Evidence map›Paper›PMID 37187482›Full record

ArticleInfection and drug resistance2023

COVID-19 and Severe Acute Respiratory Infections: Monitoring Trends in 421 German Hospitals During the First Four Pandemic Waves.

Johannes Leiner, Sven Hohenstein, Vincent Pellissier, Sebastian König, Claudia Winklmair, Irit Nachtigall, Andreas Bollmann, Ralf Kuhlen, scientific advisory board of the Initiative of Quality Medicine (IQM)

Abstract read
In one paragraph

Article in Infection and drug resistance, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 2 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Johannes LeinerHeart Centre Leipzig at University of Leipzig, Department of Electrophysiology, Leipzig, Germany.ORCID 0000-0003-3678-0208
Sven HohensteinReal World Evidence and Health Technology Assessment at Helios Health Institute, Berlin, Germany.ORCID 0000-0002-9708-1593
Vincent PellissierReal World Evidence and Health Technology Assessment at Helios Health Institute, Berlin, Germany.
Sebastian KönigHeart Centre Leipzig at University of Leipzig, Department of Electrophysiology, Leipzig, Germany.
Claudia WinklmairInitiative of Quality Medicine, Berlin, Germany.
Irit NachtigallDepartment of Infectious Diseases and Infection Prevention, HELIOS Hospital Emil-von-Behring, Berlin, Germany and Charité - Universitaetsmedizin Berlin, Institute of Hygiene and Environmental Medicine, Berlin, Germany.
Andreas BollmannHeart Centre Leipzig at University of Leipzig, Department of Electrophysiology, Leipzig, Germany.
Ralf KuhlenInitiative of Quality Medicine, Berlin, Germany.
scientific advisory board of the Initiative of Quality Medicine (IQM)

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

COVID-19Germanyhospital networkinitiative of quality medicineinpatientSARI

Identifiers

PMID37187482
PMCPMC10178997

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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.