Evidence map›Paper›PMID 36107526›Full record

ArticleMedicine2022

New grading system for post-COVID-19 pulmonary fibrosis based on computed tomography findings.

Ozlem Demircioglu, Derya Kocakaya, Canan Cimsit, Nuri Cagatay Cimsit

Open access · goldAbstract read
In one paragraph

Article in Medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.6field-weighted citation impact, top 31% 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

3 citing papers in PubMed, 4 citations in OpenAlex.

  1. Cardiopulmonary Complications after Pulmonary Embolism in COVID-19.International journal of molecular sciences · 2024
    Article
  2. Article
  3. 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

4 authors at 2 institutions in 2 countries.

Ozlem DemirciogluDepartment of Radiology, Marmara University Pendik Education and Research Hospital, Istanbul, Turkey.ORCID 0000-0002-2408-76600000-0002-2408-7660
Derya KocakayaDepartment of Pulmonary Medicine and Critical Care, Marmara University Pendik Education and Research Hospital, Istanbul, Turkey.
Canan CimsitDepartment of Radiology, Marmara University Pendik Education and Research Hospital, Istanbul, Turkey.
Nuri Cagatay CimsitDepartment of Radiology, Marmara University Pendik Education and Research Hospital, Istanbul, Turkey.
S.P.E.C.I.E.S. · USMarmara University · TR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThere is currently no objective computed tomography (CT)-defined grading system for coronavirus disease (COVID-19)-related pulmonary fibrosis. We propose a CT-based radiological scale that adapts the histological fibrosis scale to pulmonary fibrosis CT findings, to evaluate possible predictive factors for the degree of fibrosis in these patients.

methodsA new radiological fibrosis grading system was created based on existing histological fibrosis scales. One hundred forty-seven COVID-19 patients with any degree of fibrosis on CT were evaluated. Smoking status, the presence of hypertension, the duration of hospital stays, the presence of comorbid diseases, and the levels of prognostic and predictive factors for COVID-19 were evaluated, and how these parameters affected the fibrosis scores was examined.

resultsOf 147 patients, 17.7% had grade 1, 17% had grade 2, 51.7% had grade 3, and 13.6% had grade 4 fibrosis. ANOVA revealed statistically significant relationships between the fibrosis scores and lactate dehydrogenase values, lymphocyte count, C-reactive protein level, and length of hospital stay. Smoking, advanced age, hypertension, and male sex showed significantly higher scores for fibrosis.

conclusionsUsing our CT-defined lung fibrosis grading system, we could predict the severity of fibrosis as well as the resultant lung pathology in COVID-19 patients. Thus, disease exacerbation and development of permanent severe fibrosis can be prevented using the appropriate treatment methods in high-risk patients.

Indexed as

COVID-19HypertensionPulmonary FibrosisC-Reactive ProteinFibrosisHumansLactate DehydrogenasesMaleTomography, X-Ray ComputedC-Reactive ProteinLactate Dehydrogenases

Identifiers

PMID36107526
PMCPMC9439634
OpenAlexW4294300964

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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 OpenQuestion graph.