Nomogram Including Neutrophil-to-Lymphocyte Ratio for the Prediction of Stroke-Associated Infections

GNRI, PLR and Stroke-Associated Pneumonia: From Association to Development of a Web-Based Dynamic Nomogram

Objective

Discussing the relationship between geriatric nutritional risk index (GNRI) and platelet-to-lymphocyte ratio (PLR) on stroke-associated pneumonia (SAP) in acute ischemic stroke (AIS) patients, developing and validating a web-based dynamic nomogram.

Methods

A total of 996 AIS patients admitted to the Department of General Medicine and Neurology at Xuzhou Medical University Affiliated Hospital were collected. They were divided into Non-SAP group and SAP group based on the occurrence of SAP. The data was randomly divided into training set and validation set in a ratio of 7:3. LASSO regression and multivariable logistic regression analysis were used to screen for independent risk factors and develop a dynamic nomogram. Area under the receiver operating characteristic curve (AUC-ROC), calibration curve, and decision curve analysis (DCA) curve were used to validate the model's discriminative ability, calibration, and clinical value, respectively.

Results

Among AIS patients, a total of 221 cases (22.19%) developed SAP