Prehabilitation and enhanced recovery after thoracic surgery: a narrative review
Bibliographic record
Abstract
Background and Objective: Over the past two decades enhanced recovery after surgery (ERAS) pathways, which were established initially in colorectal surgery, have evolved and been adapted for other surgical disciplines.Goals include minimizing complications, optimizing recovery and an efficient return to preoperative baseline functioning.The introduction of ERAS pathways has led to both clinical benefits as well as cost savings.As these pathways consist of bundles of interventions throughout the perioperative period, the relative contribution of each individual component of these programs remains to be elucidated.The following narrative review article explores the application of ERAS principles to the thoracic surgery population.The evidence for individual components of these pathways will be discussed.Additionally, the introduction of prehabilitation interventions to the care of these patients will be explored.A brief case example is provided to illustrate how such interventions can aid in perioperative decision making.Methods: Medical computerized databases (PubMed and Cochrane Library) were searched for relevant reviews and guidelines published in English up to March 31, 2021, and hand searches of the references were performed.Articles were reviewed but no formal statistical analysis was undertaken.Key Content and Findings: Preoperative, intraoperative and postoperative elements of ERAS pathways were examined.Some elements, such as smoking cessation, have fairly robust evidence of benefit, but questions still remain regarding optimal duration of intervention especially when weighed against surgical delay.Others, for example preoperative carbohydrate loading, may lack significant evidence of improved outcomes but have been adopted widely because of ow perceived risk of harm.Formal prehabilitation programs show promise, particularly in the lung resection population.Conclusions: Implementation of ERAS pathways has benefited thoracic surgical patients, however there is varying strength with regards to the evidence for individual components.There is an ongoing need to better define the roles of individual elements of these pathways and to further advance knowledge regarding the optimal ways in which to apply some of them.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".