The association of neutrophil to lymphocyte ratio, platelet to lymphocyte ratio, and lymphocyte to monocyte ratio with post-thrombolysis early neurological outcomes in patients with acute ischemic stroke

Serum fibrinogen/albumin ratio and early neurological deterioration in patients with recent small subcortical infarction

BACKGROUND

Serum fibrinogen/albumin ratio (FAR) is a new inflammatory marker related to a variety of diseases, and it has been shown to be associated with stroke. This study is to investigate the relationship between serum FAR and early neurological deterioration (END) in patients with recent small subcortical infarction (RSSI).

PATIENTS AND METHODS

Consecutive RSSI patients admitted to the First Affiliated Hospital of Zhengzhou University from June 2015 to June 2022 were enrolled. The National Institute of Health Stroke Scale (NIHSS) was utilized to evaluate the severity of the patients at admission and within seven days post-admission. END was defined as an increase of ≥2 points in NIHSS score from admission or ≥1 point in the motor item of the score within seven days post-admission. Multivariate logistic regression analysis was employed to identify risk factors for END. The correlation between FAR and END was investigated using restricted cubic spline (RCS) analysis. Subgroup analysis was used to assess stability across different populations.

RESULTS

A total of 766 RSSI patients were included in the analysis, with 538 males (70.24%). END occurred in 115 (15.01%) patients. Multivariate logistic regression analysis revealed that FAR (OR = 1.016, 95%CI: 1.005-1.028), PAD (OR = 1.805, 95%CI: 1.161-2.807) and age (OR = 1.028, 95%CI: 1.009-1.048) were associated with END in RSSI patients. RCS analysis indicated a linear correlation between FAR and END (p for nonlinear = .128). Subgroup analysis indicated association between FAR and END in male (OR = 1.02, 95%CI: 1.00-1.03), patients aged ≤65 years (OR = 1.02, 95%CI: 1.00-1.03) and patients without smoking history (OR = 1.02, 95%CI: 1.00-1.03).

CONCLUSIONS

Elevated FAR levels were associated with the occurrence of END within seven days after admission in RSSI patients, especially in men, age ≤65 years, or patients without smoking history.

"The association between HALP score and infection in acute ischemic stroke patients"

BACKGROUND AND PURPOSE

Stroke-associated infection (SAI) is related to increased mortality in acute ischemic stroke (AIS) cases. The HALP index is used to evaluate nutrition and inflammation. Our research aimed to assess the relation between HALP scores and infection risk in AIS cases.

MATERIALS AND METHODS

132 cases of acute ischemic stroke were registered. 77 cases were male and 55 cases were female. The median age of the attending cases was 66 (35-104) years. Laboratory variables were assessed within 24 h after hospitalization in the neurology care unit. The HALP score is evaluated utilizing the formula "Hemoglobin (g/dL) × Albumin (g/dL) × Lymphocyte (/10^3/uL) / Platelet (/10^3/uL)".

RESULTS

Cases were separated into two groups according to their corresponding HALP score. Group-1 cases have a low HALP score (HALP score ≤ 18227,93). Group-2 cases have a high HALP score (HALP score > 18227,93). 26 (19.6 %) cases were diagnosed with various infections after hospitalization in the neurology care unit. Urinary tract infections were frequent infection causes in AIS cases (13 cases, 50 %). Pneumonia was observed in 8 cases, making up 30 % of the total cases. Another infection was seen in 5 (20 %) of the cases. The frequently encountered bacteria were Escherichia coli ESBL + (n = 7, 27 %) and Staphylococcus aureus (n = 6, 23 %). The mortality ratio was higher in Group-1 cases than in Group-2 cases (34 % vs 7 %).

CONCLUSIONS

This investigation has suggested a relationship between infection and HALP score in AIS patients.

Application value of neutrophil to lymphocyte ratio and platelet to lymphocyte ratio in predicting stress ulcer after acute cerebral hemorrhage surgery

OBJECTIVE

The Platelet-to-Lymphocyte Ratio (PLR) and Neutrophil-to-Lymphocyte Ratio (NLR) are established biomarkers that are associated with the severity, progression, and fatality of diseases. This study aimed to determine their predictive value for the occurrence of stress ulcers (SU) following surgery for acute cerebral hemorrhage.

METHODS

Retrospective data from 210 patients with acute cerebral hemorrhage hospitalized between June 2020 and March 2023 were analyzed. Patients were categorized into two groups based on the occurrence of SU post-surgery: the SU group (42 patients) and the non-SU group (168 patients). Clinical characteristics of both groups were compared, and a multivariate logistic regression was conducted to identify independent risk factors for SU. The study evaluated the predictive value of NLR and PLR, individually and in combination, for predicting SU using Receiver Operating Characteristic (ROC) curves.

RESULTS

We observed significant differences between the SU and non-SU groups in several parameters, including GCS score, absolute neutrophils, NLR, PLR, postoperative tracheotomy, and intracranial infection (P < 0.05). Our multivariate logistic regression analysis identified four independent risk factors for SU in patients undergoing surgery for acute cerebral hemorrhage: GCS score, NLR, PLR, and fasting blood glucose (P < 0.05). Furthermore, ROC analysis demonstrated that the combination of NLR and PLR exhibited the highest AUC, sensitivity, and specificity in predicting SU following surgery for acute cerebral hemorrhage (P < 0.001), with values of 0.864 (95 % CI: 0.776-0.953), 0.778 (95 % CI: 0.658-0.899), and 0.941 (95 % CI: 0.889-0.993) respectively.

CONCLUSION

This study highlighted the combined application of PLR and NLR as a significant predictor of SU in patients post-acute cerebral hemorrhage surgery.

The Prognosis of Neutrophil-to-Lymphocyte Ratio and Lymphocyte-to-Monocyte Ratio in Elderly with Acute Ischemic Stroke

Background

Neutrophil-to-lymphocyte ratio (NLR) and Lymphocyte-to-monocyte ratio (LMR) have been reported to be associated with outcomes in acute ischemic stroke. However, research on elderly populations remains relatively scarce. We investigated the prognosis of NLR and LMR in elderly with acute ischemic stroke(AIS).

Methods

Based on the modified Rankin Score (mRS) on the 90th day after stroke, patients were divided into group and bad prognosis groups. Multivariate logistic regression analysis and receiver operating curves were used to identify prognostic factors and their predictive powers.

Results

In total, 824 elderly patients with AIS were enrolled between November 2021 and December 2023. Significant differences emerged in the NLR, LMR, and lymphocyte count between the two groups (P<0.05). Binary logistic regression identified NLR, LMR and neutrophil count as independent risk factors for an unfavorable prognosis in elderly patients with AIS. The areas under the curve (AUCs) of NLR, LMR, and the combination of NLR and LMR to discriminate poor function prognosis were 0.703, 0.672, and 0.706, respectively. ROC analysis also showed that combination of NLR and LMR was superior to NLR and LMR alone for predicting AIS.

Conclusion

NLR and LMR independently contribute to an unfavorable prognosis in elderly patients with AIS. The area under the ROC curve (AUC) for the combined NLR and LMR was higher than that for NLR and LMR individually, suggesting that combining these two indicators can improve the predictive ability for clinical outcomes in elderly patients with AIS.

Association between systemic inflammatory markers and all-cause mortality in patients with stroke: A prospective study using data from the UK Biobank

BACKGROUND AND AIMS

The systemic immune-inflammation index (SII), neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and lymphocyte-to-monocyte ratio (LMR) are novel inflammatory biomarkers used to determine various disease prognoses. However, the effects of these systemic inflammatory markers on all-cause mortality in patients with stroke remain unclear.

METHODS

We used data from the UK Biobank for this prospective analysis. Overall, 6,020 eligible individuals were included. Over a median follow-up of 13.4 years, 1,233 participants died. We examined the effects of systemic inflammatory markers on all-cause mortality using random survival forest (RSF) and Cox proportional hazards models. Covariate adjustments in the Cox model, selected by RSF, included age, sex, body mass index (BMI), Townsend deprivation index, smoking status, alcohol intake frequency, sleep duration, diabetes, and malignant neoplasms.

RESULTS

In the marginal effect plots and restricted cubic spline analysis for systemic inflammatory markers, LMR exhibited a linear negative correlation, NLR showed a linear positive correlation, and SII and PLR demonstrated a U-shaped association. After covariates were adjusted, the all-cause mortality risk increased by 14 % for LMR <4 (hazards ratio [HR]: 1.14, 95 % confidence interval [CI]: 1.01-1.29; p= 0.03), by 26 % for NLR ≥2 (HR: 1.26; 95 % CI: 1.11-1.43; p < 0.001),by 26 % for PLR ≥175 (HR: 1.26; 95 % CI: 1.07-1.47; p < 0.001), and by 31 % for SII ≥526 (HR: 1.31; 95 % CI, 1.16-1.47; p= 0.014). In addition, sensitivity analyses, excluding participants who had been followed-up for <2 years and those with malignant neoplasms, yielded results consistent with those of previous research.

CONCLUSION

SII, NLR, PLR, and LMR significantly correlate with all-cause mortality in stroke patients. Thresholds established by the RSF model could potentially refine prognostic decision-making in stroke care.

Association between neutrophil-to-lymphocyte ratio and short-term all-cause mortality in patients with cerebrovascular disease admitted to the intensive care unit-a study based on the MIMIC-IV database

Background

Inflammation plays a crucial role in cerebrovascular disease (CVD) progression. Neutrophil-to-lymphocyte ratio (NLR) is an important inflammatory marker, though its diagnostic role in CVD is still under investigation. This study evaluates the relationship between NLR and short-term all-cause mortality in patients with CVD admitted to the intensive care unit (ICU).

Methods

We conducted a retrospective study using data from the Medical Information Mart for Intensive Care (MIMIC-IV) (v2.2) database, including 4,327 adult ICU-admitted CVD patients. NLR values at admission were analyzed alongside various mortality variables. Multivariate Cox proportional hazards regression models and Kaplan-Meier (K-M) survival curves assessed the relationship between NLR and short-term all-cause mortality. Predictive power, sensitivity, specificity, and area under the curve (AUC) of NLR for short-term mortality were investigated using Receiver Operating Characteristic (ROC) analysis. Additionally, restricted cubic spline (RCS) curves and subgroup analyses were conducted.

Results

Among the 4,327 patients, 3,600 survived (survival group) and 727 died (non-survival group) within 28 days of admission (mortality rate: 16.8%). A multivariate Cox regression analysis identified NLR as an independent predictor of 28-day all-cause mortality (hazard ratio: 1.013; 95% confidence interval: 1.0086-1.0188; p < 0.001). The predictive model, incorporating NLR, age, gender, BMI, Charlson comorbidity index (CCI), WBC counts, Platelet, INR, and CRP, achieved an AUC of 0.686 (95% confidence interval: 0.665-0.70). While platelet-to-lymphocyte ratio was also analyzed, its predictive efficiency was less pronounced compared to NLR. A best NLR threshold of 6.19 was determined, distinguishing survivors from non-survivors. Kaplan-Meier survival curves showed that patients with NLR ≥ 6.19 had significantly lower survival rates at 7-, 14-, 21-, and 28-days. Subgroup analyses indicated that NLR did not significantly interact with most subgroups.

