Relationship between leukocyte, neutrophil, lymphocyte, platelet counts, and neutrophil to lymphocyte ratio and polymerase chain reaction positivity

The relationship between a series of inflammatory markers on the risk of heart failure in different gender groups: Analysis from NHANES 2015-2018

BACKGROUND

A better understanding of the level-grade inflammation for the development and worsening of heart failure (HF) in different gender groups is an unmet need. We performed an updated analysis on the impact of a series of systemic inflammation markers on HF.

METHODS

This compensatory cross-sectional study enrolled participants from the National Health and Nutrition Examination Survey (NHANES) 2015-2018. HF was based on the self-reported questions. Univariate and multivariate logistic regression were used to investigate the association between systemic immune-inflammation index (SII), high sensitivity C-reactive protein (hs-CRP), lymphocyte-to-monocyte ratio (LMR), neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR) and HF. For patients of different genders, P for trend was used to analyze potential linear trend relationships and the restricted cubic splines (RCS) were used to describe non-linear relationships. The additive interaction was evaluated by the relative excess risk due to interaction (RERI), attributable proportion (AP), and the synergy index (SI). The multiplicative interaction was evaluated by odds ratio (OR) and 95% confidence interval (CI) of product-term.

RESULTS

A total of 5,830 participants from the NHANES database were divided into two groups: the HF group (n = 210) and the non-HF group (n = 5620). After gender stratification, hs-CRP (OR: 1.01, 95% CI: 1.00-1.03), SII (OR: 1.00, 95% CI: 1.00-1.01), NLR (OR: 1.22, 95% CI: 1.11-1.35) and LMR (OR: 0.79, 95% CI: 0.65-0.93) were independent meaningful factors for HF in males, there was no non-linear relationship between the three factors (SII, NLR, hs-CRP, all P for non-linear > 0.05) and the prevalence of HF, but we detected a non-linear relationship between LMR and the prevalence of HF in males (P for non-linear < 0.05). An additive interaction of hs-CRP and NLR on the risk of HF in males (RERI (OR): 0.67, 95% CI: 0.12-1.34; AP (OR): 0.14, 95% CI: 0.02-0.24; SI (OR): 1.22, 95% CI: 1.03-1.44).

CONCLUSIONS

In summary, hs-CRP, NLR, and LMR are superior meaningful markers for HF in males. SII may be a meaningful systemic inflammation warning marker for HF, which needs to be discriminated against with caution. Only detected a non-linear relationship between LMR and the prevalence of HF in males. NLR and hs-CRP may have an additive interaction in the prevalence of male HF patients. The outcome compensated for previous studies that still needed more studies for validation.

Ferritin/lymphocyte percentage ratio to predict the severity and mortality of COVID-19

Objective

In this study, we aimed to investigate the relationship between ferritin/lymphocyte percentage ratio (FLPR) with clinical and radiological disease severity and mortality in COVID-19 patients.

Methods

This retrospective study was conducted with patients who had polymerase chain reaction positive results for COVID-19. We calculated FLPRs from laboratory tests taken during emergency clinic admission. The relationship between chest computed tomography (CT) scores, disease severity, and 30-day mortality with FLPR was evaluated.

Results

Our study included 309 patients. 30-day mortality occurred in 12.3% (n=38) of the patients. A statistically significant association was found between FLPR and clinical disease severity (p <0.001). In the post hoc analysis, the difference was caused by the critical and severe groups and FLPR was significantly higher in these groups. A significant correlation was found between CT scores and FLPR (r=0.496, p<0.001). Logistic regression analysis revealed that hypertension, smoking, C-reactive protein (CRP), and FLPR levels were independent risk factors for mortality in COVID-19 patients. In the receiver operating characteristics curve analysis, determined the predictive value and the optimal cut-off value of FLPR. The areas under the curve of WBC, lymphocyte, neutrophil, ferritin, CRP, FLPR were found 0.707, 0.233, 0.735, 0.878, 0.831, 0.924 (p<0.001), respectively. This analysis showed that the FLPR can predict 30-day mortality better than the other biomarkers in the comparison. When the optimal cut-off value of FLPR is 42.4, the sensitivity is 84.2% and specificity is 86.7%.

