Evidence map›Paper›PMID 40751248›Full record

ArticleBMC pulmonary medicine2025

Cough duration, energy and sound frequency in COVID-19 patients: the spectral analysis results.

Andrey V Budnevsky, Djuro Kosanovic, Evgeniy S Ovsyannikov, Oleg N Choporov, Alexander V Pertsev, Sofia N Feigelman, Tatiana A Chernik, Alexey V Maksimov, Galina G Prozorova, Svetlana A Kozhevnikova and 4 more

Abstract read
In one paragraph

Article in BMC pulmonary medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed, 1 pooled it
–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 synthesis or guideline pooled it.

  1. Cough biomarkers for diagnosis and monitoring of respiratory disease: a systematic review.European respiratory review : an official journal of the European Respiratory Society · 2026
    Pooled it
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

14 authors.

Andrey V BudnevskyVoronezh State Medical University named after N.N. Burdenko, Studencheskaya street 10, Voronezh, 394036, Russian Federation.
Djuro KosanovicSechenov First Moscow State Medical University, Trubetskaya street 8/2, Moscow, 119991, Russian Federation.
Evgeniy S OvsyannikovVoronezh State Medical University named after N.N. Burdenko, Studencheskaya street 10, Voronezh, 394036, Russian Federation.
Oleg N ChoporovVoronezh State Medical University named after N.N. Burdenko, Studencheskaya street 10, Voronezh, 394036, Russian Federation.
Alexander V PertsevVoronezh State Medical University named after N.N. Burdenko, Studencheskaya street 10, Voronezh, 394036, Russian Federation.
Sofia N FeigelmanVoronezh State Medical University named after N.N. Burdenko, Studencheskaya street 10, Voronezh, 394036, Russian Federation.
Tatiana A ChernikVoronezh State Medical University named after N.N. Burdenko, Studencheskaya street 10, Voronezh, 394036, Russian Federation.
Alexey V MaksimovVoronezh State University, Universitetskaya ploshchad 1, Voronezh, 394018, Russian Federation.
Galina G ProzorovaVoronezh State Medical University named after N.N. Burdenko, Studencheskaya street 10, Voronezh, 394036, Russian Federation.
Svetlana A KozhevnikovaVoronezh State Medical University named after N.N. Burdenko, Studencheskaya street 10, Voronezh, 394036, Russian Federation.
Roman E TokmachevVoronezh State Medical University named after N.N. Burdenko, Studencheskaya street 10, Voronezh, 394036, Russian Federation.
Anastasiya V BelyakovaVoronezh City Hospital #16, Poliny Osipenko street 24, Voronezh, 394029, Russian Federation.
Valeria R DrobyshevaVoronezh State Medical University named after N.N. Burdenko, Studencheskaya street 10, Voronezh, 394036, Russian Federation.
Sergey N AvdeevSechenov First Moscow State Medical University, Trubetskaya street 8/2, Moscow, 119991, Russian Federation. serg_avdeev@list.ru.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCough is one of the most common clinical manifestations of COVID-19. Objective of our study was to perform analysis of cough duration, energy and sound frequency in COVID-19 patients, compared to induced cough in controls and the cough in asthma and chronic obstructive pulmonary disease (COPD) patients.

methodsThe following characteristics of cough sounds were obtained: duration, Q coefficient - low/medium-frequency energy (60-600 Hz) to high-frequency energy (600-6000 Hz) ratio, and frequency of maximum sound energy. The cough was divided into three phases and assessment of characteristics was applied to the entire coughing act and to each phase separately in controls and patients with COVID-19, asthma and COPD.

resultsThe cough sounds of COVID-19 patients were characterized by a shorter duration, a predominance of high-frequency energy and higher maximum frequency of the energy, compared with the induced cough of controls. However, the frequencies of the maximum sound energy of the individual cough phases did not differ significantly, as did the duration of the first phase. In addition, the significant differences were demonstrated in some time-frequency parameters of cough sounds in the patients with asthma and COPD as compared to COVID-19 patients.

conclusionTherefore, we have shown the distinction between the cough characteristics of COVID-19 patients compared to controls and patients with asthma or COPD.

Indexed as

AsthmaCoughCOVID-19Pulmonary Disease, Chronic ObstructiveRespiratory SoundsAdultAgedCase-Control StudiesFemaleHumansMaleMiddle AgedSARS-CoV-2Time FactorsCough sound durationCough sound energyCough sound frequencyCOVID-19

Identifiers

PMID40751248
PMCPMC12317533

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.