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Record W3122620003 · doi:10.1097/nor.0000000000000725

Total Knee Arthroplasty in the Ambulatory Surgery Center Setting

2021· article· en· W3122620003 on OpenAlexaff
Mary Atkinson Smith, William Todd Smith, Danielle Atchley, Lance Atchley

Bibliographic record

VenueOrthopaedic Nursing · 2021
Typearticle
Languageen
FieldMedicine
TopicTotal Knee Arthroplasty Outcomes
Canadian institutionsSmiths Detection (Canada)
Fundersnot available
KeywordsMedicineAmbulatoryPhysical therapyArthroplastyPopulationOsteoarthritisAmbulatory careHealth carePatient educationNursingSurgeryAlternative medicine

Abstract

fetched live from OpenAlex

As the current population continues to increase in age, so does the degeneration of the musculoskeletal system and the development of knee osteoarthritis. Total knee arthroplasty (TKA) will be the treatment of choice when it comes to improving physical function and decreasing pain associated with osteoarthritis of the knee. The global push for more cost-effective healthcare services has led to new models of care and payment delivery methods such as performing TKA in the ambulatory surgery center (ASC) setting. With deeply invasive surgical procedures such as TKA being done in the ASC setting, orthopaedic nurses must be mindful of best practices that will promote quality and safety while considering the importance of using current evidence to guide nursing practice when promoting appropriate patient selection and effective patient education of self-management of postoperative care pertaining to TKA being performed in the ASC setting. This is critical to consider during a time when financial profits in the ASC setting may take a front seat to the delivery of high-quality and safe patient care.

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)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.102
Threshold uncertainty score0.713

Codex and Gemma teacher scores by category

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

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 head0.014
GPT teacher head0.264
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 teacher head, 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".

Quick stats

Citations7
Published2021
Admission routes1
Has abstractyes

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