Evidence map›Paper›PMID 35245277›Full record

ArticleJournal of the American Academy of Orthopaedic Surgeons. Global research & reviews2022

Characterization of More Than a Third of a Million Toy-Related Fractures.

Scott J Halperin, Sofia Prenner, Harold G Moore, Jonathan N Grauer

Abstract read
In one paragraph

Article in Journal of the American Academy of Orthopaedic Surgeons. Global research & reviews, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Scott J HalperinFrom the Yale School of Medicine, New Haven, CT (Halperin); the Weill Cornell Medical College, New York, NY (Moore); and the Department of Orthopaedics and Rehabilitation, Yale School of Medicine, New Haven, CT (Grauer).ORCID 0000-0002-0621-7716
Sofia Prenner
Jonathan N GrauerORCID 0000-0002-2626-7278

Funding

Yale Clinical and Translational Science Award (U Component)UL1TR001863 · NCATS · YALE UNIVERSITY · PI John H. Krystal, LUCILA OHNO-MACHADO · 2016 to 2026
$102.9M
NCATS NIH HHS UL1 TR001863
6 · The paper itself

Abstract

introductionThe toy industry has grown substantially over time, with billions of dollars of toys sold each year in the United States alone. Even after safety considerations, injuries can result. This study examined toy-related fractures in the US Emergency Departments (ED).

methodsThe 1999 to 2018 National Electronic Injury Surveillance System from the US Consumer Product Safety Commission was examined data for fractures involving a toy-related injury. The incidence, trends, and anatomic locations for such fractures were assessed.

resultsIn total, 347,135 toy-related fractures were identified, of which 237,754 (68%) were in patients younger than 18 years, 182,516 (53%) were sustained by male subjects, and a 95% yearly incidence increase was observed over the years of the study. Anatomically, 37% were shoulder/arm/elbow, 24% wrist/hand/finger, 19% ankle/toe/foot, 10% leg/knee, 6% face/neck/head, and 4% trunk/pubic region. DISCUSSION: Despite safety considerations with toy design, more than a third of toy-related fractures were seen in the ED, with a nearly doubling yearly incidence over the study period. This could be contributed to by increased production and prevalence of toys and/or rougher play and increased overall violence. These results are important not only for patient safety but also for orthopaedic surgeons, EDs, toy manufacturers, and policymakers.

Indexed as

Elbow JointFractures, BoneEmergency Service, HospitalHumansLower ExtremityMaleUpper Extremity

Identifiers

PMID35245277
PMCPMC8896474

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.