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

Role of thyroid function in non-basal ganglia intracerebral hemorrhage prognosis

PURPOSE

Thyroid function disorders serve as unfavorable prognosis predictors for numerous diseases. However, their role in predicting intracerebral hemorrhage outcome is unclear. This study investigated the prognostic potential of thyroid function parameters for intracerebral hemorrhage.

METHODS

Admissions for intracerebral hemorrhage caused by hypertension were retrospectively enrolled to determine thyroid function levels. Patients were subjected to three month- and three year-follow up to assess short- and long-term prognosis, respectively.

RESULTS

Elevated levels of thyroxine and decreased levels of free triiodothyronine (fT3) are associated with unfavorable short-term prognosis in non-basal ganglia intracerebral hemorrhage patients. The levels of thyroid stimulating hormone and free tetraiodothyronine did not exhibit any significant change. This alteration in thyroid function was not observed in basal-ganglia intracerebral hemorrhage patients. Furthermore, the inclusion of thyroxine and fT3 enhanced the prognostic power of the traditional model (NIHSS only) in predicting short-term outcomes. Among patients 55 years or older, subgroup analyses results are consistent with previous findings. Additionally, our clinical model is also applicable towards predicting the long-term prognosis of non-basal ganglia intracerebral hemorrhage.

CONCLUSION

Thyroid function concentrations, especially the levels of thyroxine and fT3, could serve as key prognostic predictors for non-basal ganglia cerebral hemorrhage, especially among the middle-aged and elderly groups.

Pathogenic bacteria features of central line-associated bloodstream infections in ICU patients: focus on the early predictive value of neutrophil-to-lymphocyte and platelet-to-lymphocyte ratios

Objective

Explore and analyze CLABSI pathogenic bacteria characteristics in ICU patients and the value of PCT, NLR, PLR in early infection prediction.

Methods

926 ICU patients with central venous catheters in Minhang Hospital from January 2021 to December 2023 were enrolled. They were grouped by co-infection status. PCT, NLR and PLR levels were measured, patient data analyzed, pathogenic bacteria characteristics summarized, and their predictive value evaluated via ROC curve.

Results

From January 2021 to December 2023, among the 926 patients with CVC, 73 were diagnosed with CLABSI, with an infection rate of 7.88%. A total of 81 strains of pathogenic bacteria were isolated, including 60.50% (49/81) Gram - positive bacteria, 35.80% (29/81) Gram - negative bacteria, and 3.70% (3/81) fungi. The main Gram - positive bacteria exhibited high resistance to penicillin, erythromycin, clindamycin, and oxacillin, with a resistance rate exceeding 70%, yet were sensitive to vancomycin, linezolid, and tetracycline. The main Gram - negative bacteria had high resistance to piperacillin, piperacillin/tazobactam, Aztreonam, and gentamicin, with a resistance rate over 70%, and were more sensitive to cefoperazone/sulbactam, imipenem, and amikacin. Age, the site of catheterization, the duration of catheterization, and the employment of double - cavity catheters were all factors that exerted an influence on CLABSI among ICU patients (with p < 0.05). The levels of peripheral blood NLR, PLR, and PCT in the infected group were higher than those in the non - infected group (p < 0.05). The areas under the curve (AUCs) of peripheral blood NLR, PLR, and PCT were 0.814, 0.798, and 0.856, respectively, with the largest AUC for PCT. When the cut - off point was 2.75 ng/ml, the Youden index was the largest. The AUCs of the combination of peripheral blood NLR and PLR, NLR and PCT, PLR and PCT, and all three combined were 0.877, 0.903, 0.857, and 0.917.

Conclusion

The early prediction of CLABSI in ICU patients by means of PCT, NLR, and PLR is of remarkable significance. It can provide a precious reference for clinical diagnostic and treatment strategies.

