Prehabilitation for patients undergoing metabolic/bariatric surgery: a retrospective cohort study using propensity score matching
DOI:
https://doi.org/10.2340/jrm.v58.45736Keywords:
prehabilitation, propensity score matching, bariatric surgery, cost-effectivenessAbstract
Importance: Multimodal prehabilitation improves outcomes in colorectal surgery, but its effectiveness and cost-effectiveness before metabolic and bariatric surgery are unknown.
Objective: To evaluate the effectiveness and cost-effectiveness of a 6-week multimodal prehabilitation programme compared with standard preintervention education in patients undergoing bariatric surgery.
Design, setting, and participants: Propensity score matched cohort observational study at Shanghai Tenth People’s Hospital, China, January 2022 to January 2025. Sixty prehabilitation patients were matched 1:1 to 60 controls from 254 standard care candidates using nearest-neighbour matching on the logit of the propensity score. Follow-up was 12 months.
Interventions: A 6-week programme of supervised exercise, nutritional counselling, and psychological support vs 2 standard preoperative counselling sessions. All patients underwent Roux-en-Y gastric bypass or sleeve gastrectomy.
Main outcomes and measures: Total weight loss at 12 months. Secondary outcomes included body composition, metabolic parameters, functional capacity, patient-reported outcomes, safety, and healthcare costs.
Results: Among 120 matched patients (mean [SD] age, 32.6 [5.2] years; 65.8% male; mean body mass index [BMI], 38.2 [3.2] kg/m2), total weight loss at 12 months did not differ between groups (23.7 [5.1] vs 23.4 [2.7] kg; difference, 0.3 kg; 95% CI, −1.3 to 1.8; p = 0.75). At 3 months, prehabilitation showed significantly greater weight loss (adjusted β = 2.85 kg; 95% CI, 1.77 to 3.93; p < 0.001), lower body fat, lower diastolic blood pressure, and higher Short Form-36 (SF-36) mental scores. All differences were attenuated by 6 months. No serious adverse events occurred. Total costs were modestly higher in the prehabilitation group (mean, ¥84 843 vs ¥78 051), a difference attributable almost entirely to the prehabilitation programme itself; because the incremental effect on weight loss at 12 months was not statistically significant, a meaningful incremental cost-effectiveness ratio could not be estimated.
Conclusions and relevance: A 6-week multimodal prehabilitation programme accelerated early postoperative weight loss and improved short-term functional outcomes but did not improve total weight loss at 12 months. Because prehabilitation added cost without a demonstrable difference in 12-month weight loss, a cost-effectiveness advantage could not be established. The dominant metabolic effects of bariatric surgery appear to override the incremental gains of preoperative conditioning over time.
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References
NCD Risk Factor Collaboration (NCD-RisC). Worldwide trends in underweight and obesity from 1990 to 2022: a pooled analysis of 3663 population-representative studies with 222 million children, adolescents, and adults. Lancet 2024; 403: 1027–1050.
