LSG is mainly achieved by reducing gastric volume. Removing the fundus and creating a greater stomach curvature while maintaining the anatomical structure of the original gastrointestinal tract can alter the levels of some gastrointestinal hormones involved in optimal glucose metabolism and other metabolic indicators in patients with obesity. Weight loss and the improvement of comorbidities is the most important value of LSG [34]. Robert et al. have reported that preoperative FFM could affect weight loss after MBS[17]. However, this study did not compare FFM with other body composition indicators. Therefore, this study aimed to evaluate the predictive value of body composition indicators for LSG efficacy. FMI was determined as a convenient indicator that can accurately predict the effects of weight loss and QoL immediately after LSG. Patients with low FMI had significantly better weight-loss effects and QoL than those with high FMI.
BMI can be used to quickly assess the degree of overweight in patients with obesity. However, patients with similar BMI may not achieve similar weight loss effects owing to factors such as age, sex, and race, which cause differences in body fat and muscle proportions. Compared with traditional BMI, body composition can reflect muscle and fat proportions [25]. Mastino et al. have reported that bariatric surgery was effective in patients with sarcopenia and obesity. However, the effects of weight loss were similar immediately after surgery [35]. Therefore, indicators that can accurately predict early weight loss after bariatric surgery must be identified. Yin et al. have identified low FMI as a valuable predictor of cancer survival [36]. This may be related to the low-fat body composition and high fat metabolism rates in patients with a low FMI. Similarly, these may lead to greater weight loss after LSG. Through univariate and multivariate logistic analyses, we found that preoperative weight and low-FMI were two independent positive influencing factors influencing EEWL. Moreover, the interaction analysis showed that lower preoperative weight and low-FMI exhibited an interaction. For patients with a low-FMI, each kilogram of weight reduction in weight was associated with a 0.023-fold increase in the probability of achieving EEWL. In clinical practice, we should combine low-FMI and weight to evaluate the weight loss effect of patients who undergo LSG in order to make the appropriate clinical decisions. FMI also performed well in predicting the resolution of some comorbidities, such as hyperuricemia and hyperglycemia. Owing to our small sample size and differences from the Western population, patients who underwent LSG in China had fewer comorbidities, which may explain why why the improvement of most comorbidities did not differ between the two groups. We further developed radar charts to reveal the improvements in comorbidities (eFigure 5.). The results showed that although there was no statistically significant difference in the improvement of most comorbidities between the two groups early after LSG, the low-FMI group still had a better trend in the improvement of comorbidities. This study spanned a long time (2014–2022), and the number of our patients demonstrated a ramping up trend. Most of the patients included in this study were concentrated in the past three years, especially in 2022. Considering the relatively long duration of the research, there may be inevitable biases. However, the ROC analysis showed that FMI had similar performance in achieving EEWL in patients early in the study and in the past three years. Overall, this study compared multiple widely used body component indicators and found that FMI performed well in predicting early weight loss and QoL after LSG, which was valuable for guiding clinical decision-making and follow-up.
Additionally, the complication outcomes and QoL after LSG are important for bariatric surgeons. Ursula et al. have reported that a high FMI significantly increased the length of hospital stay [37]. This may have been attributable to the surplus body fat content. Severe nutritional risks increase the incidence of obesity, comorbidities, and complications during hospitalization. In this study, patients with a low FMI performed better than those with a high FMI in terms of postoperative hospital stay and EW, QoL, and BAROS scores, indicating a better weight loss effect and QoL. This may be due to the lower body fat content in these patients. The surgeon could dissect more accurately during surgery, making it less likely to cause damage, thereby improving the quality of the surgery and achieving better weight loss and QoL. Similarly, compared to patients with a high FMI, those with a low FMI had a lower nutritional risk, which reduces the risk of postoperative complications. This may be related to a shorter postoperative hospital stay and better fat metabolism levels in patients with a low FMI after surgery. Thus, patients with a low FMI recovered better in multiple aspects after LSG than those with a high FMI. This also suggests that for patients with a high FMI, postoperative attention, rehabilitation guidance, and follow-up work should be strengthened so that more patients can achieve EEWL and obtain better postoperative QoL.
This study had some limitations. Firstly, this was a retrospective eastern small-sample study with a short-term follow-up that explored the relationship between body composition indicators and EEWL for the first time. Hence, bias may have been inevitable. We will conduct relevant prospective studies with larger sample sizes, multiple centers and long-term follow-ups to further explore the relationship between body composition indicators and EEWL. Secondly, the calculation of FMI was based on abodominal CT scan before surgery, which increases the complexity of the evaluation to a certain extent. But due to the value of FMI in predicting weight loss effect and QoL early after LSG, we think it still worthed to be included in the evolution system of LSG. Thirdly, for most patients, we did not routinely perform abdominal CT scans to measure body composition indicators after surgery. We will conduct relevant research in the future to explore the impact of postoperative body composition indicators on the weight loss effect of LSG. Forthly, The average age of patients included in this study was 29.7 ± 7.6 years old, which is similar to the average age of patients studied in other Chinese centers [38, 39]. Meanwhile, in the classic study of The SLEEVEPASS Randomized Clinical Trial in a Western center, the average age of patients underwent LSG was 48.5 ± 9.6 years old [2, 3, 4]. As you mentioned, Our patients were significantly younger than the patients in North American or European centers. This may be because of the higher acceptance of MBS among young Chinese patients. Therefore, lower in our center than in North American or European centers. We will further validating the application of FMI in older patients using international multicenter data. Lastly, total weight loss (%TWL) and %EWL are frequently used metrics to assess the effectiveness of weight loss following LSG. %TWL is a more objective and less biased measure for evaluating weight loss outcomes. However, as the most commonly used metric for evaluating weight loss outcomes, %EWL also has its advantages. So far, many important studies had used %EWL as the main indicator to evaluate weight loss effectiveness, including the renowned randomized controlled trial research in the field of weight loss metabolic surgery (the SLEEVEPASS Randomized Clinical Trial) [1–6]. Existing guidelines also recognize the use of %EWL for evaluating weight loss outcomes [40]. Additionally, the BAROS also used %EWL as the standard for evaluating weight loss point [31]. Due to the higher acceptance of LSG among Chinese patients, the preoperative BMI of Chinese patients who underwent LSG was lower than western patients. Many of them could achieve ideal BMI after surgery. Therefore, this study selected% EWL as the indicator to evaluate the weight loss effect after LSG. In the future, we hope to conduct research to explore which indicator is more suitable for low BMI patients receiving LSG in Chinese centers. Nevertheless, this study obtained different body composition indicators through widely-used and convenient CT images and compared their predictive performance for weight loss and quality of life early after LSG. To the best of our knowledge, this is the first study to discover the predictive value of FMI in this area, which supplements existing indicators and provide additional references for decision-making around clinical treatment.