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Record W2896907539 · doi:10.4103/ijpc.ijpc_14_18

Comparative impact of nonpharmacological interventions on pain of knee osteoarthritis patients reporting at a tertiary care institution: A randomized controlled trial

2018· article· en· W2896907539 on OpenAlexaboutno aff
Meenakshi Sharma, Amarjeet Singh, Mandeep Singh Dhillon, Sukhpal Kaur

Bibliographic record

VenueIndian Journal of Palliative Care · 2018
Typearticle
Languageen
FieldMedicine
TopicOsteoarthritis Treatment and Mechanisms
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineWOMACOsteoarthritisPhysical therapyRandomized controlled trialVisual analogue scalePsychological interventionRandomizationPopulationMeditationInternal medicineAlternative medicine

Abstract

fetched live from OpenAlex

CONTEXT: Nonpharmacological interventions (NPIs) have been advocated for knee osteoarthritis (KOA). There are many gaps in the evidence to their efficacy in India. AIMS: The study aims to compare the impact of two packages of NPIs on various outcome variables of KOA patients. SETTINGS AND DESIGN: This was a randomized controlled trial in a tertiary care hospital. SUBJECTS AND METHODS: = 123) of KOA patients aged 40-65 years. Stratified block randomization was done for mild or moderate KOA into two groups. Group "A" patients received a package of NPIs including a set of supervised exercise sessions, kinesthesia, balance, and agility (KBA), meditation, weight reduction advice, and weekly telephonic reminders. Group "B" patients received the same package except for KBA & meditation. Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), visual analog scale (VAS) and performance-based measures were measured. ANALYSIS: -test and repeat measures ANOVA were undertaken. RESULTS: = 0.055, F = 3.28) at 12 months. CONCLUSION: Both packages of NPIs were effective in providing relief in symptoms. No specific benefit of KBA or meditation was seen except for 50FWT.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.069
Threshold uncertainty score0.658

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.002
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 head0.041
GPT teacher head0.376
Teacher spread0.335 · 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 designRandomized trial
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

Citations12
Published2018
Admission routes1
Has abstractyes

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