Evidence map›Paper›PMID 33101684›Full record

ArticleSAGE open medical case reports2020

Use of lung ultrasound for diagnosis and monitoring of coronavirus disease 2019 pneumonia: A case report.

Debo Yun, Yan Cui, Yuan Geng, Yujiao Yang

Open access · goldAbstract readCase Reports
In one paragraph

Article in SAGE open medical case reports, 2020. 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 85% 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

4 authors at 2 institutions in 1 country.

Debo YunDepartment of Neurosurgery, Nanchong Central Hospital, Nanchong, China.
Yan CuiDepartment of Emergency, Affiliated Hospital of North Sichuan Medical College, Nanchong, China.
Yuan GengDepartment of Anesthesiology, Affiliated Hospital of North Sichuan Medical College, Nanchong, China.
Yujiao YangDepartment of Anesthesiology, Affiliated Hospital of North Sichuan Medical College, Nanchong, China.ORCID https://orcid.org/0000-0002-5409-6007
Affiliated Hospital of North Sichuan Medical College · CNNanchong Central Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Knowledge of lung ultrasound characteristics of coronavirus disease 2019 pneumonia might be useful for early diagnosis and clinical monitoring of patients, and lung ultrasound can help to control the spread of infection in healthcare settings. In this case report, a 36-year-old man with severe acute respiratory syndrome coronavirus 2 infection was diagnosed by reverse transcription-polymerase chain reaction testing of a nasopharyngeal swab. The lung ultrasound findings for this patient were the interstitial-alveolar damage showing bilateral, diffuse pleural line abnormalities, subpleural consolidations, white lung areas and thick, irregular vertical artifacts. When the patient recovered from the severe acute respiratory syndrome coronavirus 2 infection, lung ultrasound images showed a normal pleural line with A-lines regularly reverberating. Performing lung ultrasound at the bedside minimizes the need to move the patient, thus reducing the risk of spreading infection among healthcare staff. Lung ultrasound is useful for early diagnosis and evaluation of the severity of coronavirus disease 2019 pneumonia and for monitoring its progress over the course of the disease.

Indexed as

consolidationCoronavirus disease 2019 pneumonialung ultrasoundsevere acute respiratory syndrome coronavirus 2 infectionwhite lung

Identifiers

PMID33101684
PMCPMC7550954
OpenAlexW3092046339

What OpenQuestion holds

Textmetadata
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.