Abstract
Background
Although Roux-en-Y gastric bypass (RYGB) induces short-term weight loss and comorbidity amelioration, long-term data suggests a subset of patients return to their preoperative body mass index (BMI).
Objectives
Identify the clinical implications of 10-year weight-loss failure following RYGB.
Setting
Academic teaching hospital.
Methods
Adults undergoing Roux-en-Y Gastric Bypass (1985-2004) were included in this study (n=1087). Absolute weight-loss failure was defined as ≤0% reduction in excess BMI (%REBMI) 10 years after surgery. Univariate analyses compared comorbidity rates and resolution by weight-loss classification. Multivariable regression modeling analyzed preoperative predictors of 10-year %REBMI and weight-loss failure.
Results
Complete follow-up was available for 617 (57%) patients with a 10-year median %REBMI of 57.1% and 10.2% of patients had weight-loss failure. Prevalence of all comorbidities decreased, even in patients with weight loss failure (all p<0.05). Compared to patients with successful weight loss, patients with weight loss failure had similar rates of resolution of preexisting comorbidities, except for reduced resolution of apnea and cardiac comorbidities (both p<0.05). Risk factors for weight loss failure included lower BMI, non-governmental insurance, longer travel time to hospital, and year of surgery. Non-governmental insurance (OR 2.03, p=0.036) conferred the highest adjusted odds of weight loss failure.
Conclusions
The vast majority of patients experience dramatic health improvement 10 years after RYGB, even though some patients fail to maintain their weight loss. Renewed focus should be placed on prevention and treatment of chronic disease, with further investigation of weight loss independent mechanisms of health improvement.
MeSH: Bariatric Surgery, Gastric Bypass, Weight loss, Prediction Models
INTRODUCTION
The epidemic of obesity in the United States continues to represent an alarming health burden with over half of the population overweight (Body Mass Index (BMI) 25–30 kg/m2) or obese (BMI >30 kg/m2).[1] While there were hints that the rate of obesity was stabilizing, the most recent figures suggest further increase with 37.9% of adults obese and 7.7% extremely obese (BMI >40 kg/m2).[1, 2] Several studies have demonstrated the early benefits of Roux-en-Y Gastric Bypass (RYGB) including reduction in cardiovascular risks and weight loss.[3–5] These results have been confirmed by several clinical trials demonstrating superiority of bariatric surgery to best medical therapy.[6, 7]
While the short-term success of RYGB has been well documented, long-term data has been sparse due to poor long-term follow-up.[8] The Swedish Obesity Study was the first to demonstrate durable remission of diabetes at 10 and 15 years with outstanding patient follow-up in their National Health Registry.[9] Recent reports show comparable long-term results with durable weight loss and comorbidity reduction in the American population.[10–12] Our group demonstrated that most patients reach maximum percent reduction in excess BMI (%REBMI) at 2 years (72% REBMI) with gradual weight regain and plateauing at 57% REBMI at 10 years.[11]
Despite the excellent overall results reported, there is a growing body of evidence that a small proportion of patients suffer large weight regain or weight-loss failure.[10, 11, 13] A small amount of weight regain can be expected, but the impact of large weight regain is poorly understood. The definition of failure is highly variable with no accepted classification due to the paucity of data.[12, 14, 15] The purpose of this study was to characterize the population with weight-loss failure after RYGB, determine the impact of weight loss failure on comorbidity amelioration, and identify predictors of weight-loss failure.
MATERIALS AND METHODS
Study Participants
Adults undergoing bariatric surgery at a single institution between 1985 and 2003 were included in a previously validated database (n= 1,087).[11] Partial follow-up was available for 1,040 (96%) patients with at least one postoperative weight recorded and 10-year weights were available for 699 (64%) patients. All other analyses were performed on 617 (57%) patients with complete 10-year follow-up. Supplemental Figure 1 demonstrates the exclusion criteria; overall 108 (10%) patients were excluded due to mortality, 22 (2%) patients refused to participate, and 340 (31%) were lost to follow-up. Patients who underwent a revision to their RYGB were included. The University of Virginia institutional review board approved this study (IRB Protocol #17132).
End Points
Routine follow-up was completed for 151 of the 1,087 patients (14%). Additional follow-up on 500 patients was accomplished by surgical residents, medical students and study coordinators using standardized chart review alone (41.8%) or chart review and telephone interviews (58.2%) and was completed in 2015. Mortality information was obtained from the Centers for Disease Control National Death Index. Comorbid conditions were documented as present if the patient was actively undergoing treatment as previously described.[11] At 10-year follow-up, the same definitions were used, either documented in clinic visits or by telephone interview.
