Systematic review of outcomes used to evaluate enhanced recovery after surgery
Bibliographic record
Abstract
BACKGROUND: Enhanced recovery pathways (ERPs) aim to improve patient recovery. However, validated outcome measures to evaluate this complex process are lacking. The objective of this review was to identify how recovery is measured in ERP studies and to provide recommendations for the design of future studies. METHODS: A systematic search of MEDLINE, Embase and Cochrane databases was conducted. Prospective studies evaluating ERPs compared with traditional care in abdominal surgery published between 2000 and 2013 were included. All reported outcomes were classified into categories: biological and physiological variables, symptom status, functional status, general health perceptions and quality of life (QoL). The phase of recovery measured was defined as baseline, intermediate (in hospital) and late (following discharge). RESULTS: A total of 38 studies were included based on the systematic review criteria. Biological or physiological variables other than postoperative complications were reported in 30 studies, and included return of gastrointestinal function (25 studies), pulmonary function (5) and physical strength (3). Patient-reported symptoms, including pain (16 studies) and fatigue (9), were reported less commonly. Reporting of functional status outcomes, including mobilization (16 studies) and ability to perform activities of daily living (4), was similarly uncommon. Health aspects of QoL were reported in only seven studies. Length of follow-up was generally short, with 24 studies reporting outcomes within 30 days or less. All studies documented in-hospital outcomes (intermediate phase), but only 17 reported postdischarge outcomes (late phase) other than complications or readmission. CONCLUSION: Patient-reported outcomes, particularly postdischarge functional status, were not commonly reported. Future studies of the effectiveness of ERPs should include validated, patient-reported outcomes to estimate better their impact on recovery, particularly after discharge from hospital.
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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 | 0.016 | 0.080 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.012 |
| Bibliometrics | 0.020 | 0.018 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".