Conclusion

NLR may serve as an independent predictor for short-term all-cause mortality in ICU-admitted CVD patients, enhancing our understanding of the association between inflammatory biomarkers and CVD prognosis.

The value of the systemic immune-inflammation index in assessing disease severity in autoimmune encephalitis

BACKGROUND

Autoimmune encephalitis (AE) is a group of autoimmune diseases targeting the central nervous system, characterized by severe clinical symptoms and substantial consumption of medical resources. Neuroinflammation plays a crucial role in disease progression, and detecting inflammatory responses can provide insights into disease status and disease severity. The systemic immune-inflammation index (SII), a novel marker of inflammatory status, has been rarely studied in AE.

METHODS

Retrospective analysis of data from AE patients admitted to the First Affiliated Hospital of Zhengzhou University between January 2019 and September 2023 was conducted. Univariate analysis and logistic regression were used to assess the association between SII and patient severity. Nomograms for predicting AE severity were established, and receiver operating characteristic (ROC) curves, concordance index (C-index), calibration curves, and decision curve analysis were employed to evaluate predictive accuracy. Additionally, the Clinical Assessment Scale in Autoimmune Encephalitis (CASE) score was used to assess patient severity.

RESULTS

This study enrolled 157 patients, of whom 57 were classified as severe according to the CASE score. SII, cerebrospinal fluid (CSF) cell counts, disturbance of consciousness, and behavioural abnormalities independently associated with the occurrence of severe cases. The C-index of the nomograms was 0.87, indicating strong association with disease severity, as supported by the calibration. Additionally, SII levels were highest within seven days of onset and decreased after one month. In subgroup analyses of different antibodies, SII also associations with severe cases in NMDAR encephalitis.

CONCLUSIONS

Higher SII levels are associated with an increased likelihood of developing severe AE, peaking within 7 days of disease onset and decreasing thereafter, potentially offering a prognostic marker to assess disease progression early in its course.

Psychological General Well-being, Cognitive Failure, and Inflammation Biomarkers Among Workers 4 Months After a Mild/Asymptomatic SARS-CoV-2 Infection

OBJECTIVE

To investigate the relationship between cognitive complaints, systemic inflammatory biomarkers, and psychological general well-being (PGWB) after mild/asymptomatic SARS-CoV-2 infection, according to the presence of long COVID and work tasks.

METHODS

University employees and metal workers were recruited in a cross-sectional study 4 months after SARS-CoV-2 infection to assess cognitive impairment, individual PGWB index, inflammatory biomarkers, namely platelet-lymphocyte, neutrophil-lymphocyte, and lymphocyte-monocyte ratios, and the presence of long COVID symptoms.

RESULTS

A significant increase in the levels of inflammatory biomarkers was observed in subjects with long COVID. Furthermore, the PGWB index was influenced by long COVID symptoms and subjective cognitive and depressive symptoms, but not by work activity.

CONCLUSIONS

In occupational settings, it is crucial to detect the presence of long COVID symptoms and systemic inflammation early, as they may be associated with lower PGWB.

Prognostic Value of Magnetic Resonance Imaging Variables Combined with Neutrophil-to-Lymphocyte Ratio in Patients with Cervical Traumatic Spinal Cord Injury

OBJECTIVE

We aimed to explore the prognostic significance of preoperative magnetic resonance imaging (MRI) variables and novel inflammatory indicators in predicting neurological recovery post-cervical traumatic spinal cord injury (TSCI) in the study.

METHODS

We enrolled a total of 244 patients diagnosed with acute cervical TSCI from 2 hospitals and evaluated the prognostic value of MRI variables (intramedullary hemorrhage, intramedullary lesion length [IMLL], maximum spinal cord compression, and maximum canal compromise [MCC]) and novel inflammatory indicators (neutrophil-to-lymphocyte ratio [NLR], platelet-to-lymphocyte ratio, lymphocyte-to-monocyte ratio, and systemic immune-inflammatory index) in patients with acute cervical TSCI.

RESULTS

Among the 244 patients, 140 (57.38%) exhibited improved AIS grade conversion at 1-year follow-up. The results revealed intramedullary hemorrhage, IMLL, MCC, neutrophils, and NLR were significantly different compared with follow-up AIS grade. Furthermore, IMLL, MCC, white blood cells, neutrophils, NLR, and lymphocyte-to-monocyte ratio correlated with the follow-up AIS grade by Spearman's correlation analysis. Multivariate analysis showed IMLL, intramedullary hemorrhage, NLR, and admission AIS grade emerged as independent predictors of AIS grade conversion. The receiver operating characteristic curve analysis showed that the novel model (combination of MRI variables, NLR, and admission AIS grade) produced a larger area under the curve compared with using only intramedullary hemorrhage, IMLL, NLR, or admission AIS grade individually.

CONCLUSION

Intramedullary hemorrhage and IMLL and NLR are predictors of AIS grade conversion after cervical TSCI. Therefore, we suggest the combination of MRI variables and NLR for the prognostic prediction of AIS grade conversion in patients with cervical TSCI.

Association between immune-inflammation-based prognostic index and depression: An exploratory cross-sectional analysis of NHANES data

BACKGROUND

Immune-inflammatory mediators influence numerous immune and inflammatory pathways, elevating the likelihood of depression. The systemic immune-inflammation index (SII) emerges as an innovative prognostic indicator, integrating various peripheral blood immune cell subpopulations, specifically neutrophils, platelets, and lymphocytes. This exploratory study aims to examine the correlation between SII and depression.

METHODS

Data from the 2005-2020 National Health and Nutrition Examination Survey (NHANES) were utilized. Depression was diagnosed with a Patient Health Questionnaire score of 10 or higher. The relationship between log2-SII and depression incidence was analyzed using a restricted cubic spline (RCS). Logistic regression was employed to calculate the odds ratio of depression concerning log2-SII. In cases of non-linearity, piecewise linear models with change points were applied to assess the associations in both the overall population and specific subgroups. Additionally, subgroup analyses were conducted to determine the applicability of the findings to particular populations.

RESULTS

A total of 42,133 participants were included in the study, comprising 49.32 % men and 50.68 % women, with an average age of 47.02 ± 17.45 years. RCS analysis demonstrated a J-shaped non-linear relationship between log2-SII and depression incidence. When log2-SII was ≥8.50, SII showed a positive association with depression incidence, even after adjusting for covariates. Additionally, each unit increase in log2-SII corresponded to an 18 % rise in depression incidence (OR = 1.18, 95 % CI: 1.10-1.27). Subgroup analysis further revealed that the association between SII and depression incidence varied across different populations.

LIMITATIONS

Due to the cross-sectional nature of NHANES, causality or long-term implications cannot be inferred. Further research is needed to ascertain if a longitudinal relationship exists between SII and depression.

CONCLUSION

Our findings suggest a significant and complex non-linear association between SII and depression. However, further basic and prospective studies are necessary to explore SII's impact on depression and clarify its underlying mechanisms. Additionally, these studies will provide a foundation for personalized interventions targeting the immune-inflammatory processes in patients with depression and elevated SII.

Neutrophil-to-Lymphocyte Ratio, Lymphocyte-to-Monocyte Ratio and Platelet-to-Lymphocyte Ratio as Predictors of Short- and Long-Term Outcomes in Ischemic Stroke Patients with Atrial Fibrillation

Purpose

Inflammatory response plays essential roles in the pathophysiology of both ischemic stroke and atrial fibrillation (AF). We aimed to investigate whether composite inflammatory markers, including neutrophil to lymphocyte ratio (NLR), lymphocyte-to-monocyte ratio (LMR) and platelet-to-lymphocyte ratio (PLR), can serve as early predictors of short- and long-term outcomes in ischemic stroke patients with AF.

Patients and Methods

Ischemic stroke patients with AF were enrolled in this cohort study. The primary outcome was 1-year functional dependence or death (modified Rankin scale (mRS) score 3-6). Secondary outcomes included hemorrhagic transformation (HT) and early neurological deterioration (END, increase in the National Institutes of Health Stroke Scale (NIHSS) ≥4 within 7 days). Partial correlations were performed to assess the correlation between systemic inflammation markers and admission NIHSS scores. Univariate and multivariate logistic analyses were performed to investigate whether systemic inflammatory markers were independent predictors of adverse outcomes.

Results

A total of 408 patients were included. Partial correlation analysis revealed statistically significant but weak correlations between the NLR (r = 0.287; P < 0.001), PLR (r = 0.158; P = 0.001) and admission NIHSS score. Compared with patients without HT or END, patients who developed HT or END had higher NLR and PLR, and lower LMR. Patients in the functional dependence or death group had significantly higher NLR and PLR, and lower LMR than those in the functional independence group (all P < 0.001). Multivariate logistic analysis indicated that NLR, LMR and PLR were independent predictors of HT (OR = 1.069, 0.814 and 1.003, respectively), END (OR = 1.100, 0.768 and 1.006, respectively) and adverse 1-year functional outcome (OR = 1.139, 0.760 and 1.005, respectively).

Conclusion

NLR, LMR and PLR were independent predictors for in-hospital HT, END and long-term functional outcome in ischemic stroke patients with AF. Close monitoring of these inflammatory markers may help guide risk stratification and clinical treatment strategies.

Preoperative serum ferritin as a biomarker for predicting delirium among elderly patients receiving non-cardiac surgery: a retrospective cohort study

Iron metabolism disorder has been identified as a contributor to the pathogenesis and progression of multiple cognitive dysfunction-related diseases, including postoperative delirium. However, the association between preoperative iron reserves and postoperative delirium risk remains elusive. This retrospective cohort study aimed to explore the impact of preoperative serum ferritin levels on the risk of postoperative delirium in elderly patients undergoing non-neurosurgical and non-cardiac procedures. Conducted at the Chinese PLA General Hospital between January 2014 and December 2021, the study finally included 12,841 patients aged 65 years and above. Preoperative serum ferritin levels were assessed within 30 days before surgery, and postoperative delirium occurrence within the first seven days after surgery was determined through medical chart review. The analyses revealed that both low and high levels of serum ferritin were associated with an increased risk of postoperative delirium. Patients in the lowest quintile of serum ferritin exhibited an 81% increased risk, while those in the highest quintile faced a 91% increased risk compared to those in the second quintile. Furthermore, mediation analyses indicated that the direct effect of preoperative serum ferritin on postoperative delirium contradicted its indirect effect mediated by hemoglobin levels. These findings suggest that maintaining serum ferritin within moderate range preoperatively could be beneficial for managing postoperative delirium risk among elderly patients.

Construction of a machine learning-based prediction model for unfavorable discharge outcomes in patients with ischemic stroke

Background

Ischemic stroke is a common and serious disease with economic and healthcare burdens. Predicting the unfavorable discharge outcome of patients is essential for formulating appropriate treatment strategies and providing personalized care. Therefore, this study aims to establish and validate a prediction model based on machine learning methods to accurately predict the discharge outcome of ischemic stroke patients, providing valuable information for clinical decision making.

