Hemograms and serial hemogram-derived ratios in survivors and non-survivors of COVID-19 in Campinas, Brazil

INTRODUCTION

The hemogram and hemogram-derivative ratios (HDRs) are becoming markers of the severity and mortality of COVID-19. We evaluated the hemograms and serial weekly HDRs [neutrophil-lymphocyte ratio (NLR), monocyte-lymphocyte ratio (MLR), platelet-lymphocyte ratio (PLR), neutrophil-platelet ratio (NPR) and systemic immune-inflammatory index (SII)] in the survivors and non-survivors of COVID-19.

METHODS

We retrospectively reviewed the medical notes and serial hemograms of real-time reverse-transcription polymerase chain reaction (RT-PCR)-confirmed COVID-19 adults hospitalized from April 2020 to March 2021 from the time of diagnosis to the 3rd week of diagnosis.

RESULTS

Of the 320 adults, 257 (80.3%) were survivors and had a lower mean age than the non-survivors (57.73 vs. 64.65 years, p < 0.001). At diagnosis, the non-survivors had lower hematocrit (p = 0.021), and lymphocyte (p = 0.002) and basophil (p = 0.049) counts and the hematocrit showed a p-value (Is this what you meant???) of 0.021); higher NLR (p < 0.001), PLR (p = 0.047), NPR (p = 0.022) and SII (p = 0.022). Using general linear models, the survivors and non-survivors showed significant variations with weekly lymphocyte count (p < 0.001), neutrophil count (p = 0.005), NLR (p = 0.009), MLR (p = 0.010) and PLR (p = 0.035). All HDRs remained higher in the non-survivors in the 2nd week and 3rd week of diagnosis and the HDRs were higher in the intubated patients than in the non-intubated patients. The NLR and SII were more efficient predictors of mortality in COVID-19 patients.

CONCLUSIONS

This study shows that serial lymphocyte and neutrophil counts, NLR, PLR, MLR, NPR and SII could serve as good and easily accessible markers of severity and predictors of outcomes in COVID-19 patients and should be used for the monitoring of treatment response.

A score-based method of immune status evaluation for healthy individuals with complete blood cell counts

BACKGROUND

With the COVID-19 outbreak, an increasing number of individuals are concerned about their health, particularly their immune status. However, as of now, there is no available algorithm that effectively assesses the immune status of normal, healthy individuals. In response to this, a new score-based method is proposed that utilizes complete blood cell counts (CBC) to provide early warning of disease risks, such as COVID-19.

METHODS

First, data on immune-related CBC measurements from 16,715 healthy individuals were collected. Then, a three-platform model was developed to normalize the data, and a Gaussian mixture model was optimized with expectation maximization (EM-GMM) to cluster the immune status of healthy individuals. Based on the results, Random Forest (RF), Light Gradient Boosting Machine (LightGBM) and Extreme Gradient Boosting (XGBoost) were used to determine the correlation of each CBC index with the immune status. Consequently, a weighted sum model was constructed to calculate a continuous immunity score, enabling the evaluation of immune status.

RESULTS

The results demonstrated a significant negative correlation between the immunity score and the age of healthy individuals, thereby validating the effectiveness of the proposed method. In addition, a nonlinear polynomial regression model was developed to depict this trend. By comparing an individual's immune status with the reference value corresponding to their age, their immune status can be evaluated.

CONCLUSION

In summary, this study has established a novel model for evaluating the immune status of healthy individuals, providing a good approach for early detection of abnormal immune status in healthy individuals. It is helpful in early warning of the risk of infectious diseases and of significant importance.

Reconstructing the cytokine view for the multi-view prediction of COVID-19 mortality

BACKGROUND

Coronavirus disease 2019 (COVID-19) is a rapidly developing and sometimes lethal pulmonary disease. Accurately predicting COVID-19 mortality will facilitate optimal patient treatment and medical resource deployment, but the clinical practice still needs to address it. Both complete blood counts and cytokine levels were observed to be modified by COVID-19 infection. This study aimed to use inexpensive and easily accessible complete blood counts to build an accurate COVID-19 mortality prediction model. The cytokine fluctuations reflect the inflammatory storm induced by COVID-19, but their levels are not as commonly accessible as complete blood counts. Therefore, this study explored the possibility of predicting cytokine levels based on complete blood counts.

METHODS

We used complete blood counts to predict cytokine levels. The predictive model includes an autoencoder, principal component analysis, and linear regression models. We used classifiers such as support vector machine and feature selection models such as adaptive boost to predict the mortality of COVID-19 patients.

RESULTS

Complete blood counts and original cytokine levels reached the COVID-19 mortality classification area under the curve (AUC) values of 0.9678 and 0.9111, respectively, and the cytokine levels predicted by the feature set alone reached the classification AUC value of 0.9844. The predicted cytokine levels were more significantly associated with COVID-19 mortality than the original values.

