The Use of Predictive Markers for the Development of a Model to Predict Weight Loss Following Vertical Sleeve Gastrectomy

Impact of Patient- and Surgeon-Related Factors on Weight Loss after Laparoscopic Sleeve Gastrectomy-A Single-Center Study

Background and Objectives: Surgical treatment for obesity is becoming increasingly popular. Surgeons have been trying to find a simple way to predict the type of surgical intervention that is best for a specific patient. This study aimed to determine the patient- and surgeon-related factors that affect weight loss after laparoscopic sleeve gastrectomy (LSG). Materials and Methods: A total of 129 patients underwent LSG in one surgical department. The following factors were analyzed: gender; age; highest preoperative and 6-month postoperative weight; the occurrence of obesity-related diseases, such as type 2 diabetes and hypertension; the number of surgeons involved in the surgery; and who performed the surgery, a resident or specialist. The outcomes also included length of hospital stay, operative time and complications. Statistical significance was defined as p ≤ 0.05. Results: A total of 129 patients (94 female) with a median age of 43 years and BMI of 43.1 kg/m2 underwent LSG, while a total of 109 (84.5%) patients achieved ≥50% of excess BMI loss (%EBMIL). Preoperative weight loss had no impact on %EBMIL (p = 0.95), operative time (p = 0.31) and length of hospital stay (p = 0.2). Two versus three surgeons in the operating team had no impact on surgery time (p = 0.1), length of stay (p = 0.98) and %EBMIL (p = 0.14). The operative time and length of hospital stay were similar for specialists and surgeons in training. %EBMIL was higher in the residents' surgery without statistical significance (p = 0.19). Complications occurred in 3.9% without mortality or leaks. Conclusions: Preoperative comorbidities, surgeons' experience and the number of surgeons in the operating team do not impact the complication rate, length of hospital stay, operative time and postoperative weight loss after LSG.

Predicting Inadequate Weight Loss After Bariatric Surgery: Derivation and Validation of a Four Factor Model

INTRODUCTION

Weight loss following bariatric surgery is variable and predicting inadequate weight loss is required to help select patients for bariatric surgery. The aim of the present study was to determine variables associated with inadequate weight loss and to derive and validate a predictive model.

METHODS

All patients who underwent laparoscopic sleeve gastrectomy and Roux-en-Y gastrectomy (2008-2022) in a tertiary referral centre were followed up prospectively. Inadequate weight loss was defined as excess weight loss (EWL) < 50% by 24 months. A top-down approach was performed using multivariate logistic regression and then internally validated using bootstrapping. Patients were categorised into risk groups.

RESULTS

A total of 280 patients (median age, 49 years; M:F, 69:211) were included (146 LSG; 134 LRYGB). At 24 months, the median total weight loss was 30.9% and 80.0% achieved EWL ≥ 50% by 24 months. Variables associated with inadequate weight loss were T2DM (OR 2.42; p = 0.042), age 51-60 (OR 1.93, p = 0.006), age > 60 (OR 4.93, p < 0.001), starting BMI > 50 kg/m² (OR 1.93, p = 0.037) and pre-operative weight loss (OR 3.51; p = 0.036). The validation C-index was 0.75 (slope = 0.89). Low, medium and high-risk groups had a 4.9%, 16.7% and 44.6% risk of inadequate weight loss, respectively.

CONCLUSIONS

Inadequate weight loss can be predicted using a four factor model which could help patients and clinicians in decision-making for bariatric surgery.

Development and Validation of the GAASThyriC Model for Predicting Patients with Suboptimal Clinical Response After Laparoscopic Sleeve Gastrectomy and a Practical Calculator: A Retrospective Cohort Study

BACKGROUND

It might not be possible to achieve the desired outcome in every patient following bariatric surgery, even though every patient is thoroughly examined before surgery. This study aimed to develop a regression model based on parameters that affect weight loss success in patients scheduled for laparoscopic sleeve gastrectomy (LSG) and thus preoperatively predict whether the patients will have an optimal clinical response in terms of weight loss at the end of the first year.

