Prehabilitation in adult patients undergoing surgery: an umbrella review of systematic reviews

McIsaac, Daniel I.; Gill, Marlyn; Boland, Laura; Hutton, Brian; Branje, Karina; Shaw, Julia; Grudzinski, Alexa; Barone, Natasha; Gillis, Chelsia; Akhtar, Shamsuddin; Atkins, Marlis; Aucoin, Sylvie; Auer, Rebecca C.; Basualdo-Hammond, Carlota; Beaulé, Paul E.; Brindle, Mary; Bittner, Honorata; Bryson, Gregory L.; Carli, Franco; Eskander, Antoine; Fata, Paola; Fergusson, Dean; Fiore, Julio F.; Forster, Alan J.; Gillam, M.; Gramlich, Leah; Holroyd‐Leduc, Jayna; Jackson, Timothy; Jacobsohn, Eric; Khadaroo, Rachel G.; Lalu, Manoj M.; Love, C.M.; Martel, Guillaume; McCartney, Colin J. L.; McKeen, Dolores M.; Meliambro, Amanda; Moloo, Husein; Moore, Ronald B.; Muscedere, John; Nantel, Julie; Poitras, Stéphane; Scheede‐Bergdahl, Celena; Taljaard, Monica; Wallace, Tom; Wijeysundera, Duminda N.

doi:10.1016/j.bja.2021.11.014

Cited by 141 publications

(145 citation statements)

References 94 publications

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“…19 The strongest evidence for the benefit of prehabilitation is in conferring significant improvements in functional capacity from both baseline-to-surgery and postoperatively. 19,32,33,35,57,58 For patients with gastrointestinal cancer, Lau and Chamberlain 57 report a 48 meter improvement in the 6MWT distance from baseline to 4-8 weeks postoperatively, and similar trends were observed in a study of patients undergoing esophagogastric cancer resection. 35 As for reducing postoperative complications, prehabilitation appears to provide some protection in mixed surgical cohorts, 19,32 but there is minimal evidence for reduced complications in general, 32 gastrointestinal, 57,59 or esophago-gastric cancer cohorts more specifically.…”

Section: Name Cut-off Descriptionmentioning

confidence: 68%

“…Importantly, with the advent of targeted preoperative interventions to bolster patients' physiological reserve before major surgery (i.e., prehabilitation programs 31 ), numerous studies have demonstrated that functional capacity is a modifiable risk factor in the preoperative period, and can be improved via a variety of physical and/or nutritional interventions. 32,33 Further, patients with a low baseline functional capacity 34 or those with cancer (including esophago-gastric cancer) appear to have the greatest improvements. 35 These encouraging results challenge the scope of preoperative assessment to extend beyond a physician-driven investigative process (where patients are passive "passengers") to an interventional model that actively engages patients during the preoperative period and targets modifiable risk factors.…”

Section: Preoperative Assessment and Surgical Riskmentioning

confidence: 99%

“…A recent umbrella review 32 and meta-analysis 19 provide comprehensive outlines of the current state of prehabilitation research.…”

Section: Name Cut-off Descriptionmentioning

confidence: 99%

“…Firstly, both studies acknowledge the broad scope and heterogeneity in prehabilitation components evaluated (e.g., nutrition, exercise, inspiratory muscle training, psychology/counseling, smoking cessation, or patient education), intervention design (i.e., single vs. multimodal), as well as the structure, duration, and adherence to programs, and the patient cohorts studied. 19,32 Although this limits the quality and generalizability of the evidence to date, signals of benefit remain present, and the interventions appear safe with minimal adverse events. 19 The strongest evidence for the benefit of prehabilitation is in conferring significant improvements in functional capacity from both baseline-to-surgery and postoperatively.…”

Section: Name Cut-off Descriptionmentioning

confidence: 99%

“…35 As for reducing postoperative complications, prehabilitation appears to provide some protection in mixed surgical cohorts, 19,32 but there is minimal evidence for reduced complications in general, 32 gastrointestinal, 57,59 or esophago-gastric cancer cohorts more specifically. 35 Prehabilitation also appears to reduce length of stay for cancer patients by approximately 2 days, 19,32 though again, this was not always replicated in gastrointestinal cancer cohorts. 35,57 Regarding postoperative mortality, prehabilitation does not have a protective effect across all cohorts at present.…”