Methods

The derivation data consisted of 964 patients from Guangdong Provincial People's Hospital and was used for training and internal validation. A favourable discharge outcome was defined as a National Institutes of Health Stroke Scale score of ≤1 or a decrease of ≥8 points compared to the admission score. A predictive model was created based on 88 medical characteristics gathered during the patient's initial admission, using nine machine learning algorithms. The model's predictive performance was compared using various evaluation metrics. The final model's feature importance was ranked and explained using the Shapley additive explanation method.

Findings

The random forest model demonstrated the greatest discriminative ability among the nine machine learning models. We created an interpretable random forest model by ranking and reducing the features based on their importance, which included eight features. In internal validations, the final model accurately predicted the discharge outcomes of ischemic stroke with AUC values of 0.903 and has been translated into a convenient tool to facilitate its utility in clinical settings.

Conclusions

Our explainable ML model was not only successfully developed to accurately predict discharge outcomes in patients with ischemic stroke and it mitigated the concern of the "black-box" issue with an undirect interpretation of the ML technique.

Systemic immune inflammation index and risk of stroke: a cross-sectional study of the National Health and Nutrition Examination Survey 2005-2018

Background

The incidence of stroke has increased globally, resulting in medical expenditures and social burdens over the past few decades. We aimed to explore the relationship between systemic immune inflammatory index (SII) and stroke using the National Health and Nutrition Examination Survey (NHANES) from 2005 to 2018.

Methods

Based on NHANES data, 902 stroke patients and 27,364 non-stroke patients were included in this study. SII was the independent variable and stroke was the dependent variable. Univariate and multivariate logistic regression analyses were used to explore the association between SII and stroke. Restricted cubic spline (RCS) method was used to test the nonlinear association between SII and stroke.

Results

Weighted logistic regression analysis showed a significant association between SII and stroke (OR: 1.985, 95% CI: 1.245-3.166, p = 0.004). The interaction test showed that the association between SII and stroke was not significant between strata (p > 0.05). A significant positive association between SII and stroke risk (OR >1, p < 0.05) was observed in the crude model, model I and model II. RCS analysis showed no nonlinear positive association between SII and stroke risk after adjusting for all confounders.

Conclusion

Our study determined that SII is associated with stroke risk. Given the inherent limitations of cross-sectional studies, further research is necessary to validate the causality of this association and to demystify the underlying mechanisms between inflammation and stroke.

Machine learning-based prediction of early neurological deterioration after intravenous thrombolysis for stroke: insights from a large multicenter study

Background

This investigation seeks to ascertain the efficacy of various machine learning models in forecasting early neurological deterioration (END) following thrombolysis in patients with acute ischemic stroke (AIS).

Methods

Employing data from the Shenyang Stroke Emergency Map database, this multicenter study compiled information on 7,570 AIS patients from 29 comprehensive hospitals who received thrombolytic therapy between January 2019 and December 2021. An independent testing cohort was constituted from 2,046 patients at the First People's Hospital of Shenyang. The dataset incorporated 15 pertinent clinical and therapeutic variables. The principal outcome assessed was the occurrence of END post-thrombolysis. Model development was executed using an 80/20 split for training and internal validation, employing classifiers like logistic regression with lasso regularization (lasso regression), support vector machine (SVM), random forest (RF), gradient-boosted decision tree (GBDT), and multi-layer perceptron (MLP). The model with the highest area under the curve (AUC) was utilized to delineate feature significance.

Results

Baseline characteristics showed variability in END incidence between the training (n = 7,570; END incidence 22%) and external validation cohorts (n = 2,046; END incidence 10%; p < 0.001). Notably, all machine learning models demonstrated superior AUC values compared to the reference model, indicating their enhanced predictive capacity. The lasso regression model achieved the highest AUC at 0.829 (95% CI: 0.799-0.86; p < 0.001), closely followed by the MLP model with an AUC of 0.828 (95% CI: 0.799-0.858; p < 0.001). The SVM, RF, and GBDT models also showed commendable AUCs of 0.753, 0.797, and 0.774, respectively. Decision curve analysis revealed that the SVM and MLP models demonstrated a high net benefit. Feature importance analysis emphasized "Onset To Needle Time" and "Admission NIHSS Score" as significant predictors.

Conclusion

Our research establishes the MLP and lasso regression as robust tools for predicting early neurological deterioration in acute ischemic stroke patients following thrombolysis. Their superior predictive accuracy, compared to traditional models, highlights the significant potential of machine learning approaches in refining prognosis and enhancing clinical decisions in stroke care management. This advancement paves the way for more tailored therapeutic strategies, ultimately aiming to improve patient outcomes in clinical practice.

Effects of platelet-to-lymphocyte ratio on renal function following acute myocardial infarction: A retrospective observational study

Increased platelet-to-lymphocyte ratio (PLR) and neutrophil-to-lymphocyte ratio (NLR) in acute myocardial infarction (AMI), which indicate accelerated thrombus formation and inflammatory response, potentially have prognostic implications. Given that cardiovascular disease and renal function exacerbate each other, an elevated PLR and NLR at admission for AMI may worsen renal function after AMI. However, only a few clinical studies have addressed this issue. Therefore, this study aimed to examine the effects of PLR and NLR at AMI onset on renal function. This retrospective study analyzed data from 234 patients hospitalized for AMI. First, correlations between various parameters (age; sex; body mass index; hemoglobin level, albumin level, B-type natriuretic peptide level, C-reactive protein level, creatinine (Cr) level, blood urea nitrogen (BUN) level, PLR, and NLR at admission; contrast medium usage; and maximum creatine kinase) and Cr and BUN levels at discharge were examined using single and multiple regression analyses. Then, correlations between these parameters and the change in Cr (ΔCr) and BUN levels (ΔBUN) were investigated using single and multiple regression analysis, followed by structural equation modeling (SEM). Multiple regression analysis revealed significant positive correlations between PLR at admission and Cr level at discharge (β = 0.135, P = .021), PLR at admission and BUN level at discharge (β = 0.218, P = .006), PLR at admission and ΔCr (β = 0.244, P = .019), and PLR at admission and ΔBUN (β = 0.312, P = .003). SEM results revealed significant positive correlations between PLR at admission and ΔCr (β = 0.260, P = .008) and PLR at admission and ΔBUN (β = 0.292, P = .003). Conversely, NLR demonstrated a minimal association with renal function at discharge compared to PLR. This study suggests that increased PLR at admission in AMI significantly affects and exacerbates renal function but does not increase NLR at admission. PLR is one of the predictors of renal dysfunction after AMI.

Machine learning-based predictive model for the development of thrombolysis resistance in patients with acute ischemic stroke

BACKGROUND

The objective of this study was to establish a predictive model utilizing machine learning techniques to anticipate the likelihood of thrombolysis resistance (TR) in acute ischaemic stroke (AIS) patients undergoing recombinant tissue plasminogen activator (rt-PA) intravenous thrombolysis, given that nearly half of such patients exhibit poor clinical outcomes.

METHODS

Retrospective clinical data were collected from AIS patients who underwent intravenous thrombolysis with rt-PA at the First Affiliated Hospital of Bengbu Medical University. Thrombolysis resistance was defined as ([National Institutes of Health Stroke Scale (NIHSS) at admission - 24-hour NIHSS] × 100％/ NIHSS at admission) ≤ 30%. In this study, we developed five machine learning models: logistic regression (LR), extreme gradient boosting (XGBoost), support vector machine (SVM), the least absolute shrinkage and selection operator (LASSO), and random forest (RF). We assessed the model's performance by using receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA), and presented the results through a nomogram.

RESULTS

This study included a total of 218 patients with AIS who were treated with intravenous thrombolysis, 88 patients experienced TR. Among the five machine learning models, the LASSO model performed the best. The area under the curve (AUC) on the testing group was 0.765 (sensitivity: 0.767, specificity: 0.694, accuracy: 0.727). The apparent curve in the calibration curve was similar to the ideal curve, and DCA showed a positive net benefit. Key features associated with TR included NIHSS at admission, blood glucose, white blood cell count, neutrophil count, and blood urea nitrogen.

CONCLUSION

Machine learning methods with multiple clinical variables can help in early screening of patients at high risk of thrombolysis resistance, particularly in contexts where healthcare resources are limited.

Association of higher triglyceride-glucose index and triglyceride-to-high-density lipoprotein cholesterol ratio with early neurological deterioration after thrombolysis in acute ischemic stroke patients

Background

Insulin resistance (IR) can predict the prognosis of patients suffering from cerebrovascular disorders. The triglyceride-glucose (TyG) index and triglyceride-to-high-density lipoprotein cholesterol (TG/HDL-C) ratio have been confirmed to be easy and reliable indicators of IR. However, the relationships between the TyG index or TG/HDL-C ratio and early neurological deterioration (END) after thrombolysis in patients with acute ischemic stroke (AIS) are uncertain.

Methods

A retrospective analysis of 1,187 patients diagnosed with AIS who underwent intravenous thrombolysis between January 2018 and February 2024 was performed. Post-thrombolysis END was defined as an increase in the National Institutes of Health Stroke Scale (NIHSS) score of ≥4 within 24 h after thrombolysis. Logistic regression analysis was performed to explore the relationships of the TyG index and TG/HDL-C ratio with post-thrombolysis END. Receiver operating characteristic (ROC) analysis was used to assess the ability of the TyG index and TG/HDL-C ratio to discriminate post-thrombolysis END.

Results

Among the 1,187 recruited patients, 179 (15.08%) were diagnosed with post-thrombolysis END, and 1,008 (84.92%) were diagnosed with non-END. A binary logistic regression model indicated that the TyG index (odds ratio [OR], 2.015; 95% confidence interval [CI] 1.964-2.414, p = 0.015) and TG/HDL-C ratio (OR, 1.542; 95% CI, 1.160-2.049, p = 0.004) were independent factors for post-thrombolysis END. The area under the curve (AUC) values for the TyG index, TG/HDL-C ratio, and TyG index combined with the TG/HDL-C ratio for post-thrombolysis END were 0.704, 0.674, and 0.755, respectively.

Conclusion

This study indicates that the TyG index and TG/HDL-C ratio can be used as prognostic factors to predict post-thrombolysis END.

Neutrophil-to-Lymphocyte Ratio, Platelet-to-Lymphocyte Ratio, Systemic Immune Inflammation Index and Efficacy of Remote Ischemic Conditioning in Acute Ischemic Stroke: A Post Hoc Exploratory Analysis of the RICAMIS Study

Background

We conducted a post-hoc analysis of the RICAMIS trial to investigate the effect of neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and systemic immune inflammation index (SII) on the efficacy of remote ischemic conditioning treatment.

