Conservative Management of Cervicogenic Dizziness Associated With Upper Cervical Instability and Postural Orthostatic Tachycardia Syndrome: A Case Report
Bibliographic record
Abstract
Cervicogenic dizziness (CGD) is a disorder in which dizziness arises from cervical spine dysfunction and is diagnosed after excluding other conditions. We present a case of a 27-year-old woman with a six-year history of dizziness, neck and cervicothoracic pain, and occipital-temporal-orbital headaches. The patient also experienced occasional severe, incapacitating episodes of dizziness with vomiting. Previous evaluations, including advanced imaging, had helped rule out central, otolithic, and psychogenic causes of dizziness. Dynamic radiographs revealed signs of lateral instability of C1 while tilt table testing revealed postural orthostatic tachycardia syndrome (POTS). Over eight months, the patient underwent a regimen of gentle manual therapies and cervical stability exercises. The patient's dizziness substantially improved, as measured by the Dizziness Handicap Inventory (DHI), with scores reducing from 50 (moderate handicap) to 10 (less than mild handicap). This case highlights the importance of considering cervical spine dysfunction and associated conditions like POTS in the differential diagnosis of chronic dizziness. While conservative management including manual therapy appeared effective in this case for CGD with underlying upper cervical instability and POTS, additional research is needed on this topic.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.006 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".