CONCLUSIONS

Integrating the predicted cytokine levels and complete blood counts improved a COVID-19 mortality prediction model using complete blood counts only. Both the cytokine level prediction models and the COVID-19 mortality prediction models are publicly available at http://www.healthinformaticslab.org/supp/resources.php .

Evaluation of criteria of manual blood smear review following automated complete blood counts in a large university hospital

Background

There is great interest in reducing the number of automated complete blood counts requiring manual blood smear reviews without sacrificing the quality of patient care. This study was aimed at evaluating and establishing appropriate screening criteria for manual blood smear reviews to improve the performance in a hematology laboratory.

Method

A total of 1977 consecutive samples from the daily workload were used to evaluate four sets of screening criteria for manual blood smear reviews to identify samples with positive smear findings. Three sets of screening criteria were arbitrarily proposed in this study: Group 1 (narrow ranges), Group 2 (intermediate ranges), and Group 3 (wide limits) and one set (Group 4) was adapted from the International Society for Laboratory Hematology. All samples were run on Sysmex hematology analyzers and were investigated using manual blood smear reviews. Diagnostic accuracy and agreement were performed for each set of screening criteria, including an investigation of microscopic review rate and efficiency.

Results

The microscopic review rates for Groups 1, 2, 3 and 4 were 73.85%, 54.52%, 46.33% and 46.38%, respectively; the false-negative rates were 0.50%, 1.97%, 2.73% and 3.95%, respectively. The efficiency and negative predictive values of Group 3 were 73.04% and 4.91%, respectively.

Conclusions

Group 3 had the best relationship between safety (false-negative rate: ≤3%) and efficiency to estimate the limits of automation in performing complete blood counts. This study strengthens the importance of establishing screening criteria for manual blood smear reviews, which account for the different contexts in which hematological determinations are performed. Each laboratory should optimize the screening criteria for manual blood smear reviews in order to maximize their efficiency and safety.

Seasonal changes in hemograms and Theileria orientalis infection rates among Holstein cattle pastured in the mountains in the Republic of Korea

In the current study, we compared seasonal changes in complete blood counts (CBCs) and rates of infection with a tick-borne pathogen between Holstein cattle housed indoors and those maintained outside on pasture. There were differences in white blood cell (WBC) parameters, but the changes were not associated with seasons or the housing type. Analysis of red blood cell (RBC) parameters showed lower values in August and November versus March, and in the cattle maintained on pasture versus the housed cattle. In comparison with the RBC count of the housed cattle in March (10.1M/μL), the RBC counts of the pastured cattle were significantly lower in August (7.8M/μL; p<0.01) and November (7.5M/μL; p<0.01). The hematocrit (HCT) also showed a decrease in March (33.5%), August (30.0%, p<0.01) and November (28.5%, p<0.01). According to PCR analysis, the Theileria infection rate among the pastured cattle in March was only 11%, but this rate increased to 22% and 60% in August and November, respectively. The RBC count (7.4M/μL) and HCT (27.7%) values in Theileria-positive pastured cattle in November showed a dramatic decrease compared to those of cattle examined in March. Phylogenetic analysis revealed that these Theileria isolates correspond to T. orientalis. These results suggest that a remarkable increase in tick infestation in mountainous areas in the summer may cause increased rates of infection with T. orientalis, leading to significant changes in the RBC profile after grazing. Therefore, these hematological changes may be associated with T. orientalis infection caused by tick-biting; thus, additional studies on the pathogenicity of T. orientalis are needed.

Effects of 28-days ingestion of a slow-release energy supplement versus placebo on hematological and cardiovascular measures of health

Background

Recently, slow release tablets have been developed to prolong energy release throughout the day. The efficacy of the delivery of slow-release caffeine alone is fairly well documented; however, an assessment of safety and tolerability of prolonged use of slow-release energy supplements is lacking. Therefore the objective of this study was to investigate the effect of daily ingestion of a slow-release energy supplement for 28 days on blood chemistry and resting cardiovascular measures in healthy men and women.

Methods

Forty healthy individuals (20 males, 20 females; age: 22.73 ± 3.06 years; height: 171.68 ± 10.45 cm; mass: 74.49 ± 15.51 kg; BMI: 25.08 ± 3.66 (kg • m²) ^-1) participated in this randomized, double-blind, placebo controlled study. Following a 12-hour fast, participants reported for pre-testing. Testing consisted of resting heart rate (RHR) and blood pressure (BP) measures, followed by assessment of metabolic blood chemistry, blood lipids and complete cell counts. Participants then supplemented with either Energize™ (SUPP) or placebo (PL) for 28 days. Post-testing occurred 24-hours after ingestion of the final dose and consisted of the same protocol at the same time of day as pre-testing.

Results

No significant changes in outcome measures were observed. A significant difference between groups was observed for plasma glucose concentrations; however, follow-up testing revealed that pre- to post-supplementation changes were not significant for either SUPP or PL. All variables remained within normal adult reference ranges. No adverse events were reported.

Conclusions

These findings indicate that 28 consecutive days ingestion of a slow release energy supplement containing caffeine in caffeine users is both safe and tolerable.