Abstract
Introduction
The objectives of this study were to examine temporal trends in the incidence of bariatric surgery (Roux-en-Y gastric bypass (RYGB) and sleeve gastrectomy (SG)) in patients with and without type 2 diabetes mellitus (T2DM). Outcomes of hospitalization and the impact of T2DM on these outcomes were also analyzed.
Research design and methods
We performed an observational study with the Spanish national hospital discharge database. Obese patients with and without T2DM who underwent RYGB and SG between 2016 and 2022 were identified. Propensity score matching (PSM) and logistic regression were used to compare patients with and without T2DM and to evaluate the effect of T2DM and other variables on outcomes of surgery. A variable “severity” was created to cover patients who died in hospital or were admitted to the intensive care unit (ICU).
Results
A total of 32,176 bariatric surgery interventions were performed (28.86% with T2DM). 31.57% of RYGBs and 25.53% of SG patients had T2DM. The incidence of RYGB and SG increased significantly between 2016 and 2022 (p<0.001), with a higher incidence in those with T2DM than in those without (incidence rate ratio 4.07 (95% CI 3.95 to 4.20) for RYGB and 3.02 (95% CI 2.92 to 3.14) for SG). In patients who underwent SG, admission to the ICU and severity were significantly more frequent in patients with T2DM than in those without (both p<0.001). In the multivariate analysis, having T2DM was associated with more frequent severity in those who received SG (OR 1.23; 95% CI 1.07 to 1.42).
Conclusions
Between 2016 and 2022, bariatric surgery procedures performed in Spain increased in patients with and without T2DM. More interventions were performed on patients with T2DM than on patients without T2DM. RYGB was the most common procedure in patients with T2DM. The presence of T2DM was associated with more severity after SG.
Keywords: Bariatric Surgery, Type 2 Diabetes, Incidence, Obesity
WHAT IS ALREADY KNOWN ON THIS TOPIC.
WHAT THIS STUDY ADDS
Between 2016 and 2022, bariatric surgery procedures performed in Spain increased in patients with and without T2DM.
More interventions were performed on patients with T2DM than on patients without T2DM.
Among patients who underwent SG, those with T2DM more frequently experienced a severe postoperative course compared with subjects without T2DM.
HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICY
More resources must be planned to face a possible increase in bariatric surgery in Spain.
The greater use of Roux-en-Y gastric bypass (RYGB) among patients with T2DM overtime must be confirmed and the long-time outcomes of this procedure assessed.
Reasons for sex differences in the use of RYGB and sleeve gastrectomy procedures, regardless of diabetes status, should be investigated.
Introduction
In recent decades, the prevalence of both type 2 diabetes mellitus (T2DM) and obesity has increased progressively.1 This common epidemiological trend has also been reflected in the increase in shared risk factors and has accelerated the clinical course of these diseases.2
The key components of contemporary management of chronic metabolic diseases are lifestyle interventions, pharmacotherapy and metabolic-bariatric surgery. In 2009, the American Diabetes Association included metabolic-bariatric surgery for obesity-associated T2DM in its T2DM treatment guidelines.3 Since then, it has been reported that metabolic-bariatric surgery improves glycemic control and achieves higher rates of remission of T2DM than pharmacological treatment. Findings from numerous controlled clinical trials indicate that metabolic-bariatric interventions show significant efficacy in inducing remission of T2DM. The remission rate 2 years after surgery was reported to be 85%, declining to 50% at the 5-year mark, yet surpassing remission rates observed in the pharmacotherapy group. Remarkably, even at the 10-year follow-up, a substantial proportion of treated patients (37.5%) remained in remission.4,6 Furthermore, bariatric surgery has been linked to a decrease in the occurrence of cardiovascular disease, macrovascular and microvascular complications, and mortality rates in individuals diagnosed with T2DM.7
The most common bariatric surgery techniques are sleeve gastrectomy (SG) and Roux-en-Y gastric bypass (RYGB).8 The use of these techniques has changed over time. Data from the International Federation for the Surgery of Obesity and Metabolic Disorders (IFSO) indicate that SG is currently the most frequently conducted procedure, accounting for 58.2% of cases, followed by RYGB in 26.4% of cases.9 However, a recent study conducted in the UK found that RYGB is used more frequently than SG in patients with T2DM (OR 1.55; 95% CI 1.46 to 1.67).10
In Spain, a study conducted between 2000 and 2014 by the Obesity Group of the Spanish Society of Endocrinology and Nutrition found a progressive decrease in the use of RYGB, associated with a parallel increase in SG.11 Data from a previous Spanish study performed between 2001 and 2010 in patients with and without T2DM showed changes in the use of the various techniques, with a decrease in the use of open RYGB and open gastroplasty and an increase in the use of laparoscopic RYGB and laparoscopic gastroplasty since 2006.12 Nevertheless, despite consensus on the clinical indications for surgery,13 further data are required on the use of bariatric surgery in Spain, trends in the clinical characteristics and hospital outcomes of patients undergoing the procedures, and the effect of COVID-19 on their use in clinical practice.
In light of these data, the aims of our study were as follows: (1) to evaluate temporal trends in incidence, clinical characteristics, complications, and hospital outcomes in patients with and without TDM2 undergoing bariatric surgery in Spain between 2016 and 2022; (2) to compare outcomes of hospitalization between patients with and without TDM2 using propensity score matching (PSM); and (3) to identify the variables associated with poorer clinical outcome among patients with and without TDM2 and to determine the influence of TDM2 on this outcome.
Methods
Study design
We performed a descriptive observational study based on the analysis of a national hospital discharge registry.
Setting and participants
The data source was the Spanish National Hospital Discharge Database (RAE-CMBD, Specialized Care Activity Registry–Minimum Basic Data Set). The RAE-CMBD collects individualized information on all patients admitted to Spanish public hospitals including sex, age, admission and discharge date, the main diagnosis and a maximum of 20 secondary diagnoses, up to 20 procedures (therapeutic or diagnostic), and discharge destination (discharge, transfer to another health center, and death during admission).14 The RAE-CMBD encodes all this information using the International Classification of Diseases, 10th Revision (ICD-10).
The study period ranged from January 1, 2016 to December 31, 2022. The study population comprised patients with an ICD-10 code for obesity, age ≥35 years, and a code corresponding to a surgical intervention (RYGB or SG) at any position in the procedure fields of the RAE-CMBD. Subsequently, patients with and without T2DM were stratified according to the presence of T2DM at any position in the diagnostic field of the RAE-CMBD.
Patients with T1DM (type 1 diabetes mellitus) codes, patients with abdominal neoplasia, and patients with a lack of data for essential variables (age, sex, date of admission and discharge, and discharge destination) were excluded. Likewise, all patients who underwent laparoscopic gastrectomy were excluded. The ICD-10 codes used to select the study population are shown in online supplemental table 1.
Study variables
The main study variables were the annual incidence of SG and RYGB surgeries stratified by T2DM and the outcome of hospitalization measured in terms of in-hospital mortality (IHM), mean length of hospital stay (LOHS), and the need for admission to the intensive care unit (ICU). A variable “severity” was created to cover patients who died in the hospital or were admitted to the ICU.
The study covariates collected for patients undergoing bariatric surgery were age, sex, and date of surgery. Comorbidity was measured using the diseases included in the Charlson Comorbidity Index (CCI), excluding diabetes. These diseases were identified following the methodology described by Sundararajan et al.15 In addition, the CCI was analyzed as a continuous variable, categorized as CCI=0, CCI=1, and CCI≥2.
Other diseases included asthma, depression, obstructive sleep apnea (OSA), dyslipidemia, hypertension, and COVID-19. Complications of bariatric surgery were also recorded, including gastroesophageal reflux disease (GERD), pulmonary embolism, bowel obstruction, bleeding, sepsis, surgical site infection, and pneumonia.
