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Record W2809487322 · doi:10.1136/bjsports-2018-099397

2018 Consensus statement on exercise therapy and physical interventions (orthoses, taping and manual therapy) to treat patellofemoral pain: recommendations from the 5th International Patellofemoral Pain Research Retreat, Gold Coast, Australia, 2017

2018· article· en· W2809487322 on OpenAlexaff
Natalie J. Collins, Christian J. Barton, Marienke van Middelkoop, Michael J. Callaghan, Michael Skovdal Rathleff, Bill Vicenzino, Irene S. Davis, Christopher M. Powers, Erin M. Macri, Harvi F. Hart, Danilo de Oliveira Silva, Kay M. Crossley

Bibliographic record

VenueBritish Journal of Sports Medicine · 2018
Typearticle
Languageen
FieldEngineering
TopicLower Extremity Biomechanics and Pathologies
Canadian institutionsWestern UniversityUniversity of British Columbia
Fundersnot available
KeywordsMedicinePhysical therapySystematic reviewPatellofemoral pain syndromePsychological interventionManual therapyRandomized controlled trialKnee painRehabilitationPopulationDry needlingMEDLINEPhysical medicine and rehabilitationAlternative medicineAcupunctureOsteoarthritisNursingSurgery

Abstract

fetched live from OpenAlex

Patellofemoral pain affects a large proportion of the population, from adolescents to older adults, and carries a substantial personal and societal burden. An international group of scientists and clinicians meets biennially at the International Patellofemoral Research Retreat to share research findings related to patellofemoral pain conditions and develop consensus statements using best practice methods. This consensus statement, from the 5th International Patellofemoral Research Retreat held in Australia in July 2017, focuses on exercise therapy and physical interventions (eg, orthoses, taping and manual therapy) for patellofemoral pain. Literature searches were conducted to identify new systematic reviews and randomised controlled trials (RCTs) published since the 2016 Consensus Statement. The methodological quality of included systematic reviews and RCTs was graded using AMSTAR and PEDro, respectively. Evidence-based statements were developed from included papers and presented to a panel of 41 patellofemoral pain experts for consensus discussion and voting. Recommendations from the expert panel support the use of exercise therapy (especially the combination of hip-focused and knee-focused exercises), combined interventions and foot orthoses to improve pain and/or function in people with patellofemoral pain. The use of patellofemoral, knee or lumbar mobilisations in isolation, or electrophysical agents, is not recommended. There is uncertainty regarding the use of patellar taping/bracing, acupuncture/dry needling, manual soft tissue techniques, blood flow restriction training and gait retraining in patients with patellofemoral pain. In 2017, we launched the International Patellofemoral Research Network (www.ipfrn.org) to consolidate and grow our patellofemoral research community, facilitate collaboration and disseminate patellofemoral pain knowledge to clinicians and the general public. The 6th International Patellofemoral Research Retreat will be held in Milwaukee, Wisconsin, USA, in October 2019.

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)0.088
metaresearch head score (Gemma)0.115
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.088
Threshold uncertainty score0.463

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0880.115
Meta-epidemiology (narrow)0.0030.003
Meta-epidemiology (broad)0.0070.014
Bibliometrics0.0100.006
Science and technology studies0.0030.003
Scholarly communication0.0070.006
Open science0.0110.009
Research integrity0.0170.019
Insufficient payload (model declined to judge)0.0140.012

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 head0.162
GPT teacher head0.381
Teacher spread0.219 · 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 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

Citations358
Published2018
Admission routes1
Has abstractyes

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