A Systematic review of laboratory parameters predictive of long haul COVID-19 /

A Systematic review of laboratory parameters predictive of long haul COVID-19 / Aliyah B. Aurellana, Camille Serg R. De Guzman, Tom Cedrick G. Estrella, Cara Angela S. Nayve, Miryltrix A. Pedroche, Angela Mae S. Sarangaya, Erica Mae F. Shabado, Jan Naomi C. Tomes, John Robert A. Villalon, Angel Mikaela S. Villarama, Jane Louise S. Villareal and Ma. Kathlene Angela V. Villostas. - Fairview, Quezon City: School of Medical Technology, FEU-NRMF, 2023. - 55 pages: illustrations, tables; 28 cm.

Includes appendices and bibliographical references.

Abstract: The aftermath of COVID-19 infection resulted in a syndrome now called long-haul COVID-19. It is a condition wherein the clinical signs and symptoms persist for an extended period. Persistent symptoms manifested by patients are fatigue, cough, dyspnea, headache, brain fog, anosmia, and dysgeusia. But, symptoms experienced by patients may vary, thus making diagnosing the syndrome complex. A total of 14 studies published between 2020 to 2022 gathered from ScienceDirect, ResearchGate and PubMed were included in the systematic review. The researchers utilized PRISMA guidelines to systematically review all possible laboratory parameters used to predict long-haul COVID-19. Results showed that C-reactive Protein, D-dimer, Erythrocyte Sedimentation Rate, Interleukin-2, Interleukin-6, Lymphocyte, Total Antibodies, Troponin-I, Interferon-β, Interferon-λ1 and Ferritin are associated with the development and persistence of symptoms manifested by long-haul patients and can be used as the parameter for diagnosis. Meanwhile, Lactate dehydrogenase (LDH), Alanine transaminase (ALT), Aspartate aminotransferase (AST), Total Bilirubin, Creatinine, Lipocalin-2, Matrix Metalloproteinases-7, and Hepatocyte growth factor showed probable association with long-haul COVID-19. However, it still requires further validation on extensive studies before it can be used as a parameter for the long haul.

Thesis - School of Medical Technology


COVID-19
long-haul COVID-19
laboratory parameters

MT 2023 0009