Literature DB >> 33487128

Association Between Severity Grading Score And Acute Phase Reactants In Patients With Crimean Congo Hemorrhagic Fever.

Ilkay Bozkurt1, Saban Esen1.   

Abstract

As the COVID-19 pandemic continues, countries still have to struggle with their endemic diseases such as Crimean-Congo hemorrhagic fever (CCHF). Severity grading score (SGS) is a practical approach and may shed light on the course of the CCHF, whose pathogenesis is not clearly understood, and have no effective treatments. It is aimed to assess the association between SGS and acute phase reactants (APR). Laboratory-confirmed patients were categorized by severity scores, and the relationship between APR and SGS was evaluated. A significant correlation between SGS and C-reactive protein (CRP) was found (p < 0.001). High SGS was associated with mortality and high CRP levels were used to predict the mortality at the beginning of the hospital admission. To predict the outcome of the disease and for appropriate patient management, SGS and APR can be used simultaneously.

Entities:  

Keywords:  C-reactive protein; Crimean-Congo hemorrhagic fever; acute phase reactants; hemorrhagic fever; severity criteria

Mesh:

Substances:

Year:  2021        PMID: 33487128      PMCID: PMC8635591          DOI: 10.1080/20477724.2021.1878450

Source DB:  PubMed          Journal:  Pathog Glob Health        ISSN: 2047-7724            Impact factor:   2.894


  11 in total

1.  The effectiveness of routine laboratory findings in determining disease severity in patients with Crimean-Congo hemorrhagic fever: severity prediction criteria.

Authors:  Gurdal Yilmaz; Iftihar Koksal; Murat Topbas; Hulya Yilmaz; Firdevs Aksoy
Journal:  J Clin Virol       Date:  2010-02-09       Impact factor: 3.168

Review 2.  Crimean-Congo haemorrhagic fever in Eurasia.

Authors:  Hakan Leblebicioglu
Journal:  Int J Antimicrob Agents       Date:  2010-11       Impact factor: 5.283

Review 3.  Crimean-Congo hemorrhagic fever in Turkey: Current status and future challenges.

Authors:  Hakan Leblebicioglu; Resat Ozaras; Hasan Irmak; Irfan Sencan
Journal:  Antiviral Res       Date:  2015-12-13       Impact factor: 5.970

4.  Evaluation of factors predictive of the prognosis in Crimean-Congo hemorrhagic fever: new suggestions.

Authors:  Baris Ozturk; Ediz Tutuncu; Ferit Kuscu; Yunus Gurbuz; Irfan Sencan; Hakan Tuzun
Journal:  Int J Infect Dis       Date:  2011-12-06       Impact factor: 3.623

5.  A new perspective to determine the severity of cases with Crimean-Congo hemorrhagic fever.

Authors:  Mehmet Bakir; Aynur Engin; Mustafa Gokhan Gozel; Nazif Elaldi; Saadettin Kilickap; Ziynet Cinar
Journal:  J Vector Borne Dis       Date:  2012-06       Impact factor: 1.688

6.  Some acute phase reactants and cholesterol levels in serum of patient with Crimean-Congo haemorrhagic fever.

Authors:  Ismail Sari; Sevtap Bakir; Aynur Engin; Hüseyin Aydin; Omer Poyraz
Journal:  Bosn J Basic Med Sci       Date:  2013-02       Impact factor: 3.363

7.  Validation of a severity grading score (SGS) system for predicting the course of disease and mortality in patients with Crimean-Congo hemorrhagic fever (CCHF).

Authors:  M Bakır; M G Gözel; I Köksal; Z Aşık; Ö Günal; H Yılmaz; A But; G Yılmaz; A Engin
Journal:  Eur J Clin Microbiol Infect Dis       Date:  2014-09-12       Impact factor: 3.267

Review 8.  Prognostic factors, pathophysiology and novel biomarkers in Crimean-Congo hemorrhagic fever.

Authors:  Esragul Akinci; Hurrem Bodur; Mustafa Sunbul; Hakan Leblebicioglu
Journal:  Antiviral Res       Date:  2016-07-01       Impact factor: 5.970

9.  Direct healthcare costs for patients hospitalized with Crimean-Congo haemorrhagic fever can be predicted by a clinical illness severity scoring system.

Authors:  Ilkay Bozkurt; Mustafa Sunbul; Hava Yilmaz; Saban Esen; Hakan Leblebicioglu; Nicholas J Beeching
Journal:  Pathog Glob Health       Date:  2016-02-25       Impact factor: 2.894

10.  Evaluation of clinical and laboratory predictors of fatality in patients with Crimean-Congo haemorrhagic fever in a tertiary care hospital in Turkey.

Authors:  Cigdem Ataman Hatipoglu; Cemal Bulut; Meltem Arzu Yetkin; Gunay Tuncer Ertem; Fatma Sebnem Erdinc; Esra Kaya Kilic; Tugba Sari; Sami Kinikli; Behic Oral; Ali Pekcan Demiroz
Journal:  Scand J Infect Dis       Date:  2010-07
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  1 in total

1.  Machine-learning based prediction of prognostic risk factors in patients with invasive candidiasis infection and bacterial bloodstream infection: a singled centered retrospective study.

Authors:  Yaling Li; Yutong Wu; Yali Gao; Xueli Niu; Jingyi Li; Mingsui Tang; Chang Fu; Ruiqun Qi; Bing Song; Hongduo Chen; Xinghua Gao; Ying Yang; Xiuhao Guan
Journal:  BMC Infect Dis       Date:  2022-02-13       Impact factor: 3.090

  1 in total

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