Laboratory Markers and Mortality in Novel Coronavirus Disease 2019 (COVID-19): A Systematic Review and Meta-Analysis

The novel coronavirus SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) infection has been predominantly linked to respiratory distress syndrome, but gastrointestinal symptoms and hepatic injury have also been reported. The mechanism of liver injury is poorly understood and may result as a consequence of viral hepatitis, systemic inflammatory response, gut barrier and microbiome alterations, intensive care treatment or drug toxicity. The incidence of hepatopathy among patients with coronavirus disease 2019 (COVID-19) is unclear, but studies have reported liver injury in patients with SARS and Middle East respiratory syndrome (MERS). We aimed to systematically review data on the prevalence of hepatic impairments and their clinical course in SARS and MERS Coronaviridae infections. A systematic literature search (PubMed/Embase/Cinahl/Web of Science) according to preferred reporting items for systematic review and meta-analysis protocols (PRISMA) was conducted from database inception until 17/03/2020 for studies that evaluated the incidence of hepatic abnormalities in SARS CoV-1, SARS CoV-2 and MERS infected patients with reported liver-related parameters. A total of forty-three studies were included. Liver anomalies were predominantly mild to moderately elevated transaminases, hypoalbuminemia and prolongation of prothrombin time. Histopathology varied between non-specific inflammation, mild steatosis, congestion and massive necrosis. More studies to elucidate the mechanism and importance of liver injury on the clinical course and prognosis in patients with novel SARS-CoV-2 infection are warranted.

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Clinical laboratory parameters associated with severe or critical novel coronavirus disease 2019 (COVID-19): A systematic review and meta-analysis

PLoS ONE ◽

10.1371/journal.pone.0239802 ◽

2020 ◽

Vol 15 (10) ◽

pp. e0239802 ◽

Cited By ~ 1

Author(s):

Jude Moutchia ◽

Pratik Pokharel ◽

Aldiona Kerri ◽

Kaodi McGaw ◽

Shreeshti Uchai ◽

...

Keyword(s):

Systematic Review ◽

Clinical Laboratory ◽

Meta Analysis ◽

Laboratory Parameters ◽

Novel Coronavirus

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Olfactory and gustatory dysfunction in 2019 novel coronavirus: An updated systematic review and meta-analysis

10.21203/rs.3.rs-44648/v1 ◽

2020 ◽

Author(s):

Marzieh Esmaeili ◽

Fatemeh Abdi ◽

Gita Shafiee ◽

Hadis Rastad ◽

Hamid Asayesh ◽

...

Keyword(s):

Systematic Review ◽

English Language ◽

Meta Analysis ◽

Random Effect ◽

Eligibility Criteria ◽

Language Studies ◽

Pooled Prevalence ◽

Comprehensive Search ◽

Novel Coronavirus

Abstract BackgroundEvidence showed that partial or complete loss of smell and taste might be a possible primary symptom of the 2019 novel coronavirus (COVID-19). This study aimed to systematically review and pool all available evidence on the olfactory and gustatory dysfunction in COVID-19 patients. MethodsIn this systematic review, a comprehensive search was carried out systematically through e-databases including PubMed, EMBASE, Scopus, and Web of Science (WoS); that was limited to English-language studies published from 2019 up to 6th May 2020. Afterward, all studies reported the taste and smell dysfunction in the COVID-19 patients were included. The quality of the studies was assessed by the Mixed Methods Appraisal Tool (MMAT). The pooled prevalence of olfactory and gustatory dysfunction was estimated using the random effects meta-analysis method.ResultsAmong 28 eligible included studies in this systematic review, finally, 22 studies met the eligibility criteria and were included in the meta-analysis. According to the random effect meta-analysis, the global pooled prevalence (95% confidence interval) of any olfactory dysfunction, anosmia, and hyposmia was 55% (40%-70%), 40% (22%-57%), and 40% (20%-61%) respectively. The pooled estimated prevalence of any gustatory dysfunction, ageusia, and dysgeusia was 41% (23%-59%), 31% (3%-59%), and 34% (19%-48%) respectively. ConclusionOlfactory and gustatory dysfunction is prevalent among COVID-19 patients. Therefore, olfactory and gustatory dysfunction seems to be part of important symptoms and notify for the diagnosis of COVID-19, especially in the early phase of the infection.

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Cardiovascular manifestations in COVID-19 patients: A systematic review and meta-analysis

Journal of Cardiovascular and Thoracic Research ◽

10.34172/jcvtr.2021.30 ◽

2021 ◽

Vol 13 (3) ◽

pp. 181-189

Author(s):

Seyyedmohammadsadeq Mirmoeeni ◽

Amirhossein Azari Jafari ◽

Seyedeh Zohreh Hashemi ◽

Elham Angouraj Taghavi ◽

Alireza Azani ◽

...

Keyword(s):

