Evolving phenotypes of non-hospitalized patients that indicate long COVID
| Title: | Evolving phenotypes of non-hospitalized patients that indicate long COVID |
|---|---|
| Authors: | Estiri H.; Strasser Z. H.; Brat G. A.; Semenov Y. R.; Aaron J. R.; Agapito G.; Albayrak A.; Alessiani M.; Amendola D. F.; Anthony L. L. L. J.; Aronow B. J.; Ashraf F.; Atz A.; Avillach P.; Balshi J.; Beaulieu-Jones B. K.; Bell D. S.; Bellasi A.; Bellazzi R.; Benoit V.; Beraghi M.; Sobrino J. L. B.; Bernaux M.; Bey R.; Martinez A. B.; Boeker M.; Bonzel C. -L.; Booth J.; Bosari S.; Bourgeois F. T.; Bradford R. L.; Breant S.; Brown N. W.; Bryant W. A.; Bucalo M.; Burgun A.; Cai T.; Cannataro M.; Carmona A.; Caucheteux C.; Champ J.; Chen J.; Chen K.; Chiovato L.; Chiudinelli L.; Cho K.; Cimino J. J.; Colicchio T. K.; Cormont S.; Cossin S.; Craig J. B.; Bermudez J. L. C.; Rojo J. C.; Dagliati A.; Daniar M.; Daniel C.; Davoudi A.; Devkota B.; Dubiel J.; Esteve L.; Fan S.; Follett R. W.; Gaiolla P. S. A.; Ganslandt T.; Barrio N. G.; Garmire L. X.; Gehlenborg N.; Geva A.; Gradinger T.; Gramfort A.; Griffier R.; Griffon N.; Grisel O.; Gutierrez-Sacristan A.; Hanauer D. A.; Haverkamp C.; He B.; Henderson D. W.; Hilka M.; Holmes J. H.; Hong C.; Horki P.; Huling K. M.; Hutch M. R.; Issitt R. W.; Jannot A. S.; Jouhet V.; Keller M. S.; Kirchoff K.; Klann J. G.; Kohane I. S.; Krantz I. D.; Kraska D.; Krishnamurthy A. K.; L'Yi S.; Le T. T.; Leblanc J.; Leite A. R. R.; Lemaitre G.; Lenert L.; Leprovost D.; Liu M.; Loh N. H. W.; Lozano-Zahonero S.; Luo Y.; Lynch K. E.; Mahmood S.; Maidlow S.; Malovini A.; Mandl K. D.; Mao C.; Maram A.; Martel P.; Masino A. J.; Mazzitelli M.; Mensch A.; Milano M.; Minicucci M. F.; Moal B.; Moore J. H.; Moraleda C.; Morris J. S.; Morris M.; Moshal K. L.; Mousavi S.; Mowery D. L.; Murad D. A.; Naughton T. P.; Neuraz A.; Ngiam K. Y.; Norman J. B.; Obeid J.; Okoshi M. P.; Olson K. L.; Omenn G. S.; Orlova N.; Ostasiewski B. D.; Palmer N. P.; Paris N.; Patel L. P.; Jimenez M. P.; Pfaff E. R.; Pillion D.; Prokosch H. U.; Prudente R. A.; Gonzalez V. Q.; Ramoni R. B.; Raskin M.; Rieg S.; Dominguez G. R.; Rojo P.; Saez C.; Salamanca E.; Samayamuthu M. J.; Sandrin A.; Santos J. C. C.; Savino M.; Schriver E. R.; Schubert P.; Schuettler J.; Scudeller L.; Sebire N. J.; Balazote P. S.; Serre P.; Serret-Larmande A.; Shakeri Z.; Silvio D.; Sliz P.; Son J.; Sonday C.; South A. M.; Spiridou A.; Tan A. L. M.; Tan B. W. Q.; Tan B. W. L.; Tanni S. E.; Taylor D. M.; Terriza Torres A. I.; Tibollo V.; Tippmann P.; Torti C.; Trecarichi E. M.; Tseng Y. -J.; Vallejos A. K.; Varoquaux G.; Vella M. E.; Verdy G.; Vie J. -J.; Visweswaran S.; Vitacca M.; Wagholikar K. B.; Waitman L. R.; Wang X.; Wassermann D.; Weber G. M.; Xia Z.; Yehya N.; Yuan W.; Zambelli A.; Zhang H. G.; Zoeller D.; Zucco C.; Murphy S. N.; Patel C. J. |
| Contributors: | Estiri, H.; Strasser, Z. H.; Brat, G. A.; Semenov, Y. R.; Aaron, J. R.; Agapito, G.; Albayrak, A.; Alessiani, M.; Amendola, D. F.; Anthony, L. L. L. J.; Aronow, B. J.; Ashraf, F.; Atz, A.; Avillach, P.; Balshi, J.; Beaulieu-Jones, B. K.; Bell, D. S.; Bellasi, A.; Bellazzi, R.; Benoit, V.; Beraghi, M.; Sobrino, J. L. B.; Bernaux, M.; Bey, R.; Martinez, A. B.; Boeker, M.; Bonzel, C. -L.; Booth, J.; Bosari, S.; Bourgeois, F. T.; Bradford, R. L.; Breant, S.; Brown, N. W.; Bryant, W. A.; Bucalo, M.; Burgun, A.; Cai, T.; Cannataro, M.; Carmona, A.; Caucheteux, C.; Champ, J.; Chen, J.; Chen, K.; Chiovato, L.; Chiudinelli, L.; Cho, K.; Cimino, J. J.; Colicchio, T. K.; Cormont, S.; Cossin