Intensive Care Risk Estimation in COVID-19 Pneumonia Based on Clinical and Imaging Parameters: Experiences from the Munich Cohort

Burian, Egon; Jungmann, Friederike; Kaissis, Georgios; Lohöfer, Fabian; Spinner, Christoph D.; Lahmer, Tobias; Treiber, Matthias; Dommasch, Michael; Schneider, Gerhard; Geisler, Fabian; Huber, Wolfgang; Protzer, Ulrike; Schmid, Roland M.; Schwaiger, Markus; Makowski, Marcus R.; Braren, Rickmer

doi:10.2139/ssrn.3572889

Cited by 29 publications

(38 citation statements)

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“…For the disease severity categorized into severe and non-severe groups, 17 out of 24 studies [ 10 – 26 ] reporting on circulating IL-6 levels in patients with and without severe COVID-19 and including a total of 1881 COVID-19 patients were meta-analyzed. Compared with patients with non-severe COVID-19, circulating IL-6 levels were found to be significantly elevated in those with severe COVID-19 (MD = 18.63, 95% CI: 10.91, 26.35, P < 0.00001, I 2 = 95%) (Fig.…”

Section: Resultsmentioning

confidence: 99%

“…For this reason, the uncontrolled overproduction of inflammatory cytokines is considered to be one of the major contributing mediators of severe COVID-19 and mortality in the patients. This assumption has been partially addressed by a number of clinical studies, which denoted the significant associations between circulating levels of inflammatory cytokines, particularly IL-6 and the severity and mortality of COVID-19 [ 10 – 13 , 17 – 22 , 26 , 28 – 30 , 32 , 33 ]. More precisely, a previous meta-analysis [ 34 ] added another piece of supporting data, revealing that circulating IL-6 levels in severe COVID-19 patients was significantly higher than that in the non-severe patients.…”

Section: Discussionmentioning

confidence: 99%

“…Besides IL-6, IL-10 is synthesized from regulatory T cells and even TH 1 cells and has been reportedly implicated in immunoregulation and inflammation [ 9 ], thereby highlighting the power of IL-10 to influence immune and inflammatory responses in the context of COVID-19. Indeed, a number of clinical studies have unveiled that circulating IL-6 levels were elevated in COVID-19 patients, particularly in those with severe stage and were positively associated with the severity and mortality of COVID-19 [ 10 – 33 ], commensurate with circulating levels of IL-10 and TNF-α [ 12 , 14 , 15 , 17 , 18 , 20 , 21 , 24 , 28 , 29 ]. Based on these previous findings, alterations in circulating levels of IL-6, IL-10, and TNF-α have been hypothesized to be biomarkers of disease severity and mortality for COVID-19.…”

Section: Introductionmentioning

confidence: 99%

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Circulating Levels of Interleukin-6 and Interleukin-10, But Not Tumor Necrosis Factor-Alpha, as Potential Biomarkers of Severity and Mortality for COVID-19: Systematic Review with Meta-analysis

et al. 2020

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Purpose Cytokine storm, an uncontrolled overproduction of inflammatory cytokines contributing to an aberrant systemic inflammatory response, is a major pathological feature of acute respiratory distress syndromes being severe manifestations of COVID-19, thus highlighting its potential as a biomarker and therapeutic target for COVID-19. We aimed to determine associations of circulating levels of inflammatory cytokines with severity and mortality of COVID-19 by systematic review and meta-analysis. Methods A comprehensive literature search in electronic databases consisting of PubMed, Scopus, and Cochrane Library and in a hand searching of reference lists from inception to July 31, 2020, was performed using the following search terms: COVID-19, interleukin (IL)-6, IL-10, and tumor necrosis factor-alpha (TNF-α). Mean difference (MD) from individual studies was pooled using a random-effects model. Quality assessment, publication bias, meta-regression, subgroup, and sensitivity analyses were performed. Results A total of 6212 COVID-19 patients from 24 eligible studies were included. Compared with non-severe COVID-19 patients, systemic levels of IL-6 and IL-10, but not TNF-α, were significantly elevated in severe COVID-19 patients (MD = 18.63, 95% CI: 10.91, 26.35, P < 0.00001; MD = 2.61, 95% CI: 2.00, 2.32, P < 0.00001; respectively). For COVID-19 mortality, circulating levels of IL-6, IL-10, and TNF-α were found to be significantly increased in non-survivors when compared with survivors (MD = 57.82, 95% CI: 10.04, 105.59, P = 0.02; MD = 4.94, 95% CI: 3.89, 6.00, P < 0.00001; MD = 5.60, 95% CI: 4.03, 7.17, P < 0.00001; respectively). Conclusion Circulating levels of IL-6 and IL-10 might have great potential as biomarkers for the disease severity and mortality in COVID-19 patients. Supplementary Information The online version contains supplementary material available at 10.1007/s10875-020-00899-z.