Systematic Review ◽

Meta Analysis ◽

Systolic Pressure ◽

Clinical Manifestations ◽

Laboratory Findings ◽

Cross Sectional ◽

Cardiovascular Comorbidities ◽

Study Characteristics ◽

Novel Coronavirus ◽

Cardiac Manifestations

Since December 2019, the COVID-19 pandemic has affected the global population, and one of the major causes of mortality in infected patients is cardiovascular diseases (CVDs).For this systematic review and meta-analysis, we systematically searched Google Scholar, Scopus, PubMed, Web of Science, and Cochrane databases for all articles published by April 2, 2020. Observational studies (cohort and cross-sectional designs) were included in this meta-analysis if they reported at least one of the related cardiovascular symptoms or laboratory findings in COVID-19 patients. Furthermore, we did not use any language, age, diagnostic COVID-19 criteria, and hospitalization criteria restrictions. The following keywords alone or in combination with OR and AND operators were used for searching the literature: "Wuhan coronavirus", "COVID-19", "coronavirus disease 2019", "SARS-CoV-2", "2019 novel coronavirus" "cardiovascular disease", "CVD", "hypertension", "systolic pressure", "dyspnea", "hemoptysis", and "arrhythmia". Study characteristics, exposure history, laboratory findings, clinical manifestations, and comorbidities were extracted from the retrieved articles. Sixteen studies were selected which involved 4754 patients, including 2103 female and 2639 male patients. Among clinical cardiac manifestations, chest pain and arrhythmia were found to have the highest incidence proportion. In addition, elevated lactate dehydrogenase (LDH) and D-dimer levels were the most common cardiovascular laboratory findings. Finally, hypertension, chronic heart failure, and coronary heart disease were the most frequently reported comorbidities. The findings suggest that COVID-19 can cause various cardiovascular symptoms and laboratory findings. It is also worth noting that cardiovascular comorbidities like hypertension have a notable prevalence among COVID-19 patients.

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COVID-19 Associated Multisystem Inflammatory Syndrome: A Systematic Review and Meta-analysis

Iranian Journal of Allergy Asthma and Immunology ◽

10.18502/ijaai.v19i6.4927 ◽

2020 ◽

Author(s):

Ashkan Baradaran ◽

Abdolreza Malek ◽

Nasrin Moazzen ◽

Zahra Abbasi Shaye

Keyword(s):

Systematic Review ◽

Meta Analysis ◽

Gastrointestinal Symptoms ◽

Multiple Organ ◽

Current Evidence ◽

Cardiac Complications ◽

Clinical Presentations ◽

Atypical Kawasaki Disease ◽

Novel Coronavirus ◽

Inflammatory Syndrome

The prevalence of multisystem inflammatory syndrome in children (MIS-C) has increased since the coronavirus disease 2019 (COVID-19) pandemic started. This study was aimed to describe clinical manifestation and outcomes of MIS-C associated with COVID-19. This systematic review and meta-analysis were conducted on all available literature until July 3rd, 2020. The screening was done by using the following keywords: (“novel coronavirus” Or COVID-19 or severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) or coronavirus) and ("MIS-C" or "multisystem inflammatory" or Kawasaki). Data on gender, ethnicity, clinical presentations, need for mechanical ventilation or admission to intensive care unit (ICU), imaging, cardiac complications, and COVID-19 laboratory results were extracted to measure the pooled estimates. Out of 314 found articles, 16 articles with a total of 600 patients were included in the study, the most common presentation was fever (97%), followed by gastrointestinal symptoms (80%), and skin rashes (60%) as well as shock (55%), conjunctivitis (54%), and respiratory symptoms (39%). Less common presentations were neurologic problems (33%), and skin desquamation (30%), MIS-C was slightly more prevalent in males (53.7%) compared to females (46.3%). The findings of this meta-analysis on current evidence found that the common clinical presentations of COVID-19 associated MIS-C include a combination of fever and mucocutaneous involvements, similar to atypical Kawasaki disease, and multiple organ dysfunction. Due to the relatively higher morbidity and mortality rate, it is very important to diagnose this condition promptly.

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The Role of Machine Learning Techniques to Tackle COVID-19 Crisis: A Systematic Review.

10.1101/2020.08.23.20180158 ◽

2020 ◽

Author(s):

Hafsa Bareen Syeda ◽

Mahanazuddin Syed ◽

Kevin Wayne Sexton ◽

Shorabuddin Syed ◽

Salma Begum ◽

...

Keyword(s):

Machine Learning ◽

Systematic Review ◽

Disease Progression ◽

Meta Analysis ◽

Machine Learning Techniques ◽

Data Types ◽

Detection And Diagnosis ◽

Novel Coronavirus ◽

The Impact

Background: The novel coronavirus responsible for COVID-19 has caused havoc with patients presenting a spectrum of complications forcing the healthcare experts around the globe to explore new technological solutions, and treatment plans. Machine learning (ML) based technologies have played a substantial role in solving complex problems, and several organizations have been swift to adopt and customize them in response to the challenges posed by the COVID-19 pandemic. Objective: The objective of this study is to conduct a systematic literature review on the role of ML as a comprehensive and decisive technology to fight the COVID-19 crisis in the arena of epidemiology, diagnosis, and disease progression. Methods: A systematic search in PubMed, Web of Science, and CINAHL databases was performed according to the Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) guidelines to identify all potentially relevant studies published and made available between December 1, 2019, and June 27, 2020. The search syntax was built using keywords specific to COVID-19 and ML. A total of 128 qualified articles were reviewed and analyzed based on the study objectives. Results: The 128 publications selected were classified into three themes based on ML applications employed to combat the COVID-19 crisis: Computational Epidemiology (CE), Early Detection and Diagnosis (EDD), and Disease Progression (DP). Of the 128 studies, 70 focused on predicting the outbreak, the impact of containment policies, and potential drug discoveries, which were grouped into the CE theme. For the EDD, we grouped forty studies that applied ML techniques to detect the presence of COVID-19 using the patient's radiological images or lab results. Eighteen publications that focused on predicting the disease progression, outcomes (recovery and mortality), Length of Stay (LOS), and number of Intensive Care Unit (ICU) days for COVID-19 positive patients were classified under the DP theme. Conclusions: In this systematic review, we assembled the current COVID-19 literature that utilized ML methods to provide insights into the COVID-19 themes, highlighting the important variables, data types, and available COVID-19 resources that can assist in facilitating clinical and translational research.

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