Correlation of hematological parameters and cycle threshold in ambulatory patients with SARS-CoV-2 infection

Dynamic alterations in white blood cell counts and SARS-CoV-2 shedding in saliva: an infection predictor parameter

Introduction

The recent coronavirus (COVID-19) outbreak posed a global threat and quickly escalated to a pandemic. However, accurate information on potential relationships between SARS-CoV-2 shedding in body fluids, especially saliva, and white blood cell (WBC) count is limited. In the present study we investigated the potential correlation between alterations in blood cell counts and viral shedding in saliva in a cohort of COVID-19 patients.

Method

In this preliminary clinical research, 24 age-matched COVID-19 patients without comorbidities, 12 (50%) men and 12 (50%) women, were followed up for a period of 5 days to investigate whether changes in the level of viral shedding in saliva might parallel with temporal alterations in WBC count. Viral shedding in saliva was qualitatively measured by performing SARS-CoV-2 rapid antigen tests on patient saliva samples, using SARS-CoV-2 Rapid Antigen Test Kit (Roche, Basel, Switzerland). These patients were classified into two groups with sputum and non-sputum cough. WBCs counts including leukocyte (LYM), neutrophil (NEU), and LYM counts were recorded for each patient on days 1, 3, and 5.

Results

The results of the present study showed that the levels of WBC, LYM, and NEU as well as erythrocyte sedimentation rate (ESR) increased significantly on the 5th day compared to the first day in both groups with sputum. However, the levels of C-reactive protein (CRP), Neutrophil-to-Lymphocyte Ratio (NLR) and lactate dehydrogenase (LDH) did not show significant changes.

Conclusion

This study proves that investigating the change in the number of blood LYMs as well as laboratory parameters such as CRP, LDH, and ESR as biomarkers is an accurate indicator to detect the amount of viral shedding in people with sputum and non-sputum. The results of our study denote that the measured parameters exhibit the intensity of viral shedding in people with sputum.

Hematologic analysis of hospitalized patients and outpatients infected with SARS-CoV-2 and possible use as a prognostic biomarker

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is a global health problem; this has caused thousands of deaths around the world. This infection induces hematologic alterations, and it is necessary to recognize predictive biomarkers to address the need for hospitalization or the severity of the disease. This study aimed to analyze different parameters in outpatients and hospitalized patients infected with SARS-CoV-2 and determine whether hematic biometry can be used for prognosis rapidly. We analyzed 689 patients, of whom 355 were outpatients (162 women and 193 men) and 334 required hospitalization (197 men and 137 women). The average age of the hospitalized patients was 46 years (men, 49 years; women, 52 years), whereas the average age of the outpatients was 49 years (men, 51 years; women, 44 years). Hematologic parameters were analyzed and compared between the outpatients and hospitalized patients. The patients were divided into groups by age and sex. We found that in the hospitalized patients, the erythrocyte, hematocrit, and hemoglobin levels decreased, whereas the outpatients did not experience changes in the erythroid series. In leukocytes, these increased significantly, as they did in neutrophils; however, lymphocytopenia was observed. In the outpatients, we observed normal levels of neutrophils and lymphopenia. We can conclude that hematic biometry can be used as a biomarker, and the relation between neutrophils and lymphocytes is indicated for understanding the development and prognosis of the disease.

The machine learning model based on trajectory analysis of ribonucleic acid test results predicts the necessity of quarantine in recurrently positive patients with SARS-CoV-2 infection

Background

SARS-CoV-2 patients re-experiencing positive nucleic acid test results after recovery is a concerning phenomenon. Current pandemic prevention strategy demands the quarantine of all recurrently positive patients. This study provided evidence on whether quarantine is required in those patients, and predictive algorithms to detect subjects with infectious possibility.

Methods

This observational study recruited recurrently positive patients who were admitted to our shelter hospital between May 12 and June 10, 2022. The demographic and epidemiologic data was collected, and nucleic acid tests were performed daily. virus isolation was done in randomly selected cases. The group-based trajectory model was developed based on the cycle threshold (Ct) value variations. Machine learning models were validated for prediction accuracy.

Results

Among the 494 subjects, 72.04% were asymptomatic, and 23.08% had a Ct value under 30 at recurrence. Two trajectories were identified with either rapid (92.24%) or delayed (7.76%) recovery of Ct values. The latter had significantly higher incidence of comorbidities; lower Ct value at recurrence; more persistent cough; and more frequently reported close contacts infection compared with those recovered rapidly. However, negative virus isolation was reported in all selected samples. Our predictive model can efficiently discriminate those with delayed Ct value recovery and infectious potentials.

Conclusion

Quarantine seems to be unnecessary for the majority of re-positive patients who may have low transmission risks. Our predictive algorithm can screen out the suspiciously infectious individuals for quarantine. These findings may assist the enaction of SARS-CoV-2 pandemic prevention strategies regarding recurrently positive patients in the future.

Comparative Analysis of Age, Sex, and Viral Load in Outpatients during the Four Waves of SARS-CoV-2 in A Mexican Medium-Sized City

Governments have implemented measures to minimize SARS-CoV-2 spread. However, these measures were relaxed, and the appearance of new variants has prompted periods of high contagion known as waves. In Mexico, four waves distributed between July and August 2020, January and February 2021, August and September 2021, and January and February 2022 have appeared. Current health policies discourage mass sampling, preferring to focus on the corrective treatment of severe cases. Outpatients are only advised to undergo brief voluntary confinement and symptomatic treatment, with no follow-up. Therefore, the present study aimed to analyze sex, age, and viral load in outpatients during the four waves in a medium-sized city in Mexico. For each wave, the date of peak contagion was identified, and data were collected within ±15 days. In this regard, data from 916 patients (434 men and 482 women) were analyzed. The age range of positive patients (37-45 years) presented a higher frequency during the first and third waves, while 28-36 years was the most frequent age range during the second and fourth waves, while the viral load values were significantly higher, for both sexes, during the fourth wave. Obtained data of COVID-19 prevalence in population segments can be used for decision-making in the design of effective public health policies.