Cargando…
COVID-19 and Severe Acute Respiratory Infections: Monitoring Trends in 421 German Hospitals During the First Four Pandemic Waves
INTRODUCTION: Reliable surveillance systems to monitor trends of COVID-19 case numbers and the associated healthcare burden play a central role in efficient pandemic management. In Germany, the federal government agency Robert-Koch-Institute uses an ICD-code-based inpatient surveillance system, ICOS...
Autores principales: | , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Dove
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10178997/ https://www.ncbi.nlm.nih.gov/pubmed/37187482 http://dx.doi.org/10.2147/IDR.S402313 |
_version_ | 1785040993678000128 |
---|---|
author | Leiner, Johannes Hohenstein, Sven Pellissier, Vincent König, Sebastian Winklmair, Claudia Nachtigall, Irit Bollmann, Andreas Kuhlen, Ralf |
author_facet | Leiner, Johannes Hohenstein, Sven Pellissier, Vincent König, Sebastian Winklmair, Claudia Nachtigall, Irit Bollmann, Andreas Kuhlen, Ralf |
author_sort | Leiner, Johannes |
collection | PubMed |
description | INTRODUCTION: Reliable surveillance systems to monitor trends of COVID-19 case numbers and the associated healthcare burden play a central role in efficient pandemic management. In Germany, the federal government agency Robert-Koch-Institute uses an ICD-code-based inpatient surveillance system, ICOSARI, to assess temporal trends of severe acute respiratory infection (SARI) and COVID-19 hospitalization numbers. In a similar approach, we present a large-scale analysis covering four pandemic waves derived from the Initiative of Quality Medicine (IQM), a German-wide network of acute care hospitals. METHODS: Routine data from 421 hospitals for the years 2019–2021 with a “pre-pandemic” period (01–01-2019 to 03–03-2020) and a “pandemic” period (04–03-2020 to 31–12-2021) was analysed. SARI cases were defined by ICD-codes J09-J22 and COVID-19 by ICD-codes U07.1 and U07.2. The following outcomes were analysed: intensive care treatment, mechanical ventilation, in-hospital mortality. RESULTS: Over 1.1 million cases of SARI and COVID-19 were identified. Patients with COVID-19 and additional codes for SARI were at higher risk for adverse outcomes when compared to non-COVID SARI and COVID-19 without any coding for SARI. During the pandemic period, non-COVID SARI cases were associated with 28%, 23% and 27% higher odds for intensive care treatment, mechanical ventilation and in-hospital mortality, respectively, compared to pre-pandemic SARI. CONCLUSION: The nationwide IQM network could serve as an excellent data source to enhance COVID-19 and SARI surveillance in view of the ongoing pandemic. Future developments of COVID-19/SARI case numbers and associated outcomes should be closely monitored to identify specific trends, especially considering novel virus variants. |
format | Online Article Text |
id | pubmed-10178997 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Dove |
record_format | MEDLINE/PubMed |
spelling | pubmed-101789972023-05-13 COVID-19 and Severe Acute Respiratory Infections: Monitoring Trends in 421 German Hospitals During the First Four Pandemic Waves Leiner, Johannes Hohenstein, Sven Pellissier, Vincent König, Sebastian Winklmair, Claudia Nachtigall, Irit Bollmann, Andreas Kuhlen, Ralf Infect Drug Resist Original Research INTRODUCTION: Reliable surveillance systems to monitor trends of COVID-19 case numbers and the associated healthcare burden play a central role in efficient pandemic management. In Germany, the federal government agency Robert-Koch-Institute uses an ICD-code-based inpatient surveillance system, ICOSARI, to assess temporal trends of severe acute respiratory infection (SARI) and COVID-19 hospitalization numbers. In a similar approach, we present a large-scale analysis covering four pandemic waves derived from the Initiative of Quality Medicine (IQM), a German-wide network of acute care hospitals. METHODS: Routine data from 421 hospitals