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Since December 2019, coronavirus diseases-2019 (COVID-19) dispersed into 200 countries and affected more than 70 million people. The clear picture of the SARS-CoV-2 infection is still under investigation. In this review, we evaluated whether C-reactive protein biomarker is able to predict the clinical outcomes or correlated with the severity of COVID-19 disease. The databases MEDLINE, Hinari, Google Scholar, and Google search were used to find potential studies published from COVID-19 epidemic until May 2021. A format prepared in Microsoft Excel spreadsheet was used to extract the appropriate details from each original report. For further review, the extracted data were exported to STATA/MP version 16.0 software. Keywords including “COVID-19,” “SARS-CoV-2,” and “C-reactive protein,” among others were used to search relevant articles. Only studies which reported the average C-reactive protein value and COVID-19 disease stage outcomes were included. Twenty articles were included in the review. All studies found considerably higher level of C-reactive protein in patients with severe COVID-19 as compared to mildly infected patients. This review evidenced that it is still there for a given biomarker to early identify the state of progression in asymptomatic and/or mildly infected individuals into severe disease; the level of C-reactive protein may be used in predicting the likelihood of disease progression. Findings from this review showed level of C-reactive protein is a good biomarker to predict the severity of COVID-19 disease. Although COVID-19 researches are at the early stages, investigation of C-reactive protein levels throughout the disease course may have paramount importance for clinicians in early detection of severe manifestations and subsequently improve the prognosis. However, further large-scale studies are required to confirm these findings.

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Background Person-centered maternity care is providing care that is respectful and responsive to individual women’s preferences, needs, and values and ensuring that their values guide all clinical decisions during childbirth. Although person-centered health care is one of the factors that increase client satisfaction and increased health service utilization in Ethiopia, little is known about predictors of person-centered maternity care. Therefore, the aim of this study was to identify the determinant factors of person-centered maternity care among mothers who gave birth in selected health facilities in Dessie town, Northeastern, Ethiopia. Methods A community-based cross-sectional study was conducted with a total of 317 study participants at Dessie town selected by a simple random sampling technique. The data was coded and entered Epi-data version 4.4 and analyzed using SPSS version 23. Descriptive statistics was presented using tables and figures. Multivariable linear regression analysis was used to identify factors associated with Person-Centered Maternity Care. Two sides P-value < 0.05 was taken to declare statistically significant. Results Overall, 310 study participants participated with a response rate of 97.8%. In multivariable linear regression, rural residence (β = -4.12; 95% CI: -7.60, -0.67), family average monthly income ≤ 3000 birr (β = -6.20, 95% CI: -9.40, -3.04), night time delivery(β = -2.98, 95%CI: -5.90, -0.06), dead fetus outcome during delivery (β = -12.7; 95% CI: -21.80, -3.50), and 2–7 days health facility length of stay (β = -5.07, 95% CI: -9.20, -0.92) were significantly decreased Person Center Maternity Care score, whereas private health institution delivery (β = 14.13, 95% CI: 7.70, 20.60) is significantly increased Person centered maternity care score. Conclusions This study revealed that most of the factors that affect person-centered maternity care are modifiable factors. Therefore, Primary attention should be given to improve the quality of care through effective communication between clients and providers at each level of the health care delivery system to increase the uptake of high-quality facility-based births.