Trial reportBMC pulmonary medicine2023
Evaluation of long-term sequelae by cardiopulmonary exercise testing 12 months after hospitalization for severe COVID-19.
Trial report in BMC pulmonary medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04519320 (Medium and Long Term Follow-up of SARS-COV-2 Infected Patients Treated at Besançon and Dijon Hospitals), which is not on this map. Cited by 10 papers.
What it found
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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.
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.
Medium and Long Term Follow-up of SARS-COV-2 Infected Patients Treated at Besançon and Dijon Hospitals: Research and Characterization of Pulmonary Sequelae
Who cites it
10 citing papers in PubMed, 21 citations in OpenAlex.
- Persistence of fatigue in the absence of pathophysiological mechanisms in some patients more than 2 years after the original SARS-CoV-2 infection.Experimental physiology · 2026Article
- Exercise ventilatory inefficiency may be a specific feature of patients with acromegaly.Pituitary · 2025Article
- Functional Capacity Impairment in Long COVID After 17 Months of Severe Acute Disease.International journal of environmental research and public health · 2025Article
- Health-Related Quality of Life One Year After Intensive Care Unit Admission for COVID-19: A Retrospective, Cross-Sectional, Longitudinal Observational Study.Health science reports · 2025Article
- How Is Life After Severe COVID-19?: Functional Cardiopulmonary Outcome and Quality of Life.CHEST pulmonary · 2024Article
- Persisting exercise ventilatory inefficiency in subjects recovering from COVID-19. Longitudinal data analysis 34 months post-discharge.BMC pulmonary medicine · 2024Article
- Short- and Long-Term Chest-CT Findings after Recovery from COVID-19: A Systematic Review and Meta-Analysis.Diagnostics (Basel, Switzerland) · 2024Review
- Observational
- Healthcare utilization 9 months pre- and post- COVID-19 hospitalization among patients discharged alive.PloS one · 2024Article
- SARS-CoV-2 infection sequelae on exercise response: persistent or reversible? A 2-year perspective.ERJ open research · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundCardiopulmonary exercise testing (CPET) is an important clinical tool that provides a global assessment of the respiratory, circulatory and metabolic responses to exercise which are not adequately reflected through the measurement of individual organ system function at rest. In the context of critical COVID-19, CPET is an ideal approach for assessing long term sequelae.
methodsIn this prospective single-center study, we performed CPET 12 months after symptom onset in 60 patients that had required intensive care unit treatment for a severe COVID-19 infection. Lung function at rest and chest computed tomography (CT) scan were also performed.
resultsTwelve months after severe COVID-19 pneumonia, dyspnea was the most frequently reported symptom although only a minority of patients had impaired respiratory function at rest. Mild ground-glass opacities, reticulations and bronchiectasis were the most common CT scan abnormalities. The majority of the patients (80%) had a peak O
conclusionsTwelve months after severe COVID-19 pneumonia, most of the patients had a peak V'O
trial registrationNCT04519320 (19/08/2020).
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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.