Toppled television sets and head injuries in the pediatric population: a framework for prevention
Bibliographic record
Abstract
Injuries to children caused by falling televisions have become more frequent during the last decade. These injuries can be severe and even fatal and are likely to become even more common in the future as TVs increase in size and become more affordable. To formulate guidelines for the prevention of these injuries, the authors systematically reviewed the literature on injuries related to toppling televisions. The authors searched MEDLINE, PubMed, Embase, Scopus, CINAHL (Cumulative Index to Nursing and Allied Health Literature), Cochrane Library, and Google Scholar according to the Cochrane guidelines for all studies involving children 0-18 years of age who were injured by toppled TVs. Factors contributing to injury were categorized using Haddon's Matrix, and the public health approach was used as a framework for developing strategies to prevent these injuries. The vast majority (84%) of the injuries occurred in homes and more than three-fourths were unwitnessed by adult caregivers. The TVs were most commonly large and elevated off the ground. Dressers and other furniture not designed to support TVs were commonly involved in the TV-toppling incident. The case fatality rate varies widely, but almost all deaths reported (96%) were due to brain injuries. Toddlers between the ages of 1 and 3 years most frequently suffer injuries to the head and neck, and they are most likely to suffer severe injuries. Many of these injuries require brain imaging and neurosurgical intervention. Prevention of these injuries will require changes in TV design and legislation as well as increases in public education and awareness. Television-toppling injuries can be easily prevented; however, the rates of injury do not reflect a sufficient level of awareness, nor do they reflect an acceptable effort from an injury prevention perspective.
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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 | 0.032 | 0.043 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.026 | 0.009 |
| Science and technology studies | 0.005 | 0.007 |
| Scholarly communication | 0.011 | 0.015 |
| Open science | 0.007 | 0.008 |
| Research integrity | 0.010 | 0.009 |
| Insufficient payload (model declined to judge) | 0.004 | 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".