17.↵
    Graham JW, Olchowski AE, et al. How many imputations are really needed? Some practical clarifications of multiple imputation theory. Prevention Sci 2007; 8: 206–213.
    OpenUrl
  18. 18.↵
    McKenzie A, Hallberg S, Creighton BC, et al. A novel intervention including nutritional recommendations reduces hemoglobin A1c level, medication use, and weight in type 2 diabetes. JMIR Diabetes 2017; 2: e5.
    OpenUrlCrossRef
  19. 19.↵
    Lafortuna CL, Tresoldi D, Rizzo G. Influence of body adiposity on structural characteristics of skeletal muscle in men and women. Clin Physiol Funct Imaging 2014; 34: 47–55
    OpenUrl
  20. 20.↵
    Choi SJ, Files DC, Zhang T, et al. Intramyocellular lipid and impaired myofiber contraction in normal weight and obese older adults. J Gerontol A Biol Sci Med Sci 2016; 71: 557–564.
    OpenUrlCrossRefPubMed
  21. 21.↵
    Mingrone G, Marino S, DeGaetano A, et al. Different limit to the body’s ability of increasing fat-free mass. Metabolism 2001;50: 1004–1007.
    OpenUrlCrossRefPubMedWeb of Science
  22. 22.↵
    Forbes GB, Welle SL. Lean body mass in obesity. Int J Obes 1983; 7: 99–107.
    OpenUrlPubMedWeb of Science
  23. 23.↵
    Bopp MJ, Houston DK, Lenchik L, et al. Lean mass loss is associated with low protein intake during dietary-induced weight loss in postmenopausal women. J Am Diet Assoc 2008; 108: 1216–1220.
    OpenUrlCrossRefPubMedWeb of Science
  24. 24.↵
    Ciangura C, Bouillot JL, Lloret-Linares C, et al. Dynamics of change in total and regional body composition after gastric bypass in obese patients. Obesity 2010; 18: 760–765.
    OpenUrl
  25. 25.↵
    Varma S, Brown T, Clark J, et al. Comparative effects of medical vs. surgical weight loss on body composition in a randomized trial. Diabetes 2018; 67 (S1):https://doi.org/10.2337/db18-2460-PUB.
  26. 26.↵
    Zalesin KC, Franklin BA, Lillystone MA, et al. Differential loss of fat and lean mass in the morbidly obese after bariatric surgery. Met Syndrome and Related Dis 2010; 8: 15–20.
    OpenUrl
  27. 27.
    Redmon JB, Reck KP, Raatz SK, et al. Two year outcome of a combination of weight loss therapies for type 2 diabetes. Diabetes Care 2005; 28: 1311–1315.
    OpenUrlAbstract/FREE Full Text
  28. 28.↵
    Maghrabi AH, Wolski K, Abood B, et al. Two year outcomes on bone density and fracture incidence in patients with T2DM randomized to bariatric surgery vs. intensive medical therapy. Obesity 2015; 23: 2344–2348.
    OpenUrl
  29. 29.↵
    Heymsfield SB, Gonzalez MCC, Shen W, et al. Weight loss composition is one-fourth fat-free mass: A critical review and critique of this widely cited rule. Obes Rev 2014; 15: 310–321.
    OpenUrlCrossRefPubMed
  30. 30.↵
    Davis PG, Phinney SD. Differential effects of two very low calorie diets on aerobic and anaerobic performance. Int J Obesity 1990; 14: 779–787.
    OpenUrlPubMed
  31. 31.↵
    Kim JE, O’Connor LE, Sands LP, et al. Effects of dietary protein intake on body composition changes after weight loss in older adults: a systematic review and meta-analysis. Nutr Review 2016; 74: 210–224
    OpenUrl
  32. 32.↵
    Frigolet ME, Ramos Barragan VE, Tamez Gonzalez M. Low-carbohydrate diets: a matter of love or hate. Ann Nutr Metab 2011; 28: 320–334.
    OpenUrl
  33. 33.↵
    Kolanowski J, Bodson A, Desmecht P, et al. On the relationship between ketonuria and natriuresis during fasting and upon refeeding in obese patients. Eur J Clin Invest. 1978: 8: 277–282.
    OpenUrlPubMedWeb of Science
  34. 34.↵
    Ng M, Fleming T, Robinson M, et al. Global, regional, and national prevalence of overweight and obesity in children and adults during 1980–2013: a systemic analysis for the Global Burden of Disease Study 2013. Lancet 2014; 384: 766–781.
    OpenUrlCrossRefPubMedWeb of Science
  35. 35.↵
    Knop FK, Taylor R. Mechanism of metabolic advantages after bariatric surgery. Diabetes Care 2013; 36: 5287-
    OpenUrl
  36. 36.↵
    Steven S, Lim EL, Taylor R. Dietary reversal of type 2 diabetes motivated by research knowledge. Diabet Med 2010; 27: 724–725.
