Finding Optimal Neuromodulation for Chronic Pain: Waves, Bursts, and Beyond
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Spinal cord stimulation (SCS) has emerged as state-of-the-art evidence-based treatment for chronic intractable pain related to spinal and peripheral nerve disorders. Traditionally delivered as steady-state, paraesthesia-producing electrical stimulation, newer technology has augmented the SCS option and outcome in the last decade. OBJECTIVE: To present an overview of the traditional and newer SCS waveforms. MATERIALS AND METHODS: We present a short literature review of SCS waveforms in reference to newer waveforms and describing paraesthesia-free, high frequency, and burst stimulation methods as well as advances in waveform paradigms and programming modalities. Pertinent literature was reviewed, especially in the context of evolution in the waveforms of SCS and stimulation parameters. RESULTS: Conventional tonic SCS remains one of the most utilized and clinically validated SCS waveforms. Newer waveforms such as burst stimulation, high-frequency stimulation, and the sub-perception SCS have emerged in the last decades with favorable results with no or minimal paraesthesia, including in cases otherwise intractable to conventional tonic SCS. The recent evolution and experience of closed-loop SCS is promising and appealing. The experience and validation of the newer SCS waveforms, however, remain limited but optimistic. CONCLUSIONS: Advances in SCS device technology and waveforms have improved patient outcomes, leading to its increased utilization of SCS for chronic pain. These improvements and the development of closed-loop SCS have been increasingly promising development and foster a clinical translation of improved pain relief as the years of research and clinical study beyond conventional SCS waveform come to fruition.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it