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Yoga for epilepsy

2015· review· en· W4235851150 on OpenAlexaff
Mariangela Panebianco, Kalpana Sridharan, Sridharan Ramaratnam

Bibliographic record

VenueCochrane Database of Systematic Reviews · 2015
Typereview
Languageen
Field
Topic
Canadian institutionsChild, Adolescent and Family Mental Health
Fundersnot available
KeywordsMedicineCochrane LibraryEpilepsyRandomized controlled trialMEDLINEOdds ratioMeta-analysisQuality of life (healthcare)Clinical trialAdverse effectPhysical therapyPediatricsInternal medicinePsychiatry

Abstract

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BACKGROUND: This is an updated version of the original Cochrane review published in The Cochrane Library, Issue 1, 2002.Yoga may induce relaxation and stress reduction, and influence the electroencephalogram and the autonomic nervous system, thereby controlling seizures. Yoga would be an attractive therapeutic option for epilepsy if proved effective. OBJECTIVES: To assess whether people with epilepsy treated with yoga:(a) have a greater probability of becoming seizure free;(b) have a significant reduction in the frequency or duration of seizures, or both; and(c) have a better quality of life. SEARCH METHODS: We searched the Cochrane Epilepsy Group Specialized Register (26 March 2015), the Cochrane Central Register of Controlled Trials (CENTRAL, The Cochrane Library, 26 March 2015), MEDLINE (Ovid, 1946 to 26 March 2015), SCOPUS (1823 to 9 January 2014), ClinicalTrials.gov (26 March 2015), the World Health Organization (WHO) International Clinical Trials Registry Platform ICTRP (26 March 2015), and also registries of the Yoga Biomedical Trust and the Research Council for Complementary Medicine. In addition, we searched the references of all the identified studies. No language restrictions were imposed. SELECTION CRITERIA: The following study designs were eligible for inclusion: randomised controlled trials (RCT) of treatment of epilepsy with yoga. Eligible participants were adults with uncontrolled epilepsy comparing yoga with no treatment or different behavioural treatments. DATA COLLECTION AND ANALYSIS: Three review authors independently selected trials for inclusion and extracted data. The following outcomes were assessed: (a) percentage of people rendered seizure free; (b) seizure frequency and duration; (c) quality of life. Analyses were on an intention-to-treat basis. Odds ratio (OR) with 95% confidence intervals (95% Cl) were estimated for the outcomes. MAIN RESULTS: Two unblinded trials recruited a total of 50 people (18 treated with yoga and 32 to control interventions). Antiepileptic drugs were continued in all the participants. Baseline phase lasted 3 months in both studies and treatment phase from 5 weeks to 6 months in the two trials. Randomisation was by roll of a die in one study and using a computerised randomisation table in the other one but neither study provided details of concealment of allocation and were rated as unclear risk of bias. Overall, the two studies were rated as low risk of bias (all participants were included in the analysis; all expected and pre-expected outcomes were reported; no other sources of bias). The overall OR with 95% confidence interval (CI) was: (i) seizure free for six months - for yoga versus sham yoga ORs of 14.54 (95% CI 0.67 to 316.69) and for yoga versus no treatment group 17.31 (95% CI 0.80 to 373.45); for Acceptance and Commitment Therapy (ACT) versus yoga ORs of 1.00 (95% Cl 0.16 to 6.42; (ii) reduction in seizure frequency - the Mean Difference between yoga versus sham yoga group was -2.10 (95% CI -3.15 to -1.05) and for yoga versus no treatment group -1.10 (95% CI -1.80 to -0.40); (iii) more than 50% reduction in seizure frequency - for yoga versus sham yoga group ORs of 81.00 (95% CI 4.36 to 1504.46) and for the yoga versus no treatment group 158.33 (95% CI 5.78 to 4335.63); ACT versus yoga ORs of 0.78 (95% Cl 0.04 to 14.75); (iv) more than 50% reduction in seizure duration - for yoga versus sham yoga group ORs of 45.00 (95% CI 2.01 to 1006.75) and for yoga versus no treatment group 53.57 (95% CI 2.42 to 1187.26); ACT versus yoga ORs of 0.67 (95% Cl 0.10 to 4.35). In addition in Panjwani 1996 the authors reported that the one-way analysis of variance revealed no statistically significant differences between the three groups. A P-Lambda test taking into account the P values between the three groups also indicated that the duration of epilepsy in the three groups was not comparable. No data were available regarding quality of life. In Lundgren 2008 the authors reported that there was no significant difference between the yoga and ACT groups in seizure free rates, 50% or greater reduction in seizure frequency or seizure duration at one year follow-up. The yoga group showed significant improvement in their quality of life according to the Satisfaction With Life Scale (SWLS) (P < 0.05), while the ACT group had significant improvement in the World Health Organization Quality of Life-BREF (WHOQOL-BREF) scale (P < 0.01). AUTHORS' CONCLUSIONS: Study of 50 subjects with epilepsy from two trials reveals possible beneficial effect in control of seizures. Results of the overall efficacy analysis show that yoga treatment was better when compared with no intervention or interventions other than yoga (postural exercises mimicking yoga). There was no difference between yoga and Acceptance and Commitment Therapy. However no reliable conclusions can be drawn regarding the efficacy of yoga as a treatment for uncontrolled epilepsy, in view of methodological deficiencies such as limited number of studies, limited number of participants randomised to yoga, lack of blinding and limited data on quality-of-life outcome. Physician blinding would normally be taken to be the person delivering the intervention, whereas we think the 'physician' would in fact be the outcome assessor (who could be blinded), so that would be a reduction in detection bias rather than performance bias. In addition, evidence to inform outcomes is limited and of low quality. Further high-quality research is needed to fully evaluate the efficacy of yoga for refractory epilepsy.

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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)0.003
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.024
Threshold uncertainty score0.080

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.015
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.004
Bibliometrics0.0070.004
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0010.002
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0240.002

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 head0.284
GPT teacher head0.447
Teacher spread0.162 · 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 designSystematic review
Domainnot available
GenreReview

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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Citations14
Published2015
Admission routes1
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