ABSTRACT
Objectives: For a definitive diagnosis of COVID-19, respiratory tract samples are evaluated by polymerase chain reaction (PCR). In our study, PCR using a tear sample was used to diagnose COVID-19, and it was questioned whether it was a screening method. Unlike the general practice, Schirmer strips were used instead of a swab for tear sample collection in this study. In addition, the diagnostic values of serum procalcitonin (PCT), C-reactive protein (CRP), and Neutrophil (NEU) count in predicting COVID-19 disease from tears were also questioned. Method(s): A total of 94 patients who were positive for COVID-19 by PCR test were included in this study. Tear samples were obtained from patients with Schirmer strips, commonly used in eye examination, and studied with the PCR technique. CRP, PCT value, and NEU count were also compared between the positive and negative groups of the PCR. The obtained data were analyzed using the R Studio software, and the results were considered statistically significant for p<0.05. Result(s): Of these patients, 61 (64.9%) tear PCR was negative, and 33 (35.1%) tear PCR was positive. The mean age was 61.72 +/- 17.62 years. The patients were divided into two groups: tear PCR positive and negative. There was no significant age difference between these groups. As a result of ROC Analysis;When serum PCT, CRP, and NEU % values were examined in predicting COVID-19 disease from tears, it was seen that CRP (p=0.027) and especially PCT (p=0.003) values of patients with PCR-positive were significantly higher. Conclusion(s): PCR study on tears collected with Schirmer strips is a different and non-invasive method, but it was concluded that the proposed method could not be used as a screening test. In addition, significantly higher serum PCT values were found in patients with COVID-19 positivity in tears (p<0.05). Copyright © 2022 the author(s), published by De Gruyter.
ABSTRACT
BACKGROUND AND AIM: In this study, we aimed to examine the changes in Neutrophil/Lymphocyte ratio (NLR), C-Reactive Protein (CRP), Ferritin, Lactate Dehydrogenase (LDH), D-Dimer and Systemic immune inflammation index (SII) parameters according to age and gender in patients with COVID-19 infection. METHODS: A total of 322 inpatients (Female: 180, Male: 142) who applied to Lokman Hekim University Ankara Hospital between March 2019 and August 2021 and had positive PCR tests were included in the study. The patients were divided into five age groups (1st group: 1-17 years;2nd group: 18-30 years;3rd group: 31-45 years;4th group: 46-60 years;5th group: 61-92 years). Laboratory results and demographic findings of PCR-positive patients were reviewed retrospectively. WBC, NLR, CRP, Ferritin, LDH, D-Dimer, SII values of the patients included in the study were examined in the study. RESULTS: When NLR, CRP, Ferritin, LDH, D-Dimer parameters were evaluated according to age groups, there was a significant difference (p<0.05). When the first and 2nd groups were compared, there was a significant difference in the D-dimer level. When the first and 3rd groups were compared, there was a significant difference in LDH, WBC, CRP levels. When the first and 4th groups were compared, there was a significant difference in the CRP levels. When the first and 5th groups were evaluated, a significant difference was observed in the levels of Ferritin, NLR, and CRP (p<0.05). When the correlations of NLR, CRP, Ferritin, LDH, D-Dimer values with respect to age were examined, CRP, LDH and Ferritin levels showed a moderate correlation (r=0.557, r=0.408, r=0.400, respectively);No correlation was observed in NLR, D-Dimer and WBC values. When evaluated according to gender, infection-related parameters (CRP, NLR, WBC and Ferritin) were found to be higher in males (p<0.05). When SII values were evaluated according to age and gender, no significant difference was observed (p>0.05). CONCLUSIONS: Since inflammatory and prognostic markers vary in patients with COVID-19 infection, we think that it would be useful to evaluate WBC, NLR, CRP, Ferritin, LDH, D-Dimer parameters and demographic data together for the follow-up of infection.