Intradiscal Electrothermal Treatment for Chronic Discogenic Low Back Pain
Bibliographic record
Abstract
Study Design. Prospective longitudinal study with a minimum 2-year follow-up. Objective. To assess the long-term outcome of a group of patients with chronic discogenic low back pain who had failed to improve with comprehensive nonoperative care and who were subsequently treated with intradiscal electrothermal therapy (IDET). Summary of Background Data. Previous reports of patient outcomes at 1 year after IDET have demonstrated statistically significant improvement. Methods. The study group comprised 58 patients with chronic symptoms of more than 6 months who failed to improve with nonoperative care and subsequently underwent IDET. VAS pain scores, SF-36 scores, and sitting tolerance times were collected pretreatment and at 6, 12, and 24 months. Results. Mean duration of pre-IDET symptoms was 60.7 months. The minimum follow-up at data collection was 24 months. The study group (n = 58) demonstrated a significant improvement in pain as demonstrated by statistically significant improvement in VAS scores and bodily pain SF-36 scores. The IDET-treated group demonstrated a significant improvement in physical function as noted by statistically significant improvement in sitting tolerance times and physical function SF-36 scores. Bodily pain and physical function scores demonstrated significant improvement between the 1- and 2-year observation points. Additionally, quality of life improvement was demonstrated by a statistically significant improvement in all the SF-36 subscales. Conclusions. A cohort of patients with chronic discogenic low back pain who had failed to improve with comprehensive nonoperative care demonstrated a statistically significant improvement in pain, physical function, and quality of life at 2 years after IDET.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".