Characteristics of persistent postural perceptual dizziness patients in a multidisciplinary dizziness clinic
Bibliographic record
Abstract
BACKGROUND: Persistent Postural Perceptual Dizziness (PPPD) is a newly defined condition which was added to the International Classification of Vestibular Disorders in 2017. Little is known about its impact on patients. OBJECTIVE: The goal of this study was to analyze the symptomology, epidemiology and impact of PPPD on patients. METHODS: A retrospective chart review was done to identify patients who attended the Multidisciplinary Dizziness Clinic (MDC) and were diagnosed with PPPD. Responses to demographic questions, health-related quality of life surveys and several well-validated questionnaires commonly used to assess dizziness severity were analyzed. RESULTS: One hundred patients were diagnosed with PPPD between March 2017 and January 2019, of which 80%(80/100) were females. The average Dizziness Handicap Index score was 60.3±19.0. Responses to the Patient Health Questionnaire classified 53 patients (53/99;53.5%) as moderately to severely depressed. Sixty-four patients (64/100;64.0%) were minimally or mildly anxious according to the Generalized Anxiety Disorder scale. The average Vertigo Symptom Scale score was 24.1/60. The average Situational Vertigo Questionnaire score was 2.00. Forty-nine (49/100;49.0%) patients had migraine symptoms according to the Migraine Screen Questionnaire. CONCLUSIONS: In conclusion, patients with PPPD display important handicap and an elevated risk of depression, anxiety and migraines.
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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 | 0.002 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".