Invasive mechanical ventilation and non-invasive mechanical ventilation were assessed without considering the positioning of the procedures in the RAE-CMBD. ICD-10 codes for comorbidities, complications, and procedures are shown in online supplemental table 1.
Propensity score matching
A PSM analysis was carried out by pairing each patient bearing a T2DM code with another patient who underwent the same surgery but lacked a T2DM code and whose propensity score, derived from multivariate logistic regression, was identical or closely matched. The calculation of the propensity score involved applying matching conditions such as the year of hospitalization, sex, age, and all comorbidities present on admission.16 The selected matching method was a one-to-one approach using calipers with a width ≤0.2 of the SD of the logit of the PS. The quality of the PSM process was assessed by estimating the absolute standardized difference before and after matching.16 Populations are deemed well balanced when the absolute standardized differences are <10% post-PSM. A love plot was created to visually represent how populations become significantly more comparable after PSM.17
Statistical analysis
We calculated the incidence of SG and RYGB per 100,000 inhabitants with T2DM and patients without T2DM for each of the 7 years under analysis. Population data for the years 2016–2022 were sourced from the Spanish National Institute of Statistics.18 To estimate the population with and without T2DM, we used diabetes prevalence data from the National Health Surveys conducted in Spain in 2016 and 2020, as previously described.12 19 20
Incidence rate ratios (IRRs), along with their corresponding 95% CI, were computed using Poisson regression models. These models were used to compare the age-adjusted and sex-adjusted incidence rates of SG and RYGB between individuals with and without T2DM, as well as among patients with T2DM stratified by sex.
The findings from the descriptive analysis were presented as frequencies and percentages in the case of categorical variables, and as either mean and SD or median and IQR in the case of quantitative variables.
The time trend was evaluated using the Cochran-Mantel-Haenszel statistic. Fisher’s exact test was used to compare categorical variables, while the t-test or Mann-Whitney test was used as necessary to compare continuous variables.
A multivariate logistic regression model was used to detect variables linked with severity among patients undergoing RYGB and SG, taking into account the presence of T2DM. These models included sex, age, year of hospital admission, and comorbidities present at admission as covariates. The outcomes of these models are depicted in the form of ORs alongside their respective 95% CIs.
The statistical analysis was performed using Stata V.14 (Stata, College Station, Texas, USA).
Ethical aspects
The RAE-CMBD database is managed by the Spanish Ministry of Health and is accessible free of charge on request.21 Given the administrative and anonymous nature of the registry, and, in accordance with Spanish Law, individual written consent of subjects is not required on admission to the hospital. Similarly, the approval of an ethics committee is not required.
Results
A total of 32,176 bariatric procedures were performed on obese patients aged ≥35 years in Spain between 2016 and 2022. RYGB accounted for 55.52% (n=17,867) and SG for 44.48% (n=14,309). A total of 9287 patients had been diagnosed with T2DM (28.86%). By type of surgery, T2DM was coded in 31.57% of RYGBs (5643/17,876) and 25.53% of SGs (3653/14,309).
Trends in hospitalization and incidence for patients who underwent RYGB and SG
Between 2016 and 2022, RYGB surgeries increased significantly (p<0.05), and those for SG decreased significantly (p<0.05) among men and women with T2DM, as shown in table 1. In men without diabetes, the frequency of hospitalization for SG increased, whereas that for RYGB decreased; in women without diabetes, the frequency of RYGB increased and that of SG decreased (all p<0.05) (table 1).
Table 1. Trends in number of Roux-en-Y gastric bypass and sleeve gastrectomy procedures for patients with and without T2DM according to sex in Spain from year 2016 to 2022.
| 2016 | 2017 | 2018 | 2019 | 2020 | 2021 | 2022 | Total | ||
|---|---|---|---|---|---|---|---|---|---|
| T2DM | |||||||||
| Roux-en-Y gastric bypass | Both sex, n (%)* | 611 (56.47) | 740 (58.64) | 857 (60.82) | 938 (58.77) | 595 (59.98) | 817 (62.75) | 1076 (65.45) | 5634 (60.67) |
| Men, n (%)* | 243 (53.88) | 250 (55.43) | 316 (61.72) | 371 (59.08) | 207 (58.64) | 293 (59.07) | 411 (64.52) | 2091 (59.27) | |
| Women, n (%)* | 368 (58.32) | 490 (60.42) | 541 (60.31) | 567 (58.57) | 388 (60.72) | 524 (65.01) | 665 (66.04) | 3543 (61.52) | |
| Sleeve gastrectomy | Both sex, n (%)* | 471 (43.53) | 522 (41.36) | 552 (39.18) | 658 (41.23) | 397 (40.02) | 485 (37.25) | 568 (34.55) | 3653 (39.33) |
| Men, n (%)* | 208 (46.12) | 201 (44.57) | 196 (38.28) | 257 (40.92) | 146 (41.36) | 203 (40.93) | 226 (35.48) | 1437 (40.73) | |
| Women, n (%)* | 263 (41.68) | 321 (39.58) | 356 (39.69) | 401 (41.43) | 251 (39.28) | 282 (34.99) | 342 (33.96) | 2216 (38.48) | |
| Non-T2DM | |||||||||
| Roux-en-Y gastric bypass | Both sex, n (%)* | 1373 (55.43) | 1637 (52.32) | 1816 (51.99) | 2062 (52.91) | 1297 (52.9) | 1795 (54.1) | 2253 (54.64) | 12,233 (53.44) |
| Men, n (%)* | 400 (55.4) | 379 (46.73) | 465 (48.84) | 483 (47.92) | 316 (50.08) | 415 (49.94) | 520 (48.69) | 2978 (49.44) | |
| Women, n (%)* | 973 (55.44) | 1258 (54.27) | 1351 (53.17) | 1579 (54.66) | 981 (53.87) | 1380 (55.49) | 1733 (56.73) | 9255 (54.87) | |
| Sleeve gastrectomy | Both sex, n(%)* | 1104 (44.57) | 1492 (47.68) | 1677 (48.01) | 1835 (47.09) | 1155 (47.1) | 1523 (45.9) | 1870 (45.36) | 10,656 (46.56) |
| Men, n (%)* | 322 (44.6) | 432 (53.27) | 487 (51.16) | 525 (52.08) | 315 (49.92) | 416 (50.06) | 548 (51.31) | 3045 (50.56) | |
| Women, n (%)* | 782 (44.56) | 1060 (45.73) | 1190 (46.83) | 1310 (45.34) | 840 (46.13) | 1107 (44.51) | 1322 (43.27) | 7611 (45.13) | |
P value <0.05 for time trend from 2016 to 2022
T2DM, type 2 diabetes mellitus.
For both types of surgery and both sexes, the number of interventions decreased considerably in 2020 and then recovered in subsequent years.
Analysis of changes in the incidence of bariatric surgery revealed that the frequency of both RYGB and SG in patients with and without T2DM increased between 2016 and 2022 (p<0.001) (figure 1). The incidence in both procedures in 2020 decreased to values lower than in 2016 in patients with and without T2DM.
Figure 1. Changes in Roux-en-Y gastric bypass (RYGB) and sleeve gastrectomy (SG) procedures. Annual incidence rates in patients with and without type 2 diabetes expressed per 100,000 inhabitants (Spain, 2016–2022). *p<0.05 (Poisson regression analysis). T2DM, type 2 diabetes mellitus.
The incidence of bariatric surgery was significantly higher in patients with T2DM than in those without T2DM for all the years analyzed (p<0.001) (figure 1). The Poisson regression–based age-adjusted and sex-adjusted IRR was 4.07 (95% CI 3.95 to 4.20) for RYGB in people with T2DM compared with those without and 3.02 (95% CI 2.92 to 3.14) for SG.
