Clinical Trials Involving Biphasic Pulsed Current, MicroCurrent, and/or Low-Intensity Direct Current
Bibliographic record
Abstract
Significance: This invited critical review will summarize an expansive body of literature regarding electrical stimulation (ES) and wound healing. Several clinical reports have been published in which ES has been evaluated as a therapy to speed the closure of chronic wounds. Different forms of ES have been applied in varying ways and described using inconsistent terminology by researchers and clinicians around the world. It is important to compile this research and to critically appraise the findings so that clinicians who are not familiar with this field can interpret the research. Recent Advances: More recently, ES has been delivered at subsensory levels (termed microcurrent in this review) using very small electrical devices contained within wound dressing. While these newer technologies have obvious technical advances, what research has been published to date about these new devices has not produced findings that suggest this form of ES can accelerate wound closure. Critical Issues: Reviewing a collection of published reports on this subject reveals that not all forms of ES produce beneficial results. Rather, only certain ES protocols such as monophasic pulsed current applied to the wound and biphasic pulsed current current that is applied for 2 h daily to periulcer skin at intensities which produce motor responses have consistently demonstrated positive results. Future Directions: Optimal stimulus parameters and treatment schedule for ES used to treat chronic wounds need to be determined. Researchers publishing in this field should provide detailed information about their ES treatment protocol and use a similar terminology to describe the ES waveform and stimulus parameters.
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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 | 0.004 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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.
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".