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Record W3013834289 · doi:10.52386/neurona.v37i1.98

HUBUNGAN INTENSITAS NYERI PUNGGUNG BAWAH UNILATERAL DENGAN DERAJAT OSTEOARTRITIS LUTUT KONTRALATERA

2019· article· en· W3013834289 on OpenAlexaboutno aff
Edy Irwanto, Dwi Pudjonarko, Hermina Sukmaningtyas

Bibliographic record

VenueMajalah Kedokteran Neurosains Perhimpunan Dokter Spesialis Saraf Indonesia · 2019
Typearticle
Languageen
FieldHealth Professions
TopicSports and Physical Education Research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineOsteoarthritisPhysical therapyWOMACKnee JointLogistic regressionKnee painSurgeryInternal medicine

Abstract

fetched live from OpenAlex

THE CORRELATION OF UNILATERAL LOW BACK PAIN INTENSITY AND THE DEGREE OF CONTRALATERAL KNEE OSTEOARTHRITISABSTRACTIntroduction: Low back pain (LBP) is one of the most common and recurring forms of musculoskeletal pain. In back injuries or disc degenerative diseases that cause chronic LBP will increase the burden on the knee joint, thereby triggering or exacerbating the occurrence of osteoarthritis (OA) of the knee.Aims: To analyze the correlation of unilateral LBP intensity and the degree of contralateral knee OA.Methods: Cross-sectional observational analytic study of LBP patients who went to the neurology polyclinic of RSUP Dr. Kariadi, Semarang, from November 2018 to March 2019. The diagnosis of knee OA was made clinically based on the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) questionnaire and radiological with Kellgren-Lawrence scores. Fisher’s exact test was used to see the correlation between variables, and the results of the bi- variate analysis was continued with a logistic regression multivariate test to find out the variables that influence the degree of knee OA.Results: There were 36 subjects, the majority of which were women (58.3%) with an average age of 53.88±11.01 years. A significant relationship was found between the unilateral LBP intensity (p=0.004; Odds ratio/OR=32,500) and malalignment of the knee joint (p=0.024; OR=11.67) with the degree of contralateral knee OA based on the WOMAC score.Discussion: The unilateral LBP intensity and malalignment of the knee joint can increase the risk of contralateral knee OA based on WOMAC scores of 32.5 and 11.7 times, respectively.Keywords: Kellgren-Lawrence score, low back pain, osteoarthritis of the knee, WOMAC scoreABSTRAKPendahuluan: Nyeri punggung bawah (NPB) adalah salah satu bentuk nyeri muskuloskeletal yang paling umum terjadi dan dapat berulang. Pada cedera punggung atau penyakit degeneratif diskus yang menyebabkan NBP kronik akan meningkatkan beban pada sendi lutut, sehingga memicu atau memperparah terjadinya osteoartritis (OA) lutut.Tujuan: Untuk mengetahui hubungan intensitas NPB unilateral dengan derajat OA lutut kontralateral.Metode: Penelitian analitik observasional secara potong lintang terhadap pasien NPB yang berobat ke Poliklinik Saraf RSUP Dr. Kariadi, Semarang, pada bulan November 2018 hingga Maret 2019. Diagnosis OA lutut ditegakkan ber- dasarkan klinis menggunakan kuesioner Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) dan radiologis dengan skor Kellgren-Lawrence. Korelasi antar variabel menggunakan uji Fisher’s exact, hasil analisis bivariat dilanjutkan dengan uji multivariat regresi logistik untuk mengetahui variabel yang berpengaruh terhadap derajat OA lutut.Hasil: Didapatkan 36 subjek yang mayoritas perempuan (58,3%) dengan rerata usia 53,88±11,01 tahun. Didapatkan hubungan yang bermakna antara intensitas NPB unilateral (p=0,004; rasio Odds/RO=32,500) dan malalignment sendi lutut (p=0,024; RO=11,67) dengan derajat OA lutut kontralateral berdasarkan skor WOMAC.Diskusi: Intensitas NPB unilateral dan malalignment sendi lutut dapat meningkatkan risiko terjadinya OA lutut kontralateral berdasarkan skor WOMAC masing-masing sebanyak 32,5 dan 11,7 kali.Kata kunci: Nyeri punggung bawah, osteoartritis lutut, skor WOMAC, skor Kellgren-Lawrence

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 categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.129
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0020.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0040.003

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 head0.024
GPT teacher head0.367
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; both teacher heads agree on what is shown here.

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
Published2019
Admission routes1
Has abstractyes

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