, S.; Craig, J. B.; Bermudez, J. L. C.; Rojo, J. C.; Dagliati, A.; Daniar, M.; Daniel, C.; Davoudi, A.; Devkota, B.; Dubiel, J.; Esteve, L.; Fan, S.; Follett, R. W.; Gaiolla, P. S. A.; Ganslandt, T.; Barrio, N. G.; Garmire, L. X.; Gehlenborg, N.; Geva, A.; Gradinger, T.; Gramfort, A.; Griffier, R.; Griffon, N.; Grisel, O.; Gutierrez-Sacristan, A.; Hanauer, D. A.; Haverkamp, C.; He, B.; Henderson, D. W.; Hilka, M.; Holmes, J. H.; Hong, C.; Horki, P.; Huling, K. M.; Hutch, M. R.; Issitt, R. W.; Jannot, A. S.; Jouhet, V.; Keller, M. S.; Kirchoff, K.; Klann, J. G.; Kohane, I. S.; Krantz, I. D.; Kraska, D.; Krishnamurthy, A. K.; L'Yi, S.; Le, T. T.; Leblanc, J.; Leite, A. R. R.; Lemaitre, G. |
| Publication Year: | 2021 |
| Collection: | IRIS UNIPV (Università degli studi di Pavia) |
| Subject Terms: | Electronic health record; Machine learning; Phenotype; Post-acute sequelae of SARS-CoV-2 |
| Description: | Background: For some SARS-CoV-2 survivors, recovery from the acute phase of the infection has been grueling with lingering effects. Many of the symptoms characterized as the post-acute sequelae of COVID-19 (PASC) could have multiple causes or are similarly seen in non-COVID patients. Accurate identification of PASC phenotypes will be important to guide future research and help the healthcare system focus its efforts and resources on adequately controlled age- and gender-specific sequelae of a COVID-19 infection. Methods: In this retrospective electronic health record (EHR) cohort study, we applied a computational framework for knowledge discovery from clinical data, MLHO, to identify phenotypes that positively associate with a past positive reverse transcription-polymerase chain reaction (RT-PCR) test for COVID-19. We evaluated the post-test phenotypes in two temporal windows at 3-6 and 6-9 months after the test and by age and gender. Data from longitudinal diagnosis records stored in EHRs from Mass General Brigham in the Boston Metropolitan Area was used for the analyses. Statistical analyses were performed on data from March 2020 to June 2021. Study participants included over 96 thousand patients who had tested positive or negative for COVID-19 and were not hospitalized. Results: We identified 33 phenotypes among different age/gender cohorts or time windows that were positively associated with past SARS-CoV-2 infection. All identified phenotypes were newly recorded in patients' medical records 2 months or longer after a COVID-19 RT-PCR test in non-hospitalized patients regardless of the test result. Among these phenotypes, a new diagnosis record for anosmia and dysgeusia (OR 2.60, 95% CI [1.94-3.46]), alopecia (OR 3.09, 95% CI [2.53-3.76]), chest pain (OR 1.27, 95% CI [1.09-1.48]), chronic fatigue syndrome (OR 2.60, 95% CI [1.22-2.10]), shortness of breath (OR 1.41, 95% CI [1.22-1.64]), pneumonia (OR 1.66, 95% CI [1.28-2.16]), and type 2 diabetes mellitus (OR 1.41, 95% CI [1.22-1.64]) is one of the most ... |
| Document Type: | article in journal/newspaper |
| File Description: | ELETTRONICO |
| Language: | English |
| Relation: | info:eu-repo/semantics/altIdentifier/pmid/34565368; info:eu-repo/semantics/altIdentifier/wos/WOS:000700007100001; volume:19; issue:1; firstpage:249; journal:BMC MEDICINE; https://hdl.handle.net/11571/1472996 |
| DOI: | 10.1186/s12916-021-02115-0 |
| Availability: | https://hdl.handle.net/11571/1472996; https://doi.org/10.1186/s12916-021-02115-0 |
| Rights: | info:eu-repo/semantics/openAccess |
| Accession Number: | edsbas.D1B3957 |
| Database: | BASE |