Clinical application of neuromodulation therapy in patients with disorder of consciousness: A pooled analysis of 544 participants
Bibliographic record
Abstract
BACKGROUND: The number of patients with disorders of consciousness (DoC) has increased dramatically with the advancement of intensive care and emergency medicine, which brings tremendous economic burdens and even ethical issues to families and society. OBJECTIVE: To evaluate the effectiveness of neuromodulation therapy for patients with DoC. METHODS: First, we conducted a literature review of individual patient data (IPD) on PubMed, EMBASE, and Cochrane-controlled trials following PRISMA guidelines. Then, we collected neuromodulation cases from our institution. Finally, we conducted a pooled analysis using the participants from the medical literature (n = 522) and our local institutions (n = 22). RESULTS: In this pooled analysis of 544 patients with DoC with a mean age of 46.33 years, our results revealed that patients have improved CRS-R scores [1.0 points (95% CI, 0.57-1.42)] after neuromodulation. Among them, patients have better effectiveness in traumatic than non-traumatic etiology (P < 0.05). The effectiveness of consciousness improvement could be affected by the age, baseline consciousness state, and duration of stimulation. Compared with non-invasive intervention, an invasive intervention can bring more behavioral improvement (P < 0.0001) to MCS rather than UWS/VS patients. Importantly, neuromodulation is a valuable therapy even years after the onset of DoC. CONCLUSION: This pooled analysis spotlights that the application of neuromodulation can improve the behavioral performance of patients with DoC. A preliminary trend is that age, etiology, baseline consciousness state, and stimulation duration could impact its effectiveness.
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How this classification was reachedexpand
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".