Patients were stratified by weight-loss failure, which was defined as ≤0% reduction in excess BMI (%REBMI) 10 years after surgery. The primary outcome of interest was a composite of comorbidities modeled after the Charleson Comorbidity Index, defined as the sum of comorbidities (apnea, cardiac, hypertension, pulmonary, type 2 diabetes, gastroesophageal reflux disease, degenerative joint disease, and psychiatric medication use) equally weighted for a maximum score of 8. Cardiac comorbidity included heart failure, coronary disease, and arrhythmia. Pulmonary disease included chronic obstructive pulmonary disease (COPD), asthma, and emphysema. Resolution of disease was calculated as the number of patients with a disease preoperatively who no longer have that diagnosis at 10 years.
Statistical Analysis
Patients were stratified by weight-loss failure and univariate analyses characterized baseline and operative characteristics along with late outcomes. The Mann-Whitney U test was used for independent continuous variables and the Wilcoxon signed rank sum test for paired ordinal data. The Chi-Square test was used for independent categorical variables, while McNemar’s test was used for paired data. Multivariable linear regression was utilized to identify preoperative predictors of 10-year %REBMI. A priori the decision was made to include the six most statistically significant predictors in a multivariable logistic regression model for predicting weight-loss failure. Statistical significance was determined by two-sided α of 0.05. All analyses were performed using SAS version 9.4 (SAS Institute, Cary, NC).
RESULTS
Study Participants
Of the 617 (57%) of patients with complete follow-up, the median age was 41 years, median BMI was 51.5 kg/m2 and 82.7% were female. The median follow-up time point was equivalent between patients with weight-loss failure and success (14.4 vs 13.6 years, p=0.19). This group was similar to excluded patients for nearly all preoperative comorbid conditions (Supplemental Table 1) and %REBMI for known interval time points (Supplemental Table 2). Baseline and operative comparisons are reported in Table 1 with significant differences in baseline BMI, cardiac comorbidities, gastroesophageal reflux disease (GERD), gender and insurance. There were no differences in operative characteristics with 43% of cases completed laparoscopically.
Table 1.
Baseline and operative characteristics among patients with 10-year weight loss success or failure
| Baseline characteristics | Weight Loss Success (n = 554) |
Weight Loss Failure (n = 63) |
p-value |
|---|---|---|---|
| Age (years; median, IQR) | 41 (35–48) | 42 (38–48) | 0.178 |
| Female | 452 (81.6%) | 58 (92.1%) | 0.037 |
| Non-Caucasian | 79 (14.3%) | 12 (19.1%) | 0.310 |
| BMI (median, IQR) | 51.8 (46.3–58.6) | 45.3 (41.5–52.0) | < 0.0001 |
| Travel Time (hours; median, IQR) | 1.2 (0.7–1.7) | 1.2 (0.8–1.7) | 0.574 |
| Comorbidity Index (median, IQR) | 2 (1–4) | 3 (1–8) | 0.213 |
| Apnea | 193 (34.8%) | 28 (44.4%) | 0.132 |
| Cardiac comorbidity‡ | 131 (23.7%) | 23 (36.5%) | 0.025 |
| Hypertension | 324 (58.5%) | 37 (58.7%) | 0.970 |
| Pulmonary disease† | 146 (26.4%) | 22 (34.9%) | 0.148 |
| Type 2 Diabetes | 223 (40.3%) | 25 (39.7%) | 0.930 |
| Gastroesophageal reflux disease | 202 (36.5%) | 32 (50.8%) | 0.026 |
| Degenerative joint disease | 335 (60.5%) | 42 (66.7%) | 0.339 |
| Psychiatric medication use | 207 (37.4%) | 28 (44.4%) | 0.273 |
| Prior Appendectomy | 47 (8.5%) | 4 (6.4%) | 0.560 |
| Prior Bariatric Surgery | 6 (1.1%) | 1 (1.6%) | 0.720 |
| Prior Cholecystectomy | 92 (16.6%) | 14 (22.2%) | 0.263 |
| Prior Gynecologic Surgery | 124 (22.4%) | 18 (28.6%) | 0.269 |
| Non-Governmental Insurance | 347 (62.6%) | 50 (79.4%) | 0.009 |
| Operative Characteristics | |||
| Cholecystectomy | 232 (41.9%) | 24 (38.1%) | 0.564 |
| Started Laparoscopically | 267 (48.2%) | 31 (49.2%) | 0.879 |
| Finished Laparoscopically | 240 (43.3%) | 28 (44.4%) | 0.865 |
BMI = body mass index; IQR = interquartile range)
Cardiac comorbidity includes heart failure, coronary disease, and arrhythmia
Pulmonary disease includes chronic obstructive pulmonary disease (COPD), asthma, and emphysema
The trajectory of weight loss for all patients (n= 1,040) is demonstrated in Figure 1. The peak %REBMI was at 2 years postoperatively before plateauing with a 10-year median %REBMI of 57%. Weight-loss failure occurred in 67 of 699 patients (10%) at 10 years, and in 63 of 617 (10%) of patients with complete follow-up. The median %REBMI for patients with successful weight loss was 61.8 compared to −17.0 for patients with weight loss failure (Supplemental Table 3).