Methods

In this post-hoc analysis, NLR, PLR, and SII were measured before randomization. Patients were divided into two groups based on their cut-off values: high vs low NLR, high vs low PLR, and high vs low SII groups. Each group was further subdivided into RIC and control groups. The primary endpoint was a poor outcome (mRS 2-6 at 90 days). Differences in the primary endpoint between the RIC and control subgroups were compared, and the interactions of treatment assignment with NLR, PLR, and SII were evaluated.

Results

A total of 1679 patients were included in the final analysis. Compared with the control group, RIC significantly improved functional outcomes regardless of the inflammation status. The improved probability of poor outcome in the RIC vs control group was numerically greater in the high vs low inflammation group (NLR, 7.8% vs 5.1%; PLR, 7% vs 6.5%; SII, 9% vs 5.3%). However, we did not find an interaction effect of an intervention (RIC or control) with different NLR, PLR, or SII on clinical outcomes (P > 0.05). In addition, the NLR and SII were independently associated with functional outcomes in all patients, regardless of whether they received RIC.

Conclusion

Inflammation may not affect the efficacy of RIC in patients with acute moderate ischemic stroke, although a lower probability of poor outcome at 90 days was identified in patients with a high vs low inflammatory status.

Platelet-to-lymphocyte percentage ratio for assessing disease activity and predicting therapeutic outcomes in ulcerative colitis

AIMS

Disease activity assessment and treatment outcome prediction are crucial in the patient management of ulcerative colitis (UC); yet the significance of platelet-to-lymphocyte percentage ratio (PLpR) remains unknown, which was investigated in this study.

METHODS

We used data from three clinical trials: ACT 1, PURSUIT, and UNIFI. In total, 7,614 endoscopic procedures and 1,365 patients were included for assessing severity and predicting outcome, respectively. The primary outcome was endoscopic remission, defined as a Mayo endoscopic score of 0. The diagnostic capacity of PLpR was evaluated by the area under the receiver operating characteristic curve (AUC) while multivariable logistic regression was employed to assess the prognostic power of PLpR.

RESULTS

PLpR showed higher AUCs than C-reactive protein in identifying endoscopic remission (P < 0.001) and improvement (P < 0.001). Besides, combining PLpR with fecal calprotectin enhanced the power to distinguish disease activity. In therapeutic outcome analyses, higher PLpR level indicated worse long-term outcomes. PLpR ≥ 1016.7 predicted a lower likelihood of endoscopic remission (OR: 0.50 [95 % CI: 0.39-0.65]; P < 0.001), endoscopic improvement (OR: 0.45 [95 % CI: 0.36-0.57]; P < 0.001), clinical remission (OR: 0.50 [95 % CI: 0.39-0.62]; P < 0.001), histologic improvement (OR: 0.50 [95 % CI: 0.31-0.79]; P = 0.004), and histologic-endoscopic mucosal improvement (OR: 0.42 [95 % CI: 0.27-0.66]; P < 0.001). Moreover, PLpR added the prognostic value to C-reactive protein, fecal calprotectin, clinical and endoscopic scores to predict long-term outcomes.

CONCLUSION

PLpR could be a promising biomarker for monitoring disease activity and predicting long-term therapeutic outcomes in UC.

Association between systemic inflammation markers and blood pressure among children and adolescents: National Health and Nutrition Examination Survey

BACKGROUND

Few studies have estimated the associations of systemic inflammation markers and high blood pressure (HBP) in the pediatric population.

METHODS

Basing on data from the National Health and Nutrition Examination Survey (NHANES) from 1999 to 2018, we assessed the associations between four inflammation-related factors based on blood cell counts: systemic immune inflammation index (SII), neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), lymphocyte-to-monocyte ratio (LMR), and risk for pediatric HBP by estimating odds ratios (ORs) using multivariable logistic regression models.

RESULTS

A total of 17,936 children aged 8-19 years were included in the analysis, representing about 36.7 million American children. The prevalence rates of elevated blood pressure (EBP) and hypertension (HTN) were 15.79% and 6.77%, respectively. The results showed that the ORs for EBP per standard deviation (SD) increment in SII and NLR were estimated at 1.11 [95% confidence interval (95%CI): 1.04, 1.17] and 1.08 (95%CI: 1.02, 1.15), respectively; and the OR for EBP per SD increment in LMP were estimated at 0.90 (95%CI: 0.83, 0.96). These associations were stronger in boys and younger children.

CONCLUSIONS

The study suggested that inflammation-related factors could serve as easily accessible early biomarkers for HBP risk prediction and prevention in children and adolescents.

IMPACT

The study suggested that inflammation-related factors could serve as easily accessible early biomarkers for HBP risk prediction and prevention in children and adolescents. This is the first study that demonstrates the close association between systemic inflammation markers and HBP in children and adolescents using nationally representative population data. The findings have more public health implications and support that systemic inflammation markers based on blood cell counts could serve as easily accessible biomarkers of HBP risk and prevention in earlier identification of the diseases.

The clinical value of inflammation index in predicting ICU mortality of critically ill patients with intracerebral hemorrhage

Background

The inflammatory response holds paramount significance in the context of intracerebral hemorrhage (ICH) and exhibits a robust correlation with mortality rates. Biological markers such as the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), lymphocyte-to-monocyte ratio (LMR), systemic immune inflammation index (SII), and systemic inflammatory response index (SIRI) play crucial roles in influencing the systemic inflammatory response following ICH. This study aims to compare the predictive efficacy of NLR, PLR, LMR, SII, and SIRI concerning the risk of mortality in the intensive care unit (ICU) among critically ill patients with ICH. Such a comparison seeks to elucidate their early warning capabilities in the management and treatment of ICH.

Methods

Patients with severe ICH requiring admission to the ICU were screened from the Medical Information Marketplace for Intensive Care (MIMIC-IV) database. The outcomes studied included ICU mortality and 30 day ICU hospitalization rates, based on tertiles of the NLR index level. To explore the relationship between the NLR index and clinical outcomes in critically ill patients with ICH, we utilized receiver operating characteristic (ROC) analysis, decision curve analysis (DCA), and multivariate logistic regression analysis.

Results

A total of 869 patients (51.9% male) were included in the study, with an ICU mortality rate of 22.9% and a 30 day ICU hospitalization rate of 98.4%. Among the five indicators examined, both the ROC curve and DCA indicated that NLR (AUC: 0.660, 95%CI: 0.617-0.703) had the highest predictive ability for ICU mortality. Moreover, this association remained significant even after adjusting for other confounding factors during multivariate analysis (HR: 3.520, 95%CI: 2.039-6.077). Based on the results of the multivariate analysis, incorporating age, albumin, lactic acid, NLR, and GCS score as variables, we developed a nomogram to predict ICU mortality in critically ill patients with ICH.

Conclusion

NLR emerges as the most effective predictor of ICU mortality risk among critically ill patients grappling with ICH when compared to the other four indicators. Furthermore, the integration of albumin and lactic acid indicators into the NLR nomogram enhances the ability to promptly identify ICU mortality in individuals facing severe ICH.

Neutrophil-to-lymphocyte ratio as a predictor for outcomes in patients with short-term emergency department revisits

BACKGROUND

Analysis of short-term emergency department (ED) revisits is a common emergency care quality assurance practice. Previous studies have explored various risk factors of ED revisits; however, laboratory data were usually omitted. This study aimed to evaluate the prognostic significance of neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte (PLR), and systemic immune-inflammation index (SII) in predicting outcomes of patients revisiting the ED.

METHODS

This retrospective observational cohort study investigated short-term ED revisit patients. The primary outcome measure was high-risk ED revisit, a composite of in-hospital mortality or intensive care unit (ICU) admission after 72-hour ED revisit. The NLR, PLR, and SII were investigated as potential prognostic predictors of ED revisit outcomes.

RESULTS

A total of 1916 encounters with short-term ED revisit patients were included in the study; among these, 132 (6.9%) encounters, comprising 57 in-hospital mortalities and 95 ICU admissions, were high-risk revisits. High-risk revisit patients had significantly higher NLR, PLR, and SII (11.6 vs 6.6, p < 0.001; 26.2 vs 18.9, p = 0.004; 2209 vs 1486, p = 0.002, respectively). Multiple regression analysis revealed revisit-NLR as an independent factor for predicting poor outcomes post-ED revisits (odds ratio: 1.031, 95% CI: 1.017-1.045, p < 0.001); an optimal cut-off value of 7.9 was proven for predicting high-risk ED revisit.

CONCLUSION

The intensity of the inflammatory response expressed by NLR was an independent predictor for poor outcomes of ED revisits and should be considered when ED revisits occur. Future prediction models for ED revisit outcomes can include revisit-NLR as a potential predictor to reflect the progressive conditions in ED patients.

Developing a nomogram model for 3-month prognosis in patients who had an acute ischaemic stroke after intravenous thrombolysis: a multifactor logistic regression model approach

OBJECTIVES

This study is to establish a nomination graph model for individualised early prediction of the 3-month prognosis of patients who had an acute ischaemic stroke (AIS) receiving intravenous thrombolysis with recombinant tissue plasminogen activator.

DESIGN

For the period from January 2016 through August 2022, 991 patients who had an acute stroke eligible for intravenous thrombolysis were included in the retrospective analysis study. The study was based on multifactor logistic regression.

PARTICIPANTS

Patients who received treatment from January 2016 to February 2021 were included in the training cohort, and those who received treatment from March 2021 to August 2022 were included in the testing cohort.

INTERVENTIONS

Each patient received intravenous thrombolysis within 4.5 hours of onset, with treatment doses divided into standard doses (0.9 mg/kg).

PRIMARY AND SECONDARY OUTCOME MEASURES

The primary outcome measure was a 3-month adverse outcome (modified Rankin Scale 3-6).

RESULTS

The National Institutes of Health Stroke Scale Score after thrombolysis (OR=1.18; 95% CI: 1.04 to 1.36; p = 0.015), door-to-needle time (OR=1.01; 95% CI: 1.00 to 1.02; p = 0.003), baseline blood glucose (OR=1.08; 95% CI: 1.00 to 1.16; p=0.042), blood homocysteine (OR=7.14; 95% CI: 4.12 to 12.71; p<0.001), monocytes (OR=0.05; 95% CI: 0.01 to 0.043; p=0.005) and monocytes/high-density lipoprotein (OR=62.93; 95% CI: 16.51 to 283.08; p<0.001) were independent predictors of adverse outcomes 3 months after intravenous thrombolysis, and the above six factors were included in the nominated DGHM2N nomogram. The area under the receiver operating characteristic curve value of the training cohort was 0.870 (95% CI: 0.841 to 0.899) and in the testing cohort was 0.822 (95% CI: 0.769 to 0.875).

CONCLUSIONS

A reliable nomogram model (DGHM2N model) was developed and validated in this study. This nomogram could individually predict the adverse outcome of patients who had an AIS receiving intravenous thrombolysis with alteplase for 3 months.