Pan XF, Wang L, Pan A. Epidemiology and determinants of obesity in China. Lancet Diabetes Endocrinol 2021; 9: 373–392. DOI: https://doi.org/10.1016/S2213-8587(21)00045-0
Sjöström L, Lindroos AK, Peltonen M, Torgerson J, Bouchard C, Carlsson B, et al. Lifestyle, diabetes, and cardiovascular risk factors 10 years after bariatric surgery. N Engl J Med 2004; 351: 2683–2693. DOI: https://doi.org/10.1056/NEJMoa035622
Schauer PR, Bhatt DL, Kirwan JP, Wolski K, Aminian A, Brethauer SA, et al. Bariatric surgery versus intensive medical therapy for diabetes: 5-year outcomes. N Engl J Med 2017; 376: 641–651. DOI: https://doi.org/10.1056/NEJMoa1600869
Angrisani L, Santonicola A, Iovino P, Palma R, Kow L, Prager G, et al. IFSO Worldwide Survey 2020–2021: current trends for bariatric and metabolic procedures. Obes Surg 2024; 34: 1075–1085. DOI: https://doi.org/10.1007/s11695-024-07118-3
Livhits M, Mercado C, Yermilov I, Parikh JA, Dutson E, Mehran A, et al. Preoperative predictors of weight loss following bariatric surgery: systematic review. Obes Surg 2012; 22: 70–89. DOI: https://doi.org/10.1007/s11695-011-0472-4
Scheede-Bergdahl C, Minnella EM, Carli F. Multi-modal prehabilitation: addressing the why, when, what, how, who and where next? Anaesthesia 2019; 74 Suppl 1: 20–26. DOI: https://doi.org/10.1111/anae.14505
Gillis C, Ljungqvist O, Carli F. Prehabilitation, enhanced recovery after surgery, or both? A narrative review. Br J Anaesth 2022; 128: 434–448. DOI: https://doi.org/10.1016/j.bja.2021.12.007
Gillis C, Li C, Lee L, Awasthi R, Augustin B, Gamsa A,
et al. Prehabilitation versus rehabilitation: a randomized control trial in patients undergoing colorectal resection for cancer. Anesthesiology 2014; 121: 937–947. DOI: https://doi.org/10.1097/ALN.0000000000000393
Carli F, Bousquet-Dion G, Awasthi R, Elsherbini N, Liberman S, Boutros M, et al. Effect of multimodal prehabilitation vs postoperative rehabilitation on 30-day postoperative complications for frail patients undergoing resection of colorectal cancer: a randomized clinical trial. JAMA Surg 2020; 155: 233–242. DOI: https://doi.org/10.1001/jamasurg.2019.5474
Molenaar CJL, Minnella EM, Coca-Martinez M, ten Cate DWG, Regis M, Awasthi R, et al. Effect of multimodal prehabilitation on reducing postoperative complications and enhancing functional capacity following colorectal cancer surgery: the PREHAB randomized clinical trial. JAMA Surg 2023; 158: 572–581. DOI: https://doi.org/10.1001/jamasurg.2023.0198
García-Delgado Y, López-Madrazo-Hernández MJ, Alvarado-Martel D, Miranda-Calderín G, Ugarte-Lopetegui A, González-Medina RA, et al. Prehabilitation for bariatric surgery: a randomized, controlled trial protocol and pilot study. Nutrients 2021; 13: 2903. DOI: https://doi.org/10.3390/nu13092903
Rombey T, Eckhardt H, Kiselev J, Silzle J, Mathes T, Quentin W. Cost-effectiveness of prehabilitation prior to elective surgery: a systematic review of economic evaluations. BMC Med 2023; 21: 265. DOI: https://doi.org/10.1186/s12916-023-02977-6
Barberan-Garcia A, Ubré M, Pascual-Argente N, Risco R, Faner J, Balust J, et al. Post-discharge impact and cost-consequence analysis of prehabilitation in high-risk patients undergoing major abdominal surgery: secondary results from a randomised controlled trial. Br J Anaesth 2019; 123: 450–456. DOI: https://doi.org/10.1016/j.bja.2019.05.032
Xia Q, Campbell JA, Ahmad H, Si L, de Graaff B, Palmer AJ. Bariatric surgery is a cost-saving treatment for obesity: a comprehensive meta-analysis and updated systematic review of health economic evaluations of bariatric surgery. Obes Rev 2020; 21: e12932. DOI: https://doi.org/10.1111/obr.13028
