scholarly journals Safety and Efficacy of Intermediate- and Therapeutic-Dose Anticoagulation for Hospitalised Patients with COVID-19: A Systematic Review and Meta-Analysis

2021 ◽  
Vol 11 (1) ◽  
pp. 57
Author(s):  
Stefanie Reis ◽  
Maria Popp ◽  
Benedikt Schmid ◽  
Miriam Stegemann ◽  
Maria-Inti Metzendorf ◽  
...  
Keyword(s):  
Disease Severity ◽  
Therapeutic Dose ◽  
Meta Analysis ◽  
Severe Disease ◽  
Clinical Status ◽  
Thrombotic Event ◽  
Thrombotic Risk ◽  
Safety And Efficacy ◽  
Hospitalised Patients ◽  
Randomised Controlled

Background: COVID-19 patients are at high thrombotic risk. The safety and efficacy of different anticoagulation regimens in COVID-19 patients remain unclear. Methods: We searched for randomised controlled trials (RCTs) comparing intermediate- or therapeutic-dose anticoagulation to standard thromboprophylaxis in hospitalised patients with COVID-19 irrespective of disease severity. To assess efficacy and safety, we meta-analysed data for all-cause mortality, clinical status, thrombotic event or death, and major bleedings. Results: Eight RCTs, including 5580 patients, were identified, with two comparing intermediate- and six therapeutic-dose anticoagulation to standard thromboprophylaxis. Intermediate-dose anticoagulation may have little or no effect on any thrombotic event or death (RR 1.03, 95% CI 0.86–1.24), but may increase major bleedings (RR 1.48, 95% CI 0.53–4.15) in moderate to severe COVID-19 patients. Therapeutic-dose anticoagulation may decrease any thrombotic event or death in patients with moderate COVID-19 (RR 0.64, 95% CI 0.38–1.07), but may have little or no effect in patients with severe disease (RR 0.98, 95% CI 0.86–1.12). The risk of major bleedings may increase independent of disease severity (RR 1.78, 95% CI 1.15–2.74). Conclusions: Certainty of evidence is still low. Moderately affected COVID-19 patients may benefit from therapeutic-dose anticoagulation, but the risk for bleeding is increased.

scholarly journals Serum albumin concentrations are associated with disease severity and outcomes in coronavirus 19 disease (COVID-19): a systematic review and meta-analysis

2021 ◽  
Author(s):  
Panagiotis Paliogiannis ◽  
Arduino Aleksander Mangoni ◽  
Michela Cangemi ◽  
Alessandro Giuseppe Fois ◽  
Ciriaco Carru ◽  
...  
Keyword(s):  
Systematic Review ◽  
Serum Albumin ◽  
Disease Severity ◽  
Meta Analysis ◽  
Severe Disease ◽  
Geographic Area ◽  
Adverse Outcomes ◽  
Poor Outcome ◽  
Standard Mean Difference ◽  
Meta Regression Analysis

AbstractCoronavirus disease 2019 (COVID-19), an infectious disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is responsible for the most threatening pandemic in modern history. The aim of this systematic review and meta-analysis was to investigate the associations between serum albumin concentrations and COVID-19 disease severity and adverse outcomes. A systematic literature search was conducted in PubMed, from inception to October 30, 2020. Sixty-seven studies in 19,760 COVID-19 patients (6141 with severe disease or poor outcome) were selected for analysis. Pooled results showed that serum albumin concentrations were significantly lower in patients with severe disease or poor outcome (standard mean difference, SMD: − 0.99 g/L; 95% CI, − 1.11 to − 0.88, p < 0.001). In multivariate meta-regression analysis, age (t =  − 2.13, p = 0.043), publication geographic area (t = 2.16, p = 0.040), white blood cell count (t =  − 2.77, p = 0.008) and C-reactive protein (t =  − 2.43, p = 0.019) were significant contributors of between-study variance. Therefore, lower serum albumin concentrations are significantly associated with disease severity and adverse outcomes in COVID-19 patients. The assessment of serum albumin concentrations might assist with early risk stratification and selection of appropriate care pathways in this group.

