Hematologic, biochemical and immune biomarker abnormalities associated with severe illness and mortality in coronavirus disease 2019 (COVID-19): a meta-analysis

Henry, Brandon Michael; Oliveira, Maria Helena Santos de; Benoit, Stefanie; Plebani, Mario; Lippi, Giuseppe

doi:10.1515/cclm-2020-0369

Cited by 1,591 publications

(1,692 citation statements)

References 25 publications

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“…As there are no reports to date in the literature that describes the clinical features of hospitalized patients infected with COVID-19 in the US, especially outside of major metropolitan areas, our study will hopefully encourage other hospitals to publish their experiences, not only from major university hospitals but also from smaller and middle-sized community institutions. The findings of lymphocytopenia, thrombocytopenia, and abnormal renal function are similar to those reported recently in the literature in patients with SARS-CoV2 infection [8].…”

Section: Discussionsupporting

confidence: 90%

Clinical features, laboratory characteristics, and outcomes of patients hospitalized with coronavirus disease 2019 (COVID-19): Early report from the United States

et al. 2020

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Background: Coronavirus disease 2019 , caused by severe acute respiratory syndrome-coronavirus-2 (SARS-CoV2), is an ongoing pandemic that has already affected millions of patients worldwide, and is associated with significant morbidity and mortality burden. Although the clinical and laboratory characteristics of this illness have been reported in patients from China and Europe, data are scant in the United States. Methods: We extracted data regarding all patients hospitalized at our hospital with COVID-19 infection between March 1 and April 4, 2020. Presenting signs and symptoms, laboratory and imaging findings, treatment, and complications were recorded from electronic medical records (EMRs). The primary composite endpoint was admission to intensive care unit (ICU), shock, or death. Results: We had a total of 43 patients tested for COVID-19 at the emergency room (ER) or during hospitalization, 16 (37%) of whom were admitted with COVID-19 infection. The mean age was 65.5 years and 75% were males. The most common presenting symptoms were fever (94%), cough (88%), and dyspnea (81%). A loss of smell and taste sensations were reported by three (19%) patients. Low oxygen saturation was present in 38% of patients, whilst 31% were hypotensive on admission. Hyponatremia (50%), elevated C-reactive protein (CRP; 100%), and lactate dehydrogenase (LDH; 80%) were common. Acute renal failure, myocardial injury, and elevation in aminotransferases occurred in 69%, 19%, and 38% patients, respectively. The primary composite endpoint occurred in 50% of patients. A total of three patients died; all were aged 70 years or older. Conclusions: Laboratory abnormalities and acute renal failure were common in hospitalized patients with SARS-CoV2 infection in our center. Admission to ICU and mechanical ventilation were common.

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Section: Discussionsupporting

confidence: 90%

Clinical features, laboratory characteristics, and outcomes of patients hospitalized with coronavirus disease 2019 (COVID-19): Early report from the United States

et al. 2020

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“…Further analysis performed on the original data (not shown) suggest that additional clinical results can improve prediction efficiency. This conclusion is in accordance with previous findings suggesting biochemical and immunological abnormalities, in addition to hematologic alterations, can be caused by COVID-19 disease [12]. In this context, the relevance of data employed to generate ML models is emphasized.…”

Section: Applications To Scarcity Scenariossupporting

confidence: 91%

Hemogram Data as a Tool for Decision-making in COVID-19 Management: Applications to Resource Scarcity Scenarios

Avila

Dorn

Alho

et al. 2020

Preprint

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Background: COVID-19 pandemics has challenged emergency response systems worldwide, with widespread reports of essential services breakdown and collapse of health care structure. A critical element involves essential workforce management since current protocols recommend release from duty for symptomatic individuals, including essential personnel. Testing capacity is also problematic in several countries, where diagnosis demand outnumbers available local testing capacity. Purpose: This work describes a machine learning model derived from hemogram exam data performed in symptomatic patients and how they can be used to predict qRT-PCR test results. Methods: A Naïve-Bayes model for machine learning is proposed for handling different scarcity scenarios, including managing symptomatic essential workforce and absence of diagnostic tests. Hemogram result data was used to predict qRT-PCR results in situations where the latter was not performed, or results are not yet available. Adjusts in assumed prior probabilities allow fine-tuning of the model, according to actual prediction context. Results: Proposed models can predict COVID-19 qRT-PCR results in symptomatic individuals with high accuracy, sensitivity and specificity. Data assessment can be performed in an individual or simultaneous basis, according to desired outcome. Based on hemogram data and background scarcity context, resource distribution is significantly optimized when model-based patient selection is observed, compared to random choice. The model can help manage testing deficiency and other critical circumstances. Conclusions: Machine learning models can be derived from widely available, quick, and inexpensive exam data in order to predict qRT-PCR results used in COVID-19 diagnosis. These models can be used to assist strategic decision-making in resource scarcity scenarios, including personnel shortage, lack of medical resources, and testing insufficiency.

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“…Hypertension should be considered a clinical predictor of disease severity in older patients with COVID -19. with increased values of D -dimers, procalcitonin, cardiac biomarkers, proinflammatory cytokines, and ferritin. 22 Of note, some clinical predictors of worse prognosis in COVID -19 were also reported in early studies, such as older age, male sex, as well as preexisting cardiovascular diseases, diabetes, respiratory disorders, cancer, and dementia. 21,23 These findings are supported by observations regarding other respiratory and systemic diseases, as having at least one such comorbidity is now universally recognized to be care even in the most developed countries.…”

Section: What's New?mentioning

confidence: 77%

Hypertension and its severity or mortality in Coronavirus Disease 2019 (COVID-19): a pooled analysis

Lippi¹,

Wong²,

Henry³

2020

Polish Archives of Internal Medicine

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354

286

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Hematologic, biochemical and immune biomarker abnormalities associated with severe illness and mortality in coronavirus disease 2019 (COVID-19): a meta-analysis

Cited by 1,591 publications

References 25 publications

Clinical features, laboratory characteristics, and outcomes of patients hospitalized with coronavirus disease 2019 (COVID-19): Early report from the United States

Clinical features, laboratory characteristics, and outcomes of patients hospitalized with coronavirus disease 2019 (COVID-19): Early report from the United States

Hemogram Data as a Tool for Decision-making in COVID-19 Management: Applications to Resource Scarcity Scenarios

Hypertension and its severity or mortality in Coronavirus Disease 2019 (COVID-19): a pooled analysis

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