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Pediatric falls ages 0–4: understanding demographics, mechanisms, and injury severities

Overview of attention for article published in Injury Epidemiology, April 2018
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2 tweeters

Citations

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19 Dimensions

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50 Mendeley
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Title
Pediatric falls ages 0–4: understanding demographics, mechanisms, and injury severities
Published in
Injury Epidemiology, April 2018
DOI 10.1186/s40621-018-0147-x
Pubmed ID
Authors

Sofia Chaudhary, Janet Figueroa, Salah Shaikh, Elizabeth Williams Mays, Rana Bayakly, Mahwish Javed, Matthew Lee Smith, Tim P. Moran, Jonathan Rupp, Sharon Nieb

Abstract

Pediatric unintentional falls are the leading cause of injury-related emergency visits for children < 5 years old. The purpose of this study was to identify population characteristics, injury mechanisms, and injury severities and patterns among children < 5 years to better inform age-appropriate falls prevention strategies. This retrospective database study used trauma registry data from the lead pediatric trauma system in Georgia. Data were analyzed for all patients < 5 years with an international classification of disease, 9th revision, clinical modification (ICD-9 CM) external cause of injury code (E-code) for unintentional falls between 1/1/2013 and 12/31/2015. Age (months) was compared across categories of demographic variables, injury mechanisms, and emergency department (ED) disposition using Kruskal-Wallis ANOVA and the Mann Whitney U test. The relationships between demographic variables, mechanism of injury (MOI), and Injury Severity Score (ISS) were evaluated using multinomial logistic regression. Inclusion criteria were met by 1086 patients (median age = 28 months; 59.7% male; 53.8% White; 49.1% <  1 m fall height). Younger children, < 1-year-old, primarily fell from caregiver's arms, bed, or furniture, while older children sustained more falls from furniture and playgrounds. Children who fell from playground equipment were older (median = 49 months, p < 0.01) than those who fell from the bed (median = 10 months), stairs (median = 18 months), or furniture (median = 19 months). Children < 1 year had the highest proportion of head injuries including skull fracture (63.1%) and intracranial hemorrhage (65.5%), 2-year-old children had the highest proportion of femur fractures (32.9%), and 4-year-old children had the highest proportion of humerus fractures (41.0%). Medicaid patients were younger (median = 24.5 months, p < 0.01) than private payer (median = 34 months). Black patients were younger (median = 20.5 months, p < 0.001) than White patients (median = 29 months). Results from multinomial logistic regression models suggest that as age increases, odds of a severe ISS (16-25) decreased (OR = 0.95, CI = 0.93-0.97). Pediatric unintentional falls are a significant burden of injury for children < 5 years. Future work will use these risk and injury profiles to inform current safety recommendations and develop evidence-based interventions for parents/caregivers and pediatric providers.

Twitter Demographics

The data shown below were collected from the profiles of 2 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 50 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 50 100%

Demographic breakdown

Readers by professional status Count As %
Student > Postgraduate 9 18%
Student > Bachelor 8 16%
Student > Ph. D. Student 5 10%
Student > Master 4 8%
Researcher 3 6%
Other 9 18%
Unknown 12 24%
Readers by discipline Count As %
Medicine and Dentistry 19 38%
Social Sciences 4 8%
Neuroscience 3 6%
Engineering 2 4%
Nursing and Health Professions 2 4%
Other 6 12%
Unknown 14 28%

Attention Score in Context

This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 14 November 2021.
All research outputs
#11,238,938
of 19,458,329 outputs
Outputs from Injury Epidemiology
#194
of 261 outputs
Outputs of similar age
#144,485
of 294,859 outputs
Outputs of similar age from Injury Epidemiology
#1
of 1 outputs
Altmetric has tracked 19,458,329 research outputs across all sources so far. This one is in the 40th percentile – i.e., 40% of other outputs scored the same or lower than it.
So far Altmetric has tracked 261 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 39.5. This one is in the 24th percentile – i.e., 24% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 294,859 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 49th percentile – i.e., 49% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them