Evidence map›Paper›PMID 35147849›Full record

ArticleJournal of clinical monitoring and computing2022

Regional respiratory sound abnormalities in pneumothorax and pleural effusion detected via respiratory sound visualization and quantification: case report.

Kazuya Kikutani, Shinichiro Ohshimo, Takuma Sadamori, Shingo Ohki, Hiroshi Giga, Junki Ishii, Hiromi Miyoshi, Kohei Ota, Nobuaki Shime

Abstract readCase Reports
PubMed Publisher
In one paragraph

Article in Journal of clinical monitoring and computing, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.6field-weighted citation impact, top 33% 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

2 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
  2. 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 at 1 institution in 1 country.

Kazuya KikutaniDepartment of Emergency and Critical Care Medicine, Graduate School of Biomedical and Health Sciences, Hiroshima University, 1-2-3 Kasumi, Minami-ku, Hiroshima, 734-8551, Japan.
Shinichiro OhshimoDepartment of Emergency and Critical Care Medicine, Graduate School of Biomedical and Health Sciences, Hiroshima University, 1-2-3 Kasumi, Minami-ku, Hiroshima, 734-8551, Japan. ohshimos@hiroshima-u.ac.jp.ORCID 0000-0003-1119-3322
Takuma SadamoriDepartment of Emergency and Critical Care Medicine, Graduate School of Biomedical and Health Sciences, Hiroshima University, 1-2-3 Kasumi, Minami-ku, Hiroshima, 734-8551, Japan.
Shingo OhkiDepartment of Emergency and Critical Care Medicine, Graduate School of Biomedical and Health Sciences, Hiroshima University, 1-2-3 Kasumi, Minami-ku, Hiroshima, 734-8551, Japan.
Hiroshi GigaDepartment of Emergency and Critical Care Medicine, Graduate School of Biomedical and Health Sciences, Hiroshima University, 1-2-3 Kasumi, Minami-ku, Hiroshima, 734-8551, Japan.
Junki IshiiDepartment of Emergency and Critical Care Medicine, Graduate School of Biomedical and Health Sciences, Hiroshima University, 1-2-3 Kasumi, Minami-ku, Hiroshima, 734-8551, Japan.
Hiromi MiyoshiDepartment of Emergency and Critical Care Medicine, Graduate School of Biomedical and Health Sciences, Hiroshima University, 1-2-3 Kasumi, Minami-ku, Hiroshima, 734-8551, Japan.
Kohei OtaDepartment of Emergency and Critical Care Medicine, Graduate School of Biomedical and Health Sciences, Hiroshima University, 1-2-3 Kasumi, Minami-ku, Hiroshima, 734-8551, Japan.
Nobuaki ShimeDepartment of Emergency and Critical Care Medicine, Graduate School of Biomedical and Health Sciences, Hiroshima University, 1-2-3 Kasumi, Minami-ku, Hiroshima, 734-8551, Japan.
Hiroshima University · JP

Funding

Japan Agency for Medical Research and Development 20he1602002h0004
6 · The paper itself

Abstract

Assessment of respiratory sounds by auscultation with a conventional stethoscope is subjective. We developed a continuous monitoring and visualization system that enables objectively and quantitatively visualizing respiratory sounds. We herein present two cases in which the system showed regional differences in the respiratory sounds. We applied our novel continuous monitoring and visualization system to evaluate respiratory abnormalities in patients with acute chest disorders. Respiratory sounds were continuously recorded to assess regional changes in respiratory sound volumes. Because we used this system as a pilot study, the results were not shown in real time and were retrospectively analyzed. Case 1 An 89-year-old woman was admitted to our hospital for sudden-onset respiratory distress and hypoxia. Chest X-rays revealed left pneumothorax; thus, we drained the thorax. After confirming that the pneumothorax had improved, we attached the continuous monitoring and visualization system. Chest X-rays taken the next day showed exacerbation of the pneumothorax. Visual and quantitative findings showed a decreased respiratory volume in the left lung after 3 h. Case 2 A 94-year-old woman was admitted to our hospital for dyspnea. Chest X-rays showed a large amount of pleural effusion on the right side. The continuous monitoring and visualization system visually and quantitatively revealed a decreased respiratory volume in the lower right lung field compared with that in the lower left lung field. Our newly developed continuous monitoring and visualization system enabled quantitatively and visually detecting regional differences in respiratory sounds in patients with pneumothorax and pleural effusion.

Indexed as

Pleural EffusionPneumothoraxAged, 80 and overFemaleHumansPilot ProjectsRespiratory SoundsRetrospective StudiesCase reportMonitoringPleural effusionPneumothoraxRespiratory sounds

Identifiers

PMID35147849
OpenAlexW4211099663

What OpenQuestion 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 OpenQuestion graph.