The clinical value of neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio, and D-dimer-to-fibrinogen ratio for predicting pneumonia and poor outcomes in patients with acute intracerebral hemorrhage

Complete blood count-based inflammation indexes and symptom severity in people with schizophrenia spectrum disorders: An analysis based on structural equation modelling

INTRODUCTION

Schizophrenia spectrum disorders (SSDs) are associated with immune-inflammatory activation. Recently, complete blood count (CBC)-based inflammation indexes such as the neutrophil-to-lymphocyte ratio (NLR), the monocyte-to-lymphocyte ratio (MLR), and the platelet-to-lymphocyte ratio (PLR) have emerged as reproducible and cost-effective inflammation markers in mental disorders. In this study, we aimed at investigating the relationship of NLR, MLR, and PLR with symptom severity in people with SSDs, testing interactions with relevant clinical variables.

METHODS

We included inpatients with SSDs aged 18-65 consecutively hospitalized from May 2020 to March 2024. Socio-demographic and clinical data were recorded. CBC-based ratios were estimated from routinely collected blood samples. Structural equation modelling (SEM) was performed to test relationships involving symptom severity constructs and CBC-based ratios, accounting for substance use disorder, antipsychotic treatment, and obesity.

RESULTS

Two hundred sixty-six participants met inclusion criteria. The SEM analysis uncovered a significant relationship of MLR with positive (coeff.: 0.19, p=0.048) and negative (coeff.: 0.27, p=0.004) symptoms, also showing a significant link of substance use disorder and antipsychotic treatment with symptom severity as well as of antipsychotic treatment with obesity.

CONCLUSIONS

Notwithstanding the cross-sectional design and the somewhat limited sample representativeness, this study showed a significant relationship between the MLR - but not the NLR or the PLR - and the severity of both positive and negative symptoms, testing at the same time the interactions with other clinical variables. Considering the insufficiency and inconsistency of data in this field, further research is needed to validate our findings and elucidate the underlying mechanisms driving the observed relationships between the MLR and SSD symptoms.

Association between fibrinogen levels and stroke-associated pneumonia in acute ischemic stroke patients

PURPOSE

Prior research had indicated a relationship between fibrinogen and stroke-associated pneumonia (SAP), yet the nature of this relationship had not been thoroughly investigated. Therefore, this study was designed to elucidate the prognostic value of fibrinogen levels in forecasting the occurrence of SAP among patients with acute ischemic stroke (AIS).

PATIENTS AND METHODS

In this retrospective cross-sectional analysis, we included 1092 patients who had experienced AIS and were admitted to our facility within 72 h of the onset of their symptoms. Based on the SAP diagnostic criteria, patients were classified into two groups: SAP and non-SAP. The correlation between serum fibrinogen concentration and SAP was examined using univariate analysis. Curve fitting and multivariable logistic regression model were utilized for statistical evaluation.

RESULTS

Out of the ischemic stroke patients included in the study, SAP was identified in 112 (10.26%) patients. A direct correlation was observed between fibrinogen levels and the incidence of SAP. An increase in fibrinogen levels corresponded with a heightened incidence of SAP. Multivariable logistic regression revealed a significant positive association between fibrinogen levels and SAP incidence (OR = 1.53, 95% confidence interval [CI]: 1.18, 1.99)).

CONCLUSION

A linear relationship between serum fibrinogen levels and the incidence of SAP in ischemic stroke patients was shown. The serum fibrinogen levels were positively and linearly correlated to SAP risk.

A Novel Machine Learning Model for Predicting Stroke-Associated Pneumonia After Spontaneous Intracerebral Hemorrhage

BACKGROUND

Pneumonia is one of the most common complications after spontaneous intracerebral hemorrhage (sICH), i.e., stroke-associated pneumonia (SAP). Timely identification of targeted patients is beneficial to reduce poor prognosis. So far, there is no consensus on SAP prediction, and application of existing predictors is limited. The aim of this study was to develop a machine learning model to predict SAP after sICH.

METHODS

We retrospectively reviewed 748 patients diagnosed with sICH and collected data from 4 dimensions-demographic features, clinical features, medical history, and laboratory tests. Five machine learning algorithms-logistic regression, gradient boosting decision tree, random forest, extreme gradient boosting, and category boosting-were used to build and validate the predictive model. We also applied recursive feature elimination with cross-validation to obtain the best feature combination for each model. Predictive performance was evaluated by area under the receiver operating characteristic curve.

RESULTS

SAP was diagnosed in 237 patients. The model developed by category boosting yielded the most satisfactory outcomes overall with area under the receiver operating characteristic curves in the training set and test set of 0.8307 and 0.8178, respectively.