When patients with T2DM were stratified by sex, the incidence of bariatric surgery was higher in women than in men (IRR 1.89, 95% CI 1.79 to 2.00 for RYGB and IRR 1.72; 95% CI 1.61 to 1.84 for SG). These higher incidence figures in women were also observed in patients without diabetes (IRR 2.81, 95% CI 2.69 to 2.93 for RYGB and IRR 2.26; 95% CI 2.17 to 2.36 for SG).
By type of bariatric surgery, the incidence of RYGB was higher than that of SG in patients with T2DM (26.68 vs 17.30 per 100,000 inhabitants with T2DM) and in those without diabetes (6.56 and 5.72 per 100,000 inhabitants without diabetes, respectively).
Clinical characteristics and hospital outcomes for patients who underwent RYGB
As can be seen in table 2, among the patients who underwent RYGB, women accounted for 62.89% of those with T2DM and 75.66% of those without diabetes (p<0.001). Prior to PSM, mean age was significantly higher among patients with T2DM than in those without diabetes (51.87 years vs 48.56 years; p<0.001), and patients with T2DM also had a higher mean CCI (0.49 vs 0.37; p<0.001) and more specific chronic conditions (eg, congestive heart failure, myocardial infarction, peripheral vascular disease, liver disease, kidney disease, dyslipidemia, hypertension, and OSA).
Table 2. Comparison of characteristic, comorbidities, bariatric complications and hospital outcomes among patients with and without T2DM who underwent a Roux-en-Y gastric bypass in Spain from 2016 to 2022, before and after PSM.
| Before PSM | After PSM | |||||
|---|---|---|---|---|---|---|
| T2DM | Non-T2DM | P value | T2DM | Non-T2DM | P value | |
| N | 5634 | 12,233 | NA | 5634 | 5634 | NA |
| Age, mean (SD) | 51.87 (7.58) | 48.56 (7.83) | <0.001 | 51.87 (7.58) | 51.46 (7.65) | 0.004 |
| 35–49 years, n (%) | 2084 (36.99) | 6884 (56.27) | <0.001 | 2084 (36.99) | 2259 (40.1) | 0.002 |
| 50–59 years, n (%) | 2623 (46.56) | 4190 (34.25) | 2623 (46.56) | 2533 (44.96) | ||
| ≥60 years, n (%) | 927 (16.45) | 1159 (9.47) | 927 (16.45) | 842 (14.94) | ||
| Women, n (%) | 3543 (62.89) | 9255 (75.66) | <0.001 | 3543 (62.89) | 3756 (66.67) | <0.001 |
| CCI, mean (SD) | 0.49 (0.64) | 0.37 (0.57) | <0.001 | 0.49 (0.64) | 0.47 (0.61) | 0.070 |
| CCI=0, n (%) | 3289 (58.38) | 8224 (67.23) | <0.001 | 3289 (58.38) | 3327 (59.05) | 0.008 |
| CCI=1, n (%) | 1962 (34.82) | 3512 (28.71) | 1962 (34.82) | 2003 (35.55) | ||
| CCI≥2, n (%) | 383 (6.8) | 497 (4.06) | 383 (6.8) | 304 (5.4) | ||
| Myocardial infarction, n (%) | 109 (1.93) | 79 (0.65) | <0.001 | 109 (1.93) | 69 (1.22) | 0.003 |
| Congestive heart failure, n (%) | 80 (1.42) | 50 (0.41) | <0.001 | 80 (1.42) | 44 (0.78) | 0.001 |
| Peripheral vascular disease, n (%) | 56 (0.99) | 39 (0.32) | <0.001 | 56 (0.99) | 32 (0.57) | 0.01 |
| Cerebrovascular disease, n (%) | 20 (0.35) | 28 (0.23) | 0.130 | 20 (0.35) | 20 (0.35) | 1.000 |
| Dementia, n (%) | 3 (0.05) | 1 (0.01) | 0.061 | 3 (0.05) | 1 (0.02) | 0.317 |
| Chronic respiratory disease, n (%) | 603 (10.7) | 1256 (10.27) | 0.376 | 603 (10.7) | 620(11) | 0.607 |
| Rheumatoid disease, n (%) | 33 (0.59) | 98 (0.8) | 0.117 | 33 (0.59) | 32 (0.57) | 0.901 |
| Peptic ulcer, n (%) | 26 (0.46) | 39 (0.32) | 0.141 | 26 (0.46) | 17 (0.3) | 0.169 |
| Mild/moderate/severe liver disease, n (%) | 1685 (29.91) | 2835 (23.18) | <0.001 | 1685 (29.91) | 1707 (30.3) | 0.651 |
| Hemiplegia or paraplegia, n (%) | 4 (0.07) | 19 (0.16) | 0.144 | 4 (0.07) | 6 (0.11) | 0.527 |
| Renal disease, n (%) | 131 (2.33) | 94 (0.77) | <0.001 | 131 (2.33) | 82 (1.46) | 0.001 |
| Cancer and metastatic cancer, n (%) | 0 (0) | 0 (0) | 1 | 0 (0) | 0 (0) | 1 |
| AIDS, n (%) | 3 (0.05) | 3 (0.02) | 0.330 | 3 (0.05) | 3 (0.05) | 1 |
| Asthma, n (%) | 413 (7.33) | 1028 (8.4) | 0.014 | 413 (7.33) | 468 (8.31) | 0.054 |
| Depression, n (%) | 313 (5.56) | 680 (5.56) | 0.993 | 313 (5.56) | 321 (5.7) | 0.744 |
| GERD, n (%) | 560 (9.94) | 1637 (13.38) | <0.001 | 560 (9.94) | 578 (10.26) | 0.574 |
| Dyslipidemia, n (%) | 2244 (39.83) | 1923 (15.72) | <0.001 | 2244 (39.83) | 1766 (31.35) | <0.001 |
| Hypertension, n (%) | 3539 (62.82) | 4366 (35.69) | <0.001 | 3539 (62.82) | 3537 (62.78) | 0.969 |
| OSA, n (%) | 2543 (45.14) | 3965 (32.41) | <0.001 | 2543 (45.14) | 2521 (44.75) | 0.677 |
| Pulmonary embolism, n (%) | 2 (0.04) | 5 (0.04) | 0.866 | 2 (0.04) | 3 (0.05) | 0.655 |
| Bowel obstruction, n (%) | 11 (0.2) | 35 (0.29) | 0.265 | 11 (0.2) | 18 (0.32) | 0.193 |
| Bleeding, n (%) | 0 (0) | 2 (0.02) | 0.337 | 0 (0) | 1 (0.02) | 0.317 |
| Sepsis, n (%) | 7 (0.12) | 52 (0.43) | 0.001 | 7 (0.12) | 23 (0.41) | 0.003 |
| Postoperative surgical site infection, n (%) | 34 (0.6) | 88 (0.72) | 0.382 | 34 (0.6) | 43 (0.76) | 0.303 |
| Pneumonia, n (%) | 10 (0.18) | 18 (0.15) | 0.634 | 10 (0.18) | 9 (0.16) | 0.818 |
| COVID-19, n (%) | 1 (0.02) | 8 (0.07) | 0.187 | 1 (0.02) | 3 (0.05) | 0.317 |
| Invasive mechanical ventilation, n (%) | 33 (0.59) | 69 (0.56) | 0.858 | 33 (0.59) | 33 (0.59) | 1.000 |
| Non-invasive mechanical ventilation, n (%) | 26 (0.46) | 59 (0.48) | 0.851 | 26 (0.46) | 39 (0.69) | 0.106 |
| ICU admission, n (%) | 534 (9.48) | 1138 (9.3) | 0.708 | 534 (9.48) | 585 (10.38) | 0.108 |
| Severity, n (%) | 538 (9.55) | 1143 (9.34) | 0.662 | 538 (9.55) | 589 (10.45) | 0.109 |
| IHM, n (%) | 4 (0.07) | 12 (0.1) | 0.574 | 4 (0.07) | 6 (0.11) | 0.527 |
| LOHS, median (IQR) | 3 (2) | 3 (2) | 0.761 | 3 (2) | 3 (3) | 0.141 |
CCI, Charlson Comorbidity Index; GORD, gastroesophageal reflux disease; IHM, in-hospital mortality; OSA, obstructive sleep apnea; PSM, propensity score matching; T2DM, type 2 diabetes mellitus.