Rosenbaum PR, Rubin DB. The central role of the propensity score in observational studies for causal effects. Biometrika 1983; 70: 41–55. DOI: https://doi.org/10.1093/biomet/70.1.41
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: https://doi.org/10.1080/00273171.2011.568786
Carli F, Zavorsky GS. Optimizing functional exercise capacity in the elderly surgical population. Curr Opin Clin Nutr Metab Care 2005; 8: 23–32. DOI: https://doi.org/10.1097/00075197-200501000-00005
Li C, Carli F, Lee L, Charlebois P, Stein B, Liberman AS, et al. Impact of a trimodal prehabilitation program on functional recovery after colorectal cancer surgery: a pilot study. Surg Endosc 2013; 27: 1072–1082. DOI: https://doi.org/10.1007/s00464-012-2560-5
Mechanick JI, Youdim A, Jones DB, Garvey WT, Hurley DL, McMahon MM, et al. Clinical practice guidelines for the perioperative nutritional, metabolic, and nonsurgical support of the bariatric surgery patient: 2013 update. Obesity (Silver Spring) 2013; 21 Suppl 1: S1–S27. DOI: https://doi.org/10.1002/oby.20461
Mechanick JI, Apovian C, Brethauer S, Garvey WT, Joffe AM, Kim J, et al. Clinical practice guidelines for the perioperative nutrition, metabolic, and nonsurgical support of patients undergoing bariatric procedures: 2019 update. Surg Obes Relat Dis 2020; 16: 175–247. DOI: https://doi.org/10.1016/j.soard.2019.10.025
Thorell A, MacCormick AD, Awad S, Reynolds N, Roulin D, Demartines N, et al. Guidelines for perioperative care in bariatric surgery: Enhanced Recovery After Surgery (ERAS) Society recommendations. World J Surg 2016; 40: 2065–2083. DOI: https://doi.org/10.1007/s00268-016-3492-3
Hernán MA, Robins JM. Estimating causal effects from epidemiological data. J Epidemiol Community Health 2006; 60: 578–586. DOI: https://doi.org/10.1136/jech.2004.029496
Austin PC. Optimal caliper widths for propensity-score matching when estimating differences in means and differences in proportions in observational studies. Pharm Stat 2011; 10: 150–161. DOI: https://doi.org/10.1002/pst.433
Austin PC. Balance diagnostics for comparing the distribution of baseline covariates between treatment groups in propensity-score matched samples. Stat Med 2009; 28: 3083–3107. DOI: https://doi.org/10.1002/sim.3697
Stuart EA. Matching methods for causal inference: a review and a look forward. Stat Sci 2010; 25: 1–21. DOI: https://doi.org/10.1214/09-STS313
Brethauer SA, Kim J, el Chaar M, Papasavas P, Eisenberg D, Rogers A, et al. Standardized outcomes reporting in metabolic and bariatric surgery. Surg Obes Relat Dis 2015; 11: 489–506. DOI: https://doi.org/10.1016/j.soard.2015.02.003
Arterburn DE, Telem DA, Kushner RF, Courcoulas AP. Benefits and risks of bariatric surgery in adults: a review. JAMA 2020; 324: 879–887. DOI: https://doi.org/10.1001/jama.2020.12567
van de Laar A, de Caluwé L, Dillemans B. Relative outcome measures for bariatric surgery: evidence against excess weight loss and excess body mass index loss from a series of laparoscopic Roux-en-Y gastric bypass patients. Obes Surg 2011; 21: 763–767. DOI: https://doi.org/10.1007/s11695-010-0347-0
King WC, Bond DS. The importance of preoperative and postoperative physical activity counseling in bariatric surgery. Exerc Sport Sci Rev 2013; 41: 26–35. DOI: https://doi.org/10.1097/JES.0b013e31826444e0
Donnelly JE, Blair SN, Jakicic JM, Manore MM, Rankin JW, Smith BK. American College of Sports Medicine Position Stand: Appropriate physical activity intervention strategies for weight loss and prevention of weight regain for adults. Med Sci Sports Exerc 2009; 41: 459–471. DOI: https://doi.org/10.1249/MSS.0b013e3181949333
