The autonomic response following taVNS predicts changes in level of consciousness in DoC patients
Bibliographic record
Abstract
Advancements in emergency medicine and critical care have significantly improved survival rates for patients with severe acquired brain injuries(sABI), subsequently increasing the prevalence of disorders of consciousness (DoC) such as Unresponsive Wakefulness Syndrome (UWS) and Minimally Conscious State (MCS). However, the assessment of conscious states relies on the observation of behavioral responses, the interpretation of which may vary from evaluator to evaluator, as well as the high rate of misdiagnosis, which together pose significant challenges for clinical diagnosis. The study investigates the utility of transcutaneous auricular vagus nerve stimulation (taVNS) in modulating autonomic responses, as evidenced through heart rate variability (HRV), for distinguishing between healthy individuals and DoC patients and for prognosticating patient outcomes. A prospective randomized clinical trial was conducted from Februry 9, 2022, to February 4, 2024, at Hangzhou Armed Police Hospital in China. Healthy controls (HC) and DoC patients were enrolled in this study. The taVNS was administered to each subject for ten minutes. There electrocardiogram (ECG) signals were recorded for the analysis of HRV both during the stimulation and the ten minutes of rest that preceded and followed the stimulation. Subsequent investigations utilized Support Vector Machine (SVM) modeling, enhanced by a Radial Basis Function (RBF) kernel, to explore potential predictors of patient outcomes. This approach aimed to differentiate HC from DoC and MCS from UWS patients. 26 HC and 36 patients diagnosed with DoC were included in the analysis,. The DoC group consisted of 17 patients with a diagnosis of MCS and 19 with diagnosis of UWS/VS. Significant modulations in HRV parameters (HF, VLF, SampEn) were observed, indicating variations in autonomic response between the control group and DoC patients. Using the VLF, LF, and SampEn features in SVM model, DoC and HC were correctly classified with an accuracy of 86%. Similarly, MCS and UWS were classified with an accuracy of 78%. The SVM modeling achieved an 86% accuracy rate in predicting outcomes three months post-intervention, with a 71% confirmation rate at six months.The results highlight taVNS's potential as a therapeutic modality in managing DoC by demonstrating its impact on autonomic regulation and suggesting pathways for enhancing recovery, which accentuates the significance of exploring brain-heart dynamics in DoC, presenting a novel approach to therapeutic strategies. Trial Registration Information: URL: chictr.org.cn; Unique identifier: ChiCTR2100045161. Date of the first registration: 9th/ April/ 2021.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.001 | 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 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".