Compared with patients with T2DM, patients without diabetes more frequently had GERD (13.38% vs 9.94; p<0.001) and sepsis (0.43% vs 0.12; p<0.001) during admission. The median LOHS was equal irrespective of the T2DM status (3 days). The crude IHM was 0.07% for patients with T2DM and 0.1% for patients without (p=0.574). Severity was 9.55% in patients with T2DM and 9.34% in patients without T2DM (p=0.662).
After PSM, sepsis remained more frequent among patients without T2DM, and IHM and severity became similar in both groups (table 2).
The love plot (online supplemental figure 1) shows that PSM resulted in a good fit for the two populations compared.
Clinical characteristics and hospital outcomes for patients who underwent SG
As in patients undergoing RYGB, significant differences were recorded before PSM between patients with T2DM and without T2DM undergoing SG in sex distribution (60.66% vs 71.42%; p<0.001), mean age (52.59 years vs 48.78 years; p<0.001), and CCI (0.57 vs 0.4 p<0.001). The most prevalent comorbidities among patients with and without T2DM were similar to those described in patients who underwent RYGB.
No significant differences in the prevalence of complications after SG were found between the two groups (table 3).
Table 3. Comparison of characteristic, comorbidities, bariatric complications and hospital outcomes among patients with and without T2DM who underwent sleeve gastrectomy in Spain from 2016 to 2022, before and after PSM.
| Before PSM | After PSM | |||||
|---|---|---|---|---|---|---|
| T2DM | Non-T2DM | P value | T2DM | Non-T2DM | P value | |
| N | 3653 | 10 656 | NA | 3653 | 3653 | NA |
| Age, mean (SD) | 52.59 (7.91) | 48.78 (8.22) | <0.001 | 52.59 (7.91) | 52.41 (8.02) | 0.334 |
| 35–49 years, n (%) | 1272 (34.82) | 5864 (55.03) | <0.001 | 1272 (34.82) | 1329 (36.38) | 0.365 |
| 50–59 years, n (%) | 1596 (43.69) | 3535 (33.17) | 1596 (43.69) | 1549 (42.4) | ||
| ≥60 years, n (%) | 785 (21.49) | 1257 (11.8) | 785 (21.49) | 775 (21.22) | ||
| Women, n (%) | 2216 (60.66) | 7611 (71.42) | <0.001 | 2216 (60.66) | 2288 (62.63) | 0.083 |
| CCI, mean (SD) | 0.57 (0.69) | 0.4 (0.59) | <0.001 | 0.57 (0.69) | 0.52 (0.65) | 0.005 |
| CCI=0, n (%) | 1272 (34.82) | 5864 (55.03) | <0.001 | 1949 (53.35) | 2032 (55.63) | 0.012 |
| CCI=1, n (%) | 1596 (43.69) | 3535 (33.17) | 1385 (37.91) | 1365 (37.37) | ||
| CCI≥2, n (%) | 785 (21.49) | 1257 (11.8) | 319 (8.73) | 256 (7.01) | ||
| Myocardial infarction, n (%) | 73(2) | 86 (0.81) | <0.001 | 73(2) | 58 (1.59) | 0.186 |
| Congestive heart failure, n (%) | 72 (1.97) | 106 (0.99) | <0.001 | 72 (1.97) | 53 (1.45) | 0.087 |
| Peripheral vascular disease, n (%) | 52 (1.42) | 54 (0.51) | <0.001 | 52 (1.42) | 33 (0.9) | 0.038 |
| Cerebrovascular disease, n (%) | 16 (0.44) | 30 (0.28) | 0.149 | 16 (0.44) | 14 (0.38) | 0.714 |
| Dementia, n (%) | 0 (0) | 0 (0) | 1 | 0 (0) | 0 (0) | 1 |
| Chronic respiratory disease, n (%) | 452 (12.37) | 1089 (10.22) | <0.001 | 452 (12.37) | 388 (10.62) | 0.019 |
| Rheumatoid disease, n (%) | 37 (1.01) | 103 (0.97) | 0.806 | 37 (1.01) | 27 (0.74) | 0.209 |
| Peptic ulcer, n (%) | 10 (0.27) | 38 (0.36) | 0.455 | 10 (0.27) | 5 (0.14) | 0.196 |
| Mild/moderate/severe liver disease, n (%) | 1172 (32.08) | 2560 (24.02) | <0.001 | 1172 (32.08) | 1190 (32.58) | 0.653 |
| Hemiplegia or paraplegia, n (%) | 6 (0.16) | 11 (0.1) | 0.356 | 6 (0.16) | 5 (0.14) | 0.763 |
| Renal disease, n (%) | 175 (4.79) | 150 (1.41) | <0.001 | 175 (4.79) | 131 (3.59) | 0.010 |
| Cancer and metastatic cancer, n (%) | 0 (0) | 0 (0) | 1 | 0 (0) | 0 (0) | 1 |
| AIDS, n (%) | 4 (0.11) | 12 (0.11) | 0.961 | 4 (0.11) | 3 (0.08) | 0.705 |
| Asthma, n (%) | 273 (7.47) | 844 (7.92) | 0.385 | 273 (7.47) | 254 (6.95) | 0.390 |
| Depression, n (%) | 215 (5.89) | 578 (5.42) | 0.293 | 215 (5.89) | 199 (5.45) | 0.418 |
| GERD, n (%) | 171 (4.68) | 511 (4.8) | 0.780 | 171 (4.68) | 158 (4.33) | 0.463 |
| Dyslipidemia, n (%) | 1426 (39.04) | 1716 (16.1) | <0.001 | 1426 (39.04) | 1351 (36.98) | 0.071 |
| Hypertension, n (%) | 2319 (63.48) | 3964 (37.2) | <0.001 | 2319 (63.48) | 2411(66) | 0.024 |
| OSA, n (%) | 1724 (47.19) | 3774 (35.42) | <0.001 | 1724 (47.19) | 1736 (47.52) | 0.779 |
| Pulmonary embolism, n (%) | 1 (0.03) | 3 (0.03) | 0.981 | 1 (0.03) | 1 (0.03) | 1 |
| Bowel obstruction, n (%) | 3 (0.08) | 8 (0.08) | 0.894 | 3 (0.08) | 3 (0.08) | 1 |
| Bleeding, n (%) | 1 (0.03) | 1 (0.01) | 0.427 | 1 (0.03) | 0 (0) | 0.317 |
| Sepsis, n (%) | 4 (0.11) | 20 (0.19) | 0.319 | 4 (0.11) | 5 (0.14) | 0.739 |
| Postoperative surgical site infection, n (%) | 13 (0.36) | 53 (0.5) | 0.276 | 13 (0.36) | 17 (0.47) | 0.464 |
| Pneumonia, n (%) | 8 (0.22) | 13 (0.12) | 0.186 | 8 (0.22) | 4 (0.11) | 0.248 |
| COVID-19, n(%) | 0 (0) | 5 (0.05) | 0.190 | 0 (0) | 1 (0.03) | 0.317 |
| Invasive mechanical ventilation, n (%) | 15 (0.41) | 30 (0.28) | 0.229 | 15 (0.41) | 11 (0.3) | 0.432 |
| Non-invasive mechanical ventilation, n (%) | 19 (0.52) | 56 (0.53) | 0.969 | 19 (0.52) | 24 (0.66) | 0.444 |
| ICU admission, n (%) | 492 (13.47) | 1146 (10.75) | <0.001 | 492 (13.47) | 437 (11.96) | 0.053 |
| Severity, n (%) | 492 (13.47) | 1147 (10.76) | <0.001 | 492 (13.47) | 437 (11.96) | 0.053 |
| IHM, n (%) | 3 (0.08) | 9 (0.08) | 0.966 | 3 (0.08) | 3 (0.08) | 1.000 |
| LOHS, median (IQR) | 3 (2) | 3 (2) | 0.084 | 3 (2) | 3 (2) | 0.174 |
GORD, gastroesophageal reflux disease; ICU, intensive care unit; IHM, in-hospital mortality; LOHS, length of hospital stay; OSA, obstructive sleep apnea; PSM, propensity score matching; T2DM, type 2 diabetes mellitus.