MATERIALS AND METHODS

Between January 2018 and August 2022, patients who underwent LSG were analyzed retrospectively. Age, sex, comorbidities, smoking status, alcohol use status, preoperative weight, preoperative body mass index (BMI), preoperative laboratory data, weight, and total weight loss (TWL)% values at the end of the first year were recorded. At the end of the first year following LSG, patients with TWL% above 20% were defined as having an optimal clinical response in terms of weight loss. This study is designed, conducted, and reported regarding the "transparent reporting of a multivariable prediction model for individual prognosis or diagnosis" (TRIPOD) statement. The final model was used to construct an Excel-based calculator.

RESULTS

Four hundred thirty-eight patients underwent the sleeve gastrectomy procedure, and 38 of them were excluded from the study because of a lack of 1-year follow-up information, resulting in 400 eligible patients for our study. Age, glucose, thyroid stimulating hormone (TSH), alcohol consumption, systemic immune inflammation index (SII), and tobacco were the independent predictors of optimal clinical response ( P <0.001, P <0.001, P <0.001, P =0.011, P =0.039, P =0.045, respectively). The model was called the GAASThyriC score. When the final model was tested in the validation cohort, the AUC was 0.875 (95% CI, 0.742-0.999), the sensitivity was 83.3% (95% CI, 51.6-97.9), specificity was 86.4% (95% CI, 77.4-92.8), negative likelihood ratio was 0.19 (95% CI, 0.05-0.68), and accuracy was 86% (95% CI, 77.6-92.1) when the cutoff value was set to the optimal threshold (logit = 0.8451).

CONCLUSION

The GAASThyriC score can be used as an effective auxiliary tool to predict the patient population with suboptimal clinical response in terms of TWL% at the end of the first year after LSG.

Prediction Model for Chronological Weight Loss After Bariatric Surgery in Korean Patients

Purpose

This study aimed to develop a predictive model for monitoring chronological weight loss during the early postoperative period following bariatric surgery in Korean patients with morbid obesity.

Materials and Methods

The baseline characteristics and postoperative weight loss outcomes were collected for up to 24 months after surgery in patients who underwent sleeve gastrectomy (SG) or Roux-en-Y gastric bypass (RYGB). The factors influencing weight loss outcomes were analyzed, and longitudinal percentile charts were plotted using quantile regression models adjusted for the identified independent factors.

Results

The analysis included 491 and 274 patients who underwent SG and RYGB, respectively, of whom 225 (29.4%) were men. A positive association was found between the maximum percentage of total weight loss (%TWL) and female sex, body mass index (BMI) ≥40, and age <40 years. Among patients who reached nadir BMI or had at least 12 months of follow-up data (n=304), 7.6% exhibited inadequate weight loss (TWL <20%). The predictors of insufficient weight loss were older age (>40 years), male sex, and psychological problems. Centile charts were generated for the entire cohort, incorporating age, sex, and the type of procedure as covariates.

Conclusion

The percentile charts proposed in the present study can assist surgeons and healthcare providers in gauging patients' progress toward their weight loss goals and determining the timing of adjunctive intervention in poor responders during early postoperative follow-up.

Comparative Analysis of Various Weight Loss Success Criteria Models After Bariatric Metabolic Surgery in Korean Morbid Obese Patients

Purpose

To identify weight loss prediction models by validating previous models using weight loss success criteria.

Materials and Methods

Patients with morbid obesity from 4 hospitals were retrospectively analyzed between Jan 2019 and 2022. Preoperative demographics, postoperative data, and 1-year follow-up weight loss outcomes were compared between 2 groups who underwent laparoscopic sleeve gastrectomy (LSG) and laparoscopic Roux-en-Y gastric bypass (LRYGB). Additionally, the predictive factors for the success of excess weight loss (EWL) (>50%) and total weight loss (TWL) (>25%) were analyzed.

