Neuromodulation of dyspnea – A literature review
Bibliographic record
Abstract
Dyspnea is a complex sensation resulting from the interplay between neural, biochemical, and mechanical pathways. Because dyspnea is a perception created and interpreted by the central nervous system, it could theoretically be targeted by neuromodulation approaches. This technique is used in pain to modulate the function of neuronal circuits. However, a safe surgical and/or non-invasive modus operandi is not established for refractory dyspnea. Nevertheless, the following literature review will discuss different neuromodulation techniques that may treat refractory dyspnea, even though the understanding of its pathophysiology is limited. More precisely, the diaphragm and its phrenic control, the ventral respiratory complexes (such as Kolliker-Fuse complex and the pre-Bötzinger complex), the vagal nerve, the periaqueductal gray, the insula, the cingular cortex, and the thalamus appear to play an important role in the pathophysiology of breathlessness. Consequently, deep brain stimulation, trigeminal nerve, spinal and vagal nerve stimulations are potentially effective approaches to diminish dyspnea. The discovery of useful dyspnea-reducing neuromodulation techniques could replace or be added to actual treatments like pulmonary rehabilitation, facial ventilators, oxygen, and opioids could be replaced, consequently enhancing the quality of life of dyspneic individuals.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".