CONCLUSIONS

The incidence of SAP after sICH in our center was 31.68%. Machine learning could potentially provide assistance in the prediction of SAP after sICH.

Neutrophil-to-Lymphocyte Ratio (NLR), Platelet-to-Lymphocyte Ratio (PLR) and Monocyte-to-Lymphocyte Ratio (MLR) as Biomarkers in Diagnosis Evaluation of Acute Exacerbation of Chronic Obstructive Pulmonary Disease: A Retrospective, Observational Study

Purpose

Hierarchical management is advocated in China to effectively manage chronic obstructive pulmonary disease (COPD) patients and reduce the incidence and mortality of acute exacerbation of COPD (AE-COPD). However, primary and community hospitals often have limited access to advanced equipment and technology. Complete blood count (CBC), which is commonly used in these hospitals, offers the advantages of being cost-effective and easily accessible. This study aims to evaluate the significance of routine blood indicators in aiding of diagnosing AE-COPD.

Patients and Methods

In this research, we enrolled a total of 112 patients diagnosed with AE-COPD, 92 patients with stable COPD, and a control group comprising 60 healthy individuals. Clinical characteristics, CBC parameters, and serum CRP levels were collected within two hours. To assess the associations between NLR/PLR/MLR and CRP by Spearman correlation test. The diagnostic accuracy of NLR, PLR and MLR in AE-COPD was assessed using Receiver Operating Characteristic Curve (ROC) and the area under the curve (AUC). Binary Logistic Regression analysis was conducted for the indicators of NLR, PLR and MLR.

Results

We found that patients with AE-COPD had significantly higher levels of NLR, PLR and MLR in contrast to patients with stable COPD. Additionally, the study revealed a noteworthy correlation between CRP and NLR (rs=0.5319, P<0.001), PLR (rs=0.4424, P<0.001), and MLR (rs=0.4628, P<0.001). By utilizing specific cut-off values, the amalgamation of NLR, PLR and MLR augmented diagnostic sensitivity. Binary logistic regression analysis demonstrated that heightened NLR and MLR act as risk factors for the progression of AE-COPD.

Conclusion

The increasing levels of NLR, PLR and MLR could function as biomarkers, akin to CRP, for diagnosis and assessment of acute exacerbations among COPD patients. Further research is required to validate this concept.

Systemic inflammatory biomarkers in Schizophrenia are changed by ECT administration and related to the treatment efficacy

Immune inflammation has long been implicated in the pathogenesis of schizophrenia. Despite as a rapid and effective physical therapy, the role of immune inflammation in electroconvulsive therapy (ECT) for schizophrenia remains elusive. The neutrophils to lymphocytes (NLR), platelets to monocytes (PLR) and monocytes to lymphocytes (MLR) are inexpensive and accessible biomarkers of systemic inflammation. In this study, 70 schizophrenia patients and 70 age- and sex-matched healthy controls were recruited. The systemic inflammatory biomarkers were measured before and after ECT. Our results indicated schizophrenia had significantly higher peripheral NLR, PLR and MLR compared to health controls at baseline, while lymphocytes did not differ. After 6 ECT, the psychiatric symptoms were significantly improved, as demonstrated by the Positive and Negative Syndrome Scale (PANSS). However, there was a decline in cognitive function scores, as indicated by the Mini-Mental State Examination (MMSE). Notably, the neutrophils and NLR were significantly reduced following ECT. Although lymphocytes remained unchanged following ECT, responders had significantly higher lymphocytes compared to non-responders. Moreover, the linear regression analyses revealed that higher lymphocytes served as a predictor of larger improvement in positive symptom following ECT. Overall, our findings further highlighted the presence of systemic inflammation in schizophrenia patients, and that ECT may exert a therapeutic effect in part by attenuating systemic inflammation. Further research may therefore lead to new treatment strategies for schizophrenia targeting the immune system.

Neutrophil-to-lymphocyte ratio, white blood cell, and C-reactive protein predicts poor outcome and increased mortality in intracerebral hemorrhage patients: a meta-analysis

Objective

Inflammation participates in the pathology and progression of secondary brain injury after intracerebral hemorrhage (ICH). This meta-analysis intended to explore the prognostic role of inflammatory indexes, including neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), white blood cell (WBC), and C-reactive protein (CRP) in ICH patients.

Methods

Embase, PubMed, Web of Science, and Cochrane Library were searched until June 2023. Two outcomes, including poor outcome and mortality were extracted and measured. Odds ratio (OR) and 95% confidence interval (CI) were presented for outcome assessment.

