Cargando…
Trends in COVID-19 patient characteristics in a large electronic health record database in the United States: A cohort study
BACKGROUND: Electronic health record (EHR) databases provide an opportunity to facilitate characterization and trends in patients with COVID-19. METHODS: Patients with COVID-19 were identified based on an ICD-10 diagnosis code for COVID-19 (U07.1) and/or a positive SARS-CoV-2 viral lab result from J...
Autores principales: | , , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9299343/ https://www.ncbi.nlm.nih.gov/pubmed/35857793 http://dx.doi.org/10.1371/journal.pone.0271501 |
_version_ | 1784750949227560960 |
---|---|
author | Liang, Caihua Ogilvie, Rachel P. Doherty, Michael Clifford, C. Robin Chomistek, Andrea K. Gately, Robert Song, Jennifer Enger, Cheryl Seeger, John Lin, Nancy D. Wang, Florence T. |
author_facet | Liang, Caihua Ogilvie, Rachel P. Doherty, Michael Clifford, C. Robin Chomistek, Andrea K. Gately, Robert Song, Jennifer Enger, Cheryl Seeger, John Lin, Nancy D. Wang, Florence T. |
author_sort | Liang, Caihua |
collection | PubMed |
description | BACKGROUND: Electronic health record (EHR) databases provide an opportunity to facilitate characterization and trends in patients with COVID-19. METHODS: Patients with COVID-19 were identified based on an ICD-10 diagnosis code for COVID-19 (U07.1) and/or a positive SARS-CoV-2 viral lab result from January 2020 to November 2020. Patients were characterized in terms of demographics, healthcare utilization, clinical comorbidities, therapies, laboratory results, and procedures/care received, including critical care, intubation/ventilation, and occurrence of death were described, overall and by month. RESULTS: There were 393,773 patients with COVID-19 and 56,996 with a COVID-19 associated hospitalization. A greater percentage of patients hospitalized with COVID-19 relative to all COVID-19 cases were older, male, African American, and lived in the Northeast and South. The most common comorbidities before admission/infection date were hypertension (40.8%), diabetes (29.5%), and obesity (23.8%), and the most common diagnoses during hospitalization were pneumonia (59.6%), acute respiratory failure (44.8%), and dyspnea (28.0%). A total of 85.7% of patients hospitalized with COVID-19 had CRP values > 10 mg/L, 75.5% had fibrinogen values > 400 mg/dL, and 76.8% had D-dimer values > 250 ng/mL. Median values for platelets, CRP, lactate dehydrogenase, D-dimer, and fibrinogen tended to decrease from January-March to November. The use of chloroquine/hydroxychloroquine during hospitalization peaked by March (71.2%) and was used rarely by May (5.1%) and less than 1% afterwards, while the use of remdesivir had increased by May (10.0%) followed by dexamethasone by June (27.7%). All-cause mortality was 3.2% overall and 15.0% among those hospitalized; 21.0% received critical care and 16.0% received intubation/ventilation/ECMO. CONCLUSIONS: This study characterizes US patients with COVID-19 and their management during hospitalization over the first eleven months of this disease pandemic. |
format | Online Article Text |
id | pubmed-9299343 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-92993432022-07-21 Trends in COVID-19 patient characteristics in a large electronic health record database in the United States: A cohort study Liang, Caihua Ogilvie, Rachel P. Doherty, Michael Clifford, C. Robin Chomistek, Andrea K. Gately, Robert Song, Jennifer Enger, Cheryl Seeger, John Lin, Nancy D. Wang, Florence T. PLoS One Research Article BACKGROUND: Electronic health record (EHR) databases provide an opportunity to facilitate characterization and trends in patients with COVID-19. METHODS: Patients with COVID-19 were identified based on an ICD-10 diagnosis code for COVID-19 (U07.1) and/or a positive SARS-CoV-2 viral lab result from January 2020 to November 2020. Patients were characterized in terms of demographics, healthcare utilization, clinical comorbidities, therapies, laboratory results, and procedures/care received, including critical care, intubation/ventilation, and occurrence of death were described, overall and by month. RESULTS: There were 393,773 patients with