Evidence map›Paper›PMID 35617276›Full record

ArticlePloS one2022

Evaluation of models for prognosing mortality in critical care patients with COVID-19: First- and second-wave data from a German university hospital.

Martin Kieninger, Sarah Dietl, Annemarie Sinning, Michael Gruber, Wolfram Gronwald, Florian Zeman, Dirk Lunz, Thomas Dienemann, Stephan Schmid, Bernhard Graf and 5 more

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.1field-weighted citation impact, top 59% of its field
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

1 citing paper in PubMed, 1 citations in OpenAlex.

  1. 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

15 authors at 2 institutions in 1 country.

Martin KieningerDepartment of Anesthesiology, University Medical Center Regensburg, Regensburg, Germany.ORCID 0000-0001-5347-7425
Sarah DietlDepartment of Anesthesiology, University Medical Center Regensburg, Regensburg, Germany.
Annemarie SinningDepartment of Anesthesiology, University Medical Center Regensburg, Regensburg, Germany.
Michael GruberDepartment of Anesthesiology, University Medical Center Regensburg, Regensburg, Germany.ORCID 0000-0002-5509-9760
Wolfram GronwaldInstitute of Functional Genomics, University of Regensburg, Regensburg, Germany.
Florian ZemanCenter for Clinical Studies, University Medical Center Regensburg, Regensburg, Germany.
Dirk LunzDepartment of Anesthesiology, University Medical Center Regensburg, Regensburg, Germany.
Thomas DienemannDepartment of Surgery, University Medical Center Regensburg, Regensburg, Germany.ORCID 0000-0001-8846-3445
Stephan SchmidDepartment of Internal Medicine I, University Medical Center Regensburg, Regensburg, Germany.
Bernhard GrafDepartment of Anesthesiology, University Medical Center Regensburg, Regensburg, Germany.
Matthias LubnowDepartment of Internal Medicine II, University Medical Center Regensburg, Regensburg, Germany.
Thomas MüllerDepartment of Internal Medicine II, University Medical Center Regensburg, Regensburg, Germany.
Thomas HolzmannDepartment of Infection Prevention and Infectious Diseases, University Medical Center Regensburg, Regensburg, Germany.
Bernd SalzbergerDepartment of Infection Prevention and Infectious Diseases, University Medical Center Regensburg, Regensburg, Germany.
Bärbel KieningerDepartment of Infection Prevention and Infectious Diseases, University Medical Center Regensburg, Regensburg, Germany.
University Hospital Regensburg · DEUniversity of Regensburg · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIn a previous study, we had investigated the intensive care course of patients with coronavirus disease 2019 (COVID-19) in the first wave in Germany by calculating models for prognosticating in-hospital death with univariable and multivariable regression analysis. This study analyzed if these models were also applicable to patients with COVID-19 in the second wave.

methodsThis retrospective cohort study included 98 critical care patients with COVID-19, who had been treated at the University Medical Center Regensburg, Germany, between October 2020 and February 2021. Data collected for each patient included vital signs, dosage of catecholamines, analgosedation, anticoagulation, and antithrombotic medication, diagnostic blood tests, treatment with extracorporeal membrane oxygenation (ECMO), intensive care scores, ventilator therapy, and pulmonary gas exchange. Using these data, expected mortality was calculated by means of the originally developed mathematical models, thereby testing the models for their applicability to patients in the second wave.

resultsMortality in the second-wave cohort did not significantly differ from that in the first-wave cohort (41.8% vs. 32.2%, p = 0.151). As in our previous study, individual parameters such as pH of blood or mean arterial pressure (MAP) differed significantly between survivors and non-survivors. In contrast to our previous study, however, survivors and non-survivors in this study showed significant or even highly significant differences in pulmonary gas exchange and ventilator therapy (e.g. mean and minimum values for oxygen saturation and partial pressure of oxygen, mean values for the fraction of inspired oxygen, positive expiratory pressure, tidal volume, and oxygenation ratio). ECMO therapy was more frequently administered than in the first-wave cohort. Calculations of expected mortality by means of the originally developed univariable and multivariable models showed that the use of simple cut-off values for pH, MAP, troponin, or combinations of these parameters resulted in correctly estimated outcome in approximately 75% of patients without ECMO therapy.

Indexed as

COVID-19Critical CareHospital MortalityHospitals, UniversityHumansOxygenRetrospective StudiesOxygen

Identifiers

PMID35617276
PMCPMC9135305
OpenAlexW4281571010

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.