The prognostic value of the combined neutrophil-to-lymphocyte ratio (NLR) and neutrophil-to-platelet ratio (NPR) in sepsis

Sepsis is a severe disease characterized by high mortality rates. Our aim was to develop an early prognostic indicator of adverse outcomes in sepsis, utilizing easily accessible routine blood tests. A retrospective analysis of sepsis patients from the MIMIC-IV database was conducted. We performed univariate and multivariate regression analyses to identify independent risk factors associated with in-hospital mortality within 28 days. Logistic regression was utilized to combine the neutrophil-to-lymphocyte ratio (NLR) and the neutrophil-to-platelet ratio (NPR) into a composite score, denoted as NLR_NPR. We used ROC curves to compare the prognostic performance of the models and Kaplan-Meier survival curves to assess the 28 day survival rate. Subgroup analysis was performed to evaluate the applicability of NLR_NPR in different subpopulations based on specific characteristics. This study included a total of 1263 sepsis patients, of whom 179 died within 28 days of hospitalization, while 1084 survived beyond 28 days. Multivariate regression analysis identified age, respiratory rate, neutrophil-to-lymphocyte ratio (NLR), neutrophil-to-platelet ratio (NPR), hypertension, and sequential organ failure assessment (SOFA) score as independent risk factors for 28 day mortality in septic patients (P < 0.05). Additionally, in the prediction model based on blood cell-related parameters, the combined NLR_NPR score exhibited the highest predictive value for 28 day mortality (AUC = 0.6666), followed by NLR (AUC = 0.6456) and NPR (AUC = 0.6284). Importantly, the performance of the NLR_NPR score was superior to that of the commonly used SOFA score (AUC = 0.5613). Subgroup analysis showed that NLR_NPR remained an independent risk factor for 28 day in-hospital mortality in the subgroups of age, respiratory rate, and SOFA, although not in the hypertension subgroup. The combined use of NLR and NPR from routine blood tests represents a readily available and reliable predictive marker for 28 day mortality in sepsis patients. These results imply that clinicians should prioritize patients with higher NLR_NPR scores for closer monitoring to reduce mortality rates.

Neutrophil migration participates in the side effect of recombinant human tissue plasminogen activator

AIMS

Ischemic stroke remains a challenge in medical research because of the limited treatment options. Recombinant human tissue plasminogen activator (rtPA) is the primary treatment for recanalization. However, nearly 50% of the patients experience complications that result in ineffective reperfusion. The precise factors contributing to ineffective reperfusion remain unclear; however, recent studies have suggested that immune cells, notably neutrophils, may influence the outcome of rtPA thrombolysis via mechanisms such as the formation of neutrophil extracellular traps. This study aimed to explore the nonthrombolytic effects of rtPA on neutrophils and highlight their contribution to ineffective reperfusion.

METHODS

We evaluated the effects of rtPA treatment on middle cerebral artery occlusion in rats. We also assessed neutrophil infiltration and activation after rtPA treatment in vitro and in vivo in a small cohort of patients with massive cerebral ischemia (MCI).

RESULTS

rtPA increased neutrophil infiltration into the brain microvessels and worsened blood-brain barrier damage during ischemia. It also increased the neutrophil counts of the patients with MCI.

CONCLUSION

Neutrophils play a crucial role in promoting ischemic injury and blood-brain barrier disruption, making them potential therapeutic targets.

Prevalence, early predictors, and outcomes of sepsis in neurocritical illnesses: A prospective cohort study

BACKGROUND

Patients with neurocritically illness are an under-recognized population at high risk of sepsis. We aimed to investigate the prevalence, early predictors, and outcomes of sepsis in neuro-ICU.

METHODS

Daily and accumulative incidences of sepsis in neuro-ICU were explored. Demographics, medical history, baseline disease severity scores, and baseline biomarkers regarding inflammation, immunology, organ function, and nutritional status were collected and analyzed as potential predictors of sepsis. Logistic regression analyses were used to determine the independent predictors, and a nomogram was used to estimate the individual probability of sepsis in neuro-ICU.

RESULTS

153 patients were included in this study. Fifty-nine (38.6%) patients developed sepsis, and 21 (14%) patients developed septic shock. More than 86% of the septic cases occurred within the first week. Sequential organ failure assessment score ((relative risk) RR 1.334, P = .026), history of diabetes (RR 2.346, P = .049), and transferrin (RR 0.128, P = .042) on admission are independent predictors of sepsis. Septic patients had significantly higher mortality (P = .011), higher medical cost (P = .028), and a lower rate of functional independence (P = .010), compared to patients without sepsis.

CONCLUSIONS

Sepsis afflicted more than one-third of neurocritically-ill patients and occurred mostly in the first week of admission. History of diabetes, serum transferrin, and sequential organ failure assessment score on admission were early predictors. Sepsis led to significantly worse outcomes and higher medical costs.

Associations between systemic inflammation indicators and nonalcoholic fatty liver disease: evidence from a prospective study

Background

Although inflammation has been linked to nonalcoholic fatty liver disease (NAFLD), most studies have focused only on a single indicator, leading to inconsistent results. Therefore, a large prospective study that includes a variety of well-documented single and composite indicators of inflammation is needed. This study aimed to thoroughly investigate the potential associations between different systemic inflammatory indicators and NAFLD in the UK Biobank cohort.

Methods

After excluding ineligible participants, 378,139 individuals were included in the study. Associations between systemic inflammatory indicators and hepatic steatosis were assessed using multivariate logistic regression. The relationships between systemic inflammatory indicators and nonalcoholic fatty liver disease were analysed using Cox proportional hazards models, and nonlinear associations were investigated using restricted cubic splines.

Results

According to the cross-sectional analysis, systemic inflammatory indicators significantly correlated with hepatic steatosis. Over a median follow-up of 13.9 years, 4,145 individuals developed NAFLD. After sufficient adjustment for confounding factors, CRP levels were found to be nonlinearly positively associated with NAFLD risk (P<0.001), representing the strongest correlation among the tested relationships; lymphocyte count and the LMR showed an L-shaped correlation; monocyte count and neutrophil count showed a linear positive correlation (all P< 0.001); and the NLR, PLR, and SII showed a U-shaped correlation (all P<0.001).

Conclusions

Multiple systemic inflammatory indicators are strongly associated with the development of NAFLD, and aggressive systemic inflammation management may have a favourable impact on reducing the burden of NAFLD; further randomized controlled studies are needed.

Association of systemic inflammatory indices with anthropometric measures, metabolic factors, and liver function in non-alcoholic fatty liver disease

The present cross-sectional study aimed to explore the relationship between systemic inflammatory indices (SIIs) and anthropometric measures, metabolic, and liver function biomarkers in patients with non-alcoholic fatty liver disease (NAFLD). This study was carried out on 238 NAFLD patients with overweight or obesity, aged 18-55 years. Anthropometric measurements were done and body mass index (BMI), waist-to-hip ratio (WHR), and waist-to-height ratio (WHtR) were estimated. Metabolic factors including serum glucose, lipid profile, liver function biomarkers, and complete blood cell count were assessed after a 24-h fasting state. SIIs including the ratios of neutrophil to lymphocyte (NLR), monocytes to lymphocyte (MLR), platelet to lymphocyte (PLR), and monocytes to high-density lipoprotein cholesterol (MHR) were calculated. Results indicate that apart from PLR, all of the SIIs significantly changed by increasing steatosis severity (all p < 0.05). Moreover, changes in NLR showed a significant association with anthropometric indices including waist circumference (p = 0.032), BMI (p = 0.047), and WHtR (p = 0.002), as well as levels of fasting blood sugar (p = 0.045), triglycerides, (p = 0.025) and low-density lipoprotein cholesterol (p = 0.006). The findings also indicate the relations between lipid profile and all studied SIIs, notably MHR and MLR. All of the SIIs exhibited associations with some liver function indices as well. MHR was positively correlated with the metabolic risk factors of NAFLD while, oppositely, PLR was considered as a preventive marker of NAFLD.

Association of early seizures after ischemic stroke with diffusion-weighted imaging-alberta stroke program early CT score (DWI-ASPECTS) and neutrophil-to-lymphocyte ratio

BACKGROUND

Post-stroke seizure (PSS) is a common considerable complication of acute ischemic stroke (AIS). Early risk assessment can clinical practitioners to plan effective prevention and management. We aimed to determine whether assessing Diffusion-Weighted Imaging-Alberta Stroke Program Early CT Score (DWI-ASPECTS), and neutrophil indices allows for identifying patients at risk of PSS.

METHODS

This prospective study included AIS patients with cortical involvement admitted to a single academic center between January 2020 to October 2023. For all included subjects, DWI-Brain MRI, blood neutrophils, and platelet counts were obtained and the DWI-ASPECTS score was calculated. Then, the patients were followed up for 6 months in terms of PSS occurrence. Based on the occurrence of PSS, patients were divided into two groups of PSS and non-PSS. For analysis, imaging and laboratory data were compared between two groups. Logistic regression was applied to determine the relationship between DWI-ASPECTS and neutrophil indices, with early PSS. Finally, the sensitivity and specificity of these variables for PSS were estimated.

RESULTS

A total of 309 were included in the final statistical analysis. DWI-ASPECT and neutrophil-to-lymphocyte ratio (NLR) were significantly associated with early PSS with OR of 0.74 and OR of 1.13, respectively (P < 0.05). Further analysis showed that, a combination of DWI-ASPECTS, NLR had an area under the curve (AUC) of 0.72 for predicting the occurrence of early PSS.

CONCLUSION

DWI-ASPECTS and NLR are associated with the occurrence of early PSS after cortical ischemic stroke. A combination of these predictors had higher sensitivity and specificity for PSS rather than each factor alone. These findings may be helpful for determining the risk of PSS if validated in future studies.

Correlation between blood inflammatory indices and carotid intima-media thickness in the middle-aged and elderly adults

OBJECTIVES

This study aimed to investigate the correlations between carotid intima-media thickness (IMT) and systemic immune inflammation index (SII), platelet-to-lymphocyte ratio (PLR), and neutrophil-to-lymphocyte (NLR) ratio.

MATERIALS AND METHODS

This was a cross-sectional study enrolling a total of 582 middle-aged and elderly patients. The correlations between SII, PLR, and NLR with IMT were assessed using logistic regression models, which were subsequently incorporated into the underlying models with traditional risk factors and their predictive values for IMT.

RESULTS

NLR exhibited a significant correlation with IMT in the simple regression analysis (β = 0.01, 95 %CI= 0.00-0.02, p < 0.05). After controlling for potential confounding variables in the multivariate analysis, the association between NLR and both Maximum IMT [β = 0.04, 95 %CI = 0.02-0.07, p = 0.0006] and Mean IMT [β = 0.05, 95 %CI = 0.02-0.07, p = 0.0001] remained statistically significant. Additionally, PLR was found to be a significant independent predictor of Maximum IMT [β = 0.04, 95 % CI =0.00-0.07, p = 0.0242] and Mean IMT [β = 0.04, 95 % CI = 0.01-0.07, p = 0.0061]. Similarly, SII was identified as an independent predictor of Maximum IMT [β = 1.87, 95 % CI =1.24, p = 0.0003]. The study found a significant positive correlation between Maximum IMT and the levels NLR, PLR, and SII. Specifically, in the Maximum IMT group, higher quartiles of NLR, PLR, and SII were associated with increased odds ratios (OR) for elevated IMT levels, with statistically significant results for NLR (Q4vsQ1: OR 3.87, 95 % CI 1.81-8.29), PLR (Q4vsQ1: OR 2.84, 95 % CI 1.36-5.95), and SII (Q4vsQ1: OR 2.64, 95 % CI 1.30-5.37). Finally, the inclusion of NLR, PLR, and NLR+PLR+SII in the initial model with traditional risk factors resulted in a marginal improvement in the predictive ability for Maximum IMT, as evidenced by the net reclassification index (p < 0.05).