COVID-19 and 56,996 with a COVID-19 associated hospitalization. A greater percentage of patients hospitalized with COVID-19 relative to all COVID-19 cases were older, male, African American, and lived in the Northeast and South. The most common comorbidities before admission/infection date were hypertension (40.8%), diabetes (29.5%), and obesity (23.8%), and the most common diagnoses during hospitalization were pneumonia (59.6%), acute respiratory failure (44.8%), and dyspnea (28.0%). A total of 85.7% of patients hospitalized with COVID-19 had CRP values > 10 mg/L, 75.5% had fibrinogen values > 400 mg/dL, and 76.8% had D-dimer values > 250 ng/mL. Median values for platelets, CRP, lactate dehydrogenase, D-dimer, and fibrinogen tended to decrease from January-March to November. The use of chloroquine/hydroxychloroquine during hospitalization peaked by March (71.2%) and was used rarely by May (5.1%) and less than 1% afterwards, while the use of remdesivir had increased by May (10.0%) followed by dexamethasone by June (27.7%). All-cause mortality was 3.2% overall and 15.0% among those hospitalized; 21.0% received critical care and 16.0% received intubation/ventilation/ECMO. CONCLUSIONS: This study characterizes US patients with COVID-19 and their management during hospitalization over the first eleven months of this disease pandemic. Public Library of Science 2022-07-20 /pmc/articles/PMC9299343/ /pubmed/35857793 http://dx.doi.org/10.1371/journal.pone.0271501 Text en © 2022 Liang et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Liang, Caihua Ogilvie, Rachel P. Doherty, Michael Clifford, C. Robin Chomistek, Andrea K. Gately, Robert Song, Jennifer Enger, Cheryl Seeger, John Lin, Nancy D. Wang, Florence T. Trends in COVID-19 patient characteristics in a large electronic health record database in the United States: A cohort study |
title | Trends in COVID-19 patient characteristics in a large electronic health record database in the United States: A cohort study |
title_full | Trends in COVID-19 patient characteristics in a large electronic health record database in the United States: A cohort study |
title_fullStr | Trends in COVID-19 patient characteristics in a large electronic health record database in the United States: A cohort study |
title_full_unstemmed | Trends in COVID-19 patient characteristics in a large electronic health record database in the United States: A cohort study |
title_short | Trends in COVID-19 patient characteristics in a large electronic health record database in the United States: A cohort study |
title_sort | trends in covid-19 patient characteristics in a large electronic health record database in the united states: a cohort study |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9299343/ https://www.ncbi.nlm.nih.gov/pubmed/35857793 http://dx.doi.org/10.1371/journal.pone.0271501 |
work_keys_str_mv | AT liangcaihua trendsincovid19patientcharacteristicsinalargeelectronichealthrecorddatabaseintheunitedstatesacohortstudy AT ogilvierachelp trendsincovid19patientcharacteristicsinalargeelectronichealthrecorddatabaseintheunitedstatesacohortstudy AT dohertymichael trendsincovid19patientcharacteristicsinalargeelectronichealthrecorddatabaseintheunitedstatesacohortstudy AT cliffordcrobin trendsincovid19patientcharacteristicsinalargeelectronichealthrecorddatabaseintheunitedstatesacohortstudy AT chomistekandreak trendsincovid19patientcharacteristicsinalargeelectronichealthrecorddatabaseintheunitedstatesacohortstudy AT gatelyrobert trendsincovid19patientcharacteristicsinalargeelectronichealthrecorddatabaseintheunitedstatesacohortstudy AT songjennifer trendsincovid19patientcharacteristicsinalargeelectronichealthrecorddatabaseintheunitedstatesacohortstudy AT engercheryl trendsincovid19patientcharacteristicsinalargeelectronichealthrecorddatabaseintheunitedstatesacohortstudy AT seegerjohn trendsincovid19patientcharacteristicsinalargeelectronichealthrecorddatabaseintheunitedstatesacohortstudy AT linnancyd trendsincovid19patientcharacteristicsinalargeelectronichealthrecorddatabaseintheunitedstatesacohortstudy AT wangflorencet trendsincovid19patientcharacteristicsinalargeelectronichealthrecorddatabaseintheunitedstatesacohortstudy |