EMS Access Constraints And Response Time Delays For Deprived Critically Ill Patients Near Paris, France
Bibliographic record
Abstract
Increased emergency medical services (EMS) response times and areas of low socioeconomic status are both associated with poorer outcomes for several time-sensitive medical conditions attended to by medical personnel before a patient is hospitalized. We evaluated the association between EMS response times, area deprivation level, and on-scene access constraints encountered by EMS in a large urban area in France. We conducted a multicenter prospective cohort study of EMS dispatches occurring in the forty-seven cities in a region southeast of Paris. We fit multilevel mixed-effects linear regression models for multivariate assessment of the predictors of EMS response times and then used multivariate logistic regression on outcomes among a subgroup of patients presenting with out-of-hospital cardiac arrest. We found evidence that access constraints were more frequently encountered by EMS in the most deprived areas compared to less deprived ones, and were associated with increased EMS response times until patient contact and with poorer outcomes from cardiac arrest. Strategies to anticipate and overcome access constraints should be implemented to improve outcomes for emergent conditions attended to by prehospital medical teams.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".