for the years 2019–2021 with a “pre-pandemic” period (01–01-2019 to 03–03-2020) and a “pandemic” period (04–03-2020 to 31–12-2021) was analysed. SARI cases were defined by ICD-codes J09-J22 and COVID-19 by ICD-codes U07.1 and U07.2. The following outcomes were analysed: intensive care treatment, mechanical ventilation, in-hospital mortality. RESULTS: Over 1.1 million cases of SARI and COVID-19 were identified. Patients with COVID-19 and additional codes for SARI were at higher risk for adverse outcomes when compared to non-COVID SARI and COVID-19 without any coding for SARI. During the pandemic period, non-COVID SARI cases were associated with 28%, 23% and 27% higher odds for intensive care treatment, mechanical ventilation and in-hospital mortality, respectively, compared to pre-pandemic SARI. CONCLUSION: The nationwide IQM network could serve as an excellent data source to enhance COVID-19 and SARI surveillance in view of the ongoing pandemic. Future developments of COVID-19/SARI case numbers and associated outcomes should be closely monitored to identify specific trends, especially considering novel virus variants. Dove 2023-05-08 /pmc/articles/PMC10178997/ /pubmed/37187482 http://dx.doi.org/10.2147/IDR.S402313 Text en © 2023 Leiner et al. https://creativecommons.org/licenses/by-nc/3.0/This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/ (https://creativecommons.org/licenses/by-nc/3.0/) ). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms (https://www.dovepress.com/terms.php). |
spellingShingle | Original Research Leiner, Johannes Hohenstein, Sven Pellissier, Vincent König, Sebastian Winklmair, Claudia Nachtigall, Irit Bollmann, Andreas Kuhlen, Ralf COVID-19 and Severe Acute Respiratory Infections: Monitoring Trends in 421 German Hospitals During the First Four Pandemic Waves |
title | COVID-19 and Severe Acute Respiratory Infections: Monitoring Trends in 421 German Hospitals During the First Four Pandemic Waves |
title_full | COVID-19 and Severe Acute Respiratory Infections: Monitoring Trends in 421 German Hospitals During the First Four Pandemic Waves |
title_fullStr | COVID-19 and Severe Acute Respiratory Infections: Monitoring Trends in 421 German Hospitals During the First Four Pandemic Waves |
title_full_unstemmed | COVID-19 and Severe Acute Respiratory Infections: Monitoring Trends in 421 German Hospitals During the First Four Pandemic Waves |
title_short | COVID-19 and Severe Acute Respiratory Infections: Monitoring Trends in 421 German Hospitals During the First Four Pandemic Waves |
title_sort | covid-19 and severe acute respiratory infections: monitoring trends in 421 german hospitals during the first four pandemic waves |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10178997/ https://www.ncbi.nlm.nih.gov/pubmed/37187482 http://dx.doi.org/10.2147/IDR.S402313 |
work_keys_str_mv | AT leinerjohannes covid19andsevereacuterespiratoryinfectionsmonitoringtrendsin421germanhospitalsduringthefirstfourpandemicwaves AT hohensteinsven covid19andsevereacuterespiratoryinfectionsmonitoringtrendsin421germanhospitalsduringthefirstfourpandemicwaves AT pellissiervincent covid19andsevereacuterespiratoryinfectionsmonitoringtrendsin421germanhospitalsduringthefirstfourpandemicwaves AT konigsebastian covid19andsevereacuterespiratoryinfectionsmonitoringtrendsin421germanhospitalsduringthefirstfourpandemicwaves AT winklmairclaudia covid19andsevereacuterespiratoryinfectionsmonitoringtrendsin421germanhospitalsduringthefirstfourpandemicwaves AT nachtigallirit covid19andsevereacuterespiratoryinfectionsmonitoringtrendsin421germanhospitalsduringthefirstfourpandemicwaves AT bollmannandreas covid19andsevereacuterespiratoryinfectionsmonitoringtrendsin421germanhospitalsduringthefirstfourpandemicwaves AT kuhlenralf covid19andsevereacuterespiratoryinfectionsmonitoringtrendsin421germanhospitalsduringthefirstfourpandemicwaves AT covid19andsevereacuterespiratoryinfectionsmonitoringtrendsin421germanhospitalsduringthefirstfourpandemicwaves |