Figure 1.
The median and interquartile range of percent reduction in excess BMI (%REBMI) is plotted over time for the 67 patients with weight loss failure at 10 years (in black) and the remaining 973 patients (in gray).
The weight loss success and failure groups had similar rates of most comorbidities at 10 years including the composite comorbidity index (median score 1 vs 1, p=0.29, supplemental Table 4). Only rates of obstructive sleep apnea were higher in patients with weight-loss failure (14.3% vs 12.3%, p=0.02). When compared to preoperative rates, patients with successful weight-loss at 10-years had significant reductions in every comorbidity measured (all p<0.0001; Supplemental Table 5).
As a measure of overall health, the percent improvement in comorbidity index was not statistically different between groups (67% vs 67%, p=0.760; Table 2). There were also no statistical differences in the rates of resolution for hypertension, pulmonary disease, type 2 diabetes, GERD, degenerative joint disease or psychiatric medication use between weight-loss failure compared to success (p>0.05). However, fewer patients with weight-loss failure had apnea (71.4% vs 87.1%, p=0.03) or cardiac comorbidities resolve (73.9% vs 90.8%, p=0.02).
Table 2.
Resolution of pre-existing comorbidities at 10-years among patients with weight loss success or failure
| Comorbidities | Weight Loss Success | Weight Loss Failure | p-value |
|---|---|---|---|
| Comorbidity index (% decrease; median, IQR) | 67% (0–100%) | 67% (0–100%) | 0.778 |
| Apnea | 168 (87.1%) | 20 (71.4%) | 0.030 |
| Cardiac Comorbidity | 119 (90.8%) | 17 (73.9%) | 0.020 |
| Degenerative Joint Disease | 252 (75.2%) | 28 (66.7%) | 0.232 |
| Diabetes | 190 (85.2%) | 22 (88.0%) | 0.707 |
| Gastroesophageal Reflux Disease | 156 (77.2%) | 24 (75.0%) | 0.781 |
| Hypertension | 205 (63.3%) | 24 (64.9%) | 0.849 |
| Pulmonary Disease | 121 (82.9%) | 19 (86.4%) | 0.683 |
| Psychiatric Medication Use | 163 (78.7%) | 20 (71.4%) | 0.382 |
IQR (interquartile range)
Cardiac comorbidity includes heart failure, coronary disease, and arrhythmia
Pulmonary disease includes chronic obstructive pulmonary disease (COPD), asthma, and emphysema
Table 3 shows that female gender (p=0.008), travel time to the hospital (p=0.025), non-governmental insurance (p=0.006), preoperative BMI (p=0.015), and year of surgery (p=0.016) were independently associated with %REBMI at 10 years. A history of cholecystectomy trended towards significance (p=0.078). The model performance was poor with an R2 of only 0.088.
Table 3.