LOHS (3 days) and crude IHM (0.08%) were identical irrespective of the presence of T2DM. However, the crude values for admission to ICU and severity were significantly higher in patients with T2DM (both p<0.001).
After adjustment with PSM, all variables with significant differences between patients with and without T2DM ceased to be significant (table 3). The love plot after the PSM is shown in online supplemental figure 2.
Variables associated with severity in patients with and without T2DM who underwent RYGB and SG: multivariable analysis
Female sex was associated with less severe disease only in patients without T2DM who underwent RYGB and SG. Furthermore, disease was significantly less severe during the period 2018–2022 than in 2016 for both surgeries in both sexes irrespective of diabetes status.
In patients with T2DM who underwent both RYGB and SG, multivariable adjustment showed that severity was associated with the presence of postoperative surgical site infection and the need for invasive mechanical ventilation during admission (table 4).
Table 4. Multivariable logistic regression analysis of the factors associated with severity during hospital admission for Roux-en-y gastric bypass and sleeve gastrectomy procedures in Spain, 2016–2022, according to diabetes status.
| Roux-en-Y gastric bypass | Sleeve gastrectomy | |||||
|---|---|---|---|---|---|---|
| T2DM | Non-T2DM | All | T2DM | Non-T2DM | All | |
| OR (95% CI) | OR (95% CI) | OR (95% CI) | OR (95% CI) | OR (95% CI) | OR (95% CI) | |
| Year 2016 | 1 | 1 | 1 | 1 | 1 | 1 |
| Year 2017 | 1.11 (0.9–1.38) | 0.86 (0.63–1.18) | 1.04 (0.85–1.27) | 0.94 (0.75 to 1.19) | 1.13 (0.81–1.57) | 1.01 (0.81–1.26) |
| Year 2018 | 0.59 (0.43–0.82) | 0.76 (0.6–0.95) | 0.63 (0.51–0.79) | 0.81 (0.65 to 1.03) | 0.71 (0.5–1.01) | 0.75 (0.59–0.95) |
| Year 2019 | 0.4 (0.28–0.56) | 0.55 (0.43–0.69) | 0.45 (0.35–0.57) | 0.64 (0.45 to 0.9) | 0.54 (0.42–0.69) | 0.57 (0.44–0.73) |
| Year 2020 | 0.27 (0.17–0.43) | 0.56 (0.42–0.73) | 0.37 (0.28–0.5) | 0.44 (0.29 to 0.68) | 0.53 (0.4–0.7) | 0.43 (0.31–0.6) |
| Year 2021 | 0.53 (0.38–0.75) | 0.51 (0.4–0.66) | 0.55 (0.43–0.7) | 0.56 (0.38 to 0.82) | 0.74 (0.58–0.94) | 0.52 (0.4–0.69) |
| Year 2022 | 0.56 (0.41–0.77) | 0.64 (0.51–0.8) | 0.59 (0.47–0.73) | 0.57 (0.4 to 0.82) | 0.79 (0.62–0.99) | 0.54 (0.42–0.71) |
| Women | NS | 0.77 (0.66–0.89) | NS | NS | 0.86 (0.75–0.99) | NS |
| Sepsis | NS | 9.16 (2.33–17.5) | 7.22 (2.02–14.26) | NS | 6.11 (1.35–17.73) | NS |
| Postoperative surgical site infection | 3.93 (1.76–8.75) | 2.81 (1.51–5.22) | 4.17 (2.4–7.24) | 6.7 (2.01 to 12.3) | 2.4 (1.11–5.18) | 4.43 (1.46–9.64) |
| Pneumonia | NS | NS | NS | NS | NS | 3.83 (1.01–8.49) |
| Invasive mechanical ventilation | 16.16 (2.83–29.99) | 17.35 (4.96–33.56) | 16.79 (3.93–25.49) | 16.62 (2.03 to 29.84) | 13.04 (1.64–26.64) | 14.62 (1.92–29.89) |
| Non-invasive mechanical ventilation | NS | NS | NS | NS | 4.01 (2.23–7.19) | 3.34 (1.7–6.54) |
| T2DM | NA | NA | 0.98 (0.86–1.11) | NA | NA | 1.23 (1.07–1.42) |
T2DM, type 2 diabetes mellitus.
Finally, T2DM was not associated with the severity of patients who underwent RYGB (OR 0.98; 95% CI 0.86 to 1.11), although T2DM was significantly associated with severity in those who received SG (OR 1.23; 95% CI 1.07 to 1.42).
Discussion
This nationwide study based on the T2DM status of more than 32,000 bariatric surgery interventions performed in Spain between 2016 and 2022 revealed several noteworthy findings. First, in patients with T2DM, the frequency of both bariatric surgery procedures has increased (mainly RYGB). Second, in each year of the study, the procedures were more frequent in patients with T2DM than in patients without. Third, more RYGB and SG procedures were performed on women than on men, regardless of diabetes status. Fourth, the presence of T2DM was associated with severity in SG patients.
Several epidemiological studies have indicated that RYGB was more likely to be performed than SG in patients with T2DM,10 22 possibly because RYGB seems to achieve a greater reduction in weight and for longer time in patients with T2DM than SG.7 23 24 A follow-up study of patients with T2DM in the USA comparing different bariatric surgery procedures showed that patients in the RYGB group had 6.2– 8.1% greater total body weight loss than the SG group at 1 and 5 years than those who underwent SG.25 In addition, relapse of T2DM after remission was less frequent after the use of RYGB than after SG. Aminian et al26 found that, in a patient with T2DM who had been receiving diabetes medication for 5 years prior to bariatric surgery, the projected risk of relapse would be 20% after RYGB and 36% after SG. Additionally, McTigue et al25 agreed that relapse of T2DM was less frequent for RYGB than for SG, with a HR of 0.75 (95% CI 0.67 to 0.84).
In our study, patients with T2DM were older and had more comorbid conditions than patients without diabetes. Older age, duration of diabetes, elevated baseline HbA1c values, high body mass index (BMI), and use of antidiabetic medications are predictive factors that predispose patients to a lower probability of remission of T2DM.27
Our database analysis, consistent with a previous Spanish study,12 revealed that bariatric surgery is more prevalent among patients with T2DM than among those without diabetes. Bariatric surgery has been extensively demonstrated as pivotal in addressing both obesity and T2DM, primarily owing to its long-term effectiveness.1
As in most population-based studies, bariatric surgery was more frequent in women, both with and without T2DM.28,31 Compared with men, women with obesity have lower self-esteem, more frequently experience psychological problems (such as depression) and report a greater impact on sex life and physical functioning, with the result that bariatric surgery is now the treatment of choice.30 31
In our study, we observed that disease was less severe in women without T2DM than in men. In their investigation of patients enrolled in the Michigan Bariatric Surgery Collaborative who underwent primary bariatric surgery from 2006 to 2016, Kochkodan et al32 found that male patients exhibited significantly more preoperative risk factors. These factors included a higher BMI and a greater burden of comorbidities. After surgery, male patients experienced more surgical complications and lost less weight, leading the authors to conclude that men tend to seek treatment later than women.
