How Do We Value Postoperative Recovery?
Bibliographic record
Abstract
OBJECTIVE: To appraise the level of evidence supporting the measurement properties of patient-reported outcome measures (PROMs) in the context of postoperative recovery after abdominal surgery. BACKGROUND: There is growing interest in using PROMs to support value-based care in abdominal surgery; however, to draw valid conclusions regarding patient-reported outcomes data, PROMs with robust measurement properties are required. METHODS: Eight databases (MEDLINE, EMBASE, Biosis, PsycINFO, The Cochrane Library, CINAHL, Scopus, Web of Science) were searched for studies focused on the measurement properties of PROMs in the context of recovery after abdominal surgery. The methodological quality of individual studies was evaluated using the consensus-based COSMIN checklist. Evidence supporting the measurement properties of each PROM was synthetized according to standardized criteria and compared against the International Society of Quality of Life Research minimum standards for the selection of PROMs for outcomes research. RESULTS: We identified 35 studies evaluating 22 PROMs [12 focused on nonspecific surgical populations (55%), 4 focused on abdominal surgery (18%), and 6 generic PROMs (27%)]. The great majority of the studies (74%) received only poor or fair quality ratings. Measurement properties of PROMs were predominantly supported by limited or unknown evidence. None of the PROMs fulfilled International Society of Quality of Life Research's minimum standards, hindering specific recommendations. CONCLUSIONS: There is very limited evidence supporting the measurement properties of existing PROMs used in the context of recovery after abdominal surgery. This precludes the use of these PROMs to support value-based surgical care. Further research is required to bridge this major knowledge gap. REVIEW REGISTRATION: International Prospective Register of Systematic Reviews (PROSPERO): CRD42014014349.
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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 | 0.058 | 0.282 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".