Kalarchian MA, Marcus MD, Courcoulas AP, Cheng Y, Levine MD. Preoperative lifestyle intervention in bariatric surgery: a randomized clinical trial. Surg Obes Relat Dis 2016; 12: 180–187. DOI: https://doi.org/10.1016/j.soard.2015.05.004
Brookhart MA, Schneeweiss S, Rothman KJ, Glynn RJ, Avorn J, Stürmer T. Variable selection for propensity score models. Am J Epidemiol 2006; 163: 1149–1156. DOI: https://doi.org/10.1093/aje/kwj149
West BT, Welch KB, Gałecki AT. Linear mixed models: a practical guide using statistical software. 2nd ed. Boca Raton: Chapman & Hall/CRC; 2014. DOI: https://doi.org/10.1201/b17198
Pinheiro JC, Bates DM. Mixed-effects models in S and S-PLUS. New York: Springer; 2000. DOI: https://doi.org/10.1007/978-1-4419-0318-1
Schielzeth H, Dingemanse NJ, Nakagawa S, Westneat DF, Allegue H, Teplitsky C, et al. Robustness of linear mixed-effects models to violations of distributional assumptions. Methods Ecol Evol 2020; 11: 1141–1152. DOI: https://doi.org/10.1111/2041-210X.13434
Funk MJ, Westreich D, Wiesen C, Stürmer T, Brookhart MA, Davidian M. Doubly robust estimation of causal effects. Am J Epidemiol 2011; 173: 761–767. DOI: https://doi.org/10.1093/aje/kwq439
Nguyen TL, Collins GS, Spence J, Daurès JP, Devereaux PJ, Landais P, et al. Double-adjustment in propensity score matching analysis: choosing a threshold for considering residual imbalance. BMC Med Res Methodol 2017; 17: 78. DOI: https://doi.org/10.1186/s12874-017-0338-0
Laird NM, Ware JH. Random-effects models for longitudinal data. Biometrics 1982; 38: 963–974. DOI: https://doi.org/10.2307/2529876
Detry MA, Ma Y. Analyzing repeated measurements using mixed models. JAMA 2016; 315: 407–408. DOI: https://doi.org/10.1001/jama.2015.19394
Zigmond AS, Snaith RP. The hospital anxiety and depression scale. Acta Psychiatr Scand 1983; 67: 361–370. DOI: https://doi.org/10.1111/j.1600-0447.1983.tb09716.x
Visscher TLS, Seidell JC. Time trends (1993–1997) and seasonal variation in body mass index and waist circumference in the Netherlands. Int J Obes Relat Metab Disord 2004; 28: 1309–1316. DOI: https://doi.org/10.1038/sj.ijo.0802761
Briggs AH, Wonderling DE, Mooney CZ. Pulling cost-effectiveness analysis up by its bootstraps: a non-parametric approach to confidence interval estimation. Health Econ 1997; 6: 327–340. DOI: https://doi.org/10.1002/(SICI)1099-1050(199707)6:4<327::AID-HEC282>3.0.CO;2-W
Briggs AH, Fenn P. Confidence intervals or surfaces? Uncertainty on the cost-effectiveness plane. Health Econ 1998; 7: 723–740. DOI: https://doi.org/10.1002/(SICI)1099-1050(199812)7:8<723::AID-HEC392>3.0.CO;2-O
Peduzzi P, Concato J, Kemper E, Holford TR, Feinstein AR. A simulation study of the number of events per variable in logistic regression analysis. J Clin Epidemiol 1996; 49: 1373–1379. DOI: https://doi.org/10.1016/S0895-4356(96)00236-3
Bagley SC, White H, Golomb BA. Logistic regression in the medical literature: standards for use and reporting, with particular attention to one medical domain. J Clin Epidemiol 2001; 54: 979–985. DOI: https://doi.org/10.1016/S0895-4356(01)00372-9
Cepeda MS, Boston R, Farrar JT, Strom BL. Comparison of logistic regression versus propensity score when the number of events is low and there are multiple confounders. Am J Epidemiol 2003; 158: 280–287. DOI: https://doi.org/10.1093/aje/kwg115
Glynn RJ, Schneeweiss S, Stürmer T. Indications for propensity scores and review of their use in pharmacoepidemiology. Basic Clin Pharmacol Toxicol 2006; 98: 253–259. DOI: https://doi.org/10.1111/j.1742-7843.2006.pto_293.x
Brazier J, Roberts J, Deverill M. The estimation of a preference-based measure of health from the SF-36. J Health Econ 2002; 21: 271–292. DOI: https://doi.org/10.1016/S0167-6296(01)00130-8
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