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Record W4206226551 · doi:10.1097/md.0000000000028557

Comparative clinical outcomes of different therapies for traumatic meniscal tears in adults

2022· article· en· W4206226551 on OpenAlexaboutno aff

Bibliographic record

VenueMedicine · 2022
Typearticle
Languageen
FieldMedicine
TopicKnee injuries and reconstruction techniques
Canadian institutionsnot available
FundersNatural Science Foundation of Gansu Province
KeywordsCochrane LibraryRandomized controlled trialTearsMEDLINEMeta-analysisMeniscusSystematic reviewEvidence-based medicine

Abstract

fetched live from OpenAlex

Abstract Background: Meniscus tears are usually classified as degenerative or traumatic tears according to their pathogenesis. At present, traumatic meniscal tears are generally believed to have high healing potential. In recent years, multiple treatments have been described for traumatic meniscal tears, such as the inside-out technique, outside-in technique, all-inside technique, biological augmentation of meniscal repair, meniscectomy, and non-surgical treatment. However, the functional recovery of the knee joint and healing of the meniscus after treatment are quite different from the results reported in the literature, which requires more reliable evidence-based medical findings. This study will evaluate evidence from multiple types of research comparing different therapies for traumatic meniscal tears in adults. Methods We will search the EMBASE, Cochrane Library (the Cochrane Database of Systematic Reviews, the Cochrane Central Register of Controlled Trials [CENTRAL], Cochrane Methodology Register), PubMed, Web of Science (Science and Social Science Citation Index), China Knowledge Network, CBM, Wanfang data, and VIP electronic databases from their inception to August 10, 2021, with no language restrictions. We will also manually search Baidu and Google Scholar to identify randomized controlled studies, non-randomized controlled studies, and cohort studies on the treatment of traumatic meniscal tears. Two researchers will independently screen the literature, extract the data, and evaluate the quality of the studies. Software programs, including Microsoft Access, Excel, Stata (Version 15), WinBUGS (Version 1.4.3), and ADDIS (Version 1.16.8), were used to analyze and manipulate the data. Results In this study, the main outcomes were physical function and healing rate, based on the Western Ontario and McMaster Universities Osteoarthritis Index, Lysholm Knee Scoring Scale, Knee Injury and Osteoarthritis Outcome Score, Functional Recovery Scale, and clinical healing rate. The secondary indexes included total cost, cost-effectiveness ratio, incremental cost-effectiveness ratio, Tegner activity scale score, visual analogue scale, numerical rating scale, and meniscal tear complications. Conclusions: This systematic review will provide reliable evidence-based findings for the clinical application of different therapies for traumatic meniscal tears in adults.

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)0.008
metaresearch head score (Gemma)0.025
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.025
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0050.009
Bibliometrics0.0040.004
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.062
GPT teacher head0.407
Teacher spread0.345 · 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 designObservational
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".

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Citations1
Published2022
Admission routes1
Has abstractyes

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