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Record W4389676223 · doi:10.1186/s40621-023-00476-z

A multicenter evaluation of pediatric emergency department injury visits during the COVID-19 pandemic

2023· article· en· W4389676223 on OpenAlexaff
Holly R. Hanson, Margaret K. Formica, Danielle Laraque‐Arena, Mark R. Zonfrillo, Puja Desai, Joseph O. O’Neil, Purnima Unni, Estell Lenita Johnson, Patricia Cobb, Maneesha Agarwal, Kristen Beckworth, Stephanie Schroter, Stephen Strotmeyer, Katie Donnelly, Leah K. Middelberg, Amber Morse, James Dodington, Richard F. Latuska, Brit Anderson, Karla A. Lawson, Michael Valente, Michael N. Levas, Andrew Kiragu, Kathy Monroe, Stephanie Ruest, Lois K. Lee, Tanya Charyk Stewart, Megan M. Attridge, Maya Haasz, Mubeen Jafri, Alicia McIntire, Steven C. Rogers, Neil G. Uspal, Ashley Blanchard, Max D. Hazeltine, Teresa Riech, Charles A. Jennissen, Lynn Model, Quinney Fu, Lindsay Clukies, David Juang, Michelle T. Ruda, José M. Prince, Stephanie D. Chao, Brian K. Yorkgitis, Wendy J. Pomerantz

Bibliographic record

VenueInjury Epidemiology · 2023
Typearticle
Languageen
FieldMedicine
TopicInjury Epidemiology and Prevention
Canadian institutionsLondon Health Sciences CentreWestern University
FundersNational Center for Advancing Translational SciencesCincinnati Children's Hospital Medical Center
KeywordsMedicineCoronavirus disease 2019 (COVID-19)PandemicPoison controlInjury preventionIncidence (geometry)Emergency medicineOccupational safety and healthInjury Severity ScorePediatricsEpidemiologyDiseaseInternal medicineInfectious disease (medical specialty)

Abstract

fetched live from OpenAlex

BACKGROUND: Injuries, the leading cause of death in children 1-17 years old, are often preventable. Injury patterns are impacted by changes in the child's environment, shifts in supervision, and caregiver stressors. The objective of this study was to evaluate the incidence and proportion of injuries, mechanisms, and severity seen in Pediatric Emergency Departments (PEDs) during the COVID-19 pandemic. METHODS: This multicenter, cross-sectional study from January 2019 through December 2020 examined visits to 40 PEDs for children < 18 years old. Injury was defined by at least one International Classification of Disease-10th revision (ICD-10) code for bodily injury (S00-T78). The main study outcomes were total and proportion of PED injury-related visits compared to all visits in March through December 2020 and to the same months in 2019. Weekly injury visits as a percentage of total PED visits were calculated for all weeks between January 2019 and December 2020. RESULTS: The study included 741,418 PED visits for injuries pre-COVID-19 pandemic (2019) and during the COVID-19 pandemic (2020). Overall PED visits from all causes decreased 27.4% in March to December 2020 compared to the same time frame in 2019; however, the proportion of injury-related PED visits in 2020 increased by 37.7%. In 2020, injured children were younger (median age 6.31 years vs 7.31 in 2019), more commonly White (54% vs 50%, p < 0.001), non-Hispanic (72% vs 69%, p < 0.001) and had private insurance (35% vs 32%, p < 0.001). Injury hospitalizations increased 2.2% (p < 0.001) and deaths increased 0.03% (p < 0.001) in 2020 compared to 2019. Mean injury severity score increased (2.2 to 2.4, p < 0.001) between 2019 and 2020. Injuries declined for struck by/against (- 4.9%) and overexertion (- 1.2%) mechanisms. Injuries proportionally increased for pedal cycles (2.8%), cut/pierce (1.5%), motor vehicle occupant (0.9%), other transportation (0.6%), fire/burn (0.5%) and firearms (0.3%) compared to all injuries in 2020 versus 2019. CONCLUSIONS: The proportion of PED injury-related visits in March through December 2020 increased compared to the same months in 2019. Racial and payor differences were noted. Mechanisms of injury seen in the PED during 2020 changed compared to 2019, and this can inform injury prevention initiatives.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.020
metaresearch head score (Gemma)0.021
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.022
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0200.021
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.148
GPT teacher head0.462
Teacher spread0.314 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations12
Published2023
Admission routes1
Has abstractyes

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