scholarly journals Clinical characteristics, treatment and outcomes of paediatric COVID-19: a systematic review and meta-analysis

2021 ◽  
pp. archdischild-2020-321385
Author(s):  
Omar Irfan ◽  
Fiona Muttalib ◽  
Kun Tang ◽  
Li Jiang ◽  
Zohra S Lassi ◽  
...  
Keyword(s):  
Systematic Review ◽  
Disease Severity ◽  
World Bank ◽  
Low Income ◽  
Meta Analysis ◽  
Severe Disease ◽  
Income Level ◽  
Clinical Findings ◽  
Middle Income ◽  
Middle Income Countries

ObjectiveCompare paediatric COVID-19 disease characteristics, management and outcomes according to World Bank country income level and disease severity.DesignSystematic review and meta-analysis.SettingBetween 1 December 2019 and 8 January 2021, 3350 articles were identified. Two reviewers conducted study screening, data abstraction and quality assessment independently and in duplicate. Observational studies describing laboratory-confirmed paediatric (0–19 years old) COVID-19 were considered for inclusion.Main outcomes and measuresThe pooled proportions of clinical findings, treatment and outcomes were compared according to World Bank country income level and reported disease severity.Results129 studies were included from 31 countries comprising 10 251 children of which 57.4% were hospitalised. Mean age was 7.0 years (SD 3.6), and 27.1% had a comorbidity. Fever (63.3%) and cough (33.7%) were common. Of 3670 cases, 44.1% had radiographic abnormalities. The majority of cases recovered (88.9%); however, 96 hospitalised children died. Compared with high-income countries, in low-income and middle-income countries, a lower proportion of cases were admitted to intensive care units (ICUs) (9.9% vs 26.0%) yet pooled proportion of deaths among hospitalised children was higher (relative risk 2.14, 95% CI 1.43 to 3.20). Children with severe disease received antimicrobials, inotropes and anti-inflammatory agents more frequently than those with non-severe disease. Subgroup analyses showed that a higher proportion of children with multisystem inflammatory syndrome (MIS-C) were admitted to ICU (47.1% vs 22.9%) and a higher proportion of hospitalised children with MIS-C died (4.8% vs 3.6%) compared with the overall sample.ConclusionPaediatric COVID-19 has a favourable prognosis. Further severe disease characterisation in children is needed globally.

scholarly journals Unsupervised Phenotypic Clustering for Determining Clinical Status in Children with Cystic Fibrosis

2021 ◽  
pp. 2002881
Author(s):  
Nicole Filipow ◽  
Gwyneth Davies ◽  
Eleanor Main ◽  
Neil J. Sebire ◽  
Colin Wallis ◽  
...  
Keyword(s):  
Machine Learning ◽  
Cystic Fibrosis ◽  
Lung Function ◽  
Disease Severity ◽  
Learning Algorithm ◽  
Severe Disease ◽  
Clinical Status ◽  
Oral Antibiotics ◽  
Multisystem Disease ◽  
Street Hospital

BackgroundCystic Fibrosis (CF) is a multisystem disease in which assessing disease severity based on lung function alone may not be appropriate. The aim of the study was to develop a comprehensive machine-learning algorithm to assess clinical status independent of lung function in children.MethodsA comprehensive prospectively collected clinical database (Toronto, Canada) was used to apply unsupervised cluster analysis. The defined clusters were then compared by current and future lung function, risk of future hospitalisation, and risk of future pulmonary exacerbation (PEx) treated with oral antibiotics. A K-Nearest Neighbours (KNN) algorithm was used to prospectively assign clusters. The methods were validated in a paediatric clinical CF dataset from Great Ormond Street Hospital (GOSH).ResultsThe optimal cluster model identified four (A-D) phenotypic clusters based on 12 200 encounters from 530 individuals. Two clusters (A,B) consistent with mild disease were identified with high FEV1, and low risk of both hospitalisation and PEx treated with oral antibiotics. Two clusters (C,D) consistent with severe disease were also identified with low FEV1. Cluster D had the shortest time to both hospitalisation and PEx treated with oral antibiotics. The outcomes were consistent in 3124 encounters from 171 children at GOSH. The KNN cluster allocation error rate was low, at 2.5% (Toronto), and 3.5% (GOSH).ConclusionMachine learning derived phenotypic clusters can predict disease severity independent of lung function and could be used in conjunction with functional measures to predict future disease trajectories in CF patients.

