Diaphragm neurostimulation in mechanical ventilation: current status and future prospects
Bibliographic record
Abstract
INTRODUCTION: Diaphragm neurostimulation is a muscle stimulation technique that, through electrodes placed directly on or at the vicinity of the phrenic nerves, induces diaphragm contractions independently of the patient's cooperation. Recently, the technical development of temporary diaphragm neurostimulation devices has paved the way for a new era in the management of critically ill patients. AREAS COVERED: In this review, we describe the latest technical developments in diaphragm neurostimulation and its physiological effects. We searched MEDLINE of experimental and clinical studies in English language published from database inception until 31 October 2024. We also discuss the advances in terms of patients centered outcomes and the key areas for improvement. Lastly, we introduce possible future directions and the novel improvements in patient care. EXPERT OPINION: The research on diaphragm neurostimulation promise as an emerging intervention which addresses common complications associated with mechanical ventilation. Large-scale clinical trials are necessary to validate diaphragm neurostimulation efficacy and safety in humans, establish treatment protocols, and determine cost-effectiveness, all of which are essential for diaphragm neurostimulation to be widely accepted in clinical practice.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".