Section: Name Cut-off Descriptionmentioning

confidence: 99%

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Strategies for optimal perioperative outcomes in gastric cancer

Engel

Goh

Minnella

et al. 2022

Journal of Surgical Oncology

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Cancer and surgery represent a major stress on the human body. Any condition that prevents patients from tolerating the physiological stress is a risk factor for poor outcome. There is a need to identify these impairments early in the process with a simple screening, followed by assessments that provide a holistic picture of the patient. The proposed path of multimodal prehabilitation acts synergistically with enhanced recovery after surgery care to achieve optimal patient outcomes.

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Section: Name Cut-off Descriptionmentioning

confidence: 68%

Section: Preoperative Assessment and Surgical Riskmentioning

confidence: 99%

“…A recent umbrella review 32 and meta-analysis 19 provide comprehensive outlines of the current state of prehabilitation research.…”

Section: Name Cut-off Descriptionmentioning

confidence: 99%

Section: Name Cut-off Descriptionmentioning

confidence: 99%

Section: Name Cut-off Descriptionmentioning

confidence: 99%

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Strategies for optimal perioperative outcomes in gastric cancer

Engel

Goh

Minnella

et al. 2022

Journal of Surgical Oncology

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Development and Validation of a Machine Learning Model to Identify Patients Before Surgery at High Risk for Postoperative Adverse Events

Mahajan,

Esper,

et al. 2023

JAMA Netw Open

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ImportanceIdentifying patients at high risk of adverse outcomes prior to surgery may allow for interventions associated with improved postoperative outcomes; however, few tools exist for automated prediction.ObjectiveTo evaluate the accuracy of an automated machine-learning model in the identification of patients at high risk of adverse outcomes from surgery using only data in the electronic health record.Design, Setting, and ParticipantsThis prognostic study was conducted among 1 477 561 patients undergoing surgery at 20 community and tertiary care hospitals in the University of Pittsburgh Medical Center (UPMC) health network. The study included 3 phases: (1) building and validating a model on a retrospective population, (2) testing model accuracy on a retrospective population, and (3) validating the model prospectively in clinical care. A gradient-boosted decision tree machine learning method was used for developing a preoperative surgical risk prediction tool. The Shapley additive explanations method was used for model interpretability and further validation. Accuracy was compared between the UPMC model and National Surgical Quality Improvement Program (NSQIP) surgical risk calculator for predicting mortality. Data were analyzed from September through December 2021.ExposureUndergoing any type of surgical procedure.Main Outcomes and MeasuresPostoperative mortality and major adverse cardiac and cerebrovascular events (MACCEs) at 30 days were evaluated.ResultsAmong 1 477 561 patients included in model development (806 148 females [54.5%; mean [SD] age, 56.8 [17.9] years), 1 016 966 patient encounters were used for training and 254 242 separate encounters were used for testing the model. After deployment in clinical use, another 206 353 patients were prospectively evaluated; an additional 902 patients were selected for comparing the accuracy of the UPMC model and NSQIP tool for predicting mortality. The area under the receiver operating characteristic curve (AUROC) for mortality was 0.972 (95% CI, 0.971-0.973) for the training set and 0.946 (95% CI, 0.943-0.948) for the test set. The AUROC for MACCE and mortality was 0.923 (95% CI, 0.922-0.924) on the training and 0.899 (95% CI, 0.896-0.902) on the test set. In prospective evaluation, the AUROC for mortality was 0.956 (95% CI, 0.953-0.959), sensitivity was 2148 of 2517 patients (85.3%), specificity was 186 286 of 203 836 patients (91.4%), and negative predictive value was 186 286 of 186 655 patients (99.8%). The model outperformed the NSQIP tool as measured by AUROC (0.945 [95% CI, 0.914-0.977] vs 0.897 [95% CI, 0.854-0.941], for a difference of 0.048), specificity (0.87 [95% CI, 0.83-0.89] vs 0.68 [95% CI, 0.65-0.69]), and accuracy (0.85 [95% CI, 0.82-0.87] vs 0.69 [95% CI, 0.66, 0.72]).Conclusions and RelevanceThis study found that an automated machine learning model was accurate in identifying patients undergoing surgery who were at high risk of adverse outcomes using only preoperative variables within the electronic health record, with superior performance compared with the NSQIP calculator. These findings suggest that using this model to identify patients at increased risk of adverse outcomes prior to surgery may allow for individualized perioperative care, which may be associated with improved outcomes.

