Dynamic NLR and PLR in Predicting COVID-19 Severity: A Retrospective Cohort Study

Association between glyphosate exposure and cardiovascular health using "Life's Essential 8" metrics in US adults

BACKGROUND

Glyphosate, as one of the most widely used herbicides worldwide, has been reclassified as a potential carcinogen and linked to multiple health problems. Recent data from animal experiments have proved its potential cardiovascular toxicity. However, whether glyphosate exposure influences human cardiovascular health at the population levels remains unknown. This study aims to elucidate the correlation between glyphosate exposure and Cardiovascular Health (CVH) by utilizing comprehensive Life's Essential 8 (LE8) metrics.

METHODS

Data from 2842 participants, approximating 155.24 million U.S. adults, from 2013 to 2018 in National Health and Nutrition Examination Survey were analyzed. The association between natural logarithm (ln)-transformed glyphosate exposure in urine and CVH was examined using weighted linear regression and restricted cubic spline (RCS) models. Mediation analysis was used to determine potential mediators correlated with glyphosate and CVH. Further subgroup analysis and sensitive analysis were conducted to confirm the results.

RESULTS

In fully adjusted models, the total CVH score decreased by 1.33 points for every unit increase in continuous ln-transformed glyphosate [β = -1.33, 95 % confidence interval (CI) (-2.25, -0.41)]. There was a negative correlation between the total CVH score and the lowest quantiles of ln-transformed glyphosate (Q1), Q2, Q3, and Q4 with p for trend < 0.05. A non-linear relationship between glyphosate and total CVH emerged (p for non-linear<0.001, p for overall = 0.003), and no safe threshold of glyphosate was observed. Serum insulin was an important mediator in the adverse effects of glyphosate on CVH with an 18.73 % mediation proportion. Moreover, higher serum insulin levels and higher homeostasis model assessment of insulin resistance were associated with higher glyphosate exposure but negatively correlated with total CVH score.

CONCLUSIONS

Glyphosate exposure may pose a risk to cardiovascular health at the population levels, with elevated serum insulin levels acting as a crucial mediating element. Further studies are required to investigate the safe threshold and underlying mechanism of glyphosate impairment.

Reevaluation of prognostic and severity indicators for COVID-19 patients in the emergency department

AIMS

This study aimed to re-evaluate whether the scoring systems, neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) were effective in predicting prognosis and severity of COVID-19 patients in the emergency department (ED).

METHODS

COVID-19 patients enrolled in this retrospective study divided into the death (DEA) and survival (SUR) groups, the severe/critical (SC) and non-severe/critical (non-SC) groups. The Acute Physiology and Chronic Health Evaluation (APACHE) II, Sequential Organ Failure Assessment (SOFA), National Early Warning Score (NEWS) and CCEDRRN COVID-19 Mortality Score were calculated. The neutrophil, lymphocyte and platelet counts were extracted from the first routine blood examination, and NLR and PLR were calculated accordingly. Receiver Operating Characteristic (ROC) curve and logistic regression were performed.

RESULTS

All the scoring systems, as well as NLR and PLR, significantly increased in both the DEA and SC groups. The ROC curve showed that the CCEDRRN COVID-19 Mortality Score had the highest predictive value for mortality and severity (AUC 0.779, 0.850, respectively), which outperformed the APACHE II, SOFA and NEWS. NLR presented better predictive ability for severity (AUC 0.741) than death (AUC 0.702). The APACHE II, NEWS and CCEDRRN COVID-19 Mortality Score were positively correlated with both prognosis and severity, whereas NLR only with severity.

CONCLUSION

The NEWS and CCEDRRN COVID-19 Mortality Score were reconfirmed for early and rapid predicting the poor prognosis and severity of COVID-19 patients in ED, especially the CCEDRRN COVID-19 Mortality Score with the highest discrimination capacity, and NLR was more appropriate for predicting the severity.

High inflammatory indices are significant predictors of disease severity in maintenance hemodialysis patients with COVID-19: A cross-sectional study

Background

The patients with kidney failure who undergo maintenance hemodialysis (MHD) at high risk of morbidity and mortality from COVID-19. Previous studies showed that inflammation plays an important role in the progression of COVID-19. This study aimed to evaluate the prognostic value of the inflammatory indices in MHD patients with COVID-19.

Methods

We included 141 patients receive MHD in this single-center. SARS-CoV-2 infection was confirmed by a positive result in RT-PCR analysis of nasal and pharyngeal swab samples, and the demographic, clinical, and laboratory data from December 1, 2022, to January 31, 2023 were reviewed. Inflammatory indices including PLR, NLR and SII were calculated. Binary logistics regression was used to examine the association between inflammatory indices and SARS-CoV-2 infection in MHD patients. The ROC curves were used to detect the sensitivity and specificity of these inflammatory indices in prediction of SARS-CoV-2 infection status in MHD patients.

Results

SARS-CoV-2 infection was detected in 76.43 % of the 141 MHD patients. Lymphocyte (LY), aspartate transaminase (AST), blood urea nitrogen (BUN), uric acid (UA), PLR, NLR and SII were significant predictors of no SARS-CoV-2 infection and symptomatic SARS-CoV-2 infection. In addition, LY, serum ferritin (SF), AST, BUN, UA, PLR and NLR were significant predictors of asymptomatic SARS-CoV-2 infection and symptomatic SARS-CoV-2 infection. The ROC curves showed the best sensitivity and specificity of PLR (66.7 % sensitivity; 68.8 % specificity) and NLR (51.9 % sensitivity; 86.3 % specificity) in predicting symptomatic SARS-CoV-2 infection.

Conclusion

PLR and NLR can be used as simple and inexpensive biomarkers in predicting the prognosis of COVID-19 in MHD patients.

The clinical value of KL-6 for predicting the occurrence and severity of connective tissue disease-associated interstitial lung disease is not affected by CTD type or treatment

Objective

The aim of this study was to explore the potential values of Krebs von den Lungen-6 (KL-6), neutrophil to lymphocyte ratio (NLR), systemic immune inflammation (SII), platelet to lymphocyte ratio (PLR), monocyte to lymphocyte ratio (MLR) and red blood cell distribution width (RDW) in the diagnosis and evaluation of the severity of connective tissue disease-associated interstitial lung disease (CTD-ILD).

Methods

A total of 140 connective tissue disease (CTD) patients and 85 CTD-ILD patients were recruited for this study at Shanxi Provincial People's Hospital from May 2022 to May 2023. Patients were divided into subgroups based on medication history and CTD subtypes to compare and analyze the clinical data and laboratory parameters of CTD-ILD patients and CTD patients. The receiver operating characteristic curve (ROC) was used to evaluate the diagnostic efficacy of KL-6, NLR, SII, PLR, MLR, and RDW in identifying CTD-ILD patients from CTD patients. A Spearman correlation analysis was conducted to elucidate the correlations between these markers and the lung function parameters of forced vital capacity (FVC, %), forced expired volume in one second (FEV1, %), and diffusing capacity of carbon monoxide (DLCO, %). Finally, binary logistic regression analysis was applied to discern the independent risk factors for CTD-ILD.

Results

NLR, SII, MLR, RDW, and KL-6 displayed significant statistical differences in the experimental groups. In both untreated and treated subgroups, KL-6 displayed higher values for CTD-ILD than CTD among all CTD subtypes. In untreated subgroups, there were significant differences in MLR levels between rheumatoid arthritis (RA) and RA-ILD patients and in NLR levels between Sjögren syndrome (SjS) and SjS-ILD patients. There were also significant differences in RDW-SD between the "other CTD" and "other CTD-ILD" groups. In treated subgroups, there were significant differences in both RDW-SD and RDW-CV between RA and RA-ILD patients and in NLR, SII, MLR, PLR, and RDW-SD between "other CTD" and "other CTD-ILD" groups. ROC revealed that KL-6 emerged as the most effective predictor for CTD-ILD in both treated and untreated groups. The multivariate logistic regression analysis results showed that both KL-6 and age were independent risk factors for CTD-ILD. NLR, SII, and PLR were negatively correlated with DLCO (%) in the untreated CTD-ILD group, and KL-6 was negatively correlated with various lung function parameters in both treated and untreated CTD-ILD groups.

Conclusion

KL-6 emerged as the most promising biomarker for diagnosing CTD-ILD and assessing its severity. The diagnostic value of KL-6 was unaffected by medication interference and surpassed the value of other parameters, such as NLR, SII, MLR, and RDW. The diagnostic value of RDW-SD was higher than that of RDW-CV in CTD-ILD patients. NLR, SII, MLR, and PLR have potential value in diagnosing the different types of CTD-ILD.

Developing a nomogram for predicting acute complicated course in pediatric acute hematogenous osteomyelitis

BACKGROUND

The objective of this study was to develop and validate a nomogram for predicting the risk of an acute complicated course in pediatric patients with Acute Hematogenous Osteomyelitis (AHO).

METHODS

A predictive model was developed based on a dataset of 82 pediatric AHO patients. Clinical data, imaging findings, and laboratory results were systematically collected for all patients. Subsequently, biomarker indices were calculated based on the laboratory results to facilitate a comprehensive evaluation. Univariate and multivariate logistic regression analyses were conducted to identify factors influencing early adverse outcomes in AHO. A nomogram model was constructed based on independent factors and validated internally through bootstrap methods. The discriminative ability, calibration, and clinical utility of the nomogram model were assessed using receiver operating characteristic (ROC) curves, calibration plots, and decision curve analysis (DCA), respectively. The developed nomogram model was compared with previously published A-score and Gouveia scoring systems.

RESULTS

Logistic regression analysis identified delayed source control, suppurative arthritis, albumin on admission, and platelet to lymphocyte ratio (PLR) as independent predictors of early adverse outcomes in pediatric AHO patients. The logistic regression model was formulated as: Log(P) = 7. 667-1.752 × delayed source control - 1.956 × suppurative arthritis - 0.154 × albumin on admission + 0.009 × PLR. The nomogram's AUC obtained through Bootstrap validation was 0.829 (95% CI: 0.740-0.918). Calibration plots showed good agreement between predictions and observations. Decision curve analysis demonstrated that the model achieved net benefits across all threshold probabilities. The predictive efficacy of our nomogram model for acute complicated course in pediatric AHO patients surpassed that of the A-score and Gouveia scores.

CONCLUSIONS

A predictive model for the acute complicated course of pediatric AHO was established based on four variables: delayed source control, suppurative arthritis, albumin on admission, and PLR. This model is practical, easy to use for clinicians, and can aid in guiding clinical treatment decisions.

Associations of ω-3, ω-6 polyunsaturated fatty acids intake and ω-6: ω-3 ratio with systemic immune and inflammatory biomarkers: NHANES 1999-2020

Background

In recent years, diseases caused by abnormal immune-inflammatory responses have become increasingly severe. Dietary intervention involving omega-3 polyunsaturated fatty acids (ω-3 PUFAs) has emerged as a potential treatment. However, research investigating the relationship between ω-3, ω-6 PUFAs, and ω-6 to ω-3 ratio with inflammatory biomarkers remains controversial.

Methods

To investigate the correlation between the intake of ω-3 and ω-6 PUFAs and the ratio of ω-6: ω-3 with biomarkers of inflammation, the National Health and Nutrition Examination Survey (NHANES) data (1999 to 2020) was utilized. The systemic immune-inflammation index (SII), platelet-lymphocyte ratio (PLR), neutrophil-lymphocyte ratio (NLR), and white blood cell (WBC) were selected as study subjects. Dietary data for ω-3 and ω-6 PUFAs were collected via two 24-h dietary recall interviews. SII index and other indicators were obtained from the blood routine data. The multiple linear regression and restricted cubic spline models were utilized to evaluate the association of ω-3, ω-6 PUFAs intake, and ω-6: ω-3 ratio to SII and secondary measures.

Results

This study involved a total of 43,155 American adults. ω-3 and ω-6 PUFAs exhibited negative correlations with SII, PLR, NLR, and WBC. The correlation between ω-6: ω-3 ratio and SII, PLR, NLR, and WBC was not significant. Furthermore, the dose-response relationship showed that the relationship between the intake of ω-3 and ω-6 PUFAs and SII was an "L" pattern.

Conclusion

Intake of dietary ω-3 and ω-6 PUFAs reduces the levels of several inflammatory biomarkers in the body and exerts immunomodulatory effects.

Neutrophil, lymphocyte count, and neutrophil to lymphocyte ratio predict multimorbidity and mortality-results from the Baltimore Longitudinal Study on Aging follow-up study

Immunosenescence is the age-related changes in the immune system, namely, progressively higher levels of circulating inflammatory markers, characteristics changes of circulating immune subset cells and altered immune function. The neutrophil to lymphocyte ratio (NL ratio) has been identified as a prognostic indicator for neoplastic disease progression, in predicting chronic degenerative diseases, and as a potential indirect marker of healthy aging. This study aims to examine the longitudinal association of neutrophil, lymphocyte absolute count, and their ratio with longitudinal risk for multimorbidity and mortality. The Baltimore Longitudinal Study of Aging (BLSA) is an open observational cohort study of community-dwelling volunteers that are followed every 1-4 years depending on their age. The sample considered in the study consists of 1769 participants (5090 follow-ups) with completed data for physical examination, health history assessment, and donated a blood sample. The NL ratio increased with age and was associated with a higher risk of mortality, while a lower NL ratio was inversely correlated with multimorbidity. Neutrophils increased with aging and an increase in their absolute number predicted mortality risk. However, the absolute number of lymphocytes was associated with age only in a cross-sectional analysis. In conclusion, this study supports the importance of the NL ratio and absolute neutrophil count as markers of aging health status, and as significant predictors of all-cause mortality and multimorbidity in aging individuals. It remains to be demonstrated whether interventions contrasting these trends in circulating cells may result in improved health outcomes.

Prognostic Significance of NLR and PLR in COVID-19: A Multi-Cohort Validation Study

INTRODUCTION

Recent studies have highlighted the prognostic value of easily accessible inflammatory markers, neutrophil-to-lymphocyte ratio (NLR), and platelet-to-lymphocyte ratio (PLR) for predicting severe outcomes in patients affected by Coronavirus disease 2019 (COVID-19). Our study validates NLR and PLR cut-off values from a prior cohort at IRCCS Policlinico San Matteo (OSM) of Pavia, Italy, across two new cohorts from different hospitals. This aims to enhance the generalizability of these prognostic indicators.

METHODS

In this retrospective cohort study, conducted at Milan's Ospedale Luigi Sacco (OLS) and IRCCS Ospedale Maggiore Policlinico (OMP) hospitals, we assess the predictive capacity of NLR and PLR for three main outcomes-non-invasive ventilation (NIV) or continuous positive airway pressure (CPAP) usage, invasive ventilation (IV), and death-in patients with COVID-19 at admission. For each outcome, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were computed separately for male and female cohorts. Distinct NLR and PLR cut-off values were used for men (7.00, 7.29, 7.00 for NLR; 239.22, 248.00, 250.39 for PLR) and women (6.36, 7.00, 6.28 for NLR; 233.00, 246.45, 241.54 for PLR), retrieved from the first cohort at OSM.

RESULTS

A total of 3599 patients were included in our study, 1842 from OLS and 1757 from OMP. OLS and OMP sensitivity values for both NLR and PLR (NLR: 24-67%, PLR: 40-64%) were inferior to specificity values (NLR: 64-76%, PLR: 55-72%). Additionally, PPVs generally remained lower (< 63%), while NPVs consistently surpassed 68% for PLR and 72% for NLR. Finally, both PLR and NLR exhibited consistently higher NPVs for more severe outcomes (> 82%) compared to NPVs for CPAP/NIV.

CONCLUSIONS

Consistent findings across diverse patient populations validate the reliability and applicability of NLR and PLR cut-off values. High NPVs emphasize their role in identifying individuals less likely to experience severe outcomes. These markers not only aid in risk stratification but also guide resource allocation in emergencies or limited-resource situations.

Explainable artificial intelligence approaches for COVID-19 prognosis prediction using clinical markers

The COVID-19 influenza emerged and proved to be fatal, causing millions of deaths worldwide. Vaccines were eventually discovered, effectively preventing the severe symptoms caused by the disease. However, some of the population (elderly and patients with comorbidities) are still vulnerable to severe symptoms such as breathlessness and chest pain. Identifying these patients in advance is imperative to prevent a bad prognosis. Hence, machine learning and deep learning algorithms have been used for early COVID-19 severity prediction using clinical and laboratory markers. The COVID-19 data was collected from two Manipal hospitals after obtaining ethical clearance. Multiple nature-inspired feature selection algorithms are used to choose the most crucial markers. A maximum testing accuracy of 95% was achieved by the classifiers. The predictions obtained by the classifiers have been demystified using five explainable artificial intelligence techniques (XAI). According to XAI, the most important markers are c-reactive protein, basophils, lymphocytes, albumin, D-Dimer and neutrophils. The models could be deployed in various healthcare facilities to predict COVID-19 severity in advance so that appropriate treatments could be provided to mitigate a severe prognosis. The computer aided diagnostic method can also aid the healthcare professionals and ease the burden on already suffering healthcare infrastructure.

Temporal trends, sex differences, and age-related disease influence in Neutrophil, Lymphocyte count and Neutrophil to Lymphocyte-ratio: results from InCHIANTI follow-up study

BACKGROUND

Neutrophils and lymphocytes represent the larger percentage of all white blood cells, they vary with age, with a progressive increase of the ratio in the first years of life, and then tend to remain at similar levels in steady state condition during adult age. Neutrophils to lymphocytes-ratio (NL-ratio) was proposed as an effective and low-cost marker to monitor and predict the evolution of several clinical conditions. The main objective of the study is to analyze its temporal trend variation, over twenty years' follow-up, according to age, sex, and main clinical diagnosis, in a large representative Italian population.

METHODS

The InCHIANTI study enrolled representative samples from the registry list of two towns in Tuscany, Italy. Baseline data were collected in 1998, and last follow-up visits were made in 2015-18. 1343 out of the 1453 participants enrolled were included, and consented to donate a blood sample. All subjects were assessed and followed for life-style, clinical condition, physical performance, and underwent an instrumental diagnostic session.

RESULTS

The NL-ratio showed a statistically significant interaction between birth-cohort and time of the study (p-value = 0.005). A gender dimorphism was recognized in the neutrophils absolute count and in the NL-ratio. Moreover, in female participants only, those who reported CHF had lower neutrophil-count and NL-ratio; whereas an increase in creatinine clearance was directly associated with NL-ratio. In male subjects, an increase of BMI was inversely associated with both NL-ratio and neutrophils-count during the follow-up; a similar association but in the opposite direction was observed in female participants.

CONCLUSION

NL-ratio is a more reliable predictor of healthy aging than absolute lymphocytes and/or neutrophils counts. It is associated with the changes induced by disease, lifestyle, and environmental challenges in the immune system. NL-ratio confirms the gender dimorphism in the occurrence of inflammation-driven diseases, thus providing additional evidence for the necessity of tailored sex-specific measures to prevent and treat such diseases.

Temporal trends, sex differences, and age-related disease influence in Neutrophil, Lymphocyte count and Neutrophil to Lymphocyte-ratio. Results from InCHIANTI follow-up study

Background Neutrophils and lymphocytes represent the larger percentage of all white bloodcells, they vary with age, with a progressive increase of the ratio in the first years of life, and then tend to remain at similar levels in steady state condition during adult age. Neutrophils to lymphocytes-ratio (NL-ratio) was proposed as an effective and low-cost marker to monitor and predict the evolution of severalclinical conditions. The main objective of the study is to analyze its temporal trend variation, over twenty years' follow-up, according to age, sex, and main clinical diagnosis, in a large representative Italian population. Methods The InCHIANTI study enrolled representative samples from the registry list of two towns in Tuscany, Italy. Baseline data were collected in 1998, and last follow-up visits were made in 2015-18. 1343 out of the 1453 participants enrolled were included, and consented to donate a blood sample. All subjects were assessed and followed for life-style, clinical condition, physical performance, and underwent an instrumental diagnostic session. Results The NL-ratio showed a statistically significant interaction between birth-cohort and time of the study (p-value=0.005). A gender dimorphism was recognized in the neutrophils absolute count and in the NL-ratio. Moreover, in female participants only, those who reported CHF had lower neutrophil-count and NL-ratio; whereas an increase in creatinine clearance was directly associated with NL-ratio. In male subjects, an increase of BMI was inversely associated with both NL-ratio and neutrophils-count during the follow-up; a similar association but in the opposite direction was observed in female participants. Conclusion NL-ratio is a more reliable predictor of healthy aging than absolute lymphocytes and/or neutrophils counts. It is associated with the changes induced by disease, lifestyle, and environmental challenges in the immune system. NL-ratio confirms the gender dimorphism in the occurrence of inflammation-driven diseases, thus providing additional evidence for the necessity of tailored sex-specific measures to prevent and treat such diseases.