CONCLUSIONS

This study discovered a positive correlation between SII, PLR, NLR, and IMT, which are likely to emerge as new predictors for IMT thickening. These findings lay a theoretical reference for future predictive research and pathophysiological research on carotid intima-media thickening.

Association between systemic inflammatory markers and chronic obstructive pulmonary disease: A population-based study

Objective

To investigate whether inflammatory indices, including the systemic immune-inflammation index (SII), neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), product of platelet and neutrophil count (PPN), and lymphocyte-to-monocyte ratio (LMR), correlate with chronic obstructive pulmonary disease (COPD).

Methods

This was a cross-sectional study from the National Health and Nutrition Examination Survey (NHANES) database 2007-2018. The SII, NLR, PLR, PPN and LMR were calculated based on blood cell counts and were log2-transformed. COPD was diagnosed via a questionnaire or spirometry examination. Multivariate logistic regression, sensitivity analysis, subgroup analyses, and interaction tests were performed to evaluate the relationships.

Results

23,875 participants, including 1000 COPD patients (453 diagnosed via spirometry examination, 547 diagnosed via a questionnaire), were enrolled in this study. Positive associations were observed between SII (OR 1.231, 95 % CI 1.081,1.401), NLR (OR 1.223, 95 % CI 1.064,1.405), PLR (OR 1.325, 95 % CI 1.086,1.617), PPN (OR 1.157, 95 % CI 1.031,1.298) and COPD, while a negative association was obtained between LMR and COPD (OR 0.794, 95 % CI 0.666,0.948) after covariate adjustments. When divided COPD patients into spirometry-based and questionnaire-based, only SII (OR 1.310, 95%CI 1.122,1.529), PLR (OR 1.669, 95%CI 1.272,2.191) and PPN (OR 1.218, 95%CI 1.050,1.412) significantly correlated with spirometry-based COPD, while only NLR (OR 1.303, 95%CI 1.055,1.609) and LMR (OR 0.524, 95%CI 0.406,0.677) significantly correlated with questionnaire-based COPD after covariate adjustments.

Conclusion

Significant associations are observed between different inflammation indices and COPD. Heterogeneity exists between spirometry-based and questionnaire-based COPD patients. Future studies are needed to verify the results.

Correlation of LP-PLA2 and MMP-9 with the occurrence of early neurological deterioration in patients with acute ischemic stroke

Early neurological deterioration is a common complication of acute ischemic stroke (AIS), which aggravates symptoms, worsens the condition, and counteracts the benefits of clinical treatment. The aim of this paper was to analyze the correlation between lipoprotein-associated phospholipase A2 (Lp-PLA2), matrix metalloproteinase-9 (MMP-9), and the occurrence of early neurological deterioration (END) in patients with AIS and to explore the clinical prediction of END by the combination of the 2 assays for the clinical prediction of END. A total of 500 AIS patients admitted to our hospital from October 2022 to October 2023 were included as study subjects, and the clinical data of all AIS patients were collected and organized to detect the levels of Lp-PLA2 and MMP-9. Categorized into END and non-END groups according to whether END occurred within 7 days of the onset of AIS, and comparing the clinical baseline data and laboratory index levels of the 2 groups. Logistic regression analysis was performed to determine the independent predictors of END, and the predictive effects of Lp-PLA2 and MMP-9 levels on END were assessed by subject work characteristics (ROC) curves. END occurred in 111 (22.2%) of 500 AIS patients. Multivariate logistic regression analysis showed that diabetes (OR 2.717, 95% CI:1.53-4.81, P < .001), baseline NIHSS score (OR 1.65, 95% CI:1.41-1.94, P < .001), Lp-PLA2 (OR 1.07, 95% CI:1.05-1.09, P < .001) and MMP-9 (OR 1.12, 95% CI:1.09-1.16, P < .001) levels were independent influences on the occurrence of END in patients with AIS after correcting for confounders. ROC curve analysis showed that Lp-PLA2, MMP-9, and a combination of both predicted END with an area under the curve was 0.730, 0.763, and 0.831, respectively, and the area under the curve for the combination of both predicting END was significantly higher than that for any of the inflammatory markers alone (P < .05). Both inflammatory markers, Lp-PLA2 and MMP-9, were independent predictors of the development of END in patients with AIS, and the combination of the two had a higher predictive value.

Body fluids biomarkers associated with prognosis of acute ischemic stroke: progress and prospects

Acute ischemic stroke (AIS) is one of the most common strokes posing a grave threat to human life and health. Predicting the prognosis of AIS allows for an understanding of disease progress, and a better quality of life by making individualized treatment scheme. In this paper, we conducted a systematic search on PubMed, focusing on the relevant literature in the last 5 years. Summarizing the candidate prognostic biomarkers of AIS in body fluids such as blood, urine, saliva and cerebrospinal fluid is often of great significance for the management of acute ischemic stroke, which has the potential to facilitate early diagnosis, treatment, prevention and long-term outcome improvement.

Neutrophil-to-lymphocyte ratio associated with renal function in type 2 diabetic patients

BACKGROUND

Type 2 diabetes mellitus (T2DM) is a leading risk factor for the development and progression of chronic kidney disease (CKD). However, an accurate and convenient marker for early detection and appropriate management of CKD in individuals with T2DM is limited. Recent studies have demonstrated a strong correlation between the neutrophil-to-lymphocyte ratio (NLR) and CKD. Nonetheless, the predictive value of NLR for renal damage in type 2 diabetic patients remains understudied.

AIM

To investigate the relationship between NLR and renal function in T2DM patients.

METHODS

This study included 1040 adults aged 65 or older with T2DM from Shanghai's Community Health Service Center. The total number of neutrophils and lymphocytes was detected, and NLR levels were calculated. CKD was defined as an estimated glomerular filtration rate ≤ 60 mL/min/1.73 m². Participants were divided into four groups based on NLR levels. The clinical data and biochemical characteristics were compared among groups. A multivariate logistic regression model was used to analyze the association between NLR levels and CKD.

RESULTS

Significant differences were found in terms of sex, serum creatinine, blood urea nitrogen, total cholesterol, and low-density lipoprotein cholesterol among patients with T2DM in different NLR groups (P < 0.0007). T2DM patients in the highest NLR quartile had a higher prevalence of CKD (P for trend = 0.0011). Multivariate logistic regression analysis indicated that a high NLR was an independent risk factor for CKD in T2DM patients even after adjustment for important clinical and pathological parameters (P = 0.0001, odds ratio = 1.41, 95% confidence intervals: 1.18-1.68).

CONCLUSION

An elevated NLR in patients with T2DM is associated with higher prevalence of CKD, suggesting that it could be a marker for the detection and evaluation of diabetic kidney disease.

Preoperative geriatric nutritional risk index and neutrophil-to-lymphocyte ratio relate to postoperative acute kidney injury in elderly patients undergoing laparoscopic abdominal surgery

Background

Acute kidney injury (AKI) poses a significant concern in elderly patients undergoing laparoscopic abdominal surgery due to increased vulnerability arising from aging, comorbidities, and surgery-related factors. Early detection and intervention are crucial for mitigating short- and long-term consequences. This study aims to investigate the correlation between preoperative Geriatric Nutritional Risk Index (GNRI), neutrophil-to-lymphocyte ratio (NLR), and the occurrence of postoperative AKI in elderly patients undergoing laparoscopic abdominal surgery, as well as to assess the predictive value of their combined detection for postoperative AKI.

Methods

A retrospective study involving 347 elderly patients (aged 60 years or older) undergoing laparoscopic abdominal surgery explored the relationship between preoperative GNRI, NLR, and postoperative AKI. GNRI was calculated based on serum albumin and body weight ratios, while NLR was derived from preoperative blood tests.

Results

The combined GNRI and NLR test demonstrated superior predictive value (area under the curve [AUC] = 0.87) compared to individual markers. Multivariate logistic analysis identified age, American Society of Anesthesiologists (ASA) grade, comorbidities, preoperative GNRI, and NLR as independent risk factors for AKI. Correlation analysis affirmed a negative correlation between preoperative GNRI and AKI severity, and a positive correlation between preoperative NLR and AKI severity.

Conclusion

The preoperative GNRI and NLR have clinical values in predicting postoperative AKI in elderly patients undergoing laparoscopic abdominal surgery.

Predictive value of the BDH2-MN2 nomogram model for prognosis at 3 months after receiving intravenous thrombolysis in patients with acute ischemic stroke

Introduction

The present study focused on developing a nomogram model to predict the 3-month survival of patients with acute ischemic stroke (AIS) receiving intravenous thrombolysis with tissue plasminogen activator (tPA).

Material and methods

A total of 709 patients were enrolled in the present study, including 496 patients in the training set and 213 patients in the validation set. All data were statistically analyzed using R software. We applied LASSO regression analysis to construct nomograms by screening statistically significant predictors from all variables.The model discrimination was evaluated based on the area under the receiver operating characteristic curve (AUC-ROC).

Results

LASSO regression analysis was conducted for all variables, which revealed BNP, DNT, HCY, HDL, MHR, NHR and post-thrombolysis NIHSS as independent predictors of adverse outcomes at 3 months after intravenous thrombolysis. Accordingly, these seven factors were incorporated in the nominated BDH2-MN2 nomogram. The resulting AUC-ROC values determined for the training and validation sets were 0.937 (95% CI: 0.822-0.954) and 0.898 (95% CI: 0.748-0.921), respectively.

Conclusions

A robust BDH2-MN2 (BNP, DNT, HCY, HDL, MHR, NHR and post-thrombolysis NIHSS) nomogram model was successfully developed and validated. The developed nomogram enables prediction of adverse outcomes of individual AIS patients receiving intravenous thrombolysis with alteplase for 3 months.

Left ventricular systolic dysfunction predicts clinical prognosis in patients with acute ischemic stroke after intravenous thrombolysis

BACKGROUND

Although intravenous recombinant tissue plasminogen activator (rt-PA) thrombolysis is the most effective early treatment for acute ischemic stroke (AIS), outcomes vary greatly among patients. Left ventricular systolic dysfunction (LVSD) is prone to distant organ ischemia and may be a predictor for poor prognosis in AIS patients undergoing intravenous thrombolysis (IVT). Our aim was to investigate the predictivity of LVSD diagnosis (as measured by left ventricular ejection fraction (LVEF)) on 90-day clinical outcomes in AIS patients undergoing thrombolysis.