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Prehabilitation for Patients Undergoing Orthopedic Surgery

et al. 2023

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ImportancePrehabilitation programs for patients undergoing orthopedic surgery have been gaining popularity in recent years. However, the current literature has produced varying results.ObjectiveTo evaluate whether prehabilitation is associated with improved preoperative and postoperative outcomes compared with usual care for patients undergoing orthopedic surgery.Data SourcesBibliographic databases (MEDLINE, CINAHL [Cumulative Index to Nursing and Allied Health Literature], AMED [Allied and Complementary Medicine], Embase, PEDRO [Physiotherapy Evidence Database], and Cochrane Central Register of Controlled Trials) were searched for published trials, and the Institute for Scientific Information Web of Science, System for Information on Grey Literature in Europe, and European clinical trials registry were searched for unpublished trials from January 1, 2000, to June 30, 2022.Study SelectionRandomized clinical trials (RCTs) comparing prehabilitation with standard care for any orthopedic surgical procedure were included.Data Extraction and SynthesisTwo independent reviewers screened trials. Data were pooled using a random-effects model. Recommendations were determined using the Grading of Recommendations Assessment, Development and Evaluation system and the study was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) reporting guideline.Main Outcomes and MeasuresPain, function, muscle strength, and health-related quality of life (HRQOL).ResultsForty-eight unique trials involving 3570 unique participants (2196 women [61.5%]; mean [SD] age, 64.1 [9.1] years) were analyzed. Preoperatively, moderate-certainty evidence favoring prehabilitation was reported for patients undergoing total knee replacement (TKR) for function (standardized mean difference [SMD], −0.70 [95% CI, −1.08 to −0.32]) and muscle strength and flexion (SMD, 1.00 [95% CI, 0.23-1.77]) and for patients undergoing total hip replacement (THR) for HRQOL on the 36-item Short Form Health Survey (weighted mean difference [WMD], 7.35 [95% CI, 3.15-11.54]) and muscle strength and abduction (SMD, 1.03 [95% CI, 0.03-2.02]). High-certainty evidence was reported for patients undergoing lumbar surgery for back pain (WMD, –8.20 [95% CI, −8.85 to −7.55]) and moderate-certainty evidence for HRQOL (SMD, 0.46 [95% CI, 0.13-0.78]). Postoperatively, moderate-certainty evidence favoring prehabilitation was reported for function at 6 weeks in patients undergoing TKR (SMD, −0.51 [95% CI, −0.85 to −0.17]) and at 6 months in those undergoing lumbar surgery (SMD, −2.35 [95% CI, −3.92 to −0.79]). Other differences in outcomes favoring prehabilitation were of low to very low quality of evidence.Conclusions and RelevanceIn this systematic review and meta-analysis of RCTs, moderate-certainty evidence supported prehabilitation over usual care in improving preoperative function and strength in TKR and HRQOL and muscle strength in THR, high-certainty evidence in reducing back pain, and moderate-certainty evidence in improving HRQOL in lumbar surgery. Postoperatively, moderate-certainty evidence supported prehabilitation for function following TKR at 6 weeks and lumbar surgery at 6 months. Prehabilitation showed promising results for other outcomes, although high risk of bias and heterogeneity affected overall quality of evidence. Additional RCTs with a low risk of bias investigating preoperative and postoperative outcomes for all orthopedic surgical procedures are required.

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Prehabilitation in adult patients undergoing surgery: an umbrella review of systematic reviews

Cited by 141 publications

References 94 publications

Strategies for optimal perioperative outcomes in gastric cancer

Strategies for optimal perioperative outcomes in gastric cancer

Development and Validation of a Machine Learning Model to Identify Patients Before Surgery at High Risk for Postoperative Adverse Events

Prehabilitation for Patients Undergoing Orthopedic Surgery

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