Transcutaneous Electrical Nerve Stimulation (TENS) for dementia
Bibliographic record
Abstract
BACKGROUND: Transcutaneous electrical nerve stimulation (TENS) is the application of an electrical current through electrodes attached to the skin. The commonest clinical application of TENS is pain control. TENS is also used occasionally for the treatment of a range of neurological and psychiatric conditions including drug and alcohol dependence, headaches, and depression. TENS is rarely used for the treatment of dementia. However, since the early 1990s a number of studies carried out by a group in the Netherlands, and one study carried out by a group in Japan, suggest that TENS applied to the back or head may improve cognition and behaviour in patients with Alzheimer's disease or multi-infarct dementia. It was claimed that applying TENS could benefit patients with dementia by altering the activity of various neurotransmitters, or by increasing brain activity and thereby retarding neural degeneration and stimulating regenerative processes. It is claimed that application of TENS to the head may also alleviate the sleep disorders associated with dementia. OBJECTIVES: The aim of this review is to determine the effectiveness and safety of transcutaneous electrical nerve stimulation (TENS) in the treatment of dementia. Secondary objectives of this review are to determine whether any effect of treatment of dementia with TENS is influenced by any treatment parameters or patient features, including: the duration of treatment, electrical waveform, current amplitude, pulse duration and frequency and the patient's type or severity of cognitive impairment. SEARCH STRATEGY: The trials were identified from a search of the Specialized Register of the Cochrane Dementia and Cognitive Improvement Group on 10 December 2002 using the terms TENS, transcutaneous, "transcutaneous electrical nerve stimulation", and "electric stimulation". The CDCIG Specialized Register contains records from all major health care databases and many ongoing trials databases and is regularly updated. SELECTION CRITERIA: All RCTs in which TENS was used as an intervention for people with dementia were included in this review. This included peripherally applied transcutaneous electrical stimulation as well as transcutaneous electrical stimulation applied to the head (also known as cranial electrical stimulation (CES)). DATA COLLECTION AND ANALYSIS: All RCTs that fulfilled the inclusion criteria for the review and for which sufficient data were available were included in this meta-analysis. Two reviewers extracted the data from the included trials. All except one of the included trials used similar outcome measures. Data of the same outcome measures were combined for analysis. MAIN RESULTS: Eight trials were included in the review but only 3 trials could be included in the meta-analysis. Sufficient data to include the other trials in the meta-analysis could not be obtained. From this limited analysis it appears that TENS produced a statistically significant improvement directly after treatment in: delayed recall of 8 words in one trial, face recognition in two trials and motivation in one trial however, no effect of TENS was found on any of the many other neuropsychological and behavioural measures evaluated either directly after TENS treatment or 6 weeks after treatment was completed. REVIEWER'S CONCLUSIONS: Although a number of studies suggest that TENS may produce short lived improvements in some neuropsychological or behavioural aspects of dementia, the limited presentation and availability of data from these studies does not allow definite conclusions on the possible benefits of this intervention. Since most of the currently published studies are well designed, although the numbers of subjects in each study is small, analysis of the complete original data from these and/or future studies may allow more definitive conclusions to be drawn.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".