Results

Of the 162 patients, 137 were enrolled during the study period, 75 underwent LSG, and 62 underwent LRYGB. The >50% EWL and >25% TWL 1 year after surgery were 61.3% and 43.1%, respectively. Diabetes mellitus medication use was reduced in 94.8% of patients with type 2 diabetes mellitus. Male sex and body mass index (BMI) were independent risk factors for successful weight loss (SWL) or >50% EWL (odds ratio [OR] for BMI 0.830, 95% confidence interval [CI] 0.764-0.902), whereas achieving >25% TWL was not affected by sex or BMI (OR for BMI 1.010, 95% CI 0.957-1.065). External validation of the prediction models showed an acceptable range of accuracy (adjusted R2 66.5-71.3%).

Conclusion

LSG and LRYGB are feasible and effective bariatric procedures for SWL in Korean patients with morbid obesity. The TWL model was a more appropriate criterion than EWL, and weight loss prediction models may help assess the 1-year outcomes of bariatric surgery.

Development and validation of an interpretable machine learning-based calculator for predicting 5-year weight trajectories after bariatric surgery: a multinational retrospective cohort SOPHIA study

BACKGROUND

Weight loss trajectories after bariatric surgery vary widely between individuals, and predicting weight loss before the operation remains challenging. We aimed to develop a model using machine learning to provide individual preoperative prediction of 5-year weight loss trajectories after surgery.

METHODS

In this multinational retrospective observational study we enrolled adult participants (aged ≥18 years) from ten prospective cohorts (including ABOS [NCT01129297], BAREVAL [NCT02310178], the Swedish Obese Subjects study, and a large cohort from the Dutch Obesity Clinic [Nederlandse Obesitas Kliniek]) and two randomised trials (SleevePass [NCT00793143] and SM-BOSS [NCT00356213]) in Europe, the Americas, and Asia, with a 5 year follow-up after Roux-en-Y gastric bypass, sleeve gastrectomy, or gastric band. Patients with a previous history of bariatric surgery or large delays between scheduled and actual visits were excluded. The training cohort comprised patients from two centres in France (ABOS and BAREVAL). The primary outcome was BMI at 5 years. A model was developed using least absolute shrinkage and selection operator to select variables and the classification and regression trees algorithm to build interpretable regression trees. The performances of the model were assessed through the median absolute deviation (MAD) and root mean squared error (RMSE) of BMI.

FINDINGS

10 231 patients from 12 centres in ten countries were included in the analysis, corresponding to 30 602 patient-years. Among participants in all 12 cohorts, 7701 (75·3%) were female, 2530 (24·7%) were male. Among 434 baseline attributes available in the training cohort, seven variables were selected: height, weight, intervention type, age, diabetes status, diabetes duration, and smoking status. At 5 years, across external testing cohorts the overall mean MAD BMI was 2·8 kg/m2 (95% CI 2·6-3·0) and mean RMSE BMI was 4·7 kg/m2 (4·4-5·0), and the mean difference between predicted and observed BMI was -0·3 kg/m2 (SD 4·7). This model is incorporated in an easy to use and interpretable web-based prediction tool to help inform clinical decision before surgery.

INTERPRETATION

We developed a machine learning-based model, which is internationally validated, for predicting individual 5-year weight loss trajectories after three common bariatric interventions.

FUNDING

SOPHIA Innovative Medicines Initiative 2 Joint Undertaking, supported by the EU's Horizon 2020 research and innovation programme, the European Federation of Pharmaceutical Industries and Associations, Type 1 Diabetes Exchange, and the Juvenile Diabetes Research Foundation and Obesity Action Coalition; Métropole Européenne de Lille; Agence Nationale de la Recherche; Institut national de recherche en sciences et technologies du numérique through the Artificial Intelligence chair Apprenf; Université de Lille Nord Europe's I-SITE EXPAND as part of the Bandits For Health project; Laboratoire d'excellence European Genomic Institute for Diabetes; Soutien aux Travaux Interdisciplinaires, Multi-établissements et Exploratoires programme by Conseil Régional Hauts-de-France (volet partenarial phase 2, project PERSO-SURG).

