Evidence map›Paper›PMID 35819467›Full record

ReviewRadiologie (Heidelberg, Germany)2022

[Computed tomographic imaging in chronic obstructive pulmonary disease : What pulmonologists and thoracic surgeons want to know].

Felix Döllinger, Aron Elsner, Ralf-Harto Hübner

Abstract readReview
PubMed Publisher
In one paragraph

Review in Radiologie (Heidelberg, Germany), 2022. 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
0.2field-weighted citation impact, top 51% 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

1 citing paper in PubMed, 1 citations in OpenAlex.

  1. [Tobacco smoke-related diseases].Radiologie (Heidelberg, Germany) · 2022
    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

3 authors at 1 institution in 1 country.

Felix DöllingerKlinik für Radiologie, Charité Universitätsmedizin Berlin, Augustenburger Platz 1, 13353, Berlin, Deutschland. felix.doellinger@charite.de.
Aron ElsnerChirurgische Klinik, Charité Universitätsmedizin Berlin, Berlin, Deutschland.
Ralf-Harto HübnerMedizinische Klinik m. S. Infektiologie und Pneumologie, Charité Universitätsmedizin Berlin, Berlin, Deutschland.
Charité - Universitätsmedizin Berlin · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Chronic obstructive pulmonary disease (COPD) begins with chronic inflammation of the bronchial system and leads to the development of emphysema in many patients. COPD patients are characterized by reduced performance, dyspnea in the context of an obstructive respiratory disorder and increased susceptibility to infections. COPD has a major impact on public health, as it is very common and many patients die from it. The most important preventable cause of COPD is tobacco smoke inhalation, which is why consistent smoking cessation is the most important component of any COPD treatment. There is no causal therapy, but in severely symptomatic patients with advanced emphysema, respiratory mechanics can be improved by lung volume reduction if all conservative treatment options have been exhausted. Diagnostic imaging is of great importance in the care of COPD patients. This article summarizes which indications warrant the performance of computed tomography (CT) and what we should pay special attention to during image analysis in order to provide optimal advice to our clinical partners.

Indexed as

EmphysemaPulmonary Disease, Chronic ObstructivePulmonary EmphysemaSurgeonsHumansPulmonologistsTomography, X-Ray ComputedChronic bronchitisComputed tomographyLung volume reductionPulmonary emphysemaThoracic surgery

Identifiers

PMID35819467
OpenAlexW4285077301

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.