Predictors of weight loss at 10-years
| Predictors of %REBMI | Parameter Estimate | 95% Confidence Limits | p value | |
|---|---|---|---|---|
| Age (years) | −0.28 | −0.64 | 0.07 | 0.121 |
| Female | −11.48 | −20.00 | −2.95 | 0.008 |
| Non-Caucasian | −5.36 | −14.23 | 3.50 | 0.235 |
| Travel Time to Hospital (Hours) | −2.94 | −5.51 | −0.37 | 0.025 |
| Non-Governmental Insurance | −9.19 | −15.69 | −2.68 | 0.006 |
| Body Mass Index | 0.41 | 0.08 | 0.75 | 0.015 |
| Obstructive Sleep Apnea | −7.04 | −15.64 | 1.57 | 0.109 |
| Cardiac Comorbidity‡ | −6.40 | −18.68 | 5.88 | 0.306 |
| Hypertension | 3.54 | −3.93 | 11.01 | 0.353 |
| Pulmonary disease† | 1.39 | −9.86 | 12.64 | 0.808 |
| Type 2 Diabetes | −1.09 | −9.68 | 7.50 | 0.803 |
| Gastroesophageal reflux disease | −5.26 | −13.57 | 3.05 | 0.214 |
| Degenerative joint disease | 0.76 | −6.22 | 7.74 | 0.831 |
| Psychiatric medication use | 3.52 | −4.74 | 11.79 | 0.403 |
| Prior Appendectomy | 5.51 | −6.04 | 17.05 | 0.349 |
| Prior Bariatric Surgery | −0.63 | −29.76 | 28.50 | 0.996 |
| Prior Cholecystectomy | −7.70 | −16.26 | 0.86 | 0.078 |
| Prior Gynecologic Surgery | −3.02 | −11.24 | 5.21 | 0.471 |
| Open RYGB | 4.34 | −5.55 | 14.24 | 0.389 |
| Conversion to open surgery | 3.84 | −11.00 | 18.69 | 0.611 |
| Year | 1.24 | 0.23 | 2.25 | 0.016 |
| Predictors of weight loss failure | Odds Ratio | 95% Confidence Limits | p value | |
| Non-Governmental Insurance | 2.03 | 1.05 | 3.94 | 0.036 |
| Travel Time to Hospital (Hours) | 1.25 | 1.05 | 1.49 | 0.015 |
| Body Mass Index | 0.90 | 0.87 | 0.94 | <0.0001 |
| Year | 0.94 | 0.89 | 0.99 | 0.029 |
| Female | 2.42 | 0.92 | 6.38 | 0.075 |
| Prior Cholecystectomy | 1.15 | 0.58 | 2.27 | 0.685 |
%REBMI (Percent reduction in excess BMI); IQR (interquartile range)
Cardiac comorbidity includes heart failure, coronary disease, and arrhythmia
Pulmonary disease includes chronic obstructive pulmonary disease (COPD), asthma, and emphysema
Of these six variables, the preoperative risk factor conferring the highest odds of weight-loss failure was non-governmental insurance coverage (OR 2.03, p=0.036; Table 3). Both year of surgery (OR 0.94, p=0.029) and preoperative BMI (OR 0.90, p <0.0001) were independently associated with weight-loss failure. Every hour of increased travel time to the hospital conferred a 1.25 fold increased risk of weight-loss failure (p=0.015). Neither female gender nor prior cholecystectomy were statistically associated with weight-loss failure. The model performance was adequate with an area under the curve (c-statistic) of 0.767.
DISCUSSION
Mechanisms of Health Improvement
Using the stringent definition of weight-loss failure as any patient who was at or above their preoperative weight at 10 years, we demonstrate that 10% of patients had weight-loss failure. This is a larger percentage than previously reported in the male predominant Veterans Affairs health system.[12] Additionally, the finding of dramatic comorbidity resolution is consistent with prior work suggesting that multiple comorbidities improve after RYGB in the short-term.[3, 6, 7, 16] Herein we show that these same disease factors continue to exhibit significant improvement at 10 years post RYGB even in patients with weight-loss failure.[11] Both an index of comorbidities as well as every component comorbidity showed dramatic rates of improvement that ranged from 63% to 91% resolution. These rates of resolution were similar to a large meta-analysis performed by Buchwald and colleagues, except demonstrated to persist at 10 years.[5] Only apnea and cardiac comorbidities improved significantly more in patients with long-term weight loss compared to weight-loss failure. Collectively, our overall findings suggest minimal differences in health outcomes between patients with weight-loss failure compared to success.
There is clear evidence that weight loss is associated with resolution of chronic diseases, including type 2 diabetes, hypertension and hyperlipidemia.[10, 17] The comorbidity improvement in patients with weight-loss failure suggests that at least some portion of disease resolution may occur independent of weight loss. Alternatively, the initial weight loss seen in patients with eventual failure may result in persistent health improvement despite weight regain. The two exceptions we found were apnea and cardiac comorbidities. We hypothesize that resolution of apnea is unlikely to have a weight-independent mechanism of resolution due to the mechanical nature of the disease. The difference in cardiac comorbidity resolution may be related to the extremely high rate of resolution in those with successful weight loss (91%) who likely benefited from a synergy of cardiometabolic improvements from weight loss, increased exercise, and possibly improved sleep apnea.
