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Record W4296226241 · doi:10.46799/jhs.v3i3.441

Pemberian Terapi Latihan, Ultrasound (US) Serta Transcutaneous Electrical Nerve Stimulation (TENS) Pada Pasien Osteoarthritis Knee Bilateral

2022· article· id· W4296226241 on OpenAlexaboutno aff
Kunti Latifah

Bibliographic record

VenueJurnal Health Sains · 2022
Typearticle
Languageid
FieldHealth Professions
TopicSports and Physical Education Research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineGynecology

Abstract

fetched live from OpenAlex

Osteoarthritis (OA) merupakan penyakit degeneratif yang berkembang lambat dan tersebar luas prevalensinya meningkat seiring bertambahnya usia pasien. Tujuan dari studi ini untuk mengendalikan nyeri yang dirasakan pasien serta meningkatkan kemampuan fungsional pada kegiatan sehari-hari yang dilakukan pasien. Penelitian ini termasuk case study yang dilakukan di salah satu rumah sakit yang ada di kota Surakarta pada seorang pasien Ny. S, Berusia 63 tahun, berprofesi sebagai ibu rumah tangga. Pasien mengeluhkan nyeri pada saat gerakan dari jongkok ke berdiri terutama saat gerakan sujud ke berdiri saat beribadah yaitu salat Nyeri yang di rasakan pasien terkadang hilang saat kondisi istirahat dan tidak terlalu banyak aktifitas berat yang dilakukan. Pasien terapi selama 2 x/ minggu dalam 3 minggu, satu kali terapi mengikuti selama 30 menit. Pasien diberikan terapi berupa terapi latihan, ultrasound dan tens. nyeri diukur menggunakan Visual Descriptive Scale (VDS), dan Western Ontario dan McMaster Universities Arthritis Index (WOMAC) untuk mengukur aktivitas fungsional pasien. Modalitas fisioterapi seperti Pemberian Latihan Quadriceps Setting, Passive Stretching, Ultrasound (US), serta Transcutaneous Electrical Nerve Stimulation (TENS) yang diberikan sebanyak 4 kali pertemuan belum mampu meningkatkan aktivitas fungsional sehari-hari serta terdapat sedikit penurunan nyeri

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)0.002
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 categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.285
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0050.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.004
Insufficient payload (model declined to judge)0.0150.000

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 head0.035
GPT teacher head0.382
Teacher spread0.347 · 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

Citations3
Published2022
Admission routes1
Has abstractyes

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