Reference Values for Weight Loss During 1 Year After Sleeve Gastrectomy: a Multicenter Retrospective Study in Japan

INTRODUCTION

This study aimed to provide reference values for the percentage total weight loss during 1 year after laparoscopic sleeve gastrectomy associated with primary response in Japan.

METHODS

This multicenter retrospective study comprised 248 patients with severe obesity who underwent laparoscopic sleeve gastrectomy at five institutions in Japan. A percentage total weight loss < 20% at 1 year was defined as primary non-response. Parsimonious predictive models were developed based on the results of multiple regression analyses. A receiver operating characteristic curve analysis was used to assess the discriminative performance for primary non-response.

RESULTS

The median age, initial body mass index, and percentage total weight loss at 1 year were 41 years, 41.4 kg/m², and 30.1%, respectively. There were 28 (11.3%) primary non-responders. For discriminating primary non-responders, the areas under the receiver operating characteristic curve of the parsimonious model and actual percentage of total weight loss at 3 months after laparoscopic sleeve gastrectomy were 0.846 and 0.803, respectively. Cutoffs for the predicted percentage total weight loss using the model and actual value of percentage total weight loss at 3 months attaining 80% sensitivity were 30% and 22%, and those attaining 98% specificity were 22% and 15%, respectively.

CONCLUSIONS

Reference values for the percentage total weight loss at 3 months were obtained using the predictive model and actual value of percentage total weight loss at 3 months. Patients at risk for primary non-response can be determined at 3 months with these values, which can help in considering earlier interventions.

Preoperative Prediction of Body Mass Index of Patients with Type 2 Diabetes at 1 Year After Laparoscopic Sleeve Gastrectomy: Cross-Sectional Study

Background: Very few models predict weight loss among type 2 diabetes mellitus (T2D) patients after laparoscopic sleeve gastrectomy (LSG). This retrospective study undertook such a task. Materials and Methods: We identified all patients >18 years old with T2D who underwent primary LSG at our institution and had complete data. The training set comprised 107 patients operated upon during the period April 2011 to June 2014; the validation set comprised 134 patients operated upon during the successive chronological period, July 2014 to December 2015. Sex, age, presurgery BMI, T2D duration, number of T2D medications, insulin use, hypertension, and dyslipidemia were utilized as independent predictors of 1-year BMI. We employed regression analysis, and assessed the goodness of fit and "Residuals versus Fits" plot. Paired sample t-tests compared the observed and predicted BMI at 1 year. Results: The model comprised preoperative BMI (β = 0.757, P = 0.026) + age (β = 0.142, P < 0.0001) with adjusted R² of 0.581 (P < 0.0001), and goodness of fit showed an unbiased model with accurate prediction. The equation was: BMI value 1 year after LSG = 1.777 + 0.614 × presurgery BMI (kg/m²) +0.106 × age (years). For validation, the equation exhibited an adjusted R² 0.550 (P < 0.0001), and the goodness of fit indicated an unbiased model. The BMI predicted by the model fell within -3.78 BMI points to +2.42 points of the observed 1-year BMI. Pairwise difference between the mean 1-year observed and predicted BMI was not significant (-0.41 kg/m², P = 0.225). Conclusions: This predictive model estimates the BMI 1 year after LSG. The model comprises preoperative BMI and age. It allows the forecast of patients' BMI after surgery, hence setting realistic expectations which are critical for patient satisfaction after bariatric surgery. An attainable target motivates the patient to achieve it.

Role of nutritional ketosis in the improvement of metabolic parameters following bariatric surgery

BACKGROUND

Ketone bodies (KB) might act as potential metabolic modulators besides serving as energy substrates. Bariatric metabolic surgery (BMS) offers a unique opportunity to study nutritional ketosis, as acute postoperative caloric restriction leads to increased lipolysis and circulating free fatty acids.

