SynthesisAnnals of medicine2020
Characterisation of clinical, laboratory and imaging factors related to mild vs. severe covid-19 infection: a systematic review and meta-analysis.
Synthesis in Annals of medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 3 of them syntheses that pooled it.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
14 citing papers in PubMed, 3 syntheses or guidelines pooled it, 34 citations in OpenAlex.
- Cardiovascular risk factors, cardiovascular disease, and COVID-19: an umbrella review of systematic reviews.European heart journal. Quality of care & clinical outcomes · 2021Pooled it
- Diabetes is most important cause for mortality in COVID-19 hospitalized patients: Systematic review and meta-analysis.Reviews in endocrine & metabolic disorders · 2021Pooled it
- Pooled it
- CfDNA as a surrogate marker for COVID-19 severity in patients with influenza-like symptoms with and without SARS-CoV-2 infection in general practice: a prospective cohort study.Virology journal · 2025Article
- Assessing the Association between Biomarkers and COVID-19 Mortality Using the Joint Modelling Approach.Life (Basel, Switzerland) · 2024Article
- Early Outcomes of the Surgical Treatment of Non-traumatic Massive Pericardial Effusion in the University of the Philippines - Philippine General Hospital COVID-19 Referral Center.Acta medica Philippina · 2024Article
- Several laboratory variables indicate severity and prognosis of COVID-19.The Journal of international medical research · 2024Article
- Clinical Phenotypes and Mortality Biomarkers: A Study Focused on COVID-19 Patients with Neurological Diseases in Intensive Care Units.Behavioral sciences (Basel, Switzerland) · 2022Article
- Article
- Serological surveillance of SARS-CoV-2: Six-month trends and antibody response in a cohort of public health workers.The Journal of infection · 2021Article
- A meta-meta-analysis: Evaluation of meta-analyses published in the effectiveness of cardiovascular comorbidities on the severity of COVID-19.Obesity medicine · 2021Review
- Gut Microbiota Diversity and C-Reactive Protein Are Predictors of Disease Severity in COVID-19 Patients.Frontiers in microbiology · 2021Article
- Biomarkers in COVID-19: An Up-To-Date Review.Frontiers in pediatrics · 2020Review
- Proportion of hematological cancer patients with SARS-CoV-2 infection during the COVID-19 pandemic: A systematic review and meta-analysis.Hematology, transfusion and cell therapyReview
Corrections and comments
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Authors and funding
6 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundEarly detection of disease progression associated with severe COVID-19, and access to proper medical care lowers fatality rates of severe cases. Currently, no studies had systematically examined the variables in detecting severe COVID-19.
methodSystematic searching of electronic databases identified observational studies which recruited participants with confirmed COVID-19 infection who were divided into different groups according to disease severity were identified.
resultsTo analysis 41 studies with 5064 patients were included.Patients who are elderly (SMD, 1.90; 95% CI, 1.01 to 2.8), male (OR, 1.71; 95% CI, 1.39 to 2.11) and have comorbidities or flu-like symptoms were significantly associated with the development to severe cases. Severe cases were associated with significant increased WBC (OR, 5.83; 95% CI, 2.76 to 12.32), CRP (OR, 3.62; 95% CI, 1.62 to 8.03), D-dimer (SMD, 1.69; 95% CI, 1.09 to 2.28), AST (OR, 4.64; 95% CI, 3.18 to 6.77) and LDH (OR, 7.94; 95% CI, 2.09 to 30.21). CT manifestation of bilateral lung involvement (OR, 4.55; 95% CI, 2.17 to 9.51) was associated with the severe cases.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.