Unpredictability of Cerebrovascular Ischemia Associated With Cervical Spine Manipulation Therapy
Bibliographic record
Abstract
STUDY DESIGN: A retrospective review of 64 medicolegal records describing cerebrovascular ischemia after cervical spine manipulation was conducted. OBJECTIVES: To describe 64 cases of cerebrovascular accidents temporally associated with cervical spine manipulation therapy in terms of patient characteristics, potential risk factors, nature of complication, and neurologic sequelae. SUMMARY OF BACKGROUND DATA: Approximately 117 cases of postmanipulation cerebrovascular ischemia have been reported in the English language literature. Proposed risk factors include age, gender, migraine headaches, hypertension, diabetes, birth control pills, cervical spondylosis, and smoking. It is often assumed that these complications may be avoided by clinically screening patients and by premanipulation positioning of the head and neck to evaluate the patency of the vertebral arteries. METHODS: Three researchers using a uniform data abstraction instrument performed an independent review of 64 previously unpublished medicolegal records describing cerebrovascular ischemia after cervical spine manipulation. These cases were referred to a single physician for review over a 16-year period from across the United States and Canada. Descriptive statistics were calculated for characteristics of the patients and the complications. Means and standard deviations were computed for continuous variables. Frequencies and proportions were calculated for categorical variables. RESULTS: This study was unable to identify factors from the clinical history and physical examination of the patient that would assist a physician attempting to isolate the patient at risk of cerebral ischemia after cervical manipulation. CONCLUSION: Cerebrovascular accidents after manipulation appear to be unpredictable and should be considered an inherent, idiosyncratic, and rare complication of this treatment approach.
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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 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".