Alleviation of shoulder injury related to vaccine administration (SIRVA) pain and disability following COVID-19 vaccine with chiropractic biophysics<sup>®</sup> (CBP<sup>®</sup>) methods: a case report and long-term follow-up with global implications
Why this work is in the frame
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Bibliographic record
Abstract
[Purpose] To present the dramatic improvement in posture, radiographic parameters and the alleviation of neck and severe shoulder pain related to shoulder injury associated with vaccine administration (SIRVA) after a COVID-19 injection with a shoulder mobility and posture rehabilitation program. [Participant and Methods] A middle-aged male presented complaining of severe left shoulder pain evolving since receiving a COVID-19 vaccination. The pain was severe and throbbed into the neck. Posture analysis showed a chronic stooped posture with forward head posture and thoracic hyperkyphosis. Treatment included 42 sessions of Chiropractic Biophysics® technique and a shoulder rehabilitation program using three-dimensional vibration. [Results] At 4-months, the patient reported no neck or shoulder pain. There was a 60% decrease in neck disability. The forward head decreased 34 mm, thoracic hyperkyphosis decreased 13°, and T1–T12 forward lean decreased 73 mm, among other radiographic parameters. Re-assessment after 26-months showed maintenance of the treatment induced posture/x-ray corrections and shoulder pain relief. [Conclusion] This case demonstrates immediate and long-term improvement in a patient suffering from COVID-19 vaccine SIRVA, concomitant with neck pain and disability as well as significant radiographic postural/spinal deformity. These conditions all improved and were maintained at a 2 year follow-up without further treatment.
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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 | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it