Clinical value of inflammatory indices in predicting poor prognosis and post-hemorrhagic hydrocephalus in patients with intraventricular hemorrhage

BACKGROUND

Hemorrhagic stroke has a high mortality and disability rate. Among them, intraventricular hemorrhage (IVH) is an important factor leading to adverse outcomes. IVH can induce acute obstructive hydrocephalus and chronic communicating hydrocephalus. However, there are currently no effective predictive factors for the early prediction of post-hemorrhage hydrocephalus (PHH).

OBJECTIVES

To assess the role of inflammatory indicators in predicting PHH and poor prognostic outcomes in patients with ventricular hemorrhage.

DESIGN

Single center retrospective case-control study.

METHODS

We retrospectively examined IVH patients treated at our institution from April 2017 to March 2022. Patient characteristics, laboratory data, imaging findings, and 3-month follow-up results were recorded and analyzed.

RESULTS

Among the 145 patients included in the analysis, 102 eventually developed adverse outcomes. There were significant differences between patients with good and poor prognosis in terms of age at admission, GCS score, prevalence of hypertension, lymphocyte count, albumin level, red blood cell distribution width, neutrophil count, NLR, PLR, NAR, PIV, and SII; in addition, among the 110 surviving patients, 36 eventually developed posthemorrhagic hydrocephalus within 3 months. Multivariate logistic regression showed that age and NAR are independent predictors of poor prognosis in IVH patients, while albumin is an independent predictor of posthemorrhagic hydrocephalus within 3 months.

CONCLUSION

The NLR and NAR are independent risk factors for poor prognosis in IVH patients. Additionally, albumin is an independent predictor of chronic hydrocephalus development within 3 months in IVH patients. The NLR, NAR and albumin level could provide prognostic information about IVH patients.

The predictive role of composite inflammatory ratio parameters in the conscious awareness recovery after severe acute ischemic stroke: a retrospective cohort study

BACKGROUND

Inflammatory mechanisms play a significant role in ischemic stroke. Peripheral neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), systemic immune-inflammation index (SII), systemic inflammation response index (SIRI), which are indicators capable of reflecting the magnitude of the inflammatory response, have been research hotspots. However, few research findings evaluate the prediction significance of these biomarkers in the recovery of conscious awareness following severe acute ischemic stroke.

METHODS

This was a retrospective cohort study of 142 patients with consciousness disorders after acute ischemic stroke (GCS score ≤ 8) treated from January 2022 to May 2024. The cases were divided into three groups according to the GCS score at discharge as died/ vegetative state (GCS ≤ 3),moderate/ severe coma(GCS = 4-11) and mild coma/ normal (GCS:12-15). Demographic and clinical assessment data were reviewed and abstracted. NLR, PLR, SII and SIRI were calculated based on the peripheral blood tests at admission. The study investigated the correlation between changes in GCS scores from admission to discharge (calculated as the GCS score at discharge minus the baseline GCS score, where a negative value indicates worsening and a positive value indicates improvement) and the levels of NLR, PLR, SII, and SIRI.

RESULTS

The level of NLR, PLR, SII and SIRI in died/ vegetative state group were significantly higher than those in moderate/ severe coma group (p = 0.0429, p = 0.0215, p = 0.0288, p = 0.026, respectively) and mild coma/ normal group (p = 0.0085, p = 0.0079, p = 0.0019, p = 0.0017, respectively). The area under the curve (AUC) values of NLR, PLR, SII, and SIRI to prognosis were 0.670, 0.661, 0.677, and 0.609, respectively. Spearman correlation analysis indicated NLR, PLR and SII were negatively correlated with GCS scores increase during hospitalization (r =- 0.317, p<0.0001 for NLR, r = -0.285, p = 0.001 for PLR, r = -0.3331, p < 0.0001 for SII, r= -0.199,p = 0.018 for SIRI).However, ordinal logistic regression analyses failed to indicate that NLR, PLR, SII and SIRI were independent predictors of poor consciousness response for severe acute ischemic stroke coma patients after adjusting for other confounders.

CONCLUSION

Patients with poorer consciousness outcomes exhibited a tendency towards elevated NLR, PLR, SII, and SIRI levels which were inversely correlated with GCS scores increase during hospitalization. However, the four indexes did not exhibit sufficient promise to be the valuable predictors for the prognosis of recovery from consciousness following severe acute ischemic stroke.