AIM

To characterize the relationship between KB production, weight loss (WL) and metabolic changes following BMS.

METHODS

For this retrospective study we enrolled male and female subjects aged 18-65 years who underwent BMS at a single Institution. Data on demographics, anthropometrics, body composition, laboratory values and urinary KB were collected.

RESULTS

Thirty-nine patients had data available for analyses [74.4% women, mean age 46.5 ± 9.0 years, median body mass index 41.0 (38.5; 45.4) kg/m², fat mass 45.2% ± 6.2%, 23.1% had diabetes, 43.6% arterial hypertension and 74.4% liver steatosis]. At 46.0 ± 13.6 d post-surgery, subjects had lost 12.0% ± 3.6% of pre-operative weight. Sixty-nine percent developed ketonuria. Those with nutritional ketosis were significantly younger [42.9 (37.6; 50.7) years vs 51.9 (48.3; 59.9) years, P = 0.018], and had significantly lower fasting glucose [89.5 (82.5; 96.3) mg/dL vs 96.0 (91.0; 105.3) mg/dL, P = 0.025] and triglyceride levels [108.0 (84.5; 152.5) mg/dL vs 152.0 (124.0; 186.0) mg/dL, P = 0.045] vs those with ketosis. At 6 mo, percent WL was greater in those with postoperative ketosis (-27.5% ± 5.1% vs 23.8% ± 4.3%, P = 0.035). Urinary KBs correlated with percent WL at 6 and 12 mo. Other metabolic changes were similar.

CONCLUSION

Our data support the hypothesis that subjects with worse metabolic status have reduced ketogenic capacity and, thereby, exhibit a lower WL following BMS.

Development and validation of a scoring system for pre-surgical and early post-surgical prediction of bariatric surgery unsuccess at 2 years

Bariatric surgery (BS) is an effective treatment for morbid obesity. However, a simple and easy-to-use tool for the prediction of BS unsuccess is still lacking. Baseline and follow-up data from 300 consecutive patients who underwent BS were retrospectively collected. Supervised regression and machine-learning techniques were used for model development, in which BS unsuccess at 2 years was defined as a percentage of excess-weight-loss (%EWL) < 50%. Model performances were also assessed considering the percentage of total-weight-loss (%TWL) as the reference parameter. Two scoring systems (NAG-score and ENAG-score) were developed. NAG-score, comprising only pre-surgical data, was structured on a 4.5-point-scale (2 points for neck circumference ≥ 44 cm, 1.5 for age ≥ 50 years, and 1 for fasting glucose ≥ 118 mg/dL). ENAG-score, including also early post-operative data, was structured on a 7-point-scale (3 points for %EWL at 6 months ≤ 45%, 1.5 for neck circumference ≥ 44 cm, 1 for age ≥ 50 years, and 1.5 for fasting glucose ≥ 118 mg/dL). A 3-class-clustering was proposed for clinical application. In conclusion, our study proposed two scoring systems for pre-surgical and early post-surgical prediction of 2-year BS weight-loss, which may be useful to guide the pre-operative assessment, the appropriate balance of patients' expectations, and the post-operative care.

Metabolic and Psychological Features are Associated with Weight Loss 12 Months After Sleeve Gastrectomy

CONTEXT

Laparoscopic sleeve gastrectomy (LSG) is a recognized effective procedure of bariatric surgery, but a poor response in weight loss may still represent a clinical problem. To date there are no validated predictors useful to better perform patient selection.

OBJECTIVE

To establish the association of baseline anthropometric, metabolic, and psychologic features with the percent total weight loss (%TWL) and percent excess weight loss (%EWL) 12 months after surgery.

DESIGN

Retrospective longitudinal analysis of a set of data about obese patients attending the outpatient service of a single obesity center from June 2016 to June 2019.