Conclusion

FLPR can be used as an independent biomarker of disease severity and mortality in COVID-19.

Lactiplantibacillus pentoses CCFM1227 Produces Desaminotyrosine to Protect against Influenza Virus H1N1 Infection through the Type I Interferon in Mice

Microbiota-derived desaminotyrosine (DAT) protects the host from influenza by modulating the type I interferon (IFN) response. The aim of this study was to investigate the antivirus effects of a DAT-producing bacteria strain. A comparative genomics analysis and UHPLC Q-Exactive MS were used to search for potential strains and confirm their ability to produce DAT, respectively. The anti-influenza functions of the DAT producer were evaluated using an antibiotic-treated mouse model by orally administering the specific strain before viral infection. The results showed the Lactiplantibacillus pentosus CCFM1227 contained the phy gene and produced DAT by degrading phloretin. In vivo, L. pentosus CCFM1227 re-inoculation increased the DAT level in feces, and protected from influenza through inhibiting viral replication and alleviating lung immunopathology. Furthermore, CCFM1227-derived DAT was positively correlated with the IFN-β level in the lung. The transcriptome results showed that CCFM1227 activated gene expression in the context of the defense response to the virus, and the response to interferon-beta. Moreover, CCFM1227 treatment upregulated the expression of MHC-I family genes, which regulate the adaptive immune response. In conclusion, L. pentosus CCFM1227 exerted antiviral effects by producing DAT in the gut, and this may provide a potential solution for creating effective antiviral probiotics.

Personalized prediction of one-year mental health deterioration using adaptive learning algorithms: a multicenter breast cancer prospective study

Identifying individual patient characteristics that contribute to long-term mental health deterioration following diagnosis of breast cancer (BC) is critical in clinical practice. The present study employed a supervised machine learning pipeline to address this issue in a subset of data from a prospective, multinational cohort of women diagnosed with stage I-III BC with a curative treatment intention. Patients were classified as displaying stable HADS scores (Stable Group; n = 328) or reporting a significant increase in symptomatology between BC diagnosis and 12 months later (Deteriorated Group; n = 50). Sociodemographic, life-style, psychosocial, and medical variables collected on the first visit to their oncologist and three months later served as potential predictors of patient risk stratification. The flexible and comprehensive machine learning (ML) pipeline used entailed feature selection, model training, validation and testing. Model-agnostic analyses aided interpretation of model results at the variable- and patient-level. The two groups were discriminated with a high degree of accuracy (Area Under the Curve = 0.864) and a fair balance of sensitivity (0.85) and specificity (0.87). Both psychological (negative affect, certain coping with cancer reactions, lack of sense of control/positive expectations, and difficulties in regulating negative emotions) and biological variables (baseline percentage of neutrophils, thrombocyte count) emerged as important predictors of mental health deterioration in the long run. Personalized break-down profiles revealed the relative impact of specific variables toward successful model predictions for each patient. Identifying key risk factors for mental health deterioration is an essential first step toward prevention. Supervised ML models may guide clinical recommendations toward successful illness adaptation.

The interplay between hypovitaminosis D and the immune dysfunction in the arteriovenous thrombotic complications of the sever coronavirus disease 2019 (COVID-19) infection