A Novel Nomogram for Predicting the Risk of Pneumonia After Intracerebral Hemorrhage

Background

Pneumonia is among the most dangerous complications of infection after intracerebral hemorrhage. We aimed to create a novel nomogram for pneumonia after intracerebral hemorrhage.

Methods and Results

The data from the Chinese Cerebral Hemorrhage: Mechanism and Intervention (CHEERY) study was analyzed. Thirty percent of qualified patients were placed in the validation group (n=763) while seventy percent of them were randomly placed in the training group (n=1784). In the multivariate analysis, ten variables were included in the model: age (β= 0.023, P<0.001), hospital days (β=0.392, P<0.001), baseline mRS score (β=0.484, P<0.001), baseline GCS score (β=-0.285, P<0.001), hs-CRP (β=0.328, P<0.001), hematoma volume (β=0.376, P<0.001), brainstem hemorrhage (β=0.956, P=0.002), intraventricular hemorrhage (β=0.629, P=0.001), and β-blocker (β=0.899, P<0.001) In the training subset, the areas under curve were 0.805 (95% CI, 0.773-0.833). The model was subsequently examined in the validation group, with the area under curve 0.767 (95% CI, 0.716-0.807). There was strong agreement between the anticipated and actual survival rates in the nomogram calibration curves for both the training and validation groups. The clinical value of the model is assessed by means of Decision Curve Analysis. In addition, we validated other models with this cohort, which showed that our model had better discrimination. Moreover, the area under the curve of the catboost model established using the above nine variables in the training set and the validation set is 0.87(95% CI, 0.80-0.90) and 0.77(95% CI, 0.72-0.80).

Conclusion

We have established a simple and easy predictive tool. By evaluating the incidence of pneumonia after intracerebral hemorrhage, we can identify high-risk groups early. At the same time, our study also suggests that doctors should be cautious in the use of β-blocker in clinical decision-making.

A novel nomogram for predicting postoperative pneumonia risk in patients with localized bronchiectasis

BACKGROUND

Pneumonia is one of the most common complications after lung resection. However, there are currently no reports of postoperative pneumonia in patients with bronchiectasis.

OBJECTIVES

Our study aims to construct a new nomogram to predict the risk of postoperative pneumonia in patients with localized bronchiectasis.

DESIGN

The clinical data of patients with localized bronchiectasis from April 2012 to August 2022 were retrospectively analyzed.

METHODS

Independent risk factors were identified through simple linear regression and multiple linear regression analysis, and a new nomogram was constructed based on independent risk factors. The validity of the nomogram was evaluated using the consistency index (C-index), receiver operating characteristic curve, calibration chart, and decision curve analysis chart.

RESULTS

The new nomogram prediction model included five independent risk factors: tuberculosis history, smoking history, platelet-lymphocyte ratio (PLR), diffusing capacity of the lung for carbon monoxide, and controlled nutritional status score. The area under the curve of the prediction model is 0.870 (95% CI: 0.750-0.892), showing good discrimination ability, and the probability threshold was set at 0.2013. In addition, the calibration curve shows that the nomogram has good calibration. In the decision curve, the nomogram model showed good clinical net benefit.

CONCLUSION

This study is the first to construct a nomogram prediction model for postoperative pneumonia of localized bronchiectasis, which can more accurately and directly assess the risk probability of postoperative pneumonia, and provide certain help for clinicians in prevention and treatment decisions.

Correlation between peripheral blood inflammatory markers and delayed cerebral ischemia after intracerebral hemorrhage

OBJECTIVE

To assess the predictive value of peripheral blood inflammatory markers for delayed cerebral ischemia (DCI) in patients with intracerebral hemorrhage (ICH) and explore methods for early intervention.