PATIENTS

A total of 106 obese patients underwent LSG with presurgery evaluation and follow-up at 12 months after surgery.

MAIN OUTCOME

Weight loss 12 months after LSG.

RESULTS

Patients who achieved a %TWL higher than the observed median (≥34%) were younger, with a lower fasting plasma glucose and glycated hemoglobin, with a lower prevalence of hypertension and with a lower score in the impulsiveness scale, compared with patients with a %TWL < 34%. Similar findings were found when %EWL was considered. Multivariable stepwise regression analysis showed that younger age, lower impulsiveness, higher-than-normal urinary free cortisol, and lower HbA1c were associated with higher %TWL, explaining about 31.5% of the weight loss.

CONCLUSION

Metabolic and psychologic features at baseline were independently associated with weight loss and explained a non-negligible effect on the response to LSG. These data suggest that careful metabolic and psychologic profiling could help in sharper indications and personalized pre- and postsurgical follow-up protocols in candidates for LSG.

Weight Regain Outcomes After Bariatric Surgery in the Long-term Follow-up: Role of Preoperative Factors

PURPOSE

Weight regain (WR) compromises the effectiveness of bariatric surgery. The objective of this study was to determine differences in long-term WR prevalence using different definitions and analyze possible preoperative predictors involved.

METHODS

Single-center retrospective cohort study including 445 adults who underwent 3 modalities of bariatric surgery between 2009 and 2014.

EXPOSURE

age, gender, ethnicity, body mass index (BMI), type 2 diabetes (T2D), hypertension (HTN), and type of surgery.

MAIN OUTCOMES

WR at year 6 assessed by 4 definitions and 6 multivariate models based on common thresholds.

RESULTS

Our cohort (71.1% female) had a mean age of 44.78 ± 11.94 years, and mean presurgery BMI of 44.94 ± 6.88 kg/m², with a median follow-up of 6 years (IQR=5-8). The prevalences of T2D and HTN were 36.0% and 46.7% respectively. WR rates over thresholds ranged from 25.4 to 68.1%, with significant differences between groups in the WR measured as the percentage of maximum weight loss (MWL) and the increase in excess weight loss (EWL). Presurgery BMI was a significant predictor in 3 models; restrictive techniques were associated with WR in all the models except for those considering WR over 10 kg and WR over 15% from nadir as dependent variables.

CONCLUSIONS

In this long-term study, WR defined as percentage of MWL and increase in EWL from nadir had the greatest significance in logistic regression models with preoperative BMI and type of surgery as independent variables. These findings could serve to establish a standardized outcome reporting WR in other longitudinal studies.

KEY POINTS

• Lack of standardized outcome to measure weight regain after bariatric surgery. • Lowest rates of weight regain in malabsorptive techniques in all definitions applied. • Weight regain measured as percentage of maximum weight lost.

Is It Possible to Predict Weight Loss After Bariatric Surgery?-External Validation of Predictive Models

Background

Bariatric surgery is the most effective obesity treatment. Weight loss varies among patients, and not everyone achieves desired outcome. Identification of predictive factors for weight loss after bariatric surgery resulted in several prediction tools proposed. We aimed to validate the performance of available prediction models for weight reduction 1 year after surgical treatment.

Materials and Methods

The retrospective analysis included patients after Roux-en-Y gastric bypass (RYGB) or sleeve gastrectomy (SG) who completed 1-year follow-up. Postoperative body mass index (BMI) predicted by 12 models was calculated for each patient. The correlation between predicted and observed BMI was assessed using linear regression. Accuracy was evaluated by squared Pearson’s correlation coefficient (R²). Goodness-of-fit was assessed by standard error of estimate (SE) and paired sample t test between estimated and observed BMI.

