The recommendations of a consensus panel for the screening, diagnosis, and treatment of neurogenic orthostatic hypotension and associated supine hypertension
Bibliographic record
Abstract
Neurogenic orthostatic hypotension (nOH) is common in patients with neurodegenerative disorders such as Parkinson's disease, multiple system atrophy, pure autonomic failure, dementia with Lewy bodies, and peripheral neuropathies including amyloid or diabetic neuropathy. Due to the frequency of nOH in the aging population, clinicians need to be well informed about its diagnosis and management. To date, studies of nOH have used different outcome measures and various methods of diagnosis, thereby preventing the generation of evidence-based guidelines to direct clinicians towards 'best practices' when treating patients with nOH and associated supine hypertension. To address these issues, the American Autonomic Society and the National Parkinson Foundation initiated a project to develop a statement of recommendations beginning with a consensus panel meeting in Boston on November 7, 2015, with continued communications and contributions to the recommendations through October of 2016. This paper summarizes the panel members' discussions held during the initial meeting along with continued deliberations among the panel members and provides essential recommendations based upon best available evidence as well as expert opinion for the (1) screening, (2) diagnosis, (3) treatment of nOH, and (4) diagnosis and treatment of associated supine hypertension.
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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 | 0.047 | 0.068 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.007 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.008 | 0.004 |
| Research integrity | 0.012 | 0.013 |
| Insufficient payload (model declined to judge) | 0.008 | 0.007 |
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".