Ambulance crew‐initiated non‐conveyance in the Helsinki EMS system—A retrospective cohort study
Bibliographic record
Abstract
BACKGROUND: Ambulance patients are usually transported to the hospital in the emergency medical service (EMS) system. The aim of this study was to describe the non-conveyance practice in the Helsinki EMS system and to report mortality following non-conveyance decisions. METHODS: All prehospital patients ≥16 years attended by the EMS but not transported to a hospital during 2013-2017 were included in the study. EMS mission- and patient-related factors were collected and examined in relation to patient death within 30 days of the EMS non-conveyance decision. RESULTS: The EMS performed 324,207 missions with a patient during the study period. The patient was not transported in 95,909 (29.6%) missions; 72,233 missions met the study criteria. The patient mean age (standard deviation) was 59.5 (22.5) years; 55.5% of patients were female. The most common dispatch codes were malaise (15.0%), suspected decline in vital signs (14.0%), and falling over (12.9%). A total of 960 (1.3%) patients died within 30 days after the non-conveyance decision. Multivariate logistic regression analysis revealed that mortality was associated with the patient's inability to walk (odds ratio 3.19, 95% confidence interval 2.67-3.80), ambulance dispatch due to shortness of breath (2.73, 2.27-3.27), decreased level of consciousness (2.72, 1.75-4.10), decreased blood oxygen saturation (2.64, 2.27-3.06), and abnormal systolic blood pressure (2.48, 1.79-3.37). CONCLUSION: One-third of EMS missions did not result in patient transport to the hospital. Thirty-day mortality was 1.3%. Abnormalities in multiple respiratory-related vital signs were associated with an increased likelihood of death within 30 days.
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 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".