The novel combination of theophylline and bambuterol as a potential treatment of hypoxemia in humans
Bibliographic record
Abstract
Hypoxemia can be life-threatening, both acutely and chronically. Because hypoxemia causes vascular dysregulation that further restricts oxygen availability to tissue, it can be pharmacologically addressed. We hypothesized that theophylline can be safely combined with the β2-adrenergic vasodilator bambuterol to improve oxygen availability in hypoxemic patients. Ergogenicity and hemodynamic effects of bambuterol and theophylline were measured in rats under hypobaric and normobaric hypoxia (12% O2). Feasibility in humans was assessed using randomized, double-blind testing of the influence of combined slow-release theophylline (300 mg) and bambuterol (20 mg) on adverse events (AEs), plasma K+, pulse, blood pressure, and drug interaction. Both drugs and their combination significantly improved hypoxic endurance in rats. In humans, common AEs were low K+ (<3.5 mmol/L; bambuterol: 12, theophylline: 4, combination: 13 episodes) and tremors (10, 0, 14 episodes). No exacerbation or serious AE occurred when drugs were combined. A drop in plasma K+ coincided with peak bambuterol plasma concentrations. Bambuterol increased heart rate by approximately 13 bpm. Drug interaction was present but small. We report promise, feasibility, and relative safety of combined theophylline and bambuterol as a treatment of hypoxemia in humans. Cardiac safety and blood K+ will be important safety endpoints when testing these drugs in hypoxemic subjects.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".