    OpenUrlCrossRefPubMed
  37. 37.↵
    Arterburn DE, Bogart A, Sherwood NE, et al. A multisite study of long-term remission and relapse of type 2 diabetes mellitus following gastric bypass. Obes Surg 2013; 23: 93–102.
    OpenUrlCrossRefPubMed
  38. 38.↵
    Hamdan K, Somers S, Chand M. Management of late postoperative complications of bariatric surgery. Br J Surgery 2011; 98: 1345–1355.
    OpenUrlCrossRefPubMed
  39. 39.↵
    Wing RR, Blair E, Marcus M, Epstein LH, Harvey J. Year-long weight loss treatment for obese patients with type II diabetes: does including intermittent very-low calorie diet improve outcome? Am J Med 1994; 97: 354–362.
    OpenUrlCrossRefPubMedWeb of Science
  40. 40.↵
    Goday A, Bellido D, Sajoux I, et al. Short-term safety, tolerability and efficacy of a very low-calorie-ketogenic diet interventional weight loss program versus hypocaloric diet in patients with type 2 diabetes mellitus. Nutr Diabetes 2016;6: e230
    OpenUrlCrossRefPubMed
  41. 41.↵
    Westman EC, Yancy WS, Mavropoulos JC, Marquart M, McDuffie JR. The effect of a low-carbohydrate, ketogenic diet versus a low-glycemic index diet on glycemic control in type 2 diabetes mellitus. Nutr Metab 2009; 19: 36, doi:10.1186/1743-7075-5-36.
    OpenUrlCrossRef
  42. 42.↵
    Kirk JK, Graves DE, Craven TE, et al. Restricted-carbohydrate diets in patients with type 2 diabetes: a meta-analysis. J Am Diet Assoc 2008; 108: 91–100.
    OpenUrlCrossRefPubMedWeb of Science
  43. 43.↵
    Volek JS, Sharman MJ, Gomez AL, et al. Comparison of a very low-carbohydrate and low-fat diet on fasting lipids, LDL subclasses, insulin resistance, and postprandial lipemic responses in overweight women. J Am Coll Nutr 2004; 23: 177–184.
    OpenUrlPubMedWeb of Science
  44. 44.↵
    Seshadri P, Iqbal N, Stern L, et al. A randomized study comparing the effects of a low-carbohydrate diet and a conventional diet on lipoprotein subfractions and C-reactive protein levels in patients with severe obesity. Am J Med 2004; 117: 398–405.
    OpenUrlCrossRefPubMedWeb of Science
  45. 45.↵
    McKenzie A, Hallberg S, Creighton BC, et al. A novel intervention including nutritional recommendations reduces hemoglobin A1c level, medication use, and weight in type 2 diabetes. JMIR Diabetes 2017; 2: e5.
    OpenUrlCrossRef
  46. 46.↵
    White WB, Cannon CP, Heller CR, et al. Alogliptin after acute coronary syndrome in patients with type 2 diabetes. N Engl J Med 2013; 369: 1327–1335.
    OpenUrlCrossRefPubMedWeb of Science
  47. 47.
    Bethel MA, Patel RA, Merrill P, et al. Cardiovascular outcomes with glucagon-like peptide-1 receptor agonists in patients with type 2 diabetes: a meta-analysis. Lancet Diabetes Endocrinol 2018; 6: 105–113.
    OpenUrl
  48. 48.↵
    Zinman B, Wanner C, Lachin JM, et al. Empagliflozin, cardiovascular outcomes, and mortality in type 2 diabetes. N Engl J Med 2015; 373: 2117–2118.
    OpenUrlCrossRefPubMed
  49. 49.↵
    Shai I, Schwarzfuchs D, Henkin Y, et al. Weight loss with a low-carbohydrate, mediterranean, or low-fat diet. N Engl J Med 2008; 359: 229–241.
    OpenUrlCrossRefPubMedWeb of Science
  50. 50.↵
    Iqbal N, Vetter ML, Moore RH, et al. Effects of a low-intensity intervention that prescribed a low-carbohydrate vs. a low fat diet in obese, diabetic participants. Obesity 2010; 18: 1733–1738
    OpenUrl
  51. 51.↵
    Haimoto H, Iwata M, Wakai K, Umegaki H. Long-term effects of a diet loosely restricting carbohydrates on HbA1c levels, BMI and tapering of sulfonylureas in type 2 diabetes: A 2-year follow-up study. Diab Res Clin Prac 2008; 79: 350–356.
    OpenUrl
  52. 52.
