Evidence map›Paper›PMID 38855736›Full record

ArticleInfection prevention in practice2024

Refining the hospitalization rate: A mixed methods approach to differentiate primary COVID-19 from incidental cases.

M Misailovski, D Koller, S Blaschke, M Berens, A M Köster, R Strobl, R Berner, P Boor, M Eisenmann, S von Stillfried and 8 more

Abstract read
In one paragraph

Article in Infection prevention in practice, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–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

2 citing papers in PubMed.

  1. Article
  2. Article
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

18 authors.

M MisailovskiDepartment of Infectious Control and Infectious Diseases, University Medical Center Göttingen, Göttingen, Germany.
D KollerInstitute of Medical Data Processing, Biometrics and Epidemiology, Faculty of Medicine, LMU Munich, Munich, Germany.
S BlaschkeEmergency Department, University Medical Center Göttingen, 37075 Göttingen, Germany.
M BerensDepartment of Infectious Control and Infectious Diseases, University Medical Center Göttingen, Göttingen, Germany.
A M KösterDepartment of Infectious Control and Infectious Diseases, University Medical Center Göttingen, Göttingen, Germany.
R StroblInstitute of Medical Data Processing, Biometrics and Epidemiology, Faculty of Medicine, LMU Munich, Munich, Germany.
R BernerDepartment of Pediatrics, University Hospital and Medical Faculty Carl Gustav Carus, TUD Dresden University of Technology, Dresden, Germany.
P BoorInstitute of Pathology, RWTH Aachen University Hospital, Aachen, Germany.
M EisenmannInfection Control and Antimicrobial Stewardship Unit, University Hospital Wuerzburg, Wuerzburg, Germany.
S von StillfriedInstitute of Pathology, RWTH Aachen University Hospital, Aachen, Germany.
D KreftingDepartment of Medical Informatics, University Medical Center Göttingen, Göttingen, Germany.
M KroneInfection Control and Antimicrobial Stewardship Unit, University Hospital Wuerzburg, Wuerzburg, Germany.
J LieseDepartment of Paediatrics, University Hospital Wuerzburg, Wuerzburg, Germany.
P MeybohmUniversity Hospital Würzburg, Department of Anaesthesiology, Intensive Care, Emergency and Pain Medicine, Würzburg, Germany.
G Ulrich-MerzenichSynergy Research and Experimental Medicine Lab, Medical Clinic III, University Hospital Bonn, Bonn, Germany.
S ZenkerStaff Unit for Scientific & Medical Technology Development & Coordination (MWTek), Commercial Directorate, University Hospital Bonn, Bonn, Germany.
S ScheithauerDepartment of Infectious Control and Infectious Diseases, University Medical Center Göttingen, Göttingen, Germany.
E GrillInstitute of Medical Data Processing, Biometrics and Epidemiology, Faculty of Medicine, LMU Munich, Munich, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: Until now, the Hospitalization Rate (HR) served as an indicator (among others) for the COVID-19 associated healthcare burden. To ensure that the HR accomplishes its full potential, hospitalizations caused by COVID-19 (primary cases) and hospitalizations of patients with incidental positive SARS-CoV-2 test results (incidental cases) must be differentiated. The aim of this study was to synthesize the existing evidence on differentiation criteria between hospitalizations of primary cases and incidental cases. Methods: An online survey of the members of the German Network University Medicine (NUM) was conducted. Additionally, senior clinicians with expertise in COVID-19 care were invited for qualitative, semi-structured interviews. Furthermore, a rapid literature review was undertaken on publications between 03/2020 and 12/2022. Results: In the online survey (n=30, response rate 56%), pneumonia and acute upper respiratory tract infections were the most indicative diagnoses for a primary case. In contrast, malignant neoplasms and acute myocardial infarctions were most likely to be associated with incidental cases. According to the experts (n=6), the diagnosis, ward, and type of admission (emergency or elective), low oxygen saturation, need for supplemental oxygen, and initiation of COVID-19 therapy point to a primary case. The literature review found that respiratory syndromes and symptoms, oxygen support, and elevated levels of inflammatory markers were associated with primary cases. Conclusion: There are parameters for the differentiation of primary from incidental cases to improve the objective of the HR. Ultimately, an updated HR has the potential to serve as a more accurate indicator of the COVID-19 associated healthcare burden.

Indexed as

COVID-19Hospitalization rateIncidental SARS-CoV-2

Identifiers

PMID38855736
PMCPMC11153910

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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.