Literature DB >> 33904671

The Association of Age, Sex, and RT-PCR Results with the Lymphocyte and Neutrophil Counts in SARS-CoV-2 Infection: A Cross-sectional Analysis of 1450 Iranian Patients with COVID-19.

Davood Bashash1, Hassan Abolghasemi2, Parisa Naseri3, Abdol Majid Cheraghali4, Mohammad Javad Soltanpoor5, Abbas Ali Imani Fooladi6.   

Abstract

Containment of pandemic infections mainly depends on prompt identification of carriers, achievable through strict surveillance and truthful diagnostic testing. Although molecular identification of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the gold standard method, its low sensitivity and long turnaround time are among major concerns. In this retrospective single-center study, we reviewed the results of the lymphocyte and neutrophil counts of 1450 Iranian patients with coronavirus disease 2019 (COVID-19) recruited at Baqiyatallah Hospital, Tehran, Iran. Of 1450 patients, 439 cases (30.3%) were polymerase chain reaction (PCR) negative; further emphasizing that getting negative molecular testing is not as reliable as a positive result. While the lymphocyte count in cases with less than 50 years old was 1.8×103/µL (1.2-2.5), it was 1.47×103/µL (0.84-2.16) in the older group (p<0.001). Also, men experienced lower lymphocytes as compared to women (1.53×103/µL vs 1.76×103/µL; p=0.002). Of particular interest, the lymphocyte count in the PCR-negative cases was 1.77×103/µL (0.98-2.45) which was significantly higher than its count in their positive counterparts (1.53×103/µL; p=0.004). Unlike lymphocytes, sex and PCR did not significantly affect the number of neutrophils. The odds ratio for neutrophilia in patients aged older than 50, either with a negative or a positive PCR, was 2.46 and 2.23, suggesting old age as the most significant associated factor. The number of lymphocytes along with increased neutrophil count may probably serve as simple, rapid, and economical biomarkers, and are seemingly appropriate items that should be taken into account in the identification of patients with COVID-19, especially those aged more than 50.

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Keywords:  COVID-19; Lymphocytes; Male; Neutrophils; SARS-CoV-2

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Year:  2021        PMID: 33904671

Source DB:  PubMed          Journal:  Iran J Allergy Asthma Immunol        ISSN: 1735-1502            Impact factor:   1.464


  1 in total

1.  PRCTC: a machine learning model for prediction of response to corticosteroid therapy in COVID-19 patients.

Authors:  Yue Gao; Xiaoming Xiong; Xiaofei Jiao; Yang Yu; Jianhua Chi; Wei Zhang; Lingxi Chen; Shuaicheng Li; Qinglei Gao
Journal:  Aging (Albany NY)       Date:  2022-01-12       Impact factor: 5.682

  1 in total

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