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Section: Resultsmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Circulating Levels of Interleukin-6 and Interleukin-10, But Not Tumor Necrosis Factor-Alpha, as Potential Biomarkers of Severity and Mortality for COVID-19: Systematic Review with Meta-analysis

et al. 2020

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“…Most models use more than one variable and most models predict composite outcomes. Of the 30 models, 23 were trained on patients in China , 2 were trained on patients in the United States 30,31 , and 5 were trained on patients in South Korea 32 or Europe [33][34][35][36] . Only 8 of the models underwent validation on either held-out or external datasets 7,10,14,18,19,24,26,36 , and 1 underwent prospective validation .…”

Section: Introductionmentioning

confidence: 99%

A validated, real-time prediction model for favorable outcomes in hospitalized COVID-19 patients

et al. 2020

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The COVID-19 pandemic has challenged front-line clinical decision-making, leading to numerous published prognostic tools. However, few models have been prospectively validated and none report implementation in practice. Here, we use 3345 retrospective and 474 prospective hospitalizations to develop and validate a parsimonious model to identify patients with favorable outcomes within 96 h of a prediction, based on real-time lab values, vital signs, and oxygen support variables. In retrospective and prospective validation, the model achieves high average precision (88.6% 95% CI: [88.4–88.7] and 90.8% [90.8–90.8]) and discrimination (95.1% [95.1–95.2] and 86.8% [86.8–86.9]) respectively. We implemented and integrated the model into the EHR, achieving a positive predictive value of 93.3% with 41% sensitivity. Preliminary results suggest clinicians are adopting these scores into their clinical workflows.

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“…Anonymised patient mobility trajectory data were extracted from our hospital information system. COVID-19 was diagnosed either when patients showed typical clinical symptoms or had COVID-19-typical findings in low-dose lung CT-scan and tested positive for SARS-CoV-2 by PCR or for anti-SARS-CoV-2 IgM or IgG [14]. For spatio-temporal analysis of patient data, we used all trajectories available from December 30, 2019 to May 29, 2020 for each admitted COVID-19 patient, as the exact interval of when the patients were contagious could not be determined.…”

Section: Analysis Of Patient and Staff Trajectoriesmentioning

confidence: 99%

Strategies for infection control and prevalence of anti-SARS-CoV-2 IgG in 4,554 employees of a university hospital in Munich, Germany

Erber

Kappler

Haller

et al. 2020

Preprint

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Background Hospital staff are at high risk of infection during the coronavirus disease (COVID-19) pandemic. We analysed the exposure characteristics, efficacy of protective measures, and transmission dynamics in this hospital-wide prospective seroprevalence study. Methods and Findings Overall, 4554 individuals were tested for anti-severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) IgG antibodies using a chemiluminescent immunoassay. Individual risk factors, use of personal protective equipment (PPE), occupational exposure, previous SARS-CoV-2 infection, and symptoms were assessed using a questionnaire and correlated to anti-SARS-CoV-2 IgG antibody titres and PCR testing results. Odds ratios with corresponding exact 95% confidence intervals were used to evaluate associations between individual factors and seropositivity. Spatio-temporal trajectories of SARS-CoV-2-infected patients and staff mobility within the hospital were visualised to identify local hotspots of virus transmission. The overall seroprevalence of anti-SARS-CoV-2-IgG antibody was 2.4% [95% CI 1.9-2.9]. Patient-facing staff, including those working in COVID-19 areas, had a similar probability of being seropositive as non-patient-facing staff. Prior interaction with SARS-CoV-2-infected co-workers or private contacts and unprotected exposure to COVID-19 patients increased the probability of seropositivity. Loss of smell and taste had the highest positive predictive value for seropositivity. The rate of asymptomatic SARS-CoV-2 infections was 25.9%, and higher anti-SARS-CoV-2 IgG antibody titres were observed in symptomatic individuals. Spatio-temporal hotspots of SARS-CoV-2-positive staff and patients only showed partial overlap. Conclusions Patient-facing work in a healthcare facility during the SARS-CoV-2 pandemic may be safe if adequate PPE and hygiene measures are applied. The high numbers of asymptomatic SARS-CoV-2 infections that escaped detection by symptomatic testing underline the value of cross-sectional seroprevalence studies. Unprotected contact is a major risk factor for infection and argues for the rigorous implementation of hygiene measures.

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Intensive Care Risk Estimation in COVID-19 Pneumonia Based on Clinical and Imaging Parameters: Experiences from the Munich Cohort

Cited by 29 publications

References 1 publication

Circulating Levels of Interleukin-6 and Interleukin-10, But Not Tumor Necrosis Factor-Alpha, as Potential Biomarkers of Severity and Mortality for COVID-19: Systematic Review with Meta-analysis

Circulating Levels of Interleukin-6 and Interleukin-10, But Not Tumor Necrosis Factor-Alpha, as Potential Biomarkers of Severity and Mortality for COVID-19: Systematic Review with Meta-analysis

A validated, real-time prediction model for favorable outcomes in hospitalized COVID-19 patients

Strategies for infection control and prevalence of anti-SARS-CoV-2 IgG in 4,554 employees of a university hospital in Munich, Germany

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