Evidence map›Paper›PMID 30234160›Full record

ArticleOpen medicine (Warsaw, Poland)2018

Benefits of Computed Tomography in Reducing Mortality in Emergency Medicine.

Shinya Imai, Manabu Akahane, Yuto Konishi, Tomoaki Imamura

Open access · goldAbstract read
In one paragraph

Article in Open medicine (Warsaw, Poland), 2018. 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
1.0field-weighted citation impact, top 21% 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

1 citing paper in PubMed, 7 citations in OpenAlex.

  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 at 2 institutions in 1 country.

Shinya ImaiFaculty of Health Sciences, Butsuryo College of Osaka, Osaka, Japan.
Manabu AkahaneDepartment of Public Health, Health Management and Policy, Nara Medical University, Nara, Japan.
Yuto KonishiFaculty of Health Sciences, Butsuryo College of Osaka, Osaka, Japan.
Tomoaki ImamuraDepartment of Public Health, Health Management and Policy, Nara Medical University, Nara, Japan.
Nara Medical University · JPOsaka Butsuryo University · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Performing accurate diagnosis using computed tomography (CT) in emergency medicine may reduce mortality rates in various diseases. In this observational, correlational and cross-sectional study, we conducted multiple regression analyses to investigate the relationship between CT utilization rates and mortality. In addition, we estimated the annual net profits from CT to show the profitability of introducing a CT system in each Japanese prefecture. We conducted a multiple regression analysis to investigate correlations between CT utilization rates and mortality from each disease adjusted for the population density, number of doctors, as well as transportation time to the medical institution. The results of multiple regression analysis showed that traffic accident mortality was related to CT utilization rate and population density. Extrinsic death such as mortality due to falling, drowning and asphyxia was related to CT utilization, indicating that CT in emergency medicine reduced mortality. Moreover, the annual net profit from multi-slice CT (MSCT) was estimated as positive. Our study clearly demonstrates that CT utilization rates relate to a reduction in mortality from accidents, indicating that screening patients with CT in the emergency room has a beneficial effect and reduces mortality. Therefore, CT equipment has a beneficial effect in both emergency medicine and hospital management.

Indexed as

Computed tomographyEmergency medicineHospital managementMortalityTraffic accident

Identifiers

PMID30234160
PMCPMC6141888
OpenAlexW2890039358

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.