Meniscal Tear Outcome (METRO) review: a protocol for a systematic review summarising the clinical course and patient experiences of meniscal tears in the current literature
Bibliographic record
Abstract
INTRODUCTION: Meniscal tears are a common knee injury with an incidence of 60 per 100 000. Management of meniscal tears can include either non-operative measures or operative procedures such as arthroscopic partial meniscectomy (APM). Despite substantial research evaluating the effectiveness of APM in the recent past, little is known about the clinical course or the experiences of patients with a meniscal tear. AIM: To summarise the short to long-term patterns of variability in outcome in patients with a meniscal tear.To summarise the evidence on patient experiences of meniscal tears. In particular, we will focus on patient experiences of treatment options, treatment pathways and their views of the outcomes used in meniscal tear research. METHODS AND ANALYSIS: Two search strategies will be developed to identify citations from EMBASE, MEDLINE, AMED, CENTRAL, Web of Science and Sociofile. The date of our planned search is 14 August 2020. For the quantitative review we will identify studies reporting patient-reported outcome measures in patients after a meniscal tear. The standardised mean change will be used to assess the variation in size of response and summarise the overall response to each treatment option. All studies will undergo quality assessment using either the Cochrane risk of bias or the Newcastle-Ottawa tool.A qualitative systematic review will be used to identify studies reporting views and experiences of patients with a meniscal tear. All studies will be assessed using the Critical Appraisal Skills Programme tool and if sufficient data are present a meta-synthesis will be performed to identify first, second and third-order constructs. ETHICS AND DISSEMINATION: Given the nature of this study, no formal ethical approval will be sought. Results from the review will be disseminated at national conferences and will be submitted to a peer-reviewed journal for publication. Lay summaries will be freely available via the study Twitter page. PROSPERO REGISTRATION NUMBER: CRD42019122179.
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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 | 0.066 | 0.087 |
| Meta-epidemiology (narrow) | 0.006 | 0.005 |
| Meta-epidemiology (broad) | 0.022 | 0.015 |
| Bibliometrics | 0.020 | 0.020 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.010 | 0.011 |
| Open science | 0.005 | 0.008 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.081 | 0.010 |
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".