Bibliographic record
Abstract
BACKGROUND: Autonomic dysreflexia (AD) is a frequent complication of spinal cord injury (SCI), though current clinical practice patterns for medication management of this condition are unknown. Correspondingly, it is unclear if national differences in practice patterns exist. OBJECTIVE: To determine trends in current pharmacologic management of AD throughout the Americas. DESIGN: International survey of current physician practice patterns. SETTING: Academic medical center. PARTICIPANTS: Sixty physicians managing patients with SCI and prescribing medications to manage AD. INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: Presence of a formal pharmacologic AD management protocol, first- and second-line medications, patient characteristics influencing pharmacologic management. RESULTS: The majority of physicians (69%) had a formal AD management protocol for inpatient care, with nitroglycerin ointment (82%) being the most common first-line medication. Strong national differences existed regarding the use of nitroglycerin ointment, with 98% of U.S.-based physicians using this as first-line medication and 0% of physicians in Canada or Latin America using this due to recent lack of medication availability. Only 67% of physicians had a preferred second-line medication, with preferences split between hydralazine (48%) and nifedipine (28%). A systolic blood pressure threshold for pharmacologic management was used by 56% of physicians, wheres 26% considered neurological level of injury in decisions to use medications for AD. Heart rate was used by only 5% of physicians in their decision to manage AD with medications. CONCLUSIONS: As of 2023, U.S.-based physicians caring for individuals with SCI largely have formal inpatient protocols in place for medication management of AD, with nearly all relying on nitroglycerin ointment as their first-line medication. In areas outside of the United States where nitroglycerin ointment is unavailable, pharmacologic practice patterns significantly differ.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".