F-18 FDG PET/CT as a One-Stop Shop Imaging Modality for Assessment of Neurologic and Pulmonary Manifestations of COVID-19.

Abbas Yousefi-Koma, Farahnaz Aghahosseini, Hannaneh Yousefi-Koma, Alireza Roohizadeh, Mojgan Panahmoghaddam

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In one paragraph

Article in Tanaffos, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it

0cells of the map it votes in

0citing papers in PubMed

–field-weighted citation impact, top 69% 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

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

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 3 institutions in 1 country.

Abbas Yousefi-KomaChronic Respiratory Disease Research Center, National Research Institute of Tuberculosis and Lung Diseases, Shahid Beheshti University of Medical Sciences, Tehran, Iran.

Farahnaz AghahosseiniChronic Respiratory Disease Research Center, National Research Institute of Tuberculosis and Lung Diseases, Shahid Beheshti University of Medical Sciences, Tehran, Iran.

Hannaneh Yousefi-KomaSchool of Medicine, Tehran University of Medical Sciences, Tehran, Iran.

Alireza RoohizadehChronic Respiratory Disease Research Center, National Research Institute of Tuberculosis and Lung Diseases, Shahid Beheshti University of Medical Sciences, Tehran, Iran.

Mojgan PanahmoghaddamChronic Respiratory Disease Research Center, National Research Institute of Tuberculosis and Lung Diseases, Shahid Beheshti University of Medical Sciences, Tehran, Iran.

Masih Daneshvari Hospital · IRShahid Beheshti University of Medical Sciences · IRTehran University of Medical Sciences · IR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Neurologic manifestations are now being increasingly encountered in patients who are admitted for respiratory symptoms of COVID-19. A 67-year-old male with a recent history of Wernicke's aphasia was referred to the nuclear medicine department for risk stratification of malignancy in pulmonary nodule by 18F-FDG PET-CT scan. PET-CT revealed decreased metabolic activity in the left temporoparietal lobe of the brain consistent with recent CVA and excluded malignancy in the pulmonary nodule with low-grade metabolic activity. Incidentally noted, new bilateral pulmonary hypermetabolic ground glass opacities rising suspicious for covid-19 infection which was confirmed by PCR of nasopharyngeal mucosa sample. These findings highlight the value of 18FFDG PET-CT in the assessment of COVID-19 infection especially in non-pulmonary presentations like early neurologic manifestation.

Indexed as

COVID-19PCRPET-CT scanWernicke’s aphasia

Identifiers

PMID37920311

PMCPMC10618579

OpenAlexW4388302540

What OpenQuestion holds

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LicenceCC BY-NC

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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.