METHODS

The current prospective cohort study continuously enrolled 273 AIS patients from the National Stroke Prevention and Treatment Engineering Management Special Database who underwent IVT and completed echocardiography within 24 h of admission between 2021 and 2023. LVSD was examined by evaluation of the echocardiographic LVEF values using Simpson's biplane method of discs in line with international guidelines, and defined as a LVEF value < 50%. Multivariable ordinal logistic regression model was performed to analyze the association between LVEF and functional outcome at 3 months. Restricted cubic spline (RCS) was used to examine the shape of the dose-response association between reduced LVEF and poor functional outcomes. Subgroup analysis was also employed to further verify the reliability and practicability of the results.

RESULTS

Baseline data analysis showed LVSD patients had more comorbidities including on multivariate analyses, LVSD (OR 2.78, 95% CI 1.23 to 6.24, P=0.014), pre-existing diabetes mellitus (OR 2.08, 95% CI 1.11 to 3.90, P=0.023) and NIHSS on arrival (OR 1.31, 95% CI 1.21 to 1.49, P<0.001) were independent predictors of poor functional outcomes (mRS ≥ 3) at 3 months. Multivariable-adjusted spline regression indicated a linear dose-response association between LVEF after IVT and poor functional outcomes (p for linearity < 0.001), with the optimal cutoff values of LVEF being 0.48.

CONCLUSIONS

Our finding indicated that AIS patients with LVSD after IVT had poorer outcomes, suggesting the need to monitor and optimize LVEF in stroke management.

Association of peripheral immunity and cerebral small vessel disease in older adults without dementia: A longitudinal study

This study explored the associations between peripheral immunity with cerebral small vessel diseases. Older adults without dementia from the Alzheimer's Disease Neuroimaging Initiative were investigated. Peripheral blood was obtained, and magnetic resonance imaging was performed to measure cerebral microbleeds (CMB), lacunar infarctions (LI), and white matter hyperintensities (WMH). Multivariable-adjusted regression models, linear mixed-effects models, and the Spearman correlations were used to evaluate the associations. At baseline, individuals with greater neutrophils (odds ratio [OR] =1.10, 95% confidence interval [CI] 1.00-1.20, p=0.042) and monocytes (OR=1.12, 95% CI 1.02-1.22, p=0.016) had higher WMH volume. On the contrary, a higher lymphocyte-to-monocyte ratio (LMR) was related to lower WMH volume (OR=0.91, 95% CI 0.82-1.00, p=0.041). Longitudinally, higher neutrophils (ρ=0.084, p=0.049) and NLR (ρ=0.111, p=0.009) predicted accelerated progression of WMH volume, while a greater LMR (ρ=-0.101, p=0.018) was linked to slower growth of WMH volume. Nevertheless, associations between peripheral immunity with CMB or LI were not observed at baseline and follow-up. Our study found that peripheral immune indexes could serve as convenient noninvasive biomarkers of WMH.

Beyond the fractures: A comprehensive Comparative analysis of Affordable and Accessible laboratory parameters and their coefficients for prediction and Swift confirmation of pulmonary embolism in high-risk orthopedic patients

Background

Pulmonary embolism (PE) poses a significant challenge in diagnosis and treatment, particularly in high-risk patient populations such as those hospitalized for orthopedic reasons. This study explores the predictive and diagnostic potential of laboratory parameters in identifying PE among orthopedic patients.

Objectives

The purpose of this study was to determine whether selected (inexpensive and readily available) laboratory parameters and their coefficients can be used to diagnose pulmonary embolism and whether they are applicable in predicting its occurrence.

Material and methods

Selected laboratory parameters were determined twice in 276 hospitalized orthopedic patients with suspected PE: PLT, MPV, NEU, LYM, D-dimer, troponin I, age-adjusted D-dimer and their coefficients. Depending on the angio-CT results, patients were divided into groups. Selected popular laboratory coefficients were calculated and statistically analyzed. Optimal cutoff points were determined for the above laboratory tests and ROC curves were plotted.

Results

D-dimer/troponin I [p = 0.008], D-dimer [p = 0.001], age-adjusted D-dimer [p = 0.007], NLR/D-dimer [p = 0.005] and PLR [p = 0.021] are statistically significant predictors of PE. D-dimer/troponin I [p < 0.001], troponin I [p = 0.005] and age-adjusted D-dimer [p = 0.001] correlated with the diagnosis of PE after the onset of clinical symptoms.

Conclusions

In the context of orthopedic patients, cost-effective laboratory parameters, particularly the D-dimer/troponin I ratio and age-adjusted D-dimer, exhibit considerable potential in predicting and diagnosing PE. These findings suggest that combining readily available laboratory tests with clinical observation can offer a viable and cost-effective diagnostic alternative, especially in resource-constrained settings. Further studies with larger and diverse patient populations are recommended to validate these results.

Association between the neutrophil-to-lymphocyte ratio and in-hospital mortality in patients with chronic kidney disease and coronary artery disease in the intensive care unit

BACKGROUND

The objective of this study was to investigate the correlation between neutrophil-to-lymphocyte ratios (NLR) and the risk of in-hospital death in patients admitted to the intensive care unit (ICU) with both chronic kidney disease (CKD) and coronary artery disease (CAD).

METHODS

Data from the MIMIC-IV database, which includes a vast collection of more than 50,000 ICU admissions occurring between 2008 and 2019, was utilized in the study and eICU-CRD was conducted for external verification. The Boruta algorithm was employed for feature selection. Univariable and multivariable logistic regression analyses and multivariate restricted cubic spline regression were employed to scrutinize the association between NLR and in-hospital mortality. The receiver operating characteristic (ROC) curves were conducted to estimate the predictive ability of NLR.

RESULTS

After carefully applying criteria to include and exclude participants, a total of 2254 patients with CKD and CAD were included in the research. The findings showed a median NLR of 7.3 (4.4, 12.1). The outcomes of multivariable logistic regression demonstrated that NLR significantly elevated the risk of in-hospital mortality (OR 2.122, 95% confidence interval [CI] 1.542-2.921, P < 0.001) after accounting for all relevant factors. Further insights from subgroup analyses unveiled that age and Sequential Organ Failure Assessment (SOFA) scores displayed an interactive effect in the correlation between NLR and in-hospital deaths. The NLR combined with traditional cardiovascular risk factors showed relatively great predictive value for in-hospital mortality (AUC 0.750).

CONCLUSION

The findings of this research indicate that the NLR can be used as an indicator for predicting the likelihood of death during a patient's stay in the intensive care unit, particularly for individuals with both CAD and CKD. The results indicate that NLR may serve as a valuable tool for assessing and managing risks in this group at high risk. Further investigation is required to authenticate these findings and investigate the mechanisms that underlie the correlation between NLR and mortality in individuals with CAD and CKD.

Leukocyte counts and ratios as potential predictors of large vessel occlusion in acute ischemic stroke: A retrospective cohort study

Leukocyte counts and ratios are independent biomarkers to determine the severity and prognosis of acute ischemic stroke (AIS). In AIS, the connection between leukocytes and large vessel occlusion (LVO) is uncertain. This study aims to determine the relationship between the existence of LVO and leukocyte counts and ratios on admission to AIS. Patients were retrospectively evaluated within six hours of AIS starting between January 2019 and April 2023. On admission, blood specimens were collected, and leukocyte subtype counts were promptly analyzed. Computed tomography or digital subtraction angiography were utilized to verify the existence of LVO. Regression analysis and receiver operating characteristic (ROC) curves were employed to investigate the connections between the counts and ratios of leukocytes and the existence of LVO, as well as the discriminatory ability of these variables in predicting LVO. Total white blood cell (WBC) count, neutrophil count, and neutrophil-to-lymphocyte ratio (NLR) were substantially higher in the LVO existence group compared to the LVO absence group, whereas the ratio of eosinophils to neutrophils (ENR × 102) was lower (P < .001, respectively). Significant associations were observed between total WBC counts, neutrophil counts, NLR, and ENR × 102 and the existence of LVO (P < .001, respectively). Total WBC counts, neutrophil counts, NLR, and ENR × 102 had respective areas under the curves (AUC) of 0.730, 0.748, 0.704, and 0.680 for identifying LVO. Our results show that in AIS patients, the existence of LVO is independently associated with elevated total WBC and neutrophil counts, high NLR, and low ENR × 102 levels. Neutrophil and total WBC counts, as well as NLR and levels of ENR × 102, may serve as potential biomarkers for predicting LVO. Neuroinflammation, based on the existence of LVO, should be given particular attention in future investigations.

Association between systemic inflammatory indicators with the survival of chronic kidney disease: a prospective study based on NHANES

Background

systemic inflammation disorders were observed in chronic kidney disease (CKD). Whether the systemic inflammatory indicators could be optimal predictors for the survival of CKD remains less studied.

Methods

In this study, participants were selected from the datasets of the National Health and Nutrition Examination Survey (NHANES) between 1999 to 2018 years. Four systemic inflammatory indicators were evaluated by the peripheral blood tests including systemic immune-inflammation index (SII, platelet*neutrophil/lymphocyte), neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), lymphocyte-to-monocyte ratio (LMR). Kaplan-Meier curves, restricted cubic spline (RCS), and Cox regression analysis were used to evaluate the association between the inflammatory index with the all-cause mortality of CKD. Receiver operating characteristic (ROC) and concordance index (C-index) were used to determine the predictive accuracy of varied systemic inflammatory indicators. Sensitive analyses were conducted to validate the robustness of the main findings.

Results

A total of 6,880 participants were included in this study. The mean age was 67.03 years old. Among the study population, the mean levels of systemic inflammatory indicators were 588.35 in SII, 2.45 in NLR, 133.85 in PLR, and 3.76 in LMR, respectively. The systemic inflammatory indicators of SII, NLR, and PLR were all significantly positively associated with the all-cause mortality of CKD patients, whereas the high value of LMR played a protectable role in CKD patients. NLR and LMR were the leading predictors in the survival of CKD patients [Hazard ratio (HR) =1.21, 95% confidence interval (CI): 1.07-1.36, p = 0.003 (3rd quartile), HR = 1.52, 95%CI: 1.35-1.72, p<0.001 (4th quartile) in NLR, and HR = 0.83, 95%CI: 0.75-0.92, p<0.001 (2nd quartile), HR = 0.73, 95%CI: 0.65-0.82, p<0.001 (3rd quartile), and = 0.74, 95%CI: 0.65-0.83, p<0.001 (4th quartile) in LMR], with a C-index of 0.612 and 0.624, respectively. The RCS curves showed non-linearity between systemic inflammatory indicators and all-cause mortality risk of the CKD population.

Conclusion

Our study highlights that systemic inflammatory indicators are important for predicting the survival of the U.S. population with CKD. The systemic inflammatory indicators would add additional clinical value to the health care of the CKD population.