METHODS

This single-center retrospective study reviewed medical records of ICH patients admitted to Cangzhou People's Hospital over a 12-month period from January 2022 to December 2023. Of the 150 identified patients with ICH, including 80 patients without DCI (control group) and 70 with DCI (observation group). Demographics and blood biochemical markers during hospitalization were recorded. Binary logistic regression was used to identify independent factors influencing DCI occurrence.

RESULTS

Significant differences were observed between the two groups in neutrophil percentage, lymphocyte percentage, lymphocytes absolute and neutrophil-to-lymphocyte ratio (NLR) (all P<0.05). Logistic regression analysis identified mRS score, lymphocyte percentage, educational level, uric acid, neutrophils percentage, and NLR as independent risk factors for DCI.

CONCLUSION

Neutrophil percentage and NLR are independent factors influencing delayed cerebral ischemia after intracerebral hemorrhage. These markers are readily accessible and may provide valuable insights for early ICH management.

An updated review for clinical and radiological predictors of acute intraparenchymal hematoma progression in cerebral contusion

Backgrounds

The rapid expansion of an intraparenchymal hematoma following cerebral contusion often results in high mortality rates and a poor prognosis. Effective tools are essential for predicting and monitoring the incidence of traumatic intraparenchymal hematoma (tICH) and identifying patients at high risk of tICH expansion. This enables timely surgical interventions and appropriate medical management. Recently, numerous novel predictive tools have been developed and employed to predict tICH progression. Therefore, this review aims to outline the latest advancements in predicting tICH expansion.

Methods

To find relevant studies, a search was conducted on PubMed and Google Scholar for articles published from January 2020 to April 2024. The search string used was (Cerebral Contusion) AND (Intraparenchymal Hematoma Progression OR Parenchymal Hematoma Expansion OR Intracerebral Hemorrhage Progression) AND (Predictor or Forecasting Tool).

Results

In this narrative review, we focused on various radiological, clinical, and innovative indicators of acute tICH progression that have been developed and/or validated in recently years. Additionally, we explore the impact of tICH progression on long-term outcomes, suggesting potential avenues for future research. The spread of depolarization in the cortex could be a key factor in forecasting and controlling the growth of tICH in the times ahead.

Conclusions

This study offers a comprehensive look at various cutting-edge imaging predictors, inflammatory indices, and integrated predictors that can aid neurosurgeons in categorizing, handling, and treating high-risk patients with acute tICH expansion.

A retrospective cohort study on a novel marker to predict the severity and prognosis of acute cerebral venous thrombosis: D-dimer to fibrinogen ratio

BACKGROUND AND AIM

The D-dimer to fibrinogen ratio (DFR) represents an emerging and significant clinical biomarker. However, its correlation with cerebral venous thrombosis (CVT) remains underexplored. This retrospective cohort study aims to elucidate the association between DFR values and the severity and prognosis of CVT.

METHODS

Severe CVT was defined as the presence of at least 1 of the following risk factors: mental status disorder, coma state, intracranial cerebral hemorrhage, or thrombosis of the deep cerebral venous system. The modified Rankin Scale was utilized to assess functional outcomes. DFR measurements were obtained within 24 h of hospital admission. Logistic regression analysis was employed to determine the prognostic significance of DFR. After Bonferroni correction, a two-tailed P value < 0.017 (0.05/3) was considered statistically significant.

RESULT

A total of 196 patients were included in the study, among whom 85 patients were diagnosed with severe CVT, and 35 and 14 patients experienced short-term and long-term adverse outcomes, respectively. Receiver operating characteristic curve analysis demonstrated that DFR has predictive value for severe CVT, poor short-term and long-term outcomes, with area under the curve values of 0.690 [95% CI: 0.617-0.764, P < .001], 0.773 [95% CI: 0.701-0.845, P < .001], and 0.754 [95% CI: 0.619-0.886, P = .002], respectively. DFR ≥ 0.253 was identified as a significant predictor of severe CVT [adjusted odds ratio (aOR) (95% CI): 2.03 (1.10-3.75), P = .024]. Additionally, DFR ≥ 0.322 and DFR ≥ 0.754 were significantly associated with poor short-term outcomes at discharge [aOR (95% CI): 2.63 (1.43-4.76), P = .002] and poor long-term outcomes at 12 months [aOR (95% CI): 2.86 (1.32-6.25), P = .008], respectively.

