Fecal Calprotectin as a Predictor of COVID-19 Severity

Abstract: Coronavirus disease 2019 (COVID-19) is highly transmittable through contact with respiratory droplets. The virus is also shed in fecal matter. Some patients may present with effects in more than one system; however, there are no defined biomarkers that can accurately predict the course or progression of the disease. The present study aimed to estimate the severity of the disease, to correlate the severity of the disease with biochemical predictors, to identify valuable biomarkers indicative of gastrointestinal disease, and to determine the cutoff values. A cross-sectional study was conducted on COVID-19 patients admitted to the Kafrelsheikh University Hospital (isolation unit) between July 10, 2020, and October 30, 2020. The diagnosis of COVID-19 was confirmed via reverse transcription-polymerase chain reaction (RT-PCR), which was employed for the detection of the viral RNA. We conclude that lymphopenia, elevated C-reactive protein (CRP) level, and liver enzymes were among the most important laboratory findings in COVID-19 patients. Statistically significant differences in platelet count, neutrophil count, D-dimer level, and fecal calprotectin levels were observed among patients presenting with chest symptoms only and patients with both chest and gastrointestinal symptoms (p = 0.004; < 0.001; 0.010; 0.003; and < 0.001, respectively). C-reactive protein, D-dimer, and fecal calprotectin levels positively correlated with disease severity. The cutoff value for fecal calprotectin that can predict gastrointestinal involvement in COVID-19 was 165.0, with a sensitivity of 88.1% and a specificity of 76.5%.

Object Details

• Location: Deutsche Nationalbibliothek Frankfurt am Main
• Extent: Online-Ressource
• Language: Englisch

References and Relationships

• Bibliographic citation: Fecal Calprotectin as a Predictor of COVID-19 Severity ; volume:41 ; number:04 ; year:2021 ; pages:361-366 ; Journal of coloproctology ; 41, Heft 04 (2021), 361-366

Contributors, Places and Time

• Contributor: Ahmed, Mohammed Hussien ; Ahmed, Hebat Allah Abdel Maksoud ; Nosair, Nahla Abd el-Aziz ; Hassan, Asmaa Mbarak ; Sherief, Dalia ElSayed ; Mahros, Aya Mohammed

Further information

• DOI: 10.1055/s-0041-1736646
• URN: urn:nbn:de:101:1-2022031915171337496011
• Rights: Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
• Last update: 15.08.2025, 7:33 AM CEST