Association Between Neutrophil-Lymphocyte Ratio and Gestational Diabetes-A Systematic Review and Meta-Analysis

Follow-up study to explore the relationship between Neutrophil to lymphocyte ratio and impaired fasting glucose-using the group-based trajectory modeling

Previous studies have indicated a link between neutrophil to lymphocyte ratio (NLR) and impaired fasting glucose (IFG), but the findings have been disputed. By conducting a real-world follow-up study, we can monitor the development of diseases and confirm the connection between NLR and IFG. A total of 1168 patients without IFG or T2DM were followed up for six years. At baseline, participants' NLR levels, fasting plasma glucose and other clinical characteristics were recorded. During the follow-up period, NLR levels and the prevalence of IFG were recorded. Ultimately, 45 individuals were lost to follow-up, leaving 1,123 participants for analysis. Using Group-Based Trajectory Modeling (GBTM), the sample was divided into three groups. The prevalence of IFG in the three groups was 12.1%, 19.4%, and 20.85%, respectively. Compared with the low-level NLR group, the hazard ratio of IFG in the moderate-level NLR group and high-level NLR group were 1.628 (1.109-2.390) and 1.575 (1.001-2.497), respectively. There was a significant interaction effect of BMI and NLR on the risk of IFG (P < 0.001). In this real-world follow-up study, we observed a positive association between NLR and the risk of IFG, with this relationship being exacerbated by obesity status.

Can System Inflammation Response Index or Systemic Immune Inflammation Index predict gestational diabetes mellitus in the first trimester? A prospective observational study

OBJECTIVE

To evaluate System Inflammation Response Index (SIRI) and Systemic Immune Inflammation Index (SII), which are the inflammatory indices, for the prediction of gestational diabetes mellitus (GDM) in the first trimester.

METHODS

This was a prospective observational study conducted in a tertiary center from April 2023 to September 2023. Ninety-four pregnant women with gestational diabetes and 107 healthy pregnant women were included. The two groups were compared according to first-trimester SIRI and SII values. A receiver operating characteristic (ROC) curve analysis was performed to determine the optimal cut-off levels of SII and SIRI in predicting GDM.

RESULTS

Significantly higher first-trimester SII and SIRI values were present in the gestational diabetes group (P < 0.001). Optimal cut-off values in the prediction of gestational diabetes were found to be 1.58 (area under the curve [AUC] 0.71, 67% sensitivity, 65% specificity, 95% confidence interval [CI] 0.64-0.78, P < 0.001) and 875 (AUC 0.70, 66% sensitivity, 65% specificity, 95% CI 0.63-0.77, P < 0.001) for SIRI and SII, respectively. Neutrophil counts, mean platelet volume (MPW), neutrophil to lymphocyte ratio (NLR), and red cell distribution width (RDW) were significantly higher in the GDM group (P < 0.001, P = 0.02, P = 0.01, P < 0.01, respectively).

CONCLUSION

Novel inflammatory indices SII and SIRI may be useful in the prediction of GDM in the first trimester, but their utility in the prediction of insulin requirement is questionable. They may be used as additional tools in routine clinical practice.

Postpartum Depression and Inflammatory Biomarkers of Neutrophil-Lymphocyte Ratio, Platelet-Lymphocyte Ratio, and Monocyte-Lymphocyte Ratio: A Prospective Observational Study

OBJECTIVES

Postpartum depression (PPD) is a severe mental health disorder affecting a significant proportion of mothers, often undiagnosed and untreated, with potential long-term effects. While numerous studies have identified risk factors for PPD, the relationship between inflammatory markers and PPD remains unknown. This study aimed to investigate the potential correlation between indirect inflammatory markers, specifically neutrophil-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and monocyte-lymphocyte ratio (MLR), and the risk of developing PPD, assessed by the Edinburgh Postnatal Depression Scale (EPDS).

DESIGN

This was a prospective observational study conducted in a second-level university hospital, from December 2019 to February 2021.

PARTICIPANTS

A total of 211 full-term pregnant women were enrolled. Exclusion criteria included specific psychiatric diagnoses, such as severe intellectual disability, schizophrenia, schizoaffective disorder, delusional disorder, bipolar or other unspecified psychotic spectrum disorders. Additionally, pregnancies affected by gestational and pregestational diabetes, chronic hypertension, gestational hypertension, preeclampsia/eclampsia, intrauterine fetal growth restriction, preterm delivery, multiple pregnancies, and fetal abnormalities detected prenatally were excluded.

METHODS

Socio-demographic and clinical data were recorded. Blood samples for complete blood count were obtained at hospital admission, focusing on NLR, PLR, and MLR. Analyses were conducted in our laboratory using standard techniques. The postpartum PPD evaluation was conducted 3 days after delivery, with the EPDS Italian version. Statistical analyses included descriptive statistics, group comparisons using t tests or Wilcoxon rank-sum tests for continuous variables, and Pearson χ2 or Fisher's exact tests for categorical variables. Correlation analyses employed Pearson correlation or Spearman's rank correlation tests. Simple logistic regression models, adjusted for various baseline patient characteristics, explored the correlation between inflammatory markers (PLR, NLR, MLR) and postpartum depressive symptoms. Version 4.1.3 of RStudio statistical software was utilized.

