ArticleResults in physics2021
Analysis of COVID-19 epidemic and clinical risk factors of patients under epidemiological Markov model.
Article in Results in physics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 4 of them syntheses that pooled it.
What it found
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Who cites it
6 citing papers in PubMed, 4 syntheses or guidelines pooled it, 17 citations in OpenAlex.
- Effects of the pre-existing coronary heart disease on the prognosis of COVID-19 patients: A systematic review and meta-analysis.PloS one · 2023Pooled it
- Prevalence of comorbid tuberculosis amongst COVID-19 patients: A rapid review and meta-analysis.International journal of clinical practice · 2021Pooled it
- Process Improvement Approaches for Increasing the Response of Emergency Departments against the COVID-19 Pandemic: A Systematic Review.International journal of environmental research and public health · 2021Pooled it
- Active pulmonary tuberculosis and coronavirus disease 2019: A systematic review and meta-analysis.PloS one · 2021Pooled it
- From genes to trajectories: mapping genetic influences on Huntington's disease progression.Bioinformatics (Oxford, England) · 2026Article
- Prediction of SARS-CoV-2 infection cases based on the meta-SEIRS model.Epidemiology and infection · 2024Article
Corrections and comments
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Authors and funding
8 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveIt aimed to analyze the epidemic situation of new coronary pneumonia (COVID-19) based on the epidemiological Markov model, and to study the clinical risk factors of the patients based on the patient's cardinal data and clinical symptoms.
methodsA total of 500 patients with COVID-19 diagnosed by nucleic acid testing in the X hospital from January 2020 to May 2020 were collected. According to the severity of the disease, they were classified into general group (200 cases) and acute critical group (300 cases). Markov model to predict the number of COVID-19 infections was constructed. Patient's general information, clinical characteristics, and prevention methods were analyzed.
resultsAccording to Markov model statistics, the developmental expected stay time of patients infected with COVID-19 was 14 days. 2. The two groups of patients had statistically considerable differences in complications such as gender, age, hypertension, coronary heart disease, shortness of breath, myocardial damage, and thrombocytopenia (
conclusionMarkov model can be utilized to judge the time course of the COVID-19 in various development states. In addition, the COVID-19 spread rapidly and is extremely harmful. Clinically, through active prevention, the treatment effect can be improved, the patient's respiratory function, and the quality of life can also be improved.
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