Results

Out of 760 patients enrolled, 509 (67.00%) were women with median age 42 years. Of patients, 65.92% underwent SG and 34.08% had RYGB. Median BMI decreased from 45.19 to 32.53kg/m² after 1 year. EWL amounted to 62.97%. All models presented significant relationship between predicted and observed BMI in linear regression (correlation coefficient between 0.29 and 1.22). The best predictive model explained 24% variation of weight reduction (adjusted R²=0.24). Majority of models overestimated outcome with SE 5.03 to 5.13kg/m².

Conclusion

Although predicted BMI had reasonable correlation with observed values, none of evaluated models presented acceptable accuracy. All models tend to overestimate the outcome. Accurate tool for weight loss prediction should be developed to enhance patient’s assessment.

Graphical abstract

Supplementary Information

The online version contains supplementary material available at 10.1007/s11695-021-05341-w.

Type 2 Diabetes and HbA1c Predict All-Cause Post-Metabolic and Bariatric Surgery Hospital Readmission

OBJECTIVE

The main goal of this analysis was to determine whether type 2 diabetes and hemoglobin A1c (HbA1c) predict all-cause 30-day hospital readmission after metabolic and bariatric surgery (MBS). It was hypothesized that a diagnosis of type 2 diabetes or high HbA1c values would predict all-cause hospital readmission rates post MBS.

METHODS

A retrospective analysis from the 2015-2018 Metabolic and Bariatric Surgery Accreditation and Quality Improvement Program (MBSAQIP) cohort was completed (N = 744,776); 30,972 participants were readmitted during the 30 days post MBS.

RESULTS

Mean age of the MBSAQIP sample was 45.1 (11.5) years, and the majority were female (80.7%) and non-Hispanic White (59.4%). The all-cause hospital readmission rate was 4.2% and increased by 10% in those with uncontrolled type 2 diabetes (HbA1c > 7.5% [> 58 mmol/mol]); after adjustment, diabetes was not associated with increased readmission. Uncontrolled type 2 diabetes, type 2 diabetes, and prediabetes resulted in less weight loss 30 days post MBS.

CONCLUSIONS

These results based on a national MBS cohort showed that uncontrolled type 2 diabetes is associated with a greater likelihood of all-cause hospital readmission and reduced weight loss 30 days post MBS. Both type 2 diabetes and prediabetes were also associated with decreased weight loss 30 days post MBS. These findings highlight the need to classify and optimize glycemic control prior to MBS.

Early Weight Loss Following Laparoscopic Sleeve Gastrectomy Is Predictive of Long-Term Weight Loss in Morbidly Obese Chinese

BACKGROUND

Laparoscopic sleeve gastrectomy (LSG) is a bariatric surgical approach often used to treat Chinese individuals suffering from morbid obesity.

OBJECTIVES

To verify the long-term safety and efficiency of LSG and to evaluate the predictive effect of initial weight loss on long-term weight maintenance after LSG in morbidly obese Chinese.

METHODS

Follow-up was conducted by telephone or in hospital. We measured the body mass index (BMI), percentage of total body weight loss (%TWL), and excess weight loss (%EWL), and assessed patients for the alleviation of co-morbidities. Relationships between initial weight loss and successful weight maintenance were assessed via linear regression analyses, while optimal cutoff values were determined based on receiver operative characteristic (ROC) curves.

RESULTS

We included 384 patients in this study. Before surgery, these patients had median weight and BMI values of 110 (91.00-130.75) kg and 38.49 (32.82-44.12) kg/m², respectively. Successful weight loss of > 50% EWL was accomplished in 91.21%, 82.69%, and 79.37% of patients at 1, 3, and 5 years after surgery. In addition, the %EWL at 6 months was significantly correlated with the %EWL up to 5 years (P < 0.001) in morbidly obese Chinese. Based on the ROC curve, the EWL of 56.54% at 6 months was the best predictor of successful weight loss at 5 years (sensitivity 72.38%, specificity 82.69%) in morbidly obese Chinese.

CONCLUSION

LSG has long-term safety and efficacy for morbidly obese Chinese patients. The %EWL at 6 months can be used to predict weight maintenance up to 5 years after LSG.