While the evidence for weight-independent mechanisms is limited, it is well known that RYGB improves glucose tolerance before weight loss has occurred with multiple theories examining the impact of bypassing the duodenum.[18, 19] Other pathways may involve similar anatomic changes, secondary changes to the microbiome, or represent side effects from the long-term increased access to healthcare, psychological coaching, exercise and healthy diet. Shorter-term studies show a stronger correlation between amount of weight loss and comorbidity resolution, possibly suggesting that with time the weight-independent mechanisms become more important and may become a significant determinant of the long-term mortality benefit seen with RYGB.[20, 21] As a result of the dramatic health improvements seen in the weight-loss failure group, we contend that increased focus on health improvement after RYGB and not weight loss be a key discussion point with patients.
Predictors of Weight Loss
Patients undergo RYGB for multiple reasons, and an often cited priority is body image improvement through weight loss. In this patient cohort, multiple preoperative factors are associated with blunted long-term weight loss including female gender, non-governmental insurance, longer travel times to the hospital and lower BMI. However, predicting exact weight loss at 10 years is difficult and models perform poorly, as seen with our model accounting for only 9% of variability in %REBMI.
The preoperative factors that were associated with weight-loss failure in the present study include non-governmental insurance, increased travel time to the bariatric surgery center, preoperative BMI and year of surgery. These observations build on prior work and suggest that barriers to surgery and medical care may impede success rates long-term.[17] From a clinical perspective, these findings could aid counseling sessions with patients to minimize chances of possible weight-loss failure and maximize weight-loss success.
Policy Implications for Predictors of Weight-Loss Failure
The exact reason people regain weight after RYGB is controversial, and the impact must consider the health improvement even those with weight-loss failure achieve. Nevertheless, female sex is associated with poorer weight loss over time. This is consistent with prior literature, although the interactions with other socioeconomic factors is difficult to disentangle particularly with so few males undergoing RYGB.[22, 23] During follow-up these patients may benefit from focused efforts to maintain weight loss.[3, 5]
Higher preoperative BMI was associated with increased weight loss and was protective against weight-loss failure (OR 0.9 per 1 unit increase in BMI). These results are at odds with some recent literature, although a meta-analysis demonstrated significant variation with conflicting results.[17, 24] The effect size is small compared to other predictors and the model performance is poor, which along with heterogeneity in the meta-analysis suggests that BMI is not an important predictor of weight loss. Considering such minimal impact of BMI, a lower threshold for surgery for patients with multiple cardiometabolic risk factors should be researched further.[25]
The year of surgery was associated with both weight loss and weight loss failure, with every year later in the study period associated with reduced risk of weight loss failure (OR 0.94). Although not a high-impact predictor, the significance suggests that either improving surgical technique or non-surgical practices such as interdisciplinary care teams are having an impact on weight loss. As neither laparoscopic approach nor conversion to open surgery were associated with weight loss failure, the most likely reason will be non-operative. Despite a lack of high-quality prospective data, multidisciplinary teams likely have a wide range of potential benefits and are an essential component of consensus recommendations and accreditations [26, 27].
Finally, there are practical reasons for failure to achieve persistent weight loss. Increased travel distance from a patient’s home to the bariatric surgery center is an independent risk factor for less weight loss and weight-loss failure. The current model where insurance policies restrict coverage to certified bariatric centers limits access to this procedure and forces patients to travel farther.[28–30] This increased impediment likely prevents some patients from undergoing a needed surgery, and for others decreases frequency of follow-up that is proven to help maintain weight loss.[25] Efforts should be undertaken to expand access to RYGB while maintaining the high standards found at bariatric centers that include multidisciplinary care teams and specialty trained bariatric surgeons. Telemedicine represents a promising technology that could enable multi-disciplinary follow-up without costly and inconvenient travel.[31]
Also influencing access is insurance status, where non-Governmental insurance was associated with both less weight loss and weight-loss failure. The cause of this association is likely complex involving both preoperative criteria and socioeconomic characteristics of the patients. While requirements placed on patients to qualify for bariatric surgery are variable, there is evidence that governmental policies may be more stringent. Governmental insurance has been associated with longer wait times before surgery.[32] The intended effect is to only have motivated patients undergo the procedure, and for this the policies are effective with less weight-loss failure. Further supporting evidence for selection bias is the fact that private insurance patients are overrepresented in the bariatric surgery population (82%) compared to those eligible (65%).[33] This effect is also apparent by income level where 35% of patients eligible for bariatric surgery are in the lowest income quartile, but make up only 20% of the bariatric surgery population. Given the cardiometabolic benefits of bariatric surgery even in patients with weight-loss failure, further investigation is warranted to evaluate the potential benefits of increasing access to high-quality surgery.