Results

Forty-six studies with 25,928 patients were included in this meta-analysis. The high level of NLR [OR (95% CI): 1.20 (1.13-1.27), p < 0.001], WBC [OR (95% CI): 1.11 (1.02-1.21), p = 0.013], and CRP [OR (95% CI): 1.29 (1.08-1.54), p = 0.005] were related to poor outcome in ICH patients. Additionally, the high level of NLR [OR (95% CI): 1.06 (1.02-1.10), p = 0.001], WBC [OR (95% CI): 1.39 (1.16-1.66), p < 0.001], and CRP [OR (95% CI): 1.02 (1.01-1.04), p = 0.009] were correlated with increased mortality in ICH patients. Nevertheless, PLR was not associated with poor outcome [OR (95% CI): 1.00 (0.99-1.01), p = 0.749] or mortality [OR (95% CI): 1.00 (0.99-1.01), p = 0.750] in ICH patients. The total score of risk of bias assessed by Newcastle-Ottawa Scale criteria ranged from 7-9, which indicated the low risk of bias in the included studies. Publication bias was low, and stability assessed by sensitivity analysis was good.

Conclusion

This meta-analysis summarizes that the high level of NLR, WBC, and CRP estimates poor outcome and higher mortality in ICH patients.

Association between high serum blood glucose lymphocyte ratio and all-cause mortality in non-traumatic cerebral hemorrhage: a retrospective analysis of the MIMIC-IV database

Background

This study aimed to evaluate the association between the glucose-to-lymphocyte ratio (GLR) and all-cause mortality in intensive care unit (ICU) patients with Non-traumatic cerebral hemorrhage.

Methods

This is a retrospective cohort study. Baseline data and in-hospital prognosis from patients with non-traumatic cerebral hemorrhage admitted to the intensive care unit. Multivariate COX regression analysis was applied and adjusted hazard ratios (HR) and 95% predictive values with confidence intervals (CI) were calculated. Survival curves for the two groups of cases were plotted using K-M curves, and subgroup analyses were performed in one step. Using restricted cubic spline curves, we analyzed the potential linear relationship between GLR and outcome indicators.

Results

In the Medical Information Mart for Intensive Care IV (MIMIC-IV database), we extracted 3,783 patients with nontraumatic intracerebral hemorrhage, and 1,806 patients were finally enrolled in the study after exclusion of missing values and patients with a short hospital stay. The overall ICU mortality rate was 8.2% (148/1806) and the in-hospital mortality rate was 12.5% (225/1806). The use of curve fitting yielded a significant linear relationship between GLR and both ICU mortality and in-hospital mortality. It also suggested a reference point at GLR=3.9. These patients were categorized into high and low subgroups based on the median value of their GLR (GLR = 3.9). Model comparisons based on multivariate COX regression analysis showed that in-hospital mortality was higher in the high GLR group after adjusting for all confounders (HR = 1.31, 95% CI: 1.04-1.47), while the ICU mortality in the high GLR group was (HR = 1.73, 95% CI: 1.18-2.52). Stratified analyses based on age, gender, race, GCS, BMI, and disease type showed stable correlations between the high GLR group and in-hospital and ICU mortality.

Conclusion

Based on our retrospective analysis, it is known that as the GLR increased, the in-hospital mortality rate and ICU mortality rate of patients with nontraumatic cerebral hemorrhage also increased progressively in the United States in a clear linear relationship. However, further studies are needed to confirm these findings.

The trend of neutrophil-to-lymphocyte ratio and platelet-to-lymphocyte ratio in spontaneous intracerebral hemorrhage and the predictive value of short-term postoperative prognosis in patients

Background

Neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) play an important role in the inflammatory response in various diseases, but the role in the course of spontaneous intracerebral hemorrhage (ICH) is unclear.

Methods

This study retrospectively collected baseline characteristics and laboratory findings, including NLR and PLR at different time points, from spontaneous ICH patients undergoing surgery between January 2016 and June 2021. Patients were scored using the modified Rankin Scale (mRS) to evaluate their functional status at 30 days post-operation. Patients with mRS score ≥3 were defined as poor functional status, and mRS score <3 was defined as good functional status. The NLR and PLR were calculated at admission, 48 h after surgery and 3-7 days after surgery, respectively, and their trends were observed by connecting the NLR and PLR at different time points. Multivariate logistic regression analysis was used to identify independent risk factors affecting the prognosis of ICH patients at 30 days after surgery.

