Evidence map›Paper›PMID 36281342›Full record

ArticleJournal of multidisciplinary healthcare2022

The Impact of Data Management on the Achievable Dose and Efficiency of Computed Tomography During the COVID-19 Era: A Facility-Based Ambispective Study.

Abdulaziz Mohammad Al-Sharydah, Tarek Mohammed Hegazi, Abdullah Yousef Al-Othman, Mohammad Saad Al-Aftan, Sultan Salman Al-Shehri

Open access · goldAbstract read
In one paragraph

Article in Journal of multidisciplinary healthcare, 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
0.3field-weighted citation impact, top 43% 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, 2 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

5 authors at 1 institution in 1 country.

Abdulaziz Mohammad Al-SharydahDiagnostic and Interventional Radiology Department, Imam Abdulrahman Bin Faisal University, King Fahd Hospital of the University, Al-Khobar City, Eastern Province, Saudi Arabia.ORCID 0000-0002-6590-5850
Tarek Mohammed HegaziDiagnostic and Interventional Radiology Department, Imam Abdulrahman Bin Faisal University, King Fahd Hospital of the University, Al-Khobar City, Eastern Province, Saudi Arabia.ORCID 0000-0002-8796-4923
Abdullah Yousef Al-OthmanDiagnostic and Interventional Radiology Department, Imam Abdulrahman Bin Faisal University, King Fahd Hospital of the University, Al-Khobar City, Eastern Province, Saudi Arabia.ORCID 0000-0002-0609-0380
Mohammad Saad Al-AftanDiagnostic and Interventional Radiology Department, Imam Abdulrahman Bin Faisal University, King Fahd Hospital of the University, Al-Khobar City, Eastern Province, Saudi Arabia.ORCID 0000-0003-0779-8353
Sultan Salman Al-ShehriDiagnostic and Interventional Radiology Department, Imam Abdulrahman Bin Faisal University, King Fahd Hospital of the University, Al-Khobar City, Eastern Province, Saudi Arabia.ORCID 0000-0001-9859-8343
King Fahd Hospital of the University · SA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: This study primarily aimed to evaluate the effectiveness of computational data management and analytical software for establishing departmental diagnostic reference levels (DRLs) for computed tomography (CT) scanning in clinical settings, and monitor achievable doses (ADs) for CT imaging, particularly during the coronavirus disease 2019 (COVID-19) era. Secondarily, it aimed to correlate these standards with national and international benchmarks. Patients and Methods: This ambidirectional cohort study enrolled 4668 patients (6419 CT-based examinations) who visited King Fahd Hospital of the University from May 25, 2021, to November 4, 2021. Participants' demographic data were acquired from their electronic medical charts, in addition to all corresponding CT-dose determinant parameters. The study was divided into two phases (pre- and post-data management) based on the implementation of digital data management software. Results: In both phases of the study, the size-specific dose estimate (SSDE) was the most significant confounder of dose determination compared to the dose-length product (DLP) and computed tomography dose index (CTDI) (P = 0.003). The head was the most frequently imaged body region (pre-implementation, 1051 examinations [35.1%]; post-implementation, 1071 examinations [31.3%]; P = 0.001), followed by the abdominal region (pre-implementation, 616 examinations [20.6%]; post-implementation, 256 examinations [7.48%]; P = 0.001). Based on the SSDE, DLP, and volume CTDI, the average per-section radiation exposure among organ-based scanning type was highest for the lumbar spine during the pre- and post-implementation periods. Conclusion: Data management software enabled the establishment of DRLs and reduction of ADs in CT examinations, which consequently improved key performance indicators, despite the ergonomic complexities of COVID-19. Institutions are encouraged to apply DRLs and ADs via automatic systems that monitor patient dose indices to evaluate aggregate results.

Indexed as

cross-sectional imagingdiagnostic reference levelsprotocol streamliningradiation exposureradiation protection

Identifiers

PMID36281342
PMCPMC9587732
OpenAlexW4306664812

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.