RESULTS

Overall, 211 pregnant women enrolled were categorized into two groups based on the EPDS scores: <10 (176 patients) and ≥10 (35 patients). The two groups demonstrated homogeneity in different socio-demographic factors. Stepwise regression analysis indicated that PLR, NLR, and MLR were not significantly associated with these variables. The scatterplot of PLR, NLR, and MLR on EPDS was stratified for EPDS groups. The Wilcoxon rank-sum test applied to PLR, NLR, and MLR values and EPDS groups did not reveal a statistical relationship. Additional analyses were conducted using the estimated odds ratios of the logistic regression model on EPDS groups, considering both continuous and binary values of indirect inflammatory markers (PLR, NLR, MLR). The results indicated the absence of a statistical relationship.

LIMITATIONS

Our evaluation was restricted to the postpartum period, and data for the first and second trimesters of pregnancy are lacking.

CONCLUSIONS

Our findings did not evidence a correlation between indirect inflammatory markers (NLR, PLR, and MPL) and PPD. This novel finding prompts further evaluation of the role of indirect inflammatory markers in PPD, highlighting the need for additional research to clarify the complex relationship between inflammation and psychological health in the postpartum period.

Predicting Potentially Fatal COVID-19 Disease in Pregnant Patients Using the Neutrophil-to-Lymphocyte Ratio (NLR)

OBJECTIVE

To evaluate the neutrophil-to-lymphocyte ratio (NLR) values' possible predictive role in fatal and severe cases of COVID-19 disease in pregnant women. Design and data collection: A case-control study was conducted with the inclusion of 45 pregnant COVID-19 patients. All the data were obtained from the hospital information system of Semmelweis University by two of the authors.

RESULTS

Statistical analyses showed that NLR values were significantly higher in patients with fatal COVID-19 compared to those who survived the disease, with or without mechanical ventilation. The study also assessed whether NLR values measured on the first day of hospitalization or at their peak provided better markers of disease severity. While both the first-day and peak NLR values were evaluated in patients who did not survive the disease, only the peak NLR values had predictive value regarding patient death.

CONCLUSION

Based on our results, the peak NLR values appear to be useful markers of COVID-19 severity, with a cut-off value of 18.05. However, the authors suggest and hope that larger sample size studies will be conducted to further validate the findings of their research.

Integration of clinical demographics and routine laboratory analysis parameters for early prediction of gestational diabetes mellitus in the Chinese population

Gestational diabetes mellitus (GDM) is one of the most common complications in pregnancy, impairing both maternal and fetal health in short and long term. As early interventions are considered desirable to prevent GDM, this study aims to develop a simple-to-use nomogram based on multiple common risk factors from electronic medical health records (EMHRs). A total of 924 pregnant women whose EMHRs were available at Peking University International Hospital from January 2022 to October 2022 were included. Clinical demographics and routine laboratory analysis parameters at 8-12 weeks of gestation were collected. A novel nomogram was established based on the outcomes of multivariate logistic regression. The nomogram demonstrated powerful discrimination (the area under the receiver operating characteristic curve = 0.7542), acceptable agreement (Hosmer-Lemeshow test, P = 0.3214) and favorable clinical utility. The C-statistics of 10-Fold cross validation, Leave one out cross validation and Bootstrap were 0.7411, 0.7357 and 0.7318, respectively, indicating the stability of the nomogram. A novel nomogram based on easily-accessible parameters was developed to predict GDM in early pregnancy, which may provide a paradigm for repurposing clinical data and benefit the clinical management of GDM. There is a need for prospective multi-center studies to validate the nomogram before employing the nomogram in real-world clinical practice.

The Association between Neutrophil-to-Lymphocyte Ratio and Glycemic Control in Type 2 Diabetes Mellitus: A Systematic Review and Meta-Analysis

Background

Glycated hemoglobin (HbA1c) is a commonly used clinical marker to monitor the control of type 2 diabetes mellitus patients (T2DM). However, it is unable to identify the ongoing inflammatory changes in the body. These factors could be easily identified and monitored by the neutrophil-to-lymphocyte ratio (NLR). Therefore, this study is aimed at investigating the relationship between NLR and glycemic control in T2DM.

Method

A comprehensive search of eligible studies was performed in various databases published until July 2021. A random effect model was used to estimate the standardized mean difference (SMD). A metaregression, subgroup, and sensitivity analysis were conducted to search for potential sources of heterogeneity.

Result

A total of 13 studies were included in this study. Accordingly, the SMD of the NLR values between the poor and good glycemic control groups was 0.79 (95% CI, 0.46-1.12). Our study also showed that high NLR was significantly associated with poor glycemic control in T2DM patients (OR = 1.50, 95% CI: 1.30-1.93).

Conclusion

The results of this study suggest an association between high NLR values and an elevated HbA1C in T2DM patients. Therefore, NLR should be considered a marker of glycemic control in addition to HbA1c in T2DM patients.

