Abstract P379: Patient and Caregiver Experiences With the Diagnosis of Neurogenic Orthostatic Hypotension
Bibliographic record
Abstract
Objective: To understand the challenges to diagnosis in patients with neurogenic orthostatic hypotension (nOH) Background: nOH is a sustained reduction in blood pressure (BP) with postural change associated with autonomic dysfunction. Despite symptoms of nOH, many patients struggle to find an accurate diagnosis. Methods: An online, US-based survey designed by the authors was conducted by Harris Poll. Eligible participants were ≥18 years of age with Parkinson disease, multiple system atrophy, or pure autonomic failure and ≥1 of the following: orthostatic hypotension (OH), nOH, low BP, OH/nOH symptoms, or were caregivers of eligible participants. Results: The survey included 363 patients and 128 caregivers. Groups were separate, where caregivers were not the caregivers to patient responders. Respondents indicated that patients experienced nOH symptoms long term (Table 1) . Most patients (69%) and caregivers (59%) reported discussing nOH symptoms with a healthcare provider (HCP) within the first year of symptom onset, but only 36% of patients and 16% of caregivers reported a formal diagnosis of OH or nOH. Of those with a formal diagnosis, the majority of patients (50%) were frustrated by the path to diagnosis and more than 40% of patients and caregivers reported that the patient saw ≥3 HCPs before diagnosis. After diagnosis, most patients (70%) and caregivers (60%) reported improved symptom management. Conclusions: This survey reveals that patients and caregivers may find the path to nOH diagnosis challenging and suggests increased awareness among HCPs is needed. Once a diagnosis is made nOH symptoms are better managed.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".