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Record W4361293588 · doi:10.1001/jamasurg.2023.0198

Effect of Multimodal Prehabilitation on Reducing Postoperative Complications and Enhancing Functional Capacity Following Colorectal Cancer Surgery

2023· article· en· W4361293588 on OpenAlexaff
Charlotte J. L. Molenaar, Enrico Maria Minnella, Miquel Coca-Martínez, David W.G. ten Cate, Marta Regis, Rashami Awasthi, Graciela Martínez‐Palli, Manuel López-Baamonde, Raquel Sebio, Carlo V. Feo, Stefanus J. van Rooijen, Jennifer M. J. Schreinemakers, Rasmus Dahlin Bojesen, Ismail Gögenür, Edwin R. van den Heuvel, Francesco Carli, Gerrit D. Slooter, Rudi M. H. Roumen, Loes Janssen, Jeanne P. Dieleman, Nicky Rademakers, Cathrin van Erven, Goof Schep, Suzanne A.L.M. van Lankvelt, Sandra Beijer, W van der Meij, Bhagya Tahasildar, Susanne Oksbjerg Dalton, Rosa Asbert Sagasti, Marta Ubré, Betina Campero, Marina Sisó, Raquel Risco, Silvia Terés, Antonio M. Lacy, Alessandro De Troia, Giovanni Grazzi

Bibliographic record

VenueJAMA Surgery · 2023
Typearticle
Languageen
FieldMedicine
TopicEnhanced Recovery After Surgery
Canadian institutionsMcGill UniversityMontreal General Hospital
Fundersnot available
KeywordsMedicinePrehabilitationColorectal cancerColorectal surgeryMultimodal therapySurgeryCancerGeneral surgeryAnesthesiaAbdominal surgeryPhysical therapyInternal medicine

Abstract

fetched live from OpenAlex

Importance: Colorectal surgery is associated with substantial morbidity rates and a lowered functional capacity. Optimization of the patient's condition in the weeks prior to surgery may attenuate these unfavorable sequelae. Objective: To determine whether multimodal prehabilitation before colorectal cancer surgery can reduce postoperative complications and enhance functional recovery. Design, Setting, and Participants: The PREHAB randomized clinical trial was an international, multicenter trial conducted in teaching hospitals with implemented enhanced recovery after surgery programs. Adult patients with nonmetastasized colorectal cancer were assessed for eligibility and randomized to either prehabilitation or standard care. Both arms received standard perioperative care. Patients were enrolled from June 2017 to December 2020, and follow-up was completed in December 2021. However, this trial was prematurely stopped due to the COVID-19 pandemic. Interventions: The 4-week in-hospital supervised multimodal prehabilitation program consisted of a high-intensity exercise program 3 times per week, a nutritional intervention, psychological support, and a smoking cessation program when needed. Main Outcomes and Measures: Comprehensive Complication Index (CCI) score, number of patients with CCI score more than 20, and improved walking capacity expressed as the 6-minute walking distance 4 weeks postoperatively. Results: In the intention-to-treat population of 251 participants (median [IQR] age, 69 [60-76] years; 138 [55%] male), 206 (82%) had tumors located in the colon and 234 (93%) underwent laparoscopic- or robotic-assisted surgery. The number of severe complications (CCI score >20) was significantly lower favoring prehabilitation compared with standard care (21 of 123 [17.1%] vs 38 of 128 [29.7%]; odds ratio, 0.47 [95% CI, 0.26-0.87]; P = .02). Participants in prehabilitation encountered fewer medical complications (eg, respiratory) compared with participants receiving standard care (19 of 123 [15.4%] vs 35 of 128 [27.3%]; odds ratio, 0.48 [95% CI, 0.26-0.89]; P = .02). Four weeks after surgery, 6-minute walking distance did not differ significantly between groups when compared with baseline (mean difference prehabilitation vs standard care 15.6 m [95% CI, -1.4 to 32.6]; P = .07). Secondary parameters of functional capacity in the postoperative period generally favored prehabilitation compared with standard care. Conclusions and Relevance: This PREHAB trial demonstrates the benefit of a multimodal prehabilitation program before colorectal cancer surgery as reflected by fewer severe and medical complications postoperatively and an optimized postoperative recovery compared with standard care. Trial Registration: trialregister.nl Identifier: NTR5947.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.023
GPT teacher head0.290
Teacher spread0.267 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNon-randomized trial
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations442
Published2023
Admission routes1
Has abstractyes

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