As expected, there was a decline in the number of procedures performed in 2020 due to the impact of the COVID-19 pandemic.9 Beside the lack of hospital beds and limited access to the ICU, these findings could be explained by the greater morbidity and mortality among individuals with T2DM and severe obesity when affected by COVID-19 than in the general population.33 34 Nonetheless, a multinational cohort study illustrated that with appropriate perioperative protocols,35 bariatric surgery could be performed safely, even amidst the COVID-19 pandemic.
Diabetes is considered a risk factor for intraoperative complications in multiple surgeries, and bariatric surgery is no different.36 Results from a large study of the MBSAQIP database indicated that among patients with T2DM, infectious complications were the most frequent cause of death after RYGB and SG.37 In our study, complications due to infection were associated with severity in both RYGB and SG.
As in other studies, sepsis in patients without diabetes was one of the reasons for the greatest severity after bariatric surgery.38 39 Bruschi Kelles et al39 indicated that 42.7% of deaths after bariatric surgery were due to sepsis. The primary cause of sepsis is often anastomotic leakage, that is, leakage of fluids into the abdominal cavity, which subsequently leads to peritonitis and sepsis.40
Adverse respiratory events are reported in approximately 2% of patients after bariatric surgery.41 In our study, pneumonia was associated with greater severity after SG.
As expected, IHM was very low in patients both with and without diabetes.1342,45 The reasons given for this low mortality rate are the improved use of preoperative antibiotics and prophylaxis for deep vein thrombosis, shorter hospital stay, the correct procedure and technique, and the care received in the ICU.40 42 45
The principal strength of our study lies in its use of the RAE-CMBD, a comprehensive Spanish national population database spanning a period of 7 years. The methodology has been documented elsewhere, thus enhancing the credibility and reproducibility of our findings. It should be noted that the RAE-CMBD includes practically all hospital admissions in Spain (>95%). Despite the aforementioned strengths, our study is constrained by several limitations. One such limitation is inherent in the fact that the RAE-CMBD is an administrative database, which means that it may not encompass all variables present in the medical records. Therefore, we lack information on diabetes such as duration, treatment, and laboratory results (HbA1c). Additionally, we lack information regarding whether participants opted for bariatric-metabolic surgery specifically to manage obesity or T2DM or for other purposes. Furthermore, the RAE-CMBD does not collect the BMI of subjects either before or after surgery, and this would be valuable information for developing care pathways. Second, akin to similar observational and retrospective studies that depend on ICD codes sourced from large databases, our research might be susceptible to issues of low sensitivity and specificity. This susceptibility could be contingent on the accuracy of clinicians in coding hospital procedures and diagnoses, thereby impacting the quality of the data. Nevertheless, previous studies conducted in Spain and elsewhere have demonstrated the validity of diagnosing diabetes using ICD codes in health administrative databases, as compared with clinical records. These studies concluded that such databases can effectively address research inquiries.45,49 Studies conducted in Spain evaluating the validity of the diagnosis of diabetes using the RAE-CMBD indicated a specificity of 97% (ie, almost all patients with a diabetes code actually have the disease), sensitivities of 55% and 63.7% (indicating that the condition is not encoded in some patients who actually have diabetes), and kappa indexes for agreement of 0.6 and 0.7.48 49 Third, patients who had undergone gastric banding were excluded, as this was a less frequent bariatric intervention than SG and RYGB.9 In our opinion, the exclusion of these cases would not result in a significant impact on our results but should be taken into account for future research. Fourth, we employed an age cut-off of 35 years to minimize the risk of diabetes type misclassification. Studies conducted in Spain using administrative data based on ICD-10 have indicated a risk of misclassification of diabetes type, particularly among younger individuals.50 51 However, previous reports in our country have demonstrated that the prevalence of T2DM is below 0.5% in those under 35 years.52 53 Fifth, a well-recognized limitation of administrative discharge databases is the absence of illness severity data.54 The Clavien-Dindo classification could not be used in our investigation because it incorporates information on pharmacological treatments not captured by the RAE-CMBD.55 Due to this limitation and the unavailability of other widely accepted measures of severity, we opted to develop our own definition of “severity.” Admission to the ICU and IHM have been demonstrated to be strongly associated with severity.56 Finally, re-operations were not included as a complication since the ICD-10 version used by the RAE-CMBD does not allow for the identification of patients who undergo surgery more than once during a single hospital admission. In conclusion, between 2016 and 2022, the number of RYGB and SG procedures performed in Spain rose in patients with and without T2DM. More interventions were performed on patients with T2DM than on patients without T2DM. The most common procedure in patients with T2DM is RYGB. IHM was very low after RYGB and SG, and among patients who underwent SG, those with T2DM more frequently experienced a severe postoperative course compared with subjects without T2DM.
Supplementary material
Footnotes
Funding: This work has been supported by the Madrid Government (Comunidad de Madrid-Spain) under the Multiannual Agreement with Universidad Complutense de Madrid in the line Excellence Programme for university teaching staff, in the context of the V PRICIT (Regional Programme of Research and Technological Innovation); by Universidad Complutense de Madrid. Grupo de Investigación en Epidemiología de las Enfermedades Crónicas de Alta Prevalencia en España (970970); and by the FIS (Fondo de Investigaciones Sanitarias—Health Research Fund, Instituto de Salud Carlos III) and co-financed by the European Union through the Fondo Europeo de Desarrollo Regional (FEDER, “Una manera de hacer Europa”): grant no. PI20/00118.
Provenance and peer review: Not commissioned; externally peer reviewed.
Patient consent for publication: Not applicable.
Ethics approval: Not applicable.
Data availability free text: Access to the data is restricted, since the Spanish Ministry of Health requires the investigators to accept the following obligations prior to transfer the data: (1) to treat all information under strict confidentiality conditions; (2) not to use, and not to authorize any natural or legal person to use the transferred data other than exclusively for the purposes of the work as reflected in the request; (3) to destroy the file or data provided and all copies made of it once the period of time for which the data is required has elapsed. Requesting access to the data from the Spanish Ministry of Health can be made at: https://www.mscbs.gob.es/estadEstudios/estadisticas/estadisticas/estMinisterio/SolicitudCMBDdocs/2018_Formulario_Peticion_Datos_RAE_CMBD.pdf.
Data availability statement
Data may be obtained from a third party and are not publicly available.
