Evidence map›Paper›PMID 36766456›Full record

ArticleDiagnostics (Basel, Switzerland)2023

Ultra-Low Dose CT Chest in Acute COVID-19 Pneumonia: A Pilot Study from India.

Mandeep Garg, Shritik Devkota, Nidhi Prabhakar, Uma Debi, Maninder Kaur, Inderpaul S Sehgal, Sahajal Dhooria, Ashish Bhalla, Manavjit Singh Sandhu

Abstract read
In one paragraph

Article in Diagnostics (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Can clinicians identify community-acquired pneumonia on ultralow-dose CT? A diagnostic accuracy study.Scandinavian journal of trauma, resuscitation and emergency medicine · 2024
    Article
  7. Article
  8. Article
  9. Observational
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

9 authors.

Mandeep GargDepartment of Radiodiagnosis & Imaging, Post Graduate Institute of Medical Education and Research (PGIMER), Chandigarh 160012, India.ORCID 0000-0002-4714-6299
Shritik DevkotaDepartment of Radiodiagnosis & Imaging, Post Graduate Institute of Medical Education and Research (PGIMER), Chandigarh 160012, India.ORCID 0000-0001-5051-2037
Nidhi PrabhakarDepartment of Radiodiagnosis & Imaging, Post Graduate Institute of Medical Education and Research (PGIMER), Chandigarh 160012, India.
Uma DebiDepartment of Radiodiagnosis & Imaging, Post Graduate Institute of Medical Education and Research (PGIMER), Chandigarh 160012, India.
Maninder KaurDepartment of Radiodiagnosis & Imaging, Post Graduate Institute of Medical Education and Research (PGIMER), Chandigarh 160012, India.
Inderpaul S SehgalDepartment of Pulmonary Medicine, Post Graduate Institute of Medical Education and Research (PGIMER), Chandigarh 160012, India.
Sahajal DhooriaDepartment of Pulmonary Medicine, Post Graduate Institute of Medical Education and Research (PGIMER), Chandigarh 160012, India.
Ashish BhallaDepartment of Internal Medicine, Post Graduate Institute of Medical Education and Research (PGIMER), Chandigarh 160012, India.
Manavjit Singh SandhuDepartment of Radiodiagnosis & Imaging, Post Graduate Institute of Medical Education and Research (PGIMER), Chandigarh 160012, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The rapid increase in the number of CT acquisitions during the COVID-19 pandemic raised concerns about increased radiation exposure to patients and the resultant radiation-induced health risks. It prompted researchers to explore newer CT techniques like ultra-low dose CT (ULDCT), which could improve patient safety. Our aim was to study the utility of ultra-low dose CT (ULDCT) chest in the evaluation of acute COVID-19 pneumonia with standard-dose CT (SDCT) chest as a reference standard. This was a prospective study approved by the institutional review board. 60 RT-PCR positive COVID-19 patients with valid indication for CT chest underwent SDCT and ULDCT. ULDCT and SDCT were compared in terms of objective (noise and signal-to-noise ratio) and subjective (noise, sharpness, artifacts and diagnostic confidence) image quality, various imaging patterns of COVID-19, CT severity score and effective radiation dose. The sensitivity, specificity, positive and negative predictive value, and diagnostic accuracy of ULDCT for detecting lung lesions were calculated by taking SDCT as a reference standard. The mean age of subjects was 47.2 ± 10.7 years, with 66.67% being men. 90% of ULDCT scans showed no/minimal noise and sharp images, while 93.33% had image quality of high diagnostic confidence. The major imaging findings detected by SDCT were GGOs (90%), consolidation (76.67%), septal thickening (60%), linear opacities (33.33%), crazy-paving pattern (33.33%), nodules (30%), pleural thickening (30%), lymphadenopathy (30%) and pleural effusion (23.33%). Sensitivity, specificity and diagnostic accuracy of ULDCT for detecting most of the imaging patterns were 100% (

Indexed as

COVID-19CTlow dose CTradiation doseultra-low dose CT

Identifiers

PMID36766456
PMCPMC9914217

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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.