Characterising dysfunctional breathing seen in post-acute sequelae of SARS-CoV-2 using approximate entropy
Identifying DB on CPET requires visual recognition, which has limitations. ApEn <i>V</i>'<sub>E</sub> is an objective metric that can reliably differentiate DB from normal breathing patterns on CPET. This can be a valuable addition to keen visual scrutiny of CPET data.
Authors
- Benjamin H. Natelson (ORCID: https://orcid.org/0000-0002-0141-5844)
- Beno W. Oppenheimer (ORCID: https://orcid.org/0000-0001-7195-8927)
- Donna Mancini (ORCID: https://orcid.org/0000-0002-6050-1785)
- Dane B. Cook (ORCID: https://orcid.org/0000-0002-3992-4820)
- Erin Eschbach
- Marie Lynn Miranda (ORCID: https://orcid.org/0000-0002-5670-0837)
- Kevin Rurak (ORCID: https://orcid.org/0000-0002-4496-9839)
- Ankit Parekh (ORCID: https://orcid.org/0000-0002-5396-0553)
- David M. Rapoport (ORCID: https://orcid.org/0000-0002-4855-2600)
Institutions
- William S. Middleton Memorial Veterans Hospital (US)
Publication Details
- Journal
- ERJ Open Research
- Published
- 2025-02-13
- DOI
- https://doi.org/10.1183/23120541.00652-2024
- Citations
- 1
- Primary Topic
- Long-Term Effects of COVID-19
- Type
- article
- Field-Weighted Citation Impact
- 1.39