CONCLUSION

Elevated DFR is associated with increased severity of CVT. Additionally, higher DFR levels can predict poorer clinical outcomes in CVT.

Predictive value of the dynamic systemic immune-inflammation index in the prognosis of patients with intracerebral hemorrhage: a 10-year retrospective analysis

Background and purpose

The systemic immune-inflammation index (SII) is a novel immune inflammatory marker which has been proven to have excellent predictive value for many diseases. The aim of this study was to investigate the predictive value of SII at different time points after admission for functional outcome at discharge in patients with intracerebral hemorrhage (ICH).

Methods

The clinical data of patients with ICH who were treated at a medical center for neurological diseases in China between October 2012 and April 2022 were analyzed in this retrospective study. The SII was calculated based on neutrophil×platelet/lymphocyte counts and collected within the first 14 days after admission to analyze the dynamic changes. Adverse outcome was defined as a modified Rankin Scale (mRS) score of 4-6 at discharge. The correlation between the SII and the outcome was assessed using univariate and multivariate logistic regression analyses. The ability of SII to predict outcome was evaluated by the area under the receiver operating characteristic (ROC) curve (AUC).

Results

A total of 1,569 patients with ICH were included, of whom 790 had adverse outcome (50.35%). The Univariate logistic regression analysis showed that SII at any time point within 14 days after admission was significantly associated with adverse outcome. In the multivariate logistic regression analysis, the SII within 7 days after admission was found to be an independent predictor of adverse functional outcome in ICH patients at discharge. The ROC curve demonstrated that compared to other time points, the SII on day 2 after admission exhibited stronger predictive power for the functional outcome of patients with ICH at discharge (AUC:0.733, 95%CI = 0.679-0.787) (sensitivity 47.09%, specificity 87.02%) (OR 1.074, 95%CI = 1.033-1.126, p = 0.001).

Conclusion

SII within 7 days after admission, especially on day 2, is independently associated with adverse functional outcome in ICH patients at discharge. This association could be utilized in clinical practice and warrants further investigation.

Development and validation of a nomogram for predicting mortality in patients with acute severe traumatic brain injury: A retrospective analysis

BACKGROUND

Recent evidence links the prognosis of traumatic brain injury (TBI) to various factors, including baseline clinical characteristics, TBI specifics, and neuroimaging outcomes. This study focuses on identifying risk factors for short-term survival in severe traumatic brain injury (sTBI) cases and developing a prognostic model.

METHODS

Analyzing 430 acute sTBI patients from January 2018 to December 2023 at the 904th Hospital's Neurosurgery Department, this retrospective case-control study separated patients into survival outcomes: 288 deceased and 142 survivors. It evaluated baseline, clinical, hematological, and radiological data to identify risk and protective factors through univariate and Lasso regression. A multivariate model was then formulated to pinpoint independent prognostic factors, assessing their relationships via Spearman's correlation. The model's accuracy was gauged using the Receiver Operating Characteristic (ROC) curve, with additional statistical analyses for quantitative factors and model effectiveness. Internal validation employed ROC, calibration curves, Decision Curve Analysis (DCA), and Clinical Impact Curves (CIC) to assess model discrimination, utility, and accuracy. The International Mission for Prognosis and Analysis of Clinical Trials in TBI (IMPACT) and Corticosteroid Randomization After Significant Head injury (CRASH) models were also compared through multivariate regression.

RESULTS

Factors like unilateral and bilateral pupillary non-reactivity at admission, the derived neutrophil to lymphocyte ratio (dNLR), platelet to lymphocyte ratio (PLR), D-dimer to fibrinogen ratio (DFR), infratentorial hematoma, and Helsinki CT score were identified as independent risk factors (OR > 1), whereas serum albumin emerged as a protective factor (OR < 1). The model showed superior predictive performance with an AUC of 0.955 and surpassed both IMPACT and CRASH models in predictive accuracy. Internal validation confirmed the model's high discriminative capability, clinical relevance, and effectiveness.