Results

A total of 101 patients were included in this study, and 59 patients had a poor outcome at 30 days after surgery. NLR and PLR gradually increased and then decreased, peaking at 48 h after surgery. Univariate analysis demonstrated that admission Glasgow Coma Scale (GCS) score, interval from onset to admission, hematoma location, NLR within 48 h after surgery and PLR within 48 h after surgery were associated with poor 30-day prognosis. In multivariate logistic regression analysis, NLR within 48 h after surgery (OR, 1.147; 95% CI, 1.005, 1.308; P, 0.042) was an independent risk factor for 30-day after surgery prognosis in spontaneous ICH patients.

Conclusion

In the course of spontaneous intracerebral hemorrhage, NLR and PLR initially increased and subsequently decreased, reaching their peak values at 48 h after surgery. High NLR within 48 h after surgery was an independent risk factor for poor prognosis 30 days after surgery in spontaneous ICH patients.

The Clinical Value of Neutrophil-to-Lymphocyte Ratio and Platelet-to-Lymphocyte Ratio for Predicting Hematoma Expansion and Poor Outcomes in Patients with Acute Intracerebral Hemorrhage

There is little knowledge of the effect of inflammatory markers on the prognoses of hematoma expansion (HE) in patients with intracranial hemorrhage (ICH). We evaluated the impact of neutrophil-lymphocyte ratio (NLR) and platelet-lymphocyte ratio (PLR) on HE and worse outcomes after acute ICH. This study included 520 consecutive patients with ICH from the registry database enrolled over 80 months. Patients' whole blood samples were collected upon arrival in the emergency department. Brain computed tomography scans were performed during hospitalization and repeated at 24 h and 72 h. The primary outcome measure was HE, defined as relative growth >33% or absolute growth <6 mL. A total of 520 patients were enrolled in this study. Multivariate analysis showed that NLR and PLR were associated with HE (NLR: odds ratio [OR], [95% CI] = 1.19 [1.12-1.27], p < 0.001; PLR: OR, [95% CI] = 1.01 [1.00-1.02], p = 0.04). Receiver operating characteristic curve analysis revealed that NLR and PLR could predict HE (AUC of NLR: 0.84, 95% CI [0.80-0.88], p < 0.001; AUC of PLR: 0.75 95% CI [0.70-0.80], p < 0.001). The cut-off value of NLR for predicting HE was 5.63, and that of PLR was 23.4. Higher NLR and PLR values increase HE risk in patients with ICH. NLR and PLR were reliable for predicting HE after ICH.

The clinical value of neutrophil-to-lymphocyte ratio (NLR), systemic immune-inflammation index (SII), platelet-to-lymphocyte ratio (PLR) and systemic inflammation response index (SIRI) for predicting the occurrence and severity of pneumonia in patients with intracerebral hemorrhage

Background

Inflammatory mechanisms play important roles in intracerebral hemorrhage (ICH) and have been linked to the development of stroke-associated pneumonia (SAP). The neutrophil-to-lymphocyte ratio (NLR), systemic immune-inflammation index (SII), platelet-to-lymphocyte ratio (PLR) and systemic inflammation response index (SIRI) are inflammatory indexes that influence systemic inflammatory responses after stroke. In this study, we aimed to compare the predictive value of the NLR, SII, SIRI and PLR for SAP in patients with ICH to determine their application potential in the early identification of the severity of pneumonia.

Methods

Patients with ICH in four hospitals were prospectively enrolled. SAP was defined according to the modified Centers for Disease Control and Prevention criteria. Data on the NLR, SII, SIRI and PLR were collected at admission, and the correlation between these factors and the clinical pulmonary infection score (CPIS) was assessed through Spearman's analysis.

Results

A total of 320 patients were enrolled in this study, among whom 126 (39.4%) developed SAP. The results of the receiver operating characteristic (ROC) analysis revealed that the NLR had the best predictive value for SAP (AUC: 0.748, 95% CI: 0.695-0.801), and this outcome remained significant after adjusting for other confounders in multivariable analysis (RR=1.090, 95% CI: 1.029-1.155). Among the four indexes, Spearman's analysis showed that the NLR was the most highly correlated with the CPIS (r=0.537, 95% CI: 0.395-0.654). The NLR could effectively predict ICU admission (AUC: 0.732, 95% CI: 0.671-0.786), and this finding remained significant in the multivariable analysis (RR=1.049, 95% CI: 1.009-1.089, P=0.036). Nomograms were created to predict the probability of SAP occurrence and ICU admission. Furthermore, the NLR could predict a good outcome at discharge (AUC: 0.761, 95% CI: 0.707-0.8147).

Conclusions

Among the four indexes, the NLR was the best predictor for SAP occurrence and a poor outcome at discharge in ICH patients. It can therefore be used for the early identification of severe SAP and to predict ICU admission.