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Record W4402381448 · doi:10.53555/ks.v12i4.3078

Frequency of Grade III Knee Osteoarthritis among Women in Gujranwala Pakistan

2024· article· en· W4402381448 on OpenAlexaboutno aff
Asif Yousaf

Bibliographic record

VenueKurdish Studies · 2024
Typearticle
Languageen
FieldMedicine
TopicRheumatoid Arthritis Research and Therapies
Canadian institutionsnot available
Fundersnot available
KeywordsOsteoarthritisMedicinePhysical therapyPhysical medicine and rehabilitationAlternative medicine

Abstract

fetched live from OpenAlex

Objective: To ascertain the prevalence of Grade (III) osteoarthritis (OA) in the knees among women in Gujranwala, Pakistan. Method: The cross-sectional study was carried out over the course of six months (January 2023–July 2023) at the orthopedic outpatient program at Gujranwala Teaching Hospital. This study used a 100-person sample size. The Inclusion Criteria is Women between the ages of 55 and 70 who had Grade (III) knee osteoarthritis were included. Additionally, women with a history of cancer are eliminated, as are women who did not provide us with their consent. The method of convenient sampling was applied. Data was gathered through the use of McMaster and Western Ontario Universities. Index of Osteoarthritis (WOMAC). Data analysis was done with SPSS version 21.   Results: The study's findings indicate that the participants' mean age was 53.8 + 6.024. 10% (10) of the 100 individuals indicated that they had no pain when walking. 17% indicated slight PAIN, 33% indicated mild pain while walking, 27% reported moderate pain and 24% reported severe pain. Twelve percent of the 100 individuals indicated that they have no pain when climbing stairs. (13) 13% reported slight pain (24) 24% reported moderate pain, and so on. When climbing stairs, 26% reported severe pain.   Conclusion: The study's conclusion was that women experienced knee pain quite frequently. Many tasks of daily living, such as getting out of bed, lying down, using the restroom, or bending down, are made difficult by chronic knee pain.

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)0.000
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 score0.277
Threshold uncertainty score0.593

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
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 head0.017
GPT teacher head0.320
Teacher spread0.303 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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