CONCLUSIONS

Short-term survival in sTBI is significantly influenced by factors such as pupillary response, dNLR, PLR, DFR, serum albumin levels, infratentorial hematoma occurrence, and Helsinki CT scores at admission. The developed nomogram accurately predicts sTBI outcomes, offering significant clinical utility.

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

INTRODUCTION

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

A comprehensive prediction model predicts perihematomal edema growth in the acute stage after intracerebral hemorrhage

BACKGROUND

Perihematomal edema (PHE) is regarded as a potential intervention indicator of secondary injury following intracerebral hemorrhage (ICH). But it still lacks a comprehensive prediction model for early PHE formation.

METHODS

The included ICH patients have received an initial Computed Tomography scan within 6 hours of symptom onset. Hematoma volume and PHE volume were computed using semiautomated computer-assisted software. The volume of the hematoma, edema around the hematoma, and surface area of the hematoma were calculated. The platelet-to-lymphocyte ratio (PLR) was calculated by dividing the platelet count by the lymphocyte cell count. All analyses were 2-tailed, and the significance level was determined by P <0.05.

RESULTS

A total of 226 patients were included in the final analysis. The optimal cut-off values for PHE volume increase to predict poor outcomes were determined as 5.5 mL. For clinical applicability, we identified a value of 5.5 mL as the optimal threshold for early PHE growth. In the multivariate logistic regression analyses, we finally found that baseline hematoma surface area (p < 0.001), expansion-prone hematoma (p < 0.001), and PLR (p = 0.033) could independently predict PHE growth. The comprehensive prediction model demonstrated good performance in predicting PHE growth, with an area under the curve of 0.841, sensitivity of 0.807, and specificity of 0.732.

CONCLUSION

In this study, we found that baseline hematoma surface area, expansion-prone hematoma, and PLR were independently associated with PHE growth. Additionally, a risk nomogram model was established to predict the PHE growth in patients with ICH.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

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

PURPOSE

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

PATIENTS AND METHODS

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

RESULTS

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

CONCLUSION

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

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

PURPOSE

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

PATIENTS AND METHODS

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

RESULTS

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

CONCLUSION

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

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

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

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

Objective

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

Methods

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

Results

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

Conclusion

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

Neutrophil-To-Lymphocyte Ratio as a Prognostic Indicator in Thyroid Cancer

OBJECTIVE

In this study, we aimed to perform a comprehensive analysis to assess the prognostic value of neutrophil-to-lymphocyte ratio (NLR) levels in patients diagnosed with thyroid cancer.

METHODS

We systematically searched multiple databases, including PubMed, the Cochrane Library, EMBASE, and Google Scholar, up until March 30, 2023, to identify relevant articles. The clinical outcomes evaluated in this study included overall survival (OS), progression-free survival (PFS), disease-free survival (DFS), and cause-specific survival (CSS).

RESULTS

This analysis includes 21 articles with 5187 patients in total. The pooled results revealed that patients with high NLR levels had significantly poorer OS (HR: 2.578, 95% CI: 2.050-3.242, P < 0.001), PFS (HR: 2.143, 95% CI: 1.616-2.843, P < 0.001), DFS (HR: 1.377, 95% CI: 1.045-1.816, P = 0.023), and CSS (HR: 2.842, 95% CI: 1.334-6.053, P = 0.007). The subgroup analyses were performed based on different study regions, treatment modalities, cancer types, and NLR cut-off values, and the above conclusion remained consistent in the majority of subgroup analyses. The stability and reliability of the aforementioned results were supported by the sensitivity analysis and publication bias test.

CONCLUSION

The baseline NLR levels were useful predictors of outcomes in patients with thyroid cancer.

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

Background

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

Methods

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

Results

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

Conclusion

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

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

Background

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

Methods

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

Results

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

Conclusion

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

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

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

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

Background

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

Methods

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

Results

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

Conclusions

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