ANTICIPATORY GUIDANCE FOR THE PREVENTION OF PEDIATRIC DEATHS DUE TO HEAT STROKE CAUSED BY BEING LEFT UNATTENDED IN VEHICLES
Bibliographic record
Abstract
BACKGROUND: An average of 37 children die annually in the United States from heat stroke as a result of being left unattended inside a vehicle (pediatric vehicular hyperthermia, PVH). The majority of these deaths occur because a caregiver unintentionally leaves a child in the car, often referred to as forgotten baby syndrome (FBS). Other causes include children being knowingly left in vehicles and children getting into unattended vehicles on their own. The current rates of childhood deaths from PVH in Canada are unknown. OBJECTIVES: To review the rate of childhood deaths in Canada from PVH over the past 15 years and to provide pediatricians with anticipatory guidance strategies to help prevent deaths due to PVH. DESIGN/METHODS: Incidence data of PVH deaths in Canada were obtained from coroner’s offices and from news reports found on Factiva and ProQuest databases. A scoping review was conducted using key search terms related to PVH and FBS. RESULTS: In Canada, there have been numerous reports of children being left unattended in vehicles. There have been 4 confirmed deaths due to PVH in the last 15 years. Three of the four cases were attributed to FBS. There was one reported case due to a child climbing into an unlocked, unattended vehicle. CONCLUSION: Reports of children being left unattended either knowingly or unintentionally in vehicles in Canada are not uncommon. Stress, distractions and changes in routine can contribute to a shift in attention and FBS. To help caregivers prevent incidents of PVH in Canada, we suggest the following anticipatory guidance by physicians to all parents: 1) Caregivers should be advised to never leave a child unattended in a motor vehicle; 2) Caregivers should place essential items such as wallets and cellphones near their child in the back seat to serve as a reminder when exiting the vehicle; 3) Caregivers can place a reminder (i.e. a toy or diaper bag) in the front seat when an infant or child has been placed in the back seat; 3) Caregivers should make a habit of always checking the back seat before leaving the car; 4) Caregivers should request that childcare providers contact them in the event that the child does not arrive as anticipated; 5) Parked vehicles should be kept locked at all times and keys out of reach of children; 6) If a child is missing, check the car.
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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 | 0.003 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".