MétaCan
Menu
Back to cohort
Record W2396089100

Perbedaan Skor Pasien Osteoartritis Antara Sebelum dan Sesudah Terapi Ir dan Tens Berdasarkan Li (Lequesne Index) dan Womac (Western Ontario And Mcmaster Universities Osteoarthritis Index)

2015· dissertation· id· W2396089100 on OpenAlexaboutno aff
Beata Dinda Seruni

Bibliographic record

Venuenot available
Typedissertation
Languageid
FieldHealth Professions
TopicSports and Physical Education Research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineWOMACGynecologyOsteoarthritisPathology
DOInot available

Abstract

fetched live from OpenAlex

ABSTRAK Beata Dinda Seruni, G0012042, 2015. Perbedaan Skor Pasien Osteoartritis antara Sebelum dan Sesudah Terapi IR dan TENS Berdasarkan LI (Lequesne Index) dan WOMAC (Western Ontario and McMaster Universities Osteoarthritis Index). Skripsi, Fakultas Kedokteran Universitas Sebelas Maret, Surakarta. Latar Belakang: Osteoartritis (OA) merupakan penyakit sendi degeneratif dengan progresifitas yang lambat, bersifat kronis, serta menyebabkan dampak yang besar pada kesehatan masyarakat. Terapi modalitas yang diberikan dapat berupa Transcutaneous Electrical Nerve Stimulation (TENS) dan pemanasan sinar Infra Red (IR). Kuesioner yang paling banyak digunakan dan dianjurkan untuk pengukuran serta uji klinis OA ialah LI dan WOMAC. Penelitian ini bertujuan untuk mengetahui perbedaan skor pasien OA antara sebelum dan sesudah terapi IR dan TENS berdasarkan LI dan WOMAC Metode: Penelitian ini bersifat eksperimen semu (quasi experiment) dengan menggunakan metode the pre- and posttest without control design. Dalam penelitian ini, terdapat variabel perancu yang tidak dapat dikendalikan, yaitu aktivitas fisik, IMT, gaya hidup, dan penggunaan analgesik atau steroid. Pengambilan sampel dilakukan dengan teknik purposive sampling. Sampel merupakan 30 pasien rawat jalan OA Instalasi Rehabilitasi Medik RSUD Dr. Moewardi di Surakarta. Data diambil sebelum dan sesudah dilakukan 1 sesi terapi (4 kali terapi) IR dan TENS dengan kuesioner LI dan WOMAC. Distribusi data hasil penelitian dianalisis menggunakan uji Saphiro-Wilk. Bila distribusi data normal, dianalisis dengan uji t-berpasangan, sedangkan bila tidak normal, dianalisis dengan uji Wilcoxon. Hasil: Terdapat perbedaan yang bermakna skor pasien OA antara sebelum dan sesudah terapi IR dan TENS berdasarkan LI dan WOMAC, baik secara keseluruhan total skor maupun dari masing-masing indikator, yaitu nyeri, jarak yang ditempuh, daily activity life, dan kekakuan. Hal ini ditunjukkan dengan nilai p = 0,000 yang berarti p < 0,05. Nilai IK 95% pretest LI-posttest LI adalah antara 2,21664 sampai 3,15836. Sedangkan Nilai IK 95% pretest WOMAC-posttest WOMAC adalah antara 1,12331 sampai 1,35101. Simpulan: Terapi IR dan TENS efektif dalam mengurangi rasa nyeri, meningkatkan jarak yang ditempuh, memperbaiki daily activity life, dan mengurangi kekakuan.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.097
Threshold uncertainty score0.326

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0970.029

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 head0.039
GPT teacher head0.371
Teacher spread0.333 · 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 source (direct Gemma or distilled Codex), 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

Citations2
Published2015
Admission routes1
Has abstractyes

Explore more

Same topicSports and Physical Education ResearchFrench-language works237,207