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Record W2108499361 · doi:10.1136/ebn.8.4.115

Relaxing hip precautions increased patient satisfaction and promoted quicker return to normal activities after total hip arthroplasty

2005· letter· en· W2108499361 on OpenAlexaff
Faith J Forster

Bibliographic record

VenueEvidence-Based Nursing · 2005
Typeletter
Languageen
FieldMedicine
TopicOrthopaedic implants and arthroplasty
Canadian institutionsProvidence Health Care
Fundersnot available
KeywordsMedicineArthroplastySurgeryBlindingRandomized controlled trial

Abstract

fetched live from OpenAlex

Peak EL, Parvizi J, Ciminiello M, et al . The role of patient restrictions in reducing the prevalence of early dislocation following total hip arthroplasty. A randomized, prospective study. J Bone Joint Surg Am 2005;87–A:247–53.[OpenUrl][1][PubMed][2] Q In patients who have had uncemented primary total hip arthroplasty (THA), does removal of several postoperative functional restrictions (PFR) reduce the risk of postoperative dislocation? ### ![Graphic][3] Design: randomised controlled trial. ### ![Graphic][4] Allocation: not concealed. ### ![Graphic][5] Blinding: unblinded. ### ![Graphic][6] Follow up period: ⩾6 months ### ![Graphic][7] Setting: a university hospital in Philadelphia, Pennsylvania, USA. ### ![Graphic][8] Patients: 265 patients (303 hips) (mean age 58 y, 52% men) who received uncemented primary THA through an anterolateral approach. Exclusion criteria included previous surgery on the ipsilateral hip, hyperflexibility syndromes, and neuromuscular compromise (eg, Alzheimer’s or Parkinson’s disease). ### ![Graphic][9] Intervention: PFR (n = 152) or no PFR (n = 151). All patients were expected to limit the range of motion of the hip for the first 6 weeks to <90° of flexion and 45° of external and internal rotation, and to avoid … [1]: {openurl}?query=rft.jtitle%253DThe%2BJournal%2Bof%2BBone%2Band%2BJoint%2BSurgery%26rft.stitle%253DJBJS%26rft.aulast%253DJung%26rft.auinit1%253DY.-B.%26rft.volume%253D87%26rft.issue%253D1_suppl_2%26rft.spage%253D247%26rft.epage%253D263%26rft.atitle%253DReconstruction%2Bof%2Bthe%2BPosterior%2BCruciate%2BLigament%2Bwith%2Ba%2BMid-Third%2BPatellar%2BTendon%2BGraft%2Bwith%2BUse%2Bof%2Ba%2BModified%2BTibial%2BInlay%2BMethod%26rft_id%253Dinfo%253Apmid%252F16140798%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [2]: /lookup/external-ref?access_num=16140798&link_type=MED&atom=%2Febnurs%2F8%2F4%2F115.atom [3]: /embed/inline-graphic-1.gif [4]: /embed/inline-graphic-2.gif [5]: /embed/inline-graphic-3.gif [6]: /embed/inline-graphic-4.gif [7]: /embed/inline-graphic-5.gif [8]: /embed/inline-graphic-6.gif [9]: /embed/inline-graphic-7.gif

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)0.001
metaresearch head score (Gemma)0.005
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: Commentary · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0070.000

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 head0.019
GPT teacher head0.261
Teacher spread0.242 · 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
GenreCommentary

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

Citations1
Published2005
Admission routes1
Has abstractyes

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