Thromboembolic complications including cerebrovascular accidents, pulmonary embolism, myocardial infarction, deep vein thrombosis and disseminating intravascular coagulopathy are serious encounters in sever coronavirus disease 2019 (COVID-19) infected patients. This worsens the prognosis and may lead to death or life long morbidities. The laboratory finding of the disturbed haemostasias and the hyperinflammatory response are almost invariably present in COVID-19 patients. Multiple treatment modalities are utilized by the healthcare professionals to overcome the cytokine storm, oxidative stress, endothelial dysfunction, and coagulopathy in these patients. The combined actions of vitamin D (VitD) as a steroid hormone with anti-inflammatory, immunomodulatory, and antithrombotic properties increase the potential of the possible involvement of hypovitaminosis D in the thromboembolic complications of COVID-19 infection, and stimulated researchers and physicians to administer VitD therapy to prevent the infection and/or overcome the disease complications. The current review highlighted the immunomodulatory, anti-inflammatory, antioxidative and hemostatic functions of VitD and its interrelation with the renin-angiotensin-aldosterone system (RAAS) pathway and the complement system. Additionally, the association of VitD deficiency with the incidence and progression of COVID-19 infection and the associated cytokine storm, oxidative stress, hypercoagulability, and endothelial dysfunction were emphasized. Normalizing VitD levels by daily low dose therapy in patients with hypovitaminosis D below (25 nmol/l) is essential for a balanced immune response and maintaining the health of the pulmonary epithelium. It protects against upper respiratory tract infections and decreases the complications of COVID-19 infections. Understanding the role of VitD and its associated molecules in the protection against the coagulopathy, vasculopathy, inflammation, oxidative stress and endothelial dysfunction in COVID-19 infection could lead to new therapeutic strategies to prevent, treat, and limit the complications of this deadly virus infection.

Predicting Influenza A Virus Infection in the Lung from Hematological Data with Machine Learning

The tracking of pathogen burden and host responses with minimally invasive methods during respiratory infections is central for monitoring disease development and guiding treatment decisions. Utilizing a standardized murine model of respiratory influenza A virus (IAV) infection, we developed and tested different supervised machine learning models to predict viral burden and immune response markers, i.e., cytokines and leukocytes in the lung, from hematological data. We performed independently in vivo infection experiments to acquire extensive data for training and testing of the models. We show here that lung viral load, neutrophil counts, cytokines (such as gamma interferon [IFN-γ] and interleukin 6 [IL-6]), and other lung infection markers can be predicted from hematological data. Furthermore, feature analysis of the models showed that blood granulocytes and platelets play a crucial role in prediction and are highly involved in the immune response against IAV. The proposed in silico tools pave the path toward improved tracking and monitoring of influenza virus infections and possibly other respiratory infections based on minimally invasively obtained hematological parameters. IMPORTANCE During the course of respiratory infections such as influenza, we do have a very limited view of immunological indicators to objectively and quantitatively evaluate the outcome of a host. Methods for monitoring immunological markers in a host's lungs are invasive and expensive, and some of them are not feasible to perform. Using machine learning algorithms, we show for the first time that minimally invasively acquired hematological parameters can be used to infer lung viral burden, leukocytes, and cytokines following influenza virus infection in mice. The potential of the framework proposed here consists of a new qualitative vision of the disease processes in the lung compartment as a noninvasive tool.

Evaluation of Laboratory Results with Data from Bio-Speedy Respiratory Panel 2 in Nasopharyngeal Swab Specimens of COVID-19-Suspected Patients Having PCR(-) Results

Objective: The distinction between COVID-19 and other respiratory infections can be difficult during the flu and winter seasons. The aim of this study is to detect bacterial/viral microorganisms in nasopharyngeal swab samples and to evaluate routine laboratory results of patients with PCR (-) but suspected covid 19. Methods: Between 1 July 2021 and 31 December 2021, 78 patients who were hospitalized and followed up in the suspected Covid service were included in the study. The patients were divided into two groups as those with and without growth on the respiratory panel. Laboratory, demographic and radiological data were compared between groups. Results: C-reactive protein (CRP) and ferritin levels were found to be statistically significantly higher in the group with growth on the respiratory panel compared to the group without growth (p= .05, p= .041, respectively). Reproduction was detected in nasopharyngeal swab samples taken in 56.4% of the patients. More than half of the patients were radiologically defined as CO-RADS 3. Conclusion: It should not be forgotten that other respiratory viral and bacterial infections that mimic the COVID-19 clinic are also commonly observed during this period.

