Evidence map›Paper›PMID 42519518›Full record

ArticleTrauma surgery & acute care open2026

An exponential increase in e-bike injuries in California.

John Austin, Louis Perkins, Laura N Haines, Leslie Kobayashi, Allison E Berndtson, Jessica L Weaver, Jarrett Santorelli, John Maa, Romeo C Ignacio, Sigrid Burruss and 3 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Trauma surgery & acute care open, 2026. 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

13 authors.

John AustinDepartment of Surgery, University of California San Diego, La Jolla, California, USA.ORCID https://orcid.org/0000-0002-6394-7520
Louis PerkinsDepartment of Surgery, University of California San Diego, La Jolla, California, USA.ORCID https://orcid.org/0000-0002-3136-5104
Laura N HainesDepartment of Surgery, University of California San Diego, La Jolla, California, USA.ORCID https://orcid.org/0000-0003-4088-2418
Leslie KobayashiDivision of Trauma, Surgical Critical Care, Burns and Acute Care Surgery, Department of Surgery, University of California San Diego, San Diego, California, USA.
Allison E BerndtsonDepartment of Surgery, University of California San Diego, La Jolla, California, USA.ORCID https://orcid.org/0000-0002-7299-453X
Jessica L WeaverDepartment of Surgery, University of California San Diego, La Jolla, California, USA.
Jarrett SantorelliDivision of Trauma, Surgical Critical Care, Burns and Acute Care Surgery, Department of Surgery, University of California San Diego, San Diego, California, USA.
John MaaDepartment of Surgery, MarinHealth Medical Center, Greenbrae, California, USA.
Romeo C IgnacioDivision of Pediatric Surgery, Department of Surgery, University of California San Diego, San Diego, California, USA.
Sigrid BurrussUniversity of California Irvine, Irvine, California, USA.
Amy E LiepertDepartment of Surgery, University of California San Diego, La Jolla, California, USA.
Todd W CostantiniDepartment of Surgery, University of Minnesota, Minneapolis, Minnesota, USA.ORCID https://orcid.org/0000-0002-0215-5327
Jay J DoucetDepartment of Surgery, University of California San Diego, La Jolla, California, USA.ORCID https://orcid.org/0000-0001-9617-001X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Electric bicycle (e-bike) sales are growing exponentially worldwide. These vehicles are faster and heavier, with younger riders using e-bikes more frequently, reports of inconsistent helmet use, and increased deaths and injuries. We hypothesized that California has experienced significant annual increases in e-bike rider injuries and injury severity compared with injured traditional bicyclists, using a transportation injury registry and geospatial mapping system, including socioeconomic factors. Methods: We conducted a retrospective analysis of the California Highway Patrol Statewide Integrated Traffic Records System (SWITRS) from 2018 to 2024, identifying e-bike collisions through reporter coding and vehicle brand names. We analyzed demographics, injury severity, fault status, traffic violations, and scene census tract Social Vulnerability Index (SVI). All non-e-bike traditional bicycle collisions served as the comparison group. Results: We identified 4035 e-bike and 58 332 bicycle collisions. E-bike injuries increased sharply over the study period, from two incidents in 2018 to 1566 in 2024 (p<0.001), while bicycle collisions remained stable. E-bike riders were younger (median 33 vs 36 years; p<0.001), with a significantly greater proportion aged ≤14 years (15.6% vs 10.2%). Moderate-to-severe injuries were more common among e-bike riders (15.8% vs 11.9%; p<0.001). Although overall mortality was similar (2.0% vs 1.7%), a significant divergence emerged in 2024, with higher e-bike mortality (p=0.027) and a significant interaction between year and vehicle type. E-bike collisions demonstrated more unsafe speed and improper turning violations and occurred in census tracts with lower social vulnerability. Spatial analysis showed tighter clustering of e-bike collisions relative to bicycles. Conclusions: E-bike injuries are rapidly increasing in California and are associated with a higher severity of injuries compared with traditional bicycles. Urgent efforts are needed for targeted prevention, regulatory alignment, and rider education. Level of evidence: Level III, retrospective case-control study.

Indexed as

Accidental InjuriesAccidents, Trafficepidemiology

Identifiers

PMID42519518
PMCPMC13384186

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

None linked

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.