Caudal epidural blood patch for the treatment of persistent post-dural puncture headache following intrathecal pump placement in a patient with lumbar instrumentation
Bibliographic record
Abstract
Dear Editor, According to CDC data, chronic pain affects 50 million Americans, or 20% of the national population, causing significant and prolonged morbidity.Chronic low back and neck pain carry an estimated healthcare spending cost of 67.5 to 94.1 billion USD annually, the third highest in the US after ischaemic heart disease and diabetes [1].While some patients may require surgical intervention, it is estimated that between 10% and 40% will continue to experience persistent pain after back surgery, a syndrome called failed back surgery syndrome (FBSS) or post laminectomy syndrome (PLS).With a constantly increasing number of spinal surgeries (e.g.220% increase in spinal fusion surgery between 1990 and 2000), these number are expected to remain significant [2].The aetiology of PLS varies and includes patient, operative, and post-operative factors; it includes persistent pain due to inability to achieve the aim of surgery or operating on an incorrect level, persistent radicular pain from long-term nerve root injury, re-stenosis of neuroforamen or central canal, facet disease, and pain from surgical scar [3].The complex aetiology and comorbidities of PLS make it challenging to treat; management usually includes medical optimization and psychosocial intervention, but usually requires neuromodulation, with options including spinal cord stimulation (SCS), periph-
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".