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Record W4400981097 · doi:10.55684/2024.82.e033

Quanto de perda volumétrica e de força do músculo quadríceps femoral éesperada no pós-operatório da reconstrução do ligamento cruzado anterior?

2024· article· en· W4400981097 on OpenAlexaff
André Luis Menezes Schwansee Thiele, Jurandir Marcondes Ribas-Filho, Edilson Schwansee Thiele, Luis Fernando Menezes Schwansee Thiele, Ronaldo Máfia Cuenca, Rafael Dib Possiedi, Nelson Adami Andreollo

Bibliographic record

VenueBioSCIENCE · 2024
Typearticle
Languageen
FieldMedicine
TopicKnee injuries and reconstruction techniques
Canadian institutionsSunnybrook HospitalUniversity of Toronto
Fundersnot available
KeywordsMuscle strengthQuadriceps muscleAnatomyLigamentMedicineFemoral boneMechanical strengthFemurSurgeryPhysical medicine and rehabilitationMaterials science

Abstract

fetched live from OpenAlex

Introduction: When injured and/or reconstructed the anterior cruciate ligament, not only occurs decrease in strength, but also less contraction of the quadriceps, in addition to muscle atrophy. Magnetic resonance imaging and isokinetic dynamometry have offered better evaluation of the pre- and post-surgical periods and can better monitor and predict postoperative rehabilitation. Objectives: To review the role of volume and strength of the quadriceps femoris muscle before and after reconstruction of the anterior cruciate ligament and how these measurements correlate with the predictive variables of pre- and postoperative muscle strength. Method: Integrative review collecting information on virtual platforms. The texts were selected from SciELO, Google Scholar, Pubmed and Scopus. The descriptors related to the topic were the following: anterior cruciate ligament reconstruction; magnetic resonance imaging; quadriceps muscle in Portuguese and English with AND or OR search, considering the title and/or abstract. Results: The entire selected texts were read and 61 articles were included. Conclusion: A loss of volume and strength of the quadriceps muscle was observed after reconstruction. The loss of strength was 4 times greater than the preoperative volume and 2 times greater postoperatively, with improvement 4 months after the operation.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.691
Threshold uncertainty score0.974

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.016
GPT teacher head0.316
Teacher spread0.301 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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