scholarly journals Factors Associated with Disease Severity and Mortality among Patients with Coronavirus Disease 2019: A Systematic Review and Meta-Analysis

2020 ◽  
Author(s):  
Vignesh Chidambaram ◽  
Nyan Lynn Tun ◽  
Waqas Haque ◽  
Marie Gilbert Majella ◽  
Ranjith Kumar Sivakumar ◽  
...  
Keyword(s):  
Systematic Review ◽  
Disease Severity ◽  
English Language ◽  
Clinical Decision Making ◽  
Clinical Laboratory ◽  
Data Extraction ◽  
Meta Analysis ◽  
Severe Disease ◽  
Factors Associated ◽  
Risk Of Mortality

Background: Understanding the factors associated with disease severity and mortality in Coronavirus disease (COVID19) is imperative to effectively triage patients. We performed a systematic review to determine the demographic, clinical, laboratory and radiological factors associated with severity and mortality in COVID-19. Methods: We searched PubMed, Embase and WHO database for English language articles from inception until May 8, 2020. We included Observational studies with direct comparison of clinical characteristics between a) patients who died and those who survived or b) patients with severe disease and those without severe disease. Data extraction and quality assessment were performed by two authors independently. Results: Among 15680 articles from the literature search, 109 articles were included in the analysis. The risk of mortality was higher in patients with increasing age, male gender (RR 1.45; 95%CI 1.23,1.71), dyspnea (RR 2.55; 95%CI 1.88,2.46), diabetes (RR 1.59; 95%CI 1.41,1.78), hypertension (RR 1.90; 95%CI 1.69,2.15). Congestive heart failure (OR 4.76; 95%CI 1.34,16.97), hilar lymphadenopathy (OR 8.34; 95%CI 2.57,27.08), bilateral lung involvement (OR 4.86; 95%CI 3.19,7.39) and reticular pattern (OR 5.54; 95%CI 1.24,24.67) were associated with severe disease. Clinically relevant cut-offs for leukocytosis(>10.0 x109/L), lymphopenia(< 1.1 x109/L), elevated C-reactive protein(>100mg/L), LDH(>250U/L) and D-dimer(>1mg/L) had higher odds of severe disease and greater risk of mortality. Conclusion: Knowledge of the factors associated of disease severity and mortality identified in our study may assist in clinical decision-making and critical-care resource allocation for patients with COVID-19.

scholarly journals Laboratory Tests and Outcome for Patients with Coronavirus Disease 2019: A Systematic Review and Meta-Analysis

2020 ◽  
Vol 5 (5) ◽  
pp. 1038-1049 ◽  
Author(s):  
Anne Alnor ◽  
Maria B Sandberg ◽  
Charlotte Gils ◽  
Pernille J Vinholt
Keyword(s):  
Systematic Review ◽  
Disease Severity ◽  
Laboratory Tests ◽  
Evidence Synthesis ◽  
Meta Analysis ◽  
Severe Disease ◽  
Risk Of Bias ◽  
Mean Difference ◽  
Routine Laboratory ◽  
Standard Mean Difference