    Steinberg DM, Tate DF, Bennett GG, Ennett S, Samuel-Hodge C, Ward DS. The efficacy of a daily self-weighing weight loss intervention using smart scales and email. Obesity 2013; 21: 1789–1797.
    OpenUrl
  53. 53.↵
    Arterburn D, Bogart A, Coleman KJ, et al. Comparative effectiveness of bariatric surgery versus nonsurgical treatment of type 2 diabetes among severely obese adults. Obes Res Clin Pract 2013; 7: e258–e268.
    OpenUrlCrossRefPubMed
  54. 54.↵
    Barter PJ, Ballantyne CM, Carmena R, et al. Apo B versus cholesterol in estimating cardiovascular risk and in guiding therapy: report of the thirty person/ten-country panel. J Intern Med 2006; 259: 247–258.
    OpenUrlCrossRefPubMedWeb of Science
  55. 55.↵
    Verges B. Lipid modification in type 2 diabetes: the role of LDL and HDL. Fundam Clin Pharmacol 2009; 23: 681–685.
    OpenUrlCrossRefPubMed
  56. 56.↵
    1. Cowie CC,
    2. Casagrande SS,
    3. Menke A,
    4. Cissell MA,
    5. Eberhardt MS,
    6. Meigs JB,
    7. Gregg EW,
    8. Knowler WC,
    9. Barrett-Connor E,
    10. Becker DJ,
    11. Brancati FL,
    12. Boyko EJ,
    13. Herman WH,
    14. Howard BV,
    15. Narayan KMV,
    16. Rewers M,
    17. Fradkin JE
    Menke A, Knowler WC, and Cowie CC. Physical and metabolic characteristics of persons with diabetes and prediabetes. Chapter 9 in Diabetes in America, 3rd ed. Cowie CC, Casagrande SS, Menke A, Cissell MA, Eberhardt MS, Meigs JB, Gregg EW, Knowler WC, Barrett-Connor E, Becker DJ, Brancati FL, Boyko EJ, Herman WH, Howard BV, Narayan KMV, Rewers M, Fradkin JE, eds, Bethesda, MD, National Institutes of Health, NIH Pub No. 17–1468[,p. 1–55].
  57. 57.↵
    Liu J, Sempos C, Donahue RP, et al. Joint distribution of non-HDL and LDL cholesterol and coronary heart disease risk prediction among individuals with and without diabetes. Diabetes Care 2005; 28: 1916–1921.
    OpenUrlAbstract/FREE Full Text
  58. 58.↵
    Hirano T. Pathophysiology of diabetic dyslipidemia. J Atheroscler Thromb 2018; 25: 771–785.
    OpenUrl
  59. 59.↵
    Gross BA, Goss AM. A lower-carbohydrate, higher-fat diet reduces abdominal and intermuscular fat and increases insulin sensitivity in adults at risk of type 2 diabetes. J Nutr 2015; 145: 177S–183S.
    OpenUrlAbstract/FREE Full Text
  60. 60.↵
    Vague J. The degree of masculine differentiation of obesities: a factor determining predisposition to diabetes, atherosclerosis, gout and uric calculous disease. Am J Clin Nutr 1956; 4: 20–31.
    OpenUrlAbstract
  61. 61.↵
    Jakobsen MU, Berentzen T, Sorensen TIA, et al. Abdominal obesity and fatty liver. Epidemiol Rev 2007; 29:77–87.
    OpenUrlCrossRefPubMed
  62. 62.
    Bouchi R, Nakano Y, Fukuda T, et al. Reduction of visceral fat by liraglutide is associated with ameliorations of hepatic steatosis, albuminuria, and micro-inflammation in type 2 diabetic patients with insulin treatment: a randomized control trial. Endocr J 2017; 64: 269–281.
    OpenUrlPubMed
  63. 63.
    Shimabukuro M, Higa M, Yamakawa K, et al. Miglitol, α-glycosidase inhibitor, reduces visceral fat accumulation and cardiovascular risk factors in subjects with the metabolic syndrome: a randomized comparable study. Int J Cardiol 2013; 167: 2108–2113.
    OpenUrl
  64. 64.
    Gabriely I, Ma XH, Yang XM, et al. Removal of visceral fat prevents insulin resistance and glucose intolerance of aging: an adipokine-mediated process? Diabetes 2002; 51: 2951–2958.
    OpenUrlAbstract/FREE Full Text
  65. 65.
    Garcia-Ruiz I, Solis-Munoz P, Fernandez-Moreira D, et al. Omentectomy prevents metabolic syndrome by reducing appetite and body weight in a diet induced obesity rat model. Sci Rep 2018; 8: 1540. doi: 10.10.1038/s41598-018-19973.
    OpenUrlCrossRef
  66. 66.
