Evidence map›Paper›PMID 23969507›Full record

ArticleJournal of occupational and environmental medicine2013

Work-related knee injuries treated in US emergency departments.

Zhiqiang Chen, Sangita Chakrabarty, Robert S Levine, Muktar H Aliyu, Tan Ding, Larry L Jackson

Open access · greenAbstract read
In one paragraph

Article in Journal of occupational and environmental medicine, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.5field-weighted citation impact, top 27% of its field
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

3 citing papers in PubMed, 10 citations in OpenAlex.

  1. Article
  2. Review
  3. 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

6 authors at 1 institution in 1 country.

Zhiqiang ChenDivision of Preventive and Occupational Medicine, Department of Family and Community Medicine, Nashville, Tenn., USA.
Sangita Chakrabarty
Robert S Levine
Muktar H Aliyu
Tan Ding
Larry L Jackson
Tenneco (United States) · US

Funding

Training/Education CoreP20MD000516 · NIMHD · MEHARRY MEDICAL COLLEGE · PI ZOOROB, ROGER J · 2003 to 2013
$14.2M
Meharry Occupational Medicine Residency Training ProgramT03OH009406 · OH · MEHARRY MEDICAL COLLEGE · PI OGUNDE, BOLANLE · 2011 to 2025
$2.3M
ACL HHS T03OH009406Intramural CDC HHS CC999999NIMHD NIH HHS 5P20MD000516NIMHD NIH HHS P20 MD000516NIOSH CDC HHS T03 OH009406NIOSH CDC HHS T03OH009406-04
6 · The paper itself

Abstract

objectiveTo characterize work-related knee injuries treated in US emergency departments (EDs).

methodsWe characterized work-related knee injuries treated in EDs in 2007 and examined trends from 1998 to 2007 by using the National Electronic Injury Surveillance System-occupational supplement.

resultsIn 2007, 184,300 (± 54,000; 95% confidence interval) occupational knee injuries were treated in US EDs, accounting for 5% of the 3.4 (± 0.9) million ED-treated occupational injuries. The ED-treated knee injury rate was 13 (± 4) injuries per 10,000 full-time equivalent workers. Younger workers and older female workers had high rates. Strains/sprains and contusions/abrasions were common-frequently resulting from falls and bodily reaction/overexertion events. Knee injury rates declined from 1998 through 2007.

conclusionsKnee injury prevention should emphasize reducing falls and bodily reaction/overexertion events, particularly among all youth and older women.

Indexed as

AdolescentAdultAgedAged, 80 and overAge DistributionBinomial DistributionEmergency Service, HospitalFemaleHumansKnee InjuriesMaleMiddle AgedOccupational InjuriesPopulation SurveillanceRegression AnalysisSex Distribution

Identifiers

PMID23969507
PMCPMC4553424
OpenAlexW2439728067

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

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.