References
- 1.Ruze R, Liu T, Zou X, et al. Obesity and type 2 diabetes mellitus: connections in epidemiology, pathogenesis, and treatments. Front Endocrinol (Lausanne) 2023;14:1161521. doi: 10.3389/fendo.2023.1161521. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Mingrone G, Rajagopalan H. Bariatrics and endoscopic therapies for the treatment of metabolic disease: past, present, and future. Diabetes Res Clin Pract. 2024;211:111651. doi: 10.1016/j.diabres.2024.111651. [DOI] [PubMed] [Google Scholar]
- 3.American Diabetes Association Standards of medical care in diabetes—2009. Diabetes Care. 2009;32:S13–61. doi: 10.2337/dc09-S013. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Mingrone G, Panunzi S, De Gaetano A, et al. Bariatric surgery versus conventional medical therapy for type 2 diabetes. N Engl J Med. 2012;366:1577–85. doi: 10.1056/NEJMoa1200111. [DOI] [PubMed] [Google Scholar]
- 5.Mingrone G, Panunzi S, De Gaetano A, et al. Bariatric-metabolic surgery versus conventional medical treatment in obese patients with type 2 diabetes: 5 year follow-up of an open-label, single-centre, randomised controlled trial. Lancet. 2015;386:964–73. doi: 10.1016/S0140-6736(15)00075-6. [DOI] [PubMed] [Google Scholar]
- 6.Mingrone G, Panunzi S, De Gaetano A, et al. Metabolic surgery versus conventional medical therapy in patients with type 2 diabetes: 10-year follow-up of an open-label, single-centre, randomised controlled trial. Lancet. 2021;397:293–304. doi: 10.1016/S0140-6736(20)32649-0. [DOI] [PubMed] [Google Scholar]
- 7.Schauer PR, Bhatt DL, Kirwan JP, et al. Bariatric surgery versus intensive medical therapy for diabetes - 5-year outcomes. N Engl J Med. 2017;376:641–51. doi: 10.1056/NEJMoa1600869. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Welbourn R, Hollyman M, Kinsman R, et al. Bariatric-metabolic surgery utilisation in patients with and without diabetes: data from the IFSO Global Registry 2015-2018. Obes Surg. 2021;31:2391–400. doi: 10.1007/s11695-021-05280-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Angrisani L, Santonicola A, Iovino P, et al. IFSO Worldwide survey 2020-2021: current trends for bariatric and metabolic procedures. Obes Surg. 2024;34:1075–85. doi: 10.1007/s11695-024-07118-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Currie A, Bolckmans R, Askari A, et al. Bariatric-metabolic surgery for NHS patients with type 2 diabetes in the United Kingdom National Bariatric Surgery Registry. Diabet Med. 2023;40:e15041. doi: 10.1111/dme.15041. [DOI] [PubMed] [Google Scholar]
- 11.Lecube A, de Hollanda A, Calañas A, et al. Trends in bariatric surgery in spain in the twenty-first century: baseline results and 1-month follow up of the RICIBA, a National Registry. Obes Surg. 2016;26:1836–42. doi: 10.1007/s11695-015-2001-3. [DOI] [PubMed] [Google Scholar]
- 12.Lopez-de-Andres A, Jiménez-García R, Hernández-Barrera V, et al. Trends in utilization and outcomes of bariatric surgery in obese people with and without type 2 diabetes in Spain (2001-2010) Diabetes Res Clin Pract. 2013;99:300–6. doi: 10.1016/j.diabres.2012.12.011. [DOI] [PubMed] [Google Scholar]
- 13.Eisenberg D, Shikora SA, Aarts E, et al. 2022 American Society of Metabolic and Bariatric Surgery (ASMBS) and International Federation for the Surgery of Obesity and Metabolic Disorders (IFSO) Indications for Metabolic and Bariatric Surgery. OBES SURG. 2023;33:3–14. doi: 10.1007/s11695-022-06332-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Instituto Nacional de Gestión Sanitaria . Ministerio de Sanidad y Consumo, Conjunto Mínimo Básico de Datos. Hospitales del INSALUD; 2001. [Google Scholar]
- 15.Sundararajan V, Henderson T, Perry C, et al. New ICD-10 version of the charlson comorbidity index predicted in-hospital mortality. J Clin Epidemiol. 2004;57:1288–94. doi: 10.1016/j.jclinepi.2004.03.012. [DOI] [PubMed] [Google Scholar]
- 16.Austin PC. An introduction to propensity score methods for reducing the effects of confounding in observational studies. Multivariate Behav Res. 2011;46:399–424. doi: 10.1080/00273171.2011.568786. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Hany M, Torensma B, Zidan A, et al. Outcomes of primary versus conversional Roux-En-Y gastric bypass after laparoscopic sleeve gastrectomy: a retrospective propensity score-matched cohort study. BMC Surg. 2024;24:84. doi: 10.1186/s12893-024-02374-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Instituto Nacional de Estadística Population Estimates. [30-Apr-2024]. https://www.ine.es./dyngs/INEbase/es/operacion.htm?c=Estadistica_C&cid=1254736176951&menu=ultiDatos&idp=1254735572981 Available. Accessed.
- 19.Ministerio de Sanidad Encuesta Nacional de Salud de España. 2018. [6-May-2024]. https://www.mscbs.gob.es/estadEstudios/estadisticas/encuestaNacional/encuesta2017.htm Available. Accessed.
- 20.Encuesta Europea de Salud en España. 2020. [6-May-2024]. https://www.mscbs.gob.es/estadEstudios/estadisticas/EncuestaEuropea/Enc_Eur_Salud_en_Esp_2020.htm Available. Accessed.
- 21.Ministerio de Sanidad Consumo y Bienestar Social. Solicitud de extracción de datos – Extraction request (Spanish National Hospital Discharge Database) [12-May-2021]. https://www.mscbs.gob.es/estadEstudios/estadisticas/estadisticas/estMinisterio/SolicitudCMBDdocs/2018_Formulario_Peticion_Datos_RAE_CMBD.pdf Available. Accessed.
- 22.Akpinar EO, Liem RSL, Nienhuijs SW, et al. Metabolic effects of bariatric surgery on patients with type 2 diabetes: a population-based study. Surg Obes Relat Dis. 2021;17:1349–58. doi: 10.1016/j.soard.2021.02.014. [DOI] [PubMed] [Google Scholar]
- 23.Wölnerhanssen BK, Peterli R, Hurme S, et al. Laparoscopic Roux-en-Y gastric bypass versus laparoscopic sleeve gastrectomy: 5-year outcomes of merged data from two randomized clinical trials (SLEEVEPASS and SM-BOSS) Br J Surg. 2021;108:49–57. doi: 10.1093/bjs/znaa011. [DOI] [PubMed] [Google Scholar]
- 24.Elsaigh M, Awan B, Shabana A, et al. Comparing safety and efficacy outcomes of gastric bypass and sleeve gastrectomy in patients with type 2 diabetes mellitus: a systematic review and meta-analysis. Cureus. 2024;PMCID:e52796. doi: 10.7759/cureus.52796. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.McTigue KM, Wellman R, Nauman E, et al. Comparing the 5-year diabetes outcomes of sleeve gastrectomy and gastric bypass: the national patient-centered clinical research network (PCORNet) bariatric study. JAMA Surg. 2020;155:e200087. doi: 10.1001/jamasurg.2020.0087. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Aminian A, Vidal J, Salminen P, et al. Late relapse of diabetes after bariatric surgery: not rare, but not a failure. Diabetes Care. 2020;43:534–40. doi: 10.2337/dc19-1057. [DOI] [PubMed] [Google Scholar]
- 27.Balasubaramaniam V, Pouwels S. Remission of Type 2 Diabetes Mellitus (T2DM) after Sleeve Gastrectomy (SG), One-Anastomosis Gastric Bypass (OAGB), and Roux-en-Y Gastric Bypass (RYGB): a systematic review. Medicina (Kaunas) 2023;59:985. doi: 10.3390/medicina59050985. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Reges O, Greenland P, Dicker D, et al. Association of Bariatric Surgery Using Laparoscopic Banding, Roux-en-Y Gastric Bypass, or Laparoscopic Sleeve Gastrectomy vs Usual Care Obesity Management With All-Cause Mortality. JAMA. 2018;319:279–90. doi: 10.1001/jama.2017.20513. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Jackson TN, Cox BP, Grinberg GG, et al. National usage of bariatric surgery for class i obesity: an analysis of the metabolic and bariatric surgery accreditation and quality improvement program. Surg Obes Relat Dis. 2023;19:1255–62.:S1550-7289(23)00527-0. doi: 10.1016/j.soard.2023.05.014. [DOI] [PubMed] [Google Scholar]