    Bril F, Cusi K. Management of nonalcoholic fatty liver disease in patients with type 2 diabetes: A call to action. Diabetes Care 2017; 40: 419–430.
    OpenUrlAbstract/FREE Full Text
  67. 67.
    Verrijen A, Francque S, Van Gaal L. The role of visceral adipose tissue in the pathogenesis of non-alcoholic fatty liver disease. European Endocrinology 2011; 7: 96–103.
    OpenUrl
  68. 68.↵
    Wu X, Huang Z, Wang X. et al. Ketogenic diet compromises both cancellous and corticol bone mass in mice. Calcif Tissue Int 2017; 101: 412–421.
    OpenUrl
  69. 69.↵
    Zengin A, Kropp B, Chevalier Y, et al. Low-carbohydrate, high-fat diets have sex-specific effects on bone health in rats. Eur J Nutr 2016; 55: 2307–2320.
    OpenUrl
  70. 70.↵
    Willi SM, Oexmann MJ, Wright NM, Collop NA, Key LL Jr.. The effects of a high-protein, low-fat, ketogenic diet on adolescents with morbid obesity: body composition, blood chemistries and sleep abnormalities. Pediatric 1998; 101: 61–67
    OpenUrl
  71. 71.↵
    Colica C, Merra G, Gasbarrini A, et al. Efficacy and safety of very low-calorie ketogenic diet: a double blind randomized crossover study. Eur Rev Med Pharmacol Sci 2017; 21: 2274–2289.
    OpenUrl
  72. 72.↵
    Moreno B, Bellido D, Sajoux I, et al. Comparison of a very low-calorie-ketogenic diet with a standard low-calorie diet in the treatment of obesity. Endocrine 2014; DOI 10.1007/s12020-014-0192-3
    OpenUrlCrossRef
  73. 73.
    Bertoli S, Trentani C, Ferraris C, De Giorgis V, Veggiotti P, Taglibue A. Long-term effects of a ketogenic diet on body composition and bone mineralization in GLUT-1 deficiency syndrome: A case series. Nutrition 2014; 30: 726–728.
    OpenUrlPubMed
Back to top
PreviousNext
Posted December 06, 2018.
Download PDF
Email

Thank you for your interest in spreading the word about bioRxiv.

NOTE: Your email address is requested solely to identify you as the sender of this article.

Enter multiple addresses on separate lines or separate them with commas.
Long-Term Effects of a Novel Continuous Remote Care Intervention Including Nutritional Ketosis for the Management of Type 2 Diabetes: A 2-year Non-randomized Clinical Trial
(Your Name) has forwarded a page to you from bioRxiv
(Your Name) thought you would like to see this page from the bioRxiv website.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Share
Long-Term Effects of a Novel Continuous Remote Care Intervention Including Nutritional Ketosis for the Management of Type 2 Diabetes: A 2-year Non-randomized Clinical Trial
Shaminie J. Athinarayanan, Rebecca N. Adams, Sarah J. Hallberg, Amy L. McKenzie, Nasir H. Bhanpuri, Wayne W. Campbell, Jeff S. Volek, Stephen D. Phinney, James P. McCarter
bioRxiv 476275; doi: https://doi.org/10.1101/476275
Reddit logo Twitter logo Facebook logo LinkedIn logo Mendeley logo
Citation Tools
Long-Term Effects of a Novel Continuous Remote Care Intervention Including Nutritional Ketosis for the Management of Type 2 Diabetes: A 2-year Non-randomized Clinical Trial
Shaminie J. Athinarayanan, Rebecca N. Adams, Sarah J. Hallberg, Amy L. McKenzie, Nasir H. Bhanpuri, Wayne W. Campbell, Jeff S. Volek, Stephen D. Phinney, James P. McCarter
bioRxiv 476275; doi: https://doi.org/10.1101/476275

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Subject Area

  • Clinical Trials
Subject Areas
All Articles
  • Animal Behavior and Cognition (4239)
  • Biochemistry (9171)
  • Bioengineering (6804)
  • Bioinformatics (24062)
  • Biophysics (12154)
  • Cancer Biology (9564)
  • Cell Biology (13824)
  • Clinical Trials (138)
  • Developmental Biology (7656)
  • Ecology (11736)
  • Epidemiology (2066)
  • Evolutionary Biology (15540)
  • Genetics (10670)
  • Genomics (14358)
  • Immunology (9511)
  • Microbiology (22901)
  • Molecular Biology (9129)
  • Neuroscience (49107)
  • Paleontology (357)
  • Pathology (1487)
  • Pharmacology and Toxicology (2583)
  • Physiology (3851)
  • Plant Biology (8351)
  • Scientific Communication and Education (1473)
  • Synthetic Biology (2301)
  • Systems Biology (6205)
  • Zoology (1302)