While the retrospective nature of this analysis is a limitation of the study, the bariatric surgery database was created thirty years ago and data is prospectively collected. There have been efforts to maintain yearly follow-up after two years, although a geographically large referral area causes long travel times with higher costs, and therefore we emphasize close follow-up by primary care physicians. Additionally, our findings are limited by the subjectivity of patient reported information. Telephone interviews were utilized to increase the 10-year follow up rates as validated previously by Harper and colleagues.[8] In addition, we previously found no difference in %REBMI over time between patients with routine follow-up and those with medical record and telephone interviews suggesting minimal bias with self-reporting.[34] An additional limitation of partial retrospective follow-up is incomplete weights prior to 10 years. Future investigations into weight-loss independent health improvement would benefit from calculating duration of weight loss versus weight regain. Finally, we believe the risk for selection bias based on similar baseline characteristics and weight loss in excluded and included patients.
CONCLUSION
Our results suggest that approximately 10% of patients will regain all of their weight by 10 years post-surgery. Key factors explaining this weight regain appear linked to sex, travel time to the surgery center, insurance status and preoperative BMI. Thus, when physicians counsel patients, consideration of these factors may help inform the patient on potential risk for weight-loss failure. From a public health perspective, RYGB surgery promotes durable 10-year improvement of cardiometabolic health regardless of successful weight loss. This data supports characterizing bariatric surgery as “metabolic surgery,” and by extension recruiting patients with a focus on health improvement. Further investigation is warranted to evaluate the potential weight loss independent mechanisms of health improvement and the impact of increasing access to RYGB through modification of requirements for surgery and increasing the number of highly qualified certified bariatric centers.
Supplementary Material
Acknowledgments
We appreciate the support of Beth Turrentine and Anna Dietrich Covington in help with maintaining the institutional bariatric surgery database and with follow-up efforts. This work was funded in part by The National Heart, Lung, and Blood Institute [T32 HL07849].
Primary Funding Source: National Heart, Lung, and Blood Institute [T32 HL07849]
Footnotes
Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
Presentation: Obesity Week, New Orleans, LA, Oct 31–Nov 4, 2016.
Conflicts of Interest: The authors declare that they have no conflict of interest
Disclosures: No conflicts of interest.
References
- 1.Ogden CL, Carroll MD, Kit BK, Flegal KM. Prevalence of childhood and adult obesity in the United States, 2011–2012. JAMA. 2014;311:806–14. doi: 10.1001/jama.2014.732. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Fryar CD, Carroll MD, Ogden CL. Prevalence of Overweight, Obesity, and Extreme Obesity Among Adults Aged 20 and Over: United States, 1960–1962 Through 2013–2014. National Center for Health Statistics; Jul, 2016. [Google Scholar]
- 3.Ballantyne GH. Measuring outcomes following bariatric surgery: weight loss parameters, improvement in co-morbid conditions, change in quality of life and patient satisfaction. Obes Surg. 2003;13:954–64. doi: 10.1381/096089203322618867. [DOI] [PubMed] [Google Scholar]
- 4.Ricci C, Gaeta M, Rausa E, Macchitella Y, Bonavina L. Early impact of bariatric surgery on type II diabetes, hypertension, and hyperlipidemia: a systematic review, meta-analysis and meta-regression on 6,587 patients. Obes Surg. 2014;24:522–8. doi: 10.1007/s11695-013-1121-x. [DOI] [PubMed] [Google Scholar]