COVID-19 IgG/IgM patterns, early IL-6 elevation and long-term radiological sequelae in 75 patients hospitalized due to interstitial pneumonia followed up from 3 to 12 months

BACKGROUND

COVID-19 pandemic resulted in about 165 million infections and 3.4 million deaths all over the world across 15 months. The most severe clinical presentation of COVID-19 diseases is interstitial pneumonia.

METHODS

In this paper we describe clinical outcomes based on radiological features as well as the pattern of haematochemical parameters and IgG/IgM antibodies in 75 patients hospitalized due to COVID-related interstitial pneumonia not requiring intensive care assistance. Each patient underwent routine laboratory tests, including inflammatory markers and coagulation profile at baseline. Computed Tomography (CT) was performed at baseline and after 3 months to assess the persistence of radiological sequelae. A Generalized Linear Model (GLM) was used to test for each patient the association between individual haematochemical parameters at the time of hospital admission and the subsequent radiological features after three months. The presence of IgG antibodies was quantitatively determined in 70 patients at the time of hospital admission and after 3 months. A subgroup of 49 and 21 patients underwent additional dosage of IgG after 6 and 12 months, respectively. IgM serological antibodies were available for 17 patients at baseline and 61 at T3, with additional follow-up for 51 and 20 subjects after 6 and 12 months, respectively.

RESULTS

Only 28 out of 75 patients discharged from the hospital were totally healed after 3 months, while 47 patients (62.7%) still presented radiological sequelae. According to the GLM model, specific haematochemical baseline parameters-such as IL-6, GPT, platelets and eosinophil count-showed a statistically significant association with the presence of radiological sequelae at month 3 highlighting an OR = 0.5, thus meaning that subjects completely healed after 3 months presented half levels of IL-6 at baseline compared to patients with sequelae. In general, IgG serum levels were always higher than IgM at the time of hospitalization (75% at T0; n = 12 out of 16 patients with data available in both visits), after 3 months (72.1%; n = 44 out of 61 pts.), after 6 months (56.8%; 25 out of 44 pts.), and one year after hospitalization (60%; 12 out of 20 pts.). Overall, IgG and IgM serum levels presented a statistically significant decreasing trend from the baseline to month 3, 6 and 12. One patient presented an increase in IgM between baseline and month 3 but negative PCR test for SARS-COV2 on throat swab.

CONCLUSIONS

As supported by our findings on 75 patients, COVID-related interstitial pneumonia triggers early IgG levels (higher than IgM) that gradually decrease over 12 months. Mid-term sequelae are still detectable at lung Computed Tomography after 3 months from the hospital admission. Occasionally, it is possible to observe increase of IgM levels in presence of low concentrations of IgG and negative PCR ELISA tests for SARS-COV2 RNA. Baseline levels of IL-6 could be proposed as predictor of radiological mid/long-term sequelae after COVID-related interstitial pneumonia.

Vitamin D and Platelets: A Menacing Duo in COVID-19 and Potential Relation to Bone Remodeling

Global data correlate severe vitamin D deficiency with COVID-19-associated coagulopathy, further suggesting the presence of a hypercoagulable state in severe COVID-19 patients, which could promote thrombosis in the lungs and in other organs. The feedback loop between COVID-19-associated coagulopathy and vitamin D also involves platelets (PLTs), since vitamin D deficiency stimulates PLT activation and aggregation and increases fibrinolysis and thrombosis. Vitamin D and PLTs share and play specific roles not only in coagulation and thrombosis but also during inflammation, endothelial dysfunction, and immune response. Additionally, another ‘fil rouge’ between vitamin D and PLTs is represented by their role in mineral metabolism and bone health, since vitamin D deficiency, low PLT count, and altered PLT-related parameters are linked to abnormal bone remodeling in certain pathological conditions, such as osteoporosis (OP). Hence, it is possible to speculate that severe COVID-19 patients are characterized by the presence of several predisposing factors to bone fragility and OP that may be monitored to avoid potential complications. Here, we hypothesize different pervasive actions of vitamin D and PLT association in COVID-19, also allowing for potential preliminary information on bone health status during COVID-19 infection.