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Record W2122086679 · doi:10.1503/cjs.028510

An electronic clinic for arthroplasty follow-up: a pilot study

2011· article· en· W2122086679 on OpenAlexaffvenue
Gavin Wood

Bibliographic record

VenueCanadian Journal of Surgery · 2011
Typearticle
Languageen
FieldMedicine
TopicTotal Knee Arthroplasty Outcomes
Canadian institutionsQueen's University
Fundersnot available
KeywordsMedicinePhysical therapyArthroplastyCohortOrthopedic surgeryAttendanceOutpatient clinicJoint arthroplastySurgeryInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Most outpatient orthopedic follow-up visits for patients who had total joint arthroplasty are routine among those with well-functioning implants. The technology and resources now exist to enable patient assessment without requiring attendance in hospital. We tested an electronic clinic for routine follow-up in a small cohort of arthroplasty patients. METHODS: We randomly assigned primary arthroplasty patients scheduled for routine annual outpatient review into 2 groups: group A completed a Web-based assessment 4 weeks after the clinical assessment, whereas group B completed the Web-based assessment first. Standard clinical questionnaires were included. We also collected radiographic data and information on assessment duration and cost. RESULTS: Forty patients participated in the study. The average age of participants was 58 years. There were 12 men and 8 women in each of the 2 groups. The average total time spent by patients on an outpatient visit was 115 minutes, compared with 52 minutes for the electronic assessment. Participants reported the electronic assessment to be more convenient and less costly. CONCLUSION: This pilot study supports the practical use of an electronic clinic for the follow-up of arthroplasty patients. Further studies examining the complex interaction of factors involved in patient clinics are needed.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.063
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.091
GPT teacher head0.291
Teacher spread0.200 · 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.

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

Citations40
Published2011
Admission routes2
Has abstractyes

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