Safety of Metoclopramide in Traumatic Brain Injury Patients
Bibliographic record
Abstract
Abstract Introduction Traumatic brain injuries (TBIs) occur due to severe head assault to a hard object, with headache and vomiting being amongst the most common presenting symptoms. Metoclopramide is an old antiemetic agent that has been used widely for nausea and vomiting in TBI patients. Aim A systematic review of the literature to investigate the safety of metoclopramide in treating TBI patients. Methods A literature review was conducted in six databases, where we determined the pertinence of a study to the inclusion criteria by assessing the title, keywords, and abstracts. Five studies were found to be relevant. Data were extracted using multiple variables that were formulated incongruent with the study aim and then further analyzed. Results The collective sample size was 93 patients with an average of age 38.5 years. As much as 51.6% were male and 48.6% were females. Most patients received 10 mg metoclopramide IV with a percentage of 77.4%, while only 22.5% received 20 mg IV metoclopramide. Seventy-one patients received metoclopramide alone and 22 received combination therapy. Headache was the most common reported side effect (46.2%), followed by anxiety and drowsiness with (39.7%) and (27.9%), respectively. Fatigue was reported in 24.7%, while dystonia was the least common and developed in only 5.3% of patients. Conclusion Metoclopramide is a common medication used to treat TBI patients in the emergency department. However, the review demonstrated that the central nervous system (CNS) side effect is excepted. Treatments with lower CNS side effects may be better options.
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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 | 0.005 | 0.039 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".