P REHOSPITAL H YPOGLYCEMIA : T HE S AFETY OF N OT T RANSPORTING T REATED P ATIENTS
Bibliographic record
Abstract
OBJECTIVES: Emergency medical services (EMS) personnel frequently encounter patients who refuse transport after being treated for a hypoglycemic episode. The outcomes of most of these patients are unknown. The purpose of this study was to determine the outcomes of patients treated and not transported for hypoglycemia and identify criteria that could be used to identify patients who did not require transport to hospital. METHODS: This was a prospective, observational study involving all adult (>15 years) hypoglycemic patients (blood glucose less than 4 mmol/L by glucometer) attended to by the EMS system in the Halifax Metropolitan area in the province of Nova Scotia during a ten-month interval. RESULTS: There were 220 calls for adult patients with hypoglycemia. Of the 75 calls that resulted in transport, there were 17 further hypoglycemic episodes requiring a repeat call for an ambulance (22.7%) and three recurrences (4%). Of the 145 calls that did not result in transport, 40 further episodes of hypoglycemia (27.6%) and three recurrences (2%) were reported. These differences were not statistically significant (p=0.43 and 0.33, respectively). There was also no statistically significant difference in the intervals between hypoglycemic episodes for patients transported (51.1 days +/-65) compared with patients not transported for their previous hypogylcemic episode (40.7 days +/-53.5) (p=0.6). Of the 47 calls entered in the study, there were seven repeat calls for hypoglycemia (15%) and one recurrence (2.1%). The majority of patients did not follow up with their physician. CONCLUSIONS: Repeat episodes of hypoglycemia are common; however, recurrences within 48 hours are not. Admission to hospital is rarely required. There appears to be no difference in the incidence of recurrences and repeat episodes of hypoglycemia between transported and nontransported insulin-dependent patients, regardless of age. Given the high incidence of repeat episodes, paramedics and physicians need to emphasize the importance of follow-up.
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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 | 0.000 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".