- 5.Buchwald H, Avidor Y, Braunwald E, Jensen MD, Pories W, Fahrbach K, et al. Bariatric surgery: a systematic review and meta-analysis. JAMA. 2004;292:1724–37. doi: 10.1001/jama.292.14.1724. [DOI] [PubMed] [Google Scholar]
- 6.Ikramuddin S, Korner J, Lee WJ, Connett JE, Inabnet WB, Billington CJ, et al. Roux-en-Y gastric bypass vs intensive medical management for the control of type 2 diabetes, hypertension, and hyperlipidemia: the Diabetes Surgery Study randomized clinical trial. JAMA. 2013;309:2240–9. doi: 10.1001/jama.2013.5835. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Kashyap SR, Bhatt DL, Wolski K, Watanabe RM, Abdul-Ghani M, Abood B, et al. Metabolic effects of bariatric surgery in patients with moderate obesity and type 2 diabetes: analysis of a randomized control trial comparing surgery with intensive medical treatment. Diabetes Care. 2013;36:2175–82. doi: 10.2337/dc12-1596. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Harper J, Madan AK, Ternovits CA, Tichansky DS. What happens to patients who do not follow-up after bariatric surgery? Am Surg. 2007;73:181–4. [PubMed] [Google Scholar]
- 9.Sjostrom L, Peltonen M, Jacobson P, Ahlin S, Andersson-Assarsson J, Anveden A, et al. Association of bariatric surgery with long-term remission of type 2 diabetes and with microvascular and macrovascular complications. JAMA. 2014;311:2297–304. doi: 10.1001/jama.2014.5988. [DOI] [PubMed] [Google Scholar]
- 10.Obeid NR, Malick W, Concors SJ, Fielding GA, Kurian MS, Ren-Fielding CJ. Long-term outcomes after Roux-en-Y gastric bypass: 10- to 13-year data. Surg Obes Relat Dis. 2016;12:11–20. doi: 10.1016/j.soard.2015.04.011. [DOI] [PubMed] [Google Scholar]
- 11.Mehaffey JH, LaPar DJ, Clement KC, Turrentine FE, Miller MS, Hallowell PT, et al. 10-Year Outcomes After Roux-en-Y Gastric Bypass. Ann Surg. 2015 doi: 10.1097/SLA.0000000000001544. [DOI] [PubMed] [Google Scholar]
- 12.Maciejewski ML, Arterburn DE, Van Scoyoc L, Smith VA, Yancy WS, Jr, Weidenbacher HJ, et al. Bariatric Surgery and Long-term Durability of Weight Loss. JAMA Surg. 2016 doi: 10.1001/jamasurg.2016.2317. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Moon RC, Teixeira AF, Jawad MA. Treatment of weight regain following roux-en-Y gastric bypass: revision of pouch, creation of new gastrojejunostomy and placement of proximal pericardial patch ring. Obes Surg. 2014;24:829–34. doi: 10.1007/s11695-014-1188-z. [DOI] [PubMed] [Google Scholar]
- 14.Mann JP, Jakes AD, Hayden JD, Barth JH. Systematic review of definitions of failure in revisional bariatric surgery. Obes Surg. 2015;25:571–4. doi: 10.1007/s11695-014-1541-2. [DOI] [PubMed] [Google Scholar]
- 15.McKenna D, Selzer D, Burchett M, Choi J, Mattar SG. Revisional bariatric surgery is more effective for improving obesity-related co-morbidities than it is for reinducing major weight loss. Surg Obes Relat Dis. 2014;10:654–9. doi: 10.1016/j.soard.2013.12.007. [DOI] [PubMed] [Google Scholar]
- 16.Chang SH, Stoll CR, Song J, Varela JE, Eagon CJ, Colditz GA. The effectiveness and risks of bariatric surgery: an updated systematic review and meta-analysis, 2003–2012. JAMA Surg. 2014;149:275–87. doi: 10.1001/jamasurg.2013.3654. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Wood GC, Benotti PN, Lee CJ, Mirshahi T, Still CD, Gerhard GS, et al. Evaluation of the Association Between Preoperative Clinical Factors and Long-term Weight Loss After Roux-en-Y Gastric Bypass. JAMA Surg. 2016 doi: 10.1001/jamasurg.2016.2334. [DOI] [PubMed] [Google Scholar]
- 18.Noria SF, Grantcharov T. Biological effects of bariatric surgery on obesity-related comorbidities. Can J Surg. 2013;56:47–57. doi: 10.1503/cjs.036111. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Pories WJ, Caro JF, Flickinger EG, Meelheim HD, Swanson MS. The control of diabetes mellitus (NIDDM) in the morbidly obese with the Greenville Gastric Bypass. Ann Surg. 1987;206:316–23. doi: 10.1097/00000658-198709000-00009. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Laurino Neto RM, Herbella FA, Tauil RM, Silva FS, de Lima SE., Jr Comorbidities remission after Roux-en-Y Gastric Bypass for morbid obesity is sustained in a long-term follow-up and correlates with weight regain. Obes Surg. 2012;22:1580–5. doi: 10.1007/s11695-012-0731-z. [DOI] [PubMed] [Google Scholar]
