Bibliographic record
Abstract
PURPOSE OF REVIEW: Orthostatic hypotension is a phenomenon commonly encountered in a cardiologist's clinical practice that has significant diagnostic and prognostic value for a cardiologist. Given the mounting evidence associating cardiovascular morbidity and mortality with orthostatic hypotension, cardiologists will play an increasing role in treating and managing patients with orthostatic hypotension. RECENT FINDINGS: The American College of Cardiology, American Heart Association, and Heart Rhythm Society recently published consensus guidelines on the diagnosis, treatment, and management of syncope and their instigators, including orthostatic hypotension. Additionally, consensus guidelines have also been recently updated, reinforcing the universal definition orthostatic hypotension and its closely associated pathologies. Finally, the United States Food and Drug Administration (FDA) recently approved droxidopa, a synthetic oral norepinephrine prodrug, in 2014 for the treatment of neurogenic orthostatic hypotension (nOH), and it represents a well tolerated, effective, and easy to use intervention for nOH. This represents only the second drug approved by the FDA for orthostatic hypotension, the first being midodrine in 1986. A handful of smaller head-to-head studies have pitted not only pharmacologic agents to one another but also nonpharmacologic interventions to pharmacologic agents. Additionally, recent studies have also reported on more convenient screening tools for orthostatic hypotension. SUMMARY: Though there have been many advances in the management of orthostatic hypotension, nOH remains a chronic, debilitating, and often progressively fatal condition. Cardiologists can play a very important role in optimizing hemodynamics in this patient population to improve quality of life and minimize cardiovascular risk.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 0.005 |
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".