- 30.Kolotkin RL, Crosby RD, Gress RE, et al. Health and health-related quality of life: differences between men and women who seek gastric bypass surgery. Surg Obes Relat Dis. 2008;4:651–8. doi: 10.1016/j.soard.2008.04.012. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31.Skulsky SL, Dang JT, Switzer NJ, et al. Higher edmonton obesity staging system scores are independently associated with postoperative complications and mortality following bariatric surgery: an analysis of the MBSAQIP. Surg Endosc. 2021;35:7163–73. doi: 10.1007/s00464-020-08138-7. [DOI] [PubMed] [Google Scholar]
- 32.Kochkodan J, Telem DA, Ghaferi AA. Physiologic and psychological gender differences in bariatric surgery. Surg Endosc. 2018;32:1382–8. doi: 10.1007/s00464-017-5819-z. [DOI] [PubMed] [Google Scholar]
- 33.Sanders AP, Vosburg RW. Early postoperative COVID infection is associated with significantly increased risk of venous thromboembolism after metabolic and bariatric surgery. Surg Obes Relat Dis. 2024;8:00046–7. doi: 10.1016/j.soard.2024.01.021. [DOI] [PubMed] [Google Scholar]
- 34.Ohta M, Ahn SM, Seki Y, et al. Ten years of change in bariatric/metabolic surgery in the Asia-Pacific Region with COVID-19 pandemic: IFSO-APC national reports 2021. Obes Surg. 2022;32:2994–3004. doi: 10.1007/s11695-022-06182-x. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35.Singhal R, Ludwig C, Rudge G, et al. 30-Day morbidity and mortality of bariatric surgery during the COVID-19 pandemic: a multinational cohort study of 7704 patients from 42 countries. Obes Surg. 2021;31:4272–88. doi: 10.1007/s11695-021-05493-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36.Steele KE, Prokopowicz GP, Chang H, et al. Risk of complications after bariatric surgery among individuals with and without type 2 diabetes mellitus. Surg Obes Relat Dis. 2012;8:305–30. doi: 10.1016/j.soard.2011.05.018. [DOI] [PubMed] [Google Scholar]
- 37.Leonard-Murali S, Nasser H, Ivanics T, et al. Perioperative Outcomes of Roux-en-Y Gastric Bypass and Sleeve Gastrectomy in Patients with Diabetes Mellitus: an Analysis of the Metabolic and Bariatric Surgery Accreditation and Quality Improvement Program (MBSAQIP) Database. Obes Surg. 2020;30:111–8. doi: 10.1007/s11695-019-04175-x. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 38.Hui BY, Khorgami Z, Puthoff JS, et al. Postoperative sepsis after primary bariatric surgery: an analysis of MBSAQIP. Surg Obes Relat Dis. 2021;17:667–72. doi: 10.1016/j.soard.2020.12.008. [DOI] [PubMed] [Google Scholar]
- 39.Bruschi Kelles SM, Diniz MFHS, Machado CJ, et al. Mortality rate after open Roux-in-Y gastric bypass: a 10-year follow-up. Braz J Med Biol Res. 2014;47:617–25. doi: 10.1590/1414-431x20143578. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 40.Alanzi A, Alamannaei F, Abduljawad S, et al. Patient outcomes and rate of intensive care unit admissions following bariatric surgery: a retrospective cohort study of 775 patients. Cureus. 2023;15:e49667. doi: 10.7759/cureus.49667. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 41.Avriel A, Warner E, Avinoach E, et al. Major respiratory adverse events after laparascopic gastric banding surgery for morbid obesity. Respir Med. 2012;106:1192–8. doi: 10.1016/j.rmed.2012.05.002. [DOI] [PubMed] [Google Scholar]
- 42.Robertson AGN, Wiggins T, Robertson FP, et al. Perioperative mortality in bariatric surgery: meta-analysis. Br J Surg. 2021;108:892–7. doi: 10.1093/bjs/znab245. [DOI] [PubMed] [Google Scholar]
- 43.Carlsson LMS, Carlsson B, Jacobson P, et al. Life expectancy after bariatric surgery or usual care in patients with or without baseline type 2 diabetes in Swedish Obese Subjects. Int J Obes (Lond) 2023;47:931–8. doi: 10.1038/s41366-023-01332-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 44.Doumouras AG, Lee Y, Paterson JM, et al. Association between bariatric surgery and major adverse diabetes outcomes in patients with diabetes and obesity. JAMA Netw Open . 2021;4:e216820. doi: 10.1001/jamanetworkopen.2021.6820. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 45.Stenberg E, Szabo E, Agren G, et al. Early complications after laparoscopic gastric bypass surgery: results from the scandinavian obesity surgery registry. Ann Surg. 2014;260:1040–7. doi: 10.1097/SLA.0000000000000431. [DOI] [PubMed] [Google Scholar]
- 46.Khokhar B, Jette N, Metcalfe A, et al. Systematic review of validated case definitions for diabetes in ICD-9-coded and ICD-10-coded data in adult populations. BMJ Open. 2016;6:e009952. doi: 10.1136/bmjopen-2015-009952. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 47.Fuentes S, Cosson E, Mandereau-Bruno L, et al. Identifying diabetes cases in health administrative databases: a validation study based on a large French cohort. Int J Public Health. 2019;64:441–50. doi: 10.1007/s00038-018-1186-3. [DOI] [PubMed] [Google Scholar]
- 48.Ribera A, Marsal JR, Ferreira-González I, et al. Predicting in-hospital mortality with coronary bypass surgery using hospital discharge data: comparison with a prospective observational study. Rev Esp Cardiol (Engl Ed) 2008;61:843–52. doi: 10.1016/S1885-5857(08)60232-7. [DOI] [PubMed] [Google Scholar]
- 49.Rodrigo-Rincón I, Martin-Vizcaíno MP, Tirapu-León B, et al. Usefulness of administrative databases for risk adjustment of adverse events in surgical patients. Cir Esp. 2016;94:165–74. doi: 10.1016/j.ciresp.2015.01.013. [DOI] [PubMed] [Google Scholar]
- 50.Reviriego J, Vázquez LA, Goday A, et al. Prevalence of impaired fasting glucose and type 1 and 2 diabetes mellitus in a large nationwide working population in Spain. Endocrinol Nutr. 2016;63:157–63. doi: 10.1016/j.endonu.2015.12.006. [DOI] [PubMed] [Google Scholar]
- 51.Moulis G, Ibañez B, Palmaro A, et al. Cross-national health care database utilization between Spain and France: results from the EPICHRONIC study assessing the prevalence of type 2 diabetes mellitus. Clin Epidemiol. 2018;10:863–74. doi: 10.2147/CLEP.S151890. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 52.Moreno-Iribas C, Sayon-Orea C, Delfrade J, et al. Validity of type 2 diabetes diagnosis in a population-based electronic health record database. BMC Med Inform Decis Mak. 2017;17:34. doi: 10.1186/s12911-017-0439-z. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 53.Mata-Cases M, Mauricio D, Real J, et al. Is diabetes mellitus correctly registered and classified in primary care? A population-based study in Catalonia, Spain. Endocrinol Nutr. 2016;63:440–8. doi: 10.1016/j.endonu.2016.07.004. [DOI] [PubMed] [Google Scholar]
- 54.Andrews RM. Statewide hospital discharge data: collection, use, limitations, and improvements. Health Serv Res. 2015;50 Suppl 1:1273–99. doi: 10.1111/1475-6773.12343. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 55.Dindo D, Demartines N, Clavien P-A. Classification of surgical complications: a new proposal with evaluation in a cohort of 6336 patients and results of a survey. Ann Surg. 2004;240:205–13. doi: 10.1097/01.sla.0000133083.54934.ae. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 56.Shepherd SJ. Criteria for intensive care unit admission and the assessment of illness severity. Surg (Oxford) 2018;36:171–9. doi: 10.1016/j.mpsur.2018.01.003. [DOI] [Google Scholar]
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