- 21.Sjostrom L, Narbro K, Sjostrom CD, Karason K, Larsson B, Wedel H, et al. Effects of bariatric surgery on mortality in Swedish obese subjects. N Engl J Med. 2007;357:741–52. doi: 10.1056/NEJMoa066254. [DOI] [PubMed] [Google Scholar]
- 22.Coleman KJ, Brookey J. Gender and racial/ethnic background predict weight loss after Roux-en-Y gastric bypass independent of health and lifestyle behaviors. Obes Surg. 2014;24:1729–36. doi: 10.1007/s11695-014-1268-0. [DOI] [PubMed] [Google Scholar]
- 23.Admiraal WM, Celik F, Gerdes VE, Dallal RM, Hoekstra JB, Holleman F. Ethnic differences in weight loss and diabetes remission after bariatric surgery: a meta-analysis. Diabetes Care. 2012;35:1951–8. doi: 10.2337/dc12-0260. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Livhits M, Mercado C, Yermilov I, Parikh JA, Dutson E, Mehran A, et al. Preoperative predictors of weight loss following bariatric surgery: systematic review. Obes Surg. 2012;22:70–89. doi: 10.1007/s11695-011-0472-4. [DOI] [PubMed] [Google Scholar]
- 25.Dimick JB, Nicholas LH, Ryan AM, Thumma JR, Birkmeyer JD. Bariatric surgery complications before vs after implementation of a national policy restricting coverage to centers of excellence. JAMA. 2013;309:792–9. doi: 10.1001/jama.2013.755. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Buchwald H, Consensus Conference P Consensus conference statement bariatric surgery for morbid obesity: health implications for patients, health professionals, and third-party payers. Surg Obes Relat Dis. 2005;1:371–81. doi: 10.1016/j.soard.2005.04.002. [DOI] [PubMed] [Google Scholar]
- 27.Apovian CM, Cummings S, Anderson W, Borud L, Boyer K, Day K, et al. Best practice updates for multidisciplinary care in weight loss surgery. Obesity (Silver Spring) 2009;17:871–9. doi: 10.1038/oby.2008.580. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Kwon S, Wang B, Wong E, Alfonso-Cristancho R, Sullivan SD, Flum DR. The impact of accreditation on safety and cost of bariatric surgery. Surg Obes Relat Dis. 2013;9:617–22. doi: 10.1016/j.soard.2012.11.002. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Horwitz D, Saunders JK, Ude-Welcome A, Parikh M. Insurance-mandated medical weight management before bariatric surgery. Surg Obes Relat Dis. 2016;12:496–9. doi: 10.1016/j.soard.2015.09.004. [DOI] [PubMed] [Google Scholar]
- 30.Livingston EH, Burchell I. Reduced access to care resulting from centers of excellence initiatives in bariatric surgery. Arch Surg. 2010;145:993–7. doi: 10.1001/archsurg.2010.218. [DOI] [PubMed] [Google Scholar]
- 31.Sudan R, Salter M, Lynch T, Jacobs DO. Bariatric surgery using a network and teleconferencing to serve remote patients in the Veterans Administration Health Care System: feasibility and results. Am J Surg. 2011;202:71–6. doi: 10.1016/j.amjsurg.2010.06.016. [DOI] [PubMed] [Google Scholar]
- 32.Hayes S, Napolitano MA, Lent MR, Wood GC, Gerhard GS, Irving BA, et al. The effect of insurance status on pre- and post-operative bariatric surgery outcomes. Obes Surg. 2015;25:191–4. doi: 10.1007/s11695-014-1478-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33.Martin M, Beekley A, Kjorstad R, Sebesta J. Socioeconomic disparities in eligibility and access to bariatric surgery: a national population-based analysis. Surg Obes Relat Dis. 2010;6:8–15. doi: 10.1016/j.soard.2009.07.003. [DOI] [PubMed] [Google Scholar]
- 34.Mehaffey JH, Turrentine FE, Miller MS, Schirmer BD, Hallowell PT. Roux-en-Y gastric bypass 10-year follow-up: the found population. Surgery for Obesity and Related Diseases. 2016;12:778–82. doi: 10.1016/j.soard.2015.11.012. [DOI] [PMC free article] [PubMed] [Google Scholar]
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