Evidence map›Paper›PMID 36057745›Full record

ArticleRadiological physics and technology2022

Assessment of organ and effective doses received by adult patients undergoing computed tomography in three hospitals in Brazzaville, Congo Republic.

J Bazoma, G B Dallou, P Ondo Meye, C Bouka Biona, Saïdou, G H Ben-Bolie

Abstract read
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In one paragraph

Article in Radiological physics and technology, 2022. 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

6 authors.

J BazomaFaculté des Sciences et Techniques, Université Marien Ngouabi, BP 69, Brazzaville, Congo.
G B DallouFaculté des Sciences et Techniques, Université Marien Ngouabi, BP 69, Brazzaville, Congo. dg_blanc@yahoo.fr.ORCID http://orcid.org/0000-0003-0025-2083
P Ondo MeyeDirection Générale de la Radioprotection et de la Sûreté Nucléaire, Ministère de l'Energie et des Ressources Hydrauliques, BP 1172, Libreville, Gabon.
C Bouka BionaFaculté des Sciences et Techniques, Université Marien Ngouabi, BP 69, Brazzaville, Congo.
SaïdouNuclear Physics Laboratory, Faculty of Science, University of Yaounde I, P.O. Box 812, Yaoundé, Cameroon.
G H Ben-BolieLaboratory of Atomic, Molecular and Nuclear Physics, Department of Physics, Faculty of Science, University of Yaounde I, P.O. Box 812, Yaoundé, Cameroon.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The present study aimed to evaluate adult patient data collected from three hospitals in Brazzaville, Congo Republic, for the purpose of estimating organ and effective doses for each included examination type. A total of 1277 adult patients (aged 16-97 years) who underwent head, chest, abdominopelvic (AP), chest-abdomen-pelvis (CAP), and lumbar spine computed tomography scans were considered. The organ and effective doses were estimated using a Monte Carlo-based method. The effective doses were also determined using k-factors. In general, the organ and effective doses estimated in this study were higher than those reported in the literature. The k-factor method underestimated the effective dose by up to 65.9%. This study demonstrates that urgent steps should be taken to reduce doses administered to patients to optimal levels. Such optimal levels may be achieved by adopting local diagnostic reference levels, together with the implementation of dose reduction strategies.

Indexed as

HospitalsTomography, X-Ray ComputedAdultCongoHumansMonte Carlo MethodPhantoms, ImagingRadiation DosageAdult patientComputed tomographyEffective doseMonte CarloOrgan dose

Identifiers

PMID36057745

What OpenQuestion holds

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Registered trials

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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.