Sublingual Sufentanil Tablet for Analgesia in Emergency Medical Services and Search and Rescue Agencies
Bibliographic record
Abstract
OBJECTIVES Pain management in the potentially austere search and rescue (SAR) and emergency medical services (EMS) environments can be challenging. Intravenous (IV) and intramuscular (IM) routes of administration may be less practical. This study assesses the efficacy and safety of the sublingual sufentanil tablet (SST) in prehospital settings and hypothesizes that its use will reduce pain while maintaining a reasonable safety profile.METHODS This was a retrospective case analysis examining patient records from Teton County Search and Rescue, Grand Teton National Park EMS, and Jackson Hole Fire/EMS from 2021-2023, based on the criteria that they were administered SST in a prehospital setting. Cases in which SST was used were examined to assess patient characteristics, injury classification, patient reported pain scale before and after SST, other medications administered, and vital signs.RESULTS Seventy patients met the inclusion criteria. Six individuals were excluded due to missing one or more of the key variables, and the analysis was carried out with the remaining (N = 64 cases). The mean pain score decreased from 8.0 ± 1.9 before medication administration to 5.5 ± 2.5 after administration, reflecting a statistically significant difference of 2.6 ± 2.1 (p < 0.001). The results also revealed statistically significant reductions in heart rate (HR) and systolic blood pressure (SBP) following SST administration (mean HR dropped by 4.2 ± 9.1 beats/min, p = 0.004, and mean SBP dropped by 11.1 ± 21.8 mmHg, p = 0.01). Changes in vital signs, although statistically significant, were not clinically significant and did not necessitate additional monitoring or intervention in any patients.CONCLUSIONS Our study demonstrated that SST administration led to a significant reduction in pain scores and exhibited a favorable safety profile regarding vital signs, including SBP, HR, respiratory rate (RR), and O2 saturation. These findings support the utilization of SST for pain management in the prehospital setting, particularly in austere environments where traditional routes of administration may be impractical.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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".