Abstract Background Severe acute respiratory syndrome coronavirus 2 causes coronavirus disease 2019 (COVID-19) and poses substantial challenges for healthcare systems. With a vastly expanding number of publications on COVID-19, clinicians need evidence synthesis to produce guidance for handling patients with COVID-19. In this systematic review and meta-analysis, we examine which routine laboratory tests are associated with severe COVID-19 disease. Content PubMed (Medline), Scopus, and Web of Science were searched until March 22, 2020, for studies on COVID-19. Eligible studies were original articles reporting on laboratory tests and outcome of patients with COVID-19. Data were synthesized, and we conducted random-effects meta-analysis, and determined mean difference (MD) and standard mean difference at the biomarker level for disease severity. Risk of bias and applicability concerns were evaluated using the Quality Assessment of Diagnostic Accuracy Studies-2. Summary 45 studies were included, of which 21 publications were used for the meta-analysis. Studies were heterogeneous but had low risk of bias and applicability concern in terms of patient selection and reference standard. Severe disease was associated with higher white blood cell count (MD, 1.28 ×109/L), neutrophil count (MD, 1.49 ×109/L), C-reactive protein (MD, 49.2 mg/L), lactate dehydrogenase (MD, 196 U/L), D-dimer (standardized MD, 0.58), and aspartate aminotransferase (MD, 8.5 U/L); all p &lt; 0.001. Furthermore, low lymphocyte count (MD −0.32 × 109/L), platelet count (MD −22.4 × 109/L), and hemoglobin (MD, −4.1 g/L); all p &lt; 0.001 were also associated with severe disease. In conclusion, several routine laboratory tests are associated with disease severity in COVID-19.

scholarly journals Biomarkers and outcomes of COVID-19 hospitalisations: systematic review and meta-analysis

2020 ◽  
pp. bmjebm-2020-111536
Author(s):  
Preeti Malik ◽  
Urvish Patel ◽  
Deep Mehta ◽  
Nidhi Patel ◽  
Raveena Kelkar ◽  
...  
Keyword(s):  
Systematic Review ◽  
Observational Studies ◽  
Clinical Decision Making ◽  
Meta Analysis ◽  
Severe Disease ◽  
Invasive Mechanical Ventilation ◽  
Mesh Terms ◽  
Hospitalised Patients ◽  
Poor Outcomes ◽  
D Dimer

ObjectiveTo evaluate association between biomarkers and outcomes in COVID-19 hospitalised patients. COVID-19 pandemic has been a challenge. Biomarkers have always played an important role in clinical decision making in various infectious diseases. It is crucial to assess the role of biomarkers in evaluating severity of disease and appropriate allocation of resources.Design and settingSystematic review and meta-analysis. English full text observational studies describing the laboratory findings and outcomes of COVID-19 hospitalised patients were identified searching PubMed, Web of Science, Scopus, medRxiv using Medical Subject Headings (MeSH) terms COVID-19 OR coronavirus OR SARS-CoV-2 OR 2019-nCoV from 1 December 2019 to 15 August 2020 following Meta-analyses Of Observational Studies in Epidemiology (MOOSE) guidelines.ParticipantsStudies having biomarkers, including lymphocyte, platelets, D-dimer, lactate dehydrogenase (LDH), C reactive protein (CRP), aspartate aminotransferase (AST), alanine aminotransferase (ALT), creatinine, procalcitonin (PCT) and creatine kinase (CK), and describing outcomes were selected with the consensus of three independent reviewers.Main outcome measuresComposite poor outcomes include intensive care unit admission, oxygen saturation <90%, invasive mechanical ventilation utilisation, severe disease, in-hospital admission and mortality. The OR and 95% CI were obtained and forest plots were created using random-effects models. Publication bias and heterogeneity were assessed by sensitivity analysis.Results32 studies with 10 491 confirmed COVID-19 patients were included. We found that lymphopenia (pooled-OR: 3.33 (95% CI: 2.51–4.41); p<0.00001), thrombocytopenia (2.36 (1.64–3.40); p<0.00001), elevated D-dimer (3.39 (2.66–4.33); p<0.00001), elevated CRP (4.37 (3.37–5.68); p<0.00001), elevated PCT (6.33 (4.24–9.45); p<0.00001), elevated CK (2.42 (1.35–4.32); p=0.003), elevated AST (2.75 (2.30–3.29); p<0.00001), elevated ALT (1.71 (1.32–2.20); p<0.00001), elevated creatinine (2.84 (1.80–4.46); p<0.00001) and LDH (5.48 (3.89–7.71); p<0.00001) were independently associated with higher risk of poor outcomes.ConclusionOur study found a significant association between lymphopenia, thrombocytopenia and elevated levels of CRP, PCT, LDH, D-dimer and COVID-19 severity. The results have the potential to be used as an early biomarker to improve the management of COVID-19 patients, by identification of high-risk patients and appropriate allocation of healthcare resources in the pandemic.

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