Chronic Low Back Pain Forced Me to Search for and Find Pain Solutions: An Autobiographical Case Report
Bibliographic record
Abstract
Lifelong, pregnancy-induced low back pain forced me to search for solutions to the problem of pain. Currently, low back pain is often diagnosed as "nonspecific" and, as a result, a multitude of tests and poorly effective, at times side effect-laden or habit-forming treatments are recommended. My quest for relief took me to first diagnose my pain as coming from the sacroiliac joints, then to prolotherapy, the first treatment which brought me prolonged relief. I then learned how to perform prolotherapy. In 2009, when I undertook a randomized controlled study of dextrose prolotherapy for rotator cuff tendinopathy, I restricted my practice to treating pain. As low back pain was a large part of my practice, I sought new ways to examine the sacroiliac joints. I conducted a consecutive patient data collection which suggested that over three-quarters of those with low back pain suffer from displaced sacroiliac joints. In a further randomized controlled study, I found that the two-minute corrective exercise I derived from this test provided immediate relief to 90% of those using it. With Dr. John Clark Lyftogt I discovered the safety and effectiveness of 5% dextrose perineural injections to provide immediate pain relief to any area supplied by a nerve I could reach with my needle. As I was treating many diabetics with peripheral neuropathy, I shifted my perineural injection material to 5% mannitol, which may be as effective, with less exposure to dextrose as a potential benefit for diabetics. As most people dislike injections, a pharmacist and I developed a mannitol-containing topical cream for pain relief. We compared a base cream to the same cream with mannitol on lips pretreated with capsaicin cream which made them burn. By 10 minutes the probability the two creams were as effective in relieving the burn was less than 0.001 in favor of mannitol. When given to 235 patients with a total of 289 different painful conditions, we found that it provided 53% relief in an average of 16 minutes with a median of four hours duration. Now retired, after 55 years of medical practice, I love to relieve the pain of friends and fellow hikers using exercise and cream. Searching for and finding solutions to chronic pain has enriched my life and that of many others.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.006 | 0.009 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".