TeLePhone Respiratory (TeLePoR) score to assess the risk of immediate respiratory support through phone call for acute dyspnoea: a prospective cohort study
Bibliographic record
Abstract
BACKGROUND: Acute dyspnea is a frequent cause to call the Emergency Medical Call Center (EMCC). The main challenge for EMCC dispatchers is to quickly identify patients that will require respiratory support in order to provide them with the most accurate prehospital response. Our main objective was to derivate a score assessable during the first call to detect the most severe patients needing medical assistance. METHODS: This prospective observational cohort study was conducted in four different French EMCC from January 22nd to March 7th 2024. Patients over the age of 18 years old that called once the EMCC for acute dyspnea were included in our study. The primary endpoint was an immediate respiratory support requirement (i.e. high-flow oxygen, non-invasive ventilation or mechanical ventilation after intubation) before or at the Emergency Department Registration. Variables of interest to predict respiratory support were prospectively collected in each EMCC. A multivariate analysis by stepwise logistic regression was used to select variables associated with the primary endpoint and to create in the TeLePhon Respiratory Score (TeLePoR score). The TeLePoR score was compared to medical dispatcher intuition for predicting respiratory support. RESULTS: Six hundred and forty-nine patients were analyzed, including 49 (8%) that required immediate respiratory support. The risk factors included in the TeLePoR score were: altered ability to speak complete sentences (OR = 8.62; CI95% = [3.49-21.3]), abdominal respiration (OR = 2.42; CI95% = [1.23-4.76]), altered consciousness (OR = 2.05; CI95% = [0.90-4.65]) and self-report breathing discomfort > 7/10 (OR = 1.83; CI95% = [0.96-3.47]) respectively. Considering these factors, TeLePoR score presented a 0.810 AUC. Medical dispatcher intuition was not statistically superior to TelePoR score to predict immediate respiratory support (AUC = 0.836 vs. 0.810; p = 0.431). CONCLUSION: TeLePoR score is a simple scoring system including 4 variables to predict immediate respiratory support in patients calling the EMCC for acute dyspnea.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".