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Record W4405475048 · doi:10.53730/ijhs.v8ns1.15464

Assessment study of how much Egyptian patients are satisfied following total knee arthroplasty

2024· article· en· W4405475048 on OpenAlexaboutno aff
Mahmoud Mohamed Abas El-Batra, Ayman Ebied, Bahaa Zakarya Hasan, Osama Abd El-Mohsen Sherif

Bibliographic record

VenueInternational Journal of Health Sciences · 2024
Typearticle
Languageen
FieldMedicine
TopicTotal Knee Arthroplasty Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsTotal knee arthroplastyMedicineArthroplastyPhysical therapyGeneral surgerySurgery

Abstract

fetched live from OpenAlex

Background: Advanced stages of Knee OA can be incapacitating as a result of reduced functional range of motion and pain. Joint replacement may be needed for end-stage arthritis. Among the patient-reported outcome measures is patient satisfaction. Objectives: To study patients’ satisfaction one year later of total knee arthroplasty using different outcome measures and scoring systems. Patients & Methods: This was a prospective cohort study that was performed at Menoufia University Hospitals on 132 patients who received primary TKR. All participants were subjected to complete personal and medical history, and general examination including BMI and vital signs (heart, respiratory rate, and blood pressure). Preoperative investigations include CBC, serum creatinine, RBS, Liver function tests), Electrocardiogram, imaging studies such as (knee X-ray, CT, MRI, and bone densitometry). Surgical steps for TKR, postoperative care (hydration, analgesia). Knee joint physiotherapy until discharge. Study tools: Knee Society score, Western Ontario and McMaster Universities Osteoarthritis Index score. Patient satisfaction (The patient is asked if he would recommend total knee replacement for his relatives or not. Visual Analogue Scale). Results: The average age of the study group was 58.47±8.037 years, BMI 28.79±1.364 with 78.7%were females. 72.9% of the study group were satisfied with TKR.

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)0.000
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 score0.042
Threshold uncertainty score0.375

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0000.000

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 head0.027
GPT teacher head0.370
Teacher spread0.343 · 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".

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Citations0
Published2024
Admission routes1
Has abstractyes

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