Low‐energy amplitude‐modulated electromagnetic field exposure: Feasibility study in patients with hepatocellular carcinoma
Bibliographic record
Abstract
BACKGROUND: Patients with advanced hepatocellular carcinoma (HCC) and poor liver function lack effective systemic therapies. Low-energy electromagnetic fields (EMFs) can influence cell biological processes via non-thermal effects and may represent a new treatment option. METHODS: This single-site feasibility trial enrolled patients with advanced HCC, Child-Pugh A and B, Eastern Cooperative Oncology Group 0-2. Patients underwent 90-min amplitude-modulated EMF exposure procedures every 2-4 weeks, using the AutEMdev (Autem Therapeutics). Patients could also receive standard care. The primary endpoints were safety and the identification of hemodynamic variability patterns. Exploratory endpoints included health-related quality of life (HRQoL), overall survival (OS). and objective response rate (ORR) using RECIST v1.1. RESULTS: Sixty-six patients with advanced HCC received 539 AutEMdev procedures (median follow-up, 30 months). No serious adverse events occurred during procedures. Self-limiting grade 1 somnolence occurred in 78.7% of patients. Hemodynamic variability during EMF exposure was associated with specific amplitude-modulation frequencies. HRQoL was maintained or improved among patients remaining on treatment. Median OS was 11.3 months (95% confidence interval [CI]: 6.0, 16.6) overall (16.0 months [95% CI: 4.4, 27.6] and 12.0 months [6.4, 17.6] for combination therapy and monotherapy, respectively). ORR was 24.3% (32% and 17% for combination therapy and monotherapy, respectively). CONCLUSION: AutEMdev EMF exposure has an excellent safety profile in patients with advanced HCC. Hemodynamic alterations at personalized frequencies may represent a surrogate of anti-tumor efficacy. NCT01686412.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".