Evidence map›Paper›PMID 40355745›Full record

ArticleEuropean journal of nuclear medicine and molecular imaging2025

Post-COVID-19 lung disease: utility of biochemical and imaging markers in uncovering residual lung inflammation and monitoring anti-inflammatory therapy, a prospective study.

Yogita Khandelwal, Manish Ora, Bela Jain, Manish Dixit, Prakash Singh, Ajmal Khan, Alok Nath, Vikas Agarwal, Sanjay Gambhir

Abstract read
PubMed Publisher
In one paragraph

Article in European journal of nuclear medicine and molecular imaging, 2025. 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

9 authors.

Yogita KhandelwalDepartment of Nuclear Medicine, AIIMS, New Delhi, India.
Manish OraDepartment of Nuclear Medicine, SGPGI, Lucknow, India.
Bela JainDepartment of Nuclear Medicine, AIIMS, New Delhi, India.
Manish DixitDepartment of Nuclear Medicine, SGPGI, Lucknow, India.
Prakash SinghDepartment of Nuclear Medicine, KGMC, Lucknow, India.
Ajmal KhanDepartment of Pulmonary Medicine, SGPGI, Lucknow, India.
Alok NathDepartment of Pulmonary Medicine, SGPGI, Lucknow, India.
Vikas AgarwalDepartment of Immunology, SGPGI, Lucknow, India.
Sanjay GambhirDepartment of Nuclear Medicine, SGPGI, Lucknow, India. gaambhir@yahoo.com.ORCID 0000-0001-8764-3890

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposePost-COVID-19 lung disease (PCLD) is a significant concern following the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic. PCLD encompasses persistent debilitating respiratory symptoms and radiological changes beyond the acute disease phase. It highlights the ongoing search to identify and manage lingering diseases. This prospective study utilizes F18-Fludeoxyglucose (FDG) PET/CT to identify residual inflammatory lung lesions in PCLD. Treatment response was assessed after anti-inflammatory and antifibrotic therapies. MATERIALS AND

methodsThirty patients post-severe COVID-19 pneumonia enrolled. They underwent baseline

resultsBaseline

conclusionThis prospective study identifies and quantifies ongoing significant residual lung inflammation in PCLD on CLINICAL TRIAL NUMBER: Not applicable.

Indexed as

Anti-Inflammatory AgentsCOVID-19PneumoniaAdultAgedBiomarkersFemaleFluorodeoxyglucose F18HumansLungMaleMiddle AgedPositron Emission Tomography Computed TomographyProspective StudiesAnti-Inflammatory AgentsBiomarkersFluorodeoxyglucose F1818F-FDG PET/CTLong-COVIDLung infectionsPost-COVID 19 lung disease

Identifiers

What Socratic holds

Textmetadata
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 Socratic graph.