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Cardiovascular Fitness In Recreational Athletes Prior To And After Anterior Cruciate Ligament Reconstruction

2019· article· en· W2954113890 on OpenAlexaff
Dean M. Cordingley, Sheila McRae, Jeff Leiter, Greg Stranges, Peter B. MacDonald

Bibliographic record

VenueMedicine & Science in Sports & Exercise · 2019
Typearticle
Languageen
FieldMedicine
TopicKnee injuries and reconstruction techniques
Canadian institutionsPan Am Clinic
Fundersnot available
KeywordsMedicineCardiorespiratory fitnessAnterior cruciate ligament reconstructionAnterior cruciate ligamentAthletesPhysical therapyRehabilitationSports medicineAerobic exercisePhysical fitnessQuality of life (healthcare)Prospective cohort studyVO2 maxRepeated measures designAnaerobic exerciseSurgeryInternal medicineHeart rateBlood pressure

Abstract

fetched live from OpenAlex

Emphasis of most rehabilitation programs following anterior cruciate ligament reconstruction surgery (ACLR) is on range of motion and strength, with little, if any, focus on the recovery of cardiovascular fitness. PURPOSE: To evaluate cardiovascular fitness of recreational athletes from injury to 12-months post ACLR. METHODS: This was a prospective case series. Patients were recruited from a sports medicine clinic with an ACL rupture confirmed on MRI. Participants must have been involved in aerobic sport at least twice a week based on self-report. Study time points were baseline (as soon after injury as possible; T1), 6 (T2)- and 12-months (T3) post-ACLR. The primary outcome measure was relative VO2 peak as measured during a graded aerobic exercise test (GXT) on a bike ergometer (Monark, Ergomedic 894E) using a metabolic measurement system (Oxycon Mobile, Carefusion). Secondary outcomes were absolute VO2 peak, Tegner activity score, and ACL-Quality of Life. Repeated measures ANOVA was performed to compare within groups between time points. RESULTS: Nineteen patients (13 male /6 female) consented at mean age of 22.9 ± 4.8 years. Baseline testing and surgery were performed 78 ± 48 and 152 ± 81 days post injury, respectively. Preoperative relative VO2 peak was 33.7 ± 6.3 mL·kg-1·min-1, at T2was 32.7 ± 8.9 mL·kg-1·min-1and at T3 was 32.7 ± 9.3 mL·kg-1·min-1 (p > 0.05). Based on ACSM cardiorespiratory fitness classifications by age and gender, there was no change in distribution from T1 to T3 (p=0.88). Tegner scores decreased from pre-injury to T1 (7.6 ± 1.5 vs. 3.2 ± 1.9; p<0.001), and improved by T3 (5.1 ± 2.1; p=0.003), but did not recover to pre-injury levels (p<0.001). ACL-QOL increased from T1 (32.9 ± 15.5) to T2 (53.5 ± 13.4; p<0.001) and to T3 (70.3 ± 18.7; p=0.008). Relative VO2 peak and Tegner score were not correlated at T1 but were at T3 (r= 0.735, p=0.001). CONCLUSION: Recreational athletes were aerobically deconditioned at two months post-ACL rupture and did not improve with 12-months of rehabilitation following ACLR. Pre-injury aerobic fitness level could not be determined, but participants may have become deconditioned waiting for surgery. Without a conscious effort to promote aerobic fitness, recreational athletes may return to play at a suboptimal performance level with increased risk of injury.

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)0.000
metaresearch head score (Gemma)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.007
GPT teacher head0.258
Teacher spread0.250 · 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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Citations0
Published2019
Admission routes1
Has abstractyes

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