Neutrophil to albumin ratio: a biomarker in non-alcoholic fatty liver disease and with liver fibrosis

Objective

Given the high prevalence of non-alcoholic fatty liver disease (NAFLD) and its potential to progress to liver fibrosis, it is crucial to identify the presence of NAFLD in patients to guide their subsequent management. However, the current availability of non-invasive biomarkers for NAFLD remains limited. Therefore, further investigation is needed to identify and develop non-invasive biomarkers for NAFLD.

Methods

A retrospective analysis was conducted on 11,883 patients admitted to the Healthcare Center, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, from January 2016 to December 2019 and divided into NAFLD and non-NAFLD groups. Anthropometric and laboratory examination data were collected. The correlations between variables and NAFLD were evaluated using the student's t-test or Mann-Whitney U test and binary logistic regression analysis. The predictive ability of these variables for NAFLD was assessed using the areas under the curves (AUCs) of receiver operating characteristics.

Results

Among the included patients, 3,872 (32.58%) were diagnosed with NAFLD, with 386 (9.97%) individuals having liver fibrosis. Patients with NAFLD exhibited a higher proportion of males, elevated body mass index (BMI), and increased likelihood of hypertension, diabetes mellitus, and atherosclerosis. Logistic regression analysis identified the neutrophil to albumin ratio (NAR) as the most promising novel inflammation biomarkers, with the highest AUC value of 0.701, a cut-off value of 0.797, sensitivity of 69.40%, and specificity of 66.00% in identifying the risk of NAFLD. Moreover, NAR demonstrated superior predictive value in identifying NAFLD patients at risk of liver fibrosis, with an AUC value of 0.795, sensitivity of 71.30%, and specificity of 73.60% when NAR reached 1.285.

Conclusion

These findings highlight that the novel inflammatory biomarker, NAR, is a convenient and easily accessible non-invasive predictor for NAFLD and NAFLD with liver fibrosis.

Machine learning identifies novel coagulation genes as diagnostic and immunological biomarkers in ischemic stroke

BACKGROUND

Coagulation system is currently known associated with the development of ischemic stroke (IS). Thus, the current study is designed to identify diagnostic value of coagulation genes (CGs) in IS and to explore their role in the immune microenvironment of IS.

METHODS

Aberrant expressed CGs in IS were input into unsupervised consensus clustering to classify IS subtypes. Meanwhile, key CGs involved in IS were further selected by weighted gene co-expression network analysis (WGCNA) and machine learning methods, including random forest (RF), support vector machine (SVM), generalized linear model (GLM) and extreme-gradient boosting (XGB). The diagnostic performance of key CGs were evaluated by receiver operating characteristic (ROC) curves. At last, quantitative PCR (qPCR) was performed to validate the expressions of key CGs in IS.

RESULTS

IS patients were classified into two subtypes with different immune microenvironments by aberrant expressed CGs. Further WGCNA, machine learning methods and ROC curves identified ACTN1, F5, TLN1, JMJD1C and WAS as potential diagnostic biomarkers of IS. In addition, their expressions were significantly correlated with macrophages, neutrophils and/or T cells. GSEA also revealed that those biomarkers may regulate IS via immune and inflammation. Moreover, qPCR verified the expressions of ACTN1, F5 and JMJD1C in IS.

CONCLUSIONS

The current study identified ACTN1, F5 and JMJD1C as novel coagulation-related biomarkers associated with IS immune microenvironment, which enriches our knowledge of coagulation-mediated pathogenesis of IS and sheds light on next-step in vivo and in vitro experiments to elucidate the relevant molecular mechanisms.

An Explainable Artificial Intelligence Model to Predict Malignant Cerebral Edema after Acute Anterior Circulating Large-Hemisphere Infarction

INTRODUCTION

Malignant cerebral edema (MCE) is a serious complication and the main cause of poor prognosis in patients with large-hemisphere infarction (LHI). Therefore, the rapid and accurate identification of potential patients with MCE is essential for timely therapy. This study utilized an artificial intelligence-based machine learning approach to establish an interpretable model for predicting MCE in patients with LHI.

METHODS

This study included 314 patients with LHI not undergoing recanalization therapy. The patients were divided into MCE and non-MCE groups, and the eXtreme Gradient Boosting (XGBoost) model was developed. A confusion matrix was used to measure the prediction performance of the XGBoost model. We also utilized the SHapley Additive exPlanations (SHAP) method to explain the XGBoost model. Decision curve and receiver operating characteristic curve analyses were performed to evaluate the net benefits of the model.

RESULTS

MCE was observed in 121 (38.5%) of the 314 patients with LHI. The model showed excellent predictive performance, with an area under the curve of 0.916. The SHAP method revealed the top 10 predictive variables of the MCE such as ASPECTS score, NIHSS score, CS score, APACHE II score, HbA1c, AF, NLR, PLT, GCS, and age based on their importance ranking.

CONCLUSION

An interpretable predictive model can increase transparency and help doctors accurately predict the occurrence of MCE in LHI patients not undergoing recanalization therapy within 48 h of onset, providing patients with better treatment strategies and enabling optimal resource allocation.

How well does peripheral blood neutrophil-to-lymphocyte ratio predict the severity and prognosis of hemorrhagic Stroke

OBJECTIVE

We explored the blood neutrophil-to-lymphocyte ratio (NLR) as a prognostic marker and its relation with mortality and Modified Rankin Scale (mRS) score at discharge and at 3 months following ICH and also compared NLR with intracerebral hemorrhage (ICH) score, Sequential Organ Failure Assessment (SOFA) score and National Institutes of Health Stroke Scale (NIHSS) score.

METHODS

The investigators calculated the NIHSS score, SOFA score, ICH score and NLR of 90 adult patients within 3 days of onset of stroke with evidence of hemorrhagic stroke in brain imaging and correlated it with in-hospital mortality, 3-month mortality and mRS at 3 months following stroke using regression analysis.

RESULTS

Out of 90 individuals, there were 54 (60%) males and 36 (40%) females. The mRS score at 3 months significantly related to the admission NLR ratio >7 and SOFA score. Similarly, the in-hospital death and 3-month mortality was related to the admission NLR ratio >7 and ICH score. However, at a cut off value of NLR>3 for assessing the prognosis of the patients, we did not get significant results for mRS at 3 months following stroke and for in-hospital and 3-month mortality.

CONCLUSION

A high NLR ratio >7 predicted worse outcomes in terms of mortality and morbidity at 3-months following haemorrhagic stroke. Hence, like ICH score, NLR can predict 3-month mortality following an acute haemorrhagic stroke and can also predict morbidity following 3 months of brain haemorrhage.

Automated evaluation of collateral circulation for outcome prediction in acute ischemic stroke

INTRODUCTION

The assessment of collateral circulation in acute ischemic stroke management is essential. Modern tools, such as Brainomix's e-CTA, powered by artificial intelligence, provide detailed insights into collateral assessment. This retrospective study aims to identify factors contributing to favorable collateral status and compare outcomes between patients with good collaterals (grade 3) and fair collaterals (grade 0-2).

METHOD

This retrospective study included 97 patients admitted to the Stroke Unit at the Hospital de Clínicas of the Federal University of Paraná, Brazil, from September 2021 to January 2023. Comparative analyses involved demographic factors, cardiovascular risk factors, and the combined outcome of mortality and moderate to severe disability at discharge, 30-day, and 90-day follow-ups.

RESULTS

Among the 97 cases, 58.8 % showed 'good collaterals' with a grade 3 status. Variables affecting collateral status included age (p = 0.042), neutrophil-lymphocyte ratio (p = 0.005), and initial NIHSS scores (p<0.001). The presence of good collaterals according to e-CTA reduced the odds of death and moderate-severe disability at discharge (p = 0.003; OR 0.27) and at 30 days (p = 0.015; OR 0.33), although this effect diminished at the 90-day mark after multivariate analysis.

DISCUSSION

Automated collateral assessment through e-CTA is a valuable tool in acute ischemic stroke evaluation. Good e-CTA collateral score serve as a promising imaging biomarker, guiding informed clinical decisions during Stroke Unit hospitalizations. This study highlights the relationship between collaterals and stroke outcomes and underscores the potential for AI-driven tools to enhance stroke care management.

Blood and CSF findings of cellular immunity in anti-NMDAR encephalitis

OBJECTIVES

To investigate the immunopathogenic mechanisms of anti-N-methyl-D-aspartate receptor encephalitis (NMDAR-E) by characterizing the changes of immune cells in both peripheral blood (PB) and cerebrospinal fluid (CSF) of patients with NMDAR-E.

METHODS

Cytology and flow cytometry were used to explore and compare different immunological parameters in PB and CSF of patients with NMDAR-E, viral encephalitis (VE) and healthy volunteers. Moreover, different models were established to assess the possibility of identifying NMDAR-E patients based on PB and CSF parameters.

RESULTS

The neutrophil counts and monocyte-to-lymphocyte ratios (MLR) in PB are higher in NMDAR-E patients than in both VEs and controls (P < 0.001, respectively), while the percentages of CD3 + T, CD4 + T lymphocytes, and the leukocytes count in CSF were lower in NMDAR-Es than in VEs (P < 0.01, respectively). The higher percentages of CD8 + T cells in blood and CSF were both correlated with more severe NMDAR-E (P < 0.05, respectively). The poor neurological status group had significantly higher PB leukocytes but lower CSF leukocyte count (P < 0.05). Longitudinal observations in patients with NMDAR-E showed a decreasing trend of leukocyte count, neutrophils count, neutrophil-to-monocyte ratios (NMR), and neutrophil-to-lymphocyte ratios (NLR) with the gradual recovery of neurological function.

CONCLUSIONS

The expression patterns of T lymphocyte subsets were different in patients with NMDAR-E and viral encephalitis. The changing trends of leukocyte and lymphocyte populations in peripheral blood and cerebrospinal fluid may provide clues for the diagnosis of different types of encephalitides, including NMDARE, and can be used as immunological markers to assess and predict the prognosis.

Serum ferritin is associated with the presence of ischemic stroke among individuals with type 2 diabetes

Background

Epidemiological evidence regarding the possible link between serum ferritin (SF) level and ischemic stroke risk among individuals with type 2 diabetes mellitus (T2DM) is sparse.

Aim

To evaluate the association between SF level in plasma and ischemic stroke risk among individuals with T2DM.

Methods

SF levels were measured in 210 T2DM patients with (n = 165) or without ischemic stroke (n = 45). Multivariate logistic regression analyses were used to estimate odds ratios (ORs) and 95% confidence intervals (CIs).

Results

The SF level of T2DM patients with ischemic stroke was significantly higher than that of patients without ischemic stroke (P = 0.003). The multivariate logistic regression analyses revealed that each 1-SD increase in SF (OR: 1.92; 95%CI: 1.22, 3.03) was significantly associated with increased ischemic stroke risk among T2DM patients. In addition, interaction effect of SF and BMI on ischemic stroke risk were also observed (Pfor interaction = 0.037).

Conclusions

Higher levels of SF were independently associated with increased risk of ischemic stroke among individuals with T2DM.