Risk factors of severe cases with COVID-19: a meta-analysis

Ou, Mingchun; Zhu, Jieyun; Pan, Jianji; Li, Hongyuan; Zhong, Zhimei; Li, Bocheng; Pang, Jielong; Zhang, Jianfeng; Zheng, Xiaowen

doi:10.1017/s095026882000179x

Cited by 123 publications

(128 citation statements)

References 25 publications

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“…Comorbidities were similar in both groups, while bacterial superinfection, thromboembolic complications and treatment with antibiotics or convalescent plasma were more frequent in ventilated patients (Table 1). As described before 27 , ventilated patients displayed higher plasma concentrations for biomarkers indicating in ammation (CRP, IL-6), liver and muscle dysfunction (LDH, Bilirubin, CK) and intravascular coagulation (D-dimer). Ventilated "dead" patients showed higher leukocyte counts and higher biomarkers for in ammation and liver dysfunction than ventilated "survived" patients (Supplementary Table 1).…”

Section: Clinical Characterization Of Covid-19 Patientssupporting

confidence: 65%

T cell anergy in COVID-19 reflects virus persistence and poor outcomes

Renner

Müller

Tiefenböck

et al. 2020

Preprint

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Coronavirus disease 2019 (COVID-19) can lead to severe pneumonia and hyperinflammation. So far, insufficient or excessive T cell responses were described in patients. We applied novel approaches to analyze T cell reactivity and showed that T anergy is already present in non-ventilated COVID-19 patients, very pronounced in ventilated patients, strongly associated with virus persistence and reversible with clinical recovery. T cell activation was measured by downstream effects on responder cells like basophils, plasmacytoid dendritic cells, monocytes and neutrophils in whole blood and proved to be much more meaningful than classical readouts with PBMCs. Monocytes responded stronger in males than females and IL-2 partially reversed T cell anergy. Downstream markers of T cell anergy were also found in fresh blood samples of critically ill patients with severe T cell anergy. Based on our data we were able to develop a score to predict fatal outcomes and to identify patients that may benefit from strategies to overcome T cell anergy.

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Section: Clinical Characterization Of Covid-19 Patientssupporting

confidence: 65%

T cell anergy in COVID-19 reflects virus persistence and poor outcomes

Renner

Müller

Tiefenböck

et al. 2020

Preprint

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“…Age has been reported as a prominent factor regarding the severity of COVID-19 32 – 36 . One meta-analysis examining 29 studies involving 3411 COVID-19 patients revealed that the age of mild and severe groups is significantly different (weighted mean difference of 10.69) 37 . Age needs to be adjusted to more accurately examine the different characteristics of blood proteome between mild and severe groups.…”

Section: Resultsmentioning

confidence: 99%

In-depth blood proteome profiling analysis revealed distinct functional characteristics of plasma proteins between severe and non-severe COVID-19 patients

Park

Kim

et al. 2020

Sci Rep

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The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has infected over forty million patients worldwide. Although most coronavirus disease 2019 (COVID-19) patients have a good prognosis, some develop severe illness. Markers that define disease severity or predict clinical outcome need to be urgently developed as the mortality rate in critical cases is approximately 61.5%. In the present study, we performed in-depth proteome profiling of undepleted plasma from eight COVID-19 patients. Quantitative proteomic analysis using the BoxCar method revealed that 91 out of 1222 quantified proteins were differentially expressed depending on the severity of COVID-19. Importantly, we found 76 proteins, previously not reported, which could be novel prognostic biomarker candidates. Our plasma proteome signatures captured the host response to SARS-CoV-2 infection, thereby highlighting the role of neutrophil activation, complement activation, platelet function, and T cell suppression as well as proinflammatory factors upstream and downstream of interleukin-6, interleukin-1B, and tumor necrosis factor. Consequently, this study supports the development of blood biomarkers and potential therapeutic targets to aid clinical decision-making and subsequently improve prognosis of COVID-19.

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“…4,9 Currently, several studies are striving to define the risk factors for the development of severe pneumonia in COVID-19 patients and to identify the factors that can have an impact on patient outcome. 10,11 To date, there are also no studies that have evaluated the nutritional status of patients affected by COVID-19 with bioelectrical impedance analysis (BIA). Given the prognostic value of bioimpedance parameters on different clinical outcomes already demonstrated for other categories of patients, 11,12 it can be assumed that this could also provide useful information in the management of COVID-19 patients.…”

Section: Introductionmentioning

confidence: 99%

Nutritional Risk Screening and Body Composition in COVID‐19 Patients Hospitalized in an Internal Medicine Ward

Giorno¹,

Quarenghi²,

Stefanelli³

et al. 2020

IJGM

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Background Malnutrition in patients hospitalized in internal medicine wards is highly prevalent and represents a prognostic factor of worse outcomes. Previous evidence suggested the prognostic role of the nutritional status in patients affected by the coronavirus disease 2019 (COVID-19). We aim to investigate the nutritional risk in patients with COVID-19 hospitalized in an internal medicine ward and their clinical outcomes using the Nutritional Risk Screening 2002 (NRS-2002) and parameters derived from bioelectrical impedance analysis (BIA). Methods Retrospective analysis of patients with COVID-19 aimed at exploring: 1) the prevalence of nutritional risk with NRS-2002 and BIA; 2) the relationship between NRS-2002, BIA parameters and selected outcomes: length of hospital stay (LOS); death and need of intensive care unit (ICU); prolonged LOS; and loss of appetite. Results Data of 90 patients were analyzed. Patients at nutritional risk were 92% with NRS-2002, with BIA-derived parameters: 88% by phase angle; 86% by body cell mass; 84% by fat-free mass and 84% by fat mass (p-value ≤0.001). In ROC analysis, NRS had the maximum sensitivity in predicting the risk of death and need of ICU and a prolonged hospitalization showing moderate-low specificity; phase angle showed a good predictive power in terms of AUC. NRS-2002 was significantly associated with LOS (β 12.62, SE 5.79). In a multivariate analysis, blood glucose level and the early warning score are independent predictors of death and need of ICU (OR 2.79, p ≤0.001; 1.59, p-0.029, respectively). Conclusion Present findings confirm the clinical utility of NRS-2002 to assess nutritional risk in patients with COVID-19 at hospital admission and in predicting LOS, and that bioimpedance does not seem to add further predictive value. An early detection of nutritional risk has to be systematically included in the management of COVID-19 patients hospitalized in internal medicine wards.

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Risk factors of severe cases with COVID-19: a meta-analysis

Cited by 123 publications

References 25 publications

T cell anergy in COVID-19 reflects virus persistence and poor outcomes

T cell anergy in COVID-19 reflects virus persistence and poor outcomes

In-depth blood proteome profiling analysis revealed distinct functional characteristics of plasma proteins between severe and non-severe COVID-19 patients

Nutritional Risk Screening and Body Composition in COVID‐19 Patients Hospitalized in an Internal Medicine Ward

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