Evaluation of a Semi-Quantitative CO<sub>2</sub> Monitor with Pulse Oximetry for Prehospital Endotracheal Tube Placement and Management
Bibliographic record
Abstract
OBJECTIVE: To evaluate three prototype versions of semi-quantitative end-tidal CO2 monitors with different alarm features during prehospital or interfacility use. METHODS: Subjects were 43 adult, non-pregnant patients requiring intubation, or who already were intubated and required transport. Teams at one AirEvac and seven Advanced Life Support (ALS) paramedic stations were trained in the use of the monitors. Team members at each station evaluated each model for eight days. Participants completed questionnaires following each use. RESULTS: The monitors performed properly in all cases, but in one case, vomit in the airway adapter tube prevented obtaining a readout. The monitors aided management in 40 of 43 cases (93%); in one, the monitor reading was reported as variable (between 20 and 30 mmHg) although the teams knew the monitors were semi-quantitative; in another, the monitor was not required, but performed properly; and the third was the one in which vomit in the tube prevented a reading. In 26 of 43 cases (60.4%), the monitor was used to confirm endotracheal tube placement (there were no instances of incorrect placement). In all cases, the devices were used to monitor respiration and oxygen saturation. Alarms were audible in the environment, but only preferred in the AirEvac situation. The "breath beep" feature was useful, particularly in patients in whom chest movements during respiration were difficult to observe. CONCLUSIONS: "Breath beeps" were clearly audible and were a useful feature in all prehospital and transport environments, while audible alarms were desired only in the AirEvac situation. Semi-quantitative CO2 detection is valuable in the ALS/AirEvac environment, even for teams with high intubation success rates.
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 | 0.004 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".