Low-Grade Inflammation in Gestational Diabetes Mellitus and Its Correlation with Maternal Insulin Resistance and Fetal Growth Indices

Introduction

Chronic low-grade inflammation (LGI) plays a role in the pathogenesis of gestational diabetes mellitus (GDM). LGI, on the one hand, promotes insulin resistance and at the same time, affects fetal development. The study aimed to use clinically feasible means to evaluate the association between maternal LGI and maternal insulin resistance and fetal growth indices by ultrasound in the third trimester.

Methods

A crossectional and descriptive study on 248 first-time diagnosed GDM in Vietnam.

Results

Neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte (PLR) indices were significantly higher in GDM than in normal glucose-tolerant pregnancies (p = 0.048 and 0.016, respectively). GDM with LGI witnessed significantly higher systolic blood pressure, BMI, HbA1c, and significantly lower quantitative Insulin Sensitivity Check Index (QUICKI) than those without LGI. After adjusting for maternal BMI, fasting plasma glucose (FPG), age, and parity, C-reactive protein (CRP) was positively correlated with HOMA2-IR (B=0.13, p<0.01) and Mathews index (B=0.29, p<0.01). Regarding fetal characteristics, LGI was associated with fetal growth indices in the third trimester of GDM. NLR was negatively correlated with estimated fetal weight (EFW) (B=-64.4, p<0.05) after adjusting for maternal BMI and FPG. After adjusting for maternal BMI, FPG, age, and parity, PLR was negatively correlated with biparietal diameter (B=-0.02, p<0.01) and abdominal circumference (AC) (B=-0.16, p<0.05), and EFW (B=-1.1, p<0.01), and head circumference (HC) (B=-0.06, p<0.01); CRP was negatively correlated with AC (B=-0.16, p<0.001), EFW (B=-85.3, p<0.001), and HC (B=-5.0, p<0.001).

Conclusion

In the third trimester, LGI was associated with maternal glucose and insulin resistance in GDM. Moreover, LGI was associated with fetal characteristics in ultrasonic images. There were negative correlations between LGI and fetal developmental characteristics.

Influence of Co-morbidities During SARS-CoV-2 Infection in an Indian Population

Background

Since the outbreak of COVID-19 pandemic the interindividual variability in the course of the disease has been reported, indicating a wide range of factors influencing it. Factors which were the most often associated with increased COVID-19 severity include higher age, obesity and diabetes. The influence of cytokine storm is complex, reflecting the complexity of the immunological processes triggered by SARS-CoV-2 infection. A modern challenge such as a worldwide pandemic requires modern solutions, which in this case is harnessing the machine learning for the purpose of analysing the differences in the clinical properties of the populations affected by the disease, followed by grading its significance, consequently leading to creation of tool applicable for assessing the individual risk of SARS-CoV-2 infection.

Methods

Biochemical and morphological parameters values of 5,000 patients (Curisin Healthcare (India) were gathered and used for calculation of eGFR, SII index and N/L ratio. Spearman's rank correlation coefficient formula was used for assessment of correlations between each of the features in the population and the presence of the SARS-CoV-2 infection. Feature importance was evaluated by fitting a Random Forest machine learning model to the data and examining their predictive value. Its accuracy was measured as the F1 Score.

Results

The parameters which showed the highest correlation coefficient were age, random serum glucose, serum urea, gender and serum cholesterol, whereas the highest inverse correlation coefficient was assessed for alanine transaminase, red blood cells count and serum creatinine. The accuracy of created model for differentiating positive from negative SARS-CoV-2 cases was 97%. Features of highest importance were age, alanine transaminase, random serum glucose and red blood cells count.

Conclusion

The current analysis indicates a number of parameters available for a routine screening in clinical setting. It also presents a tool created on the basis of these parameters, useful for assessing the individual risk of developing COVID-19 in patients. The limitation of the study is the demographic specificity of the studied population, which might restrict its general applicability.

Association Between Neutrophil-Lymphocyte Ratio and Gestational Diabetes-A Systematic Review and Meta-Analysis

A growing body of evidence shows that the neutrophil-lymphocyte ratio (NLR) is a surrogate index of systemic inflammation in several chronic diseases. Conflicting associations between NLR and gestational diabetes mellitus (GDM) have been reported in individual studies. This meta-analysis sought to investigate the association between NLR and GDM. The PubMed, EMBASE, and Google Scholar databases were searched to identify relevant articles. The pooled standardized mean difference with 95% CI was calculated using a random-effects model. Subgroup and meta-regression analysis were carried out to control for the effects of GDM diagnostic criteria, ethnicity, body mass index (BMI), and age. Eleven eligible articles were included, containing 1271 participants with GDM and 1504 controls. Pooled outcomes indicated a higher NLR in GDM pregnancies than in normoglycemic controls (SMD = 0.584; 95% CI, 0.339–0.830; P < .001), although extensive heterogeneity between studies was noted. Subgroup analysis revealed that the higher pooled estimate in GDM was not affected by diagnostic criteria, ethnicity, or BMI, although matching for BMI reduced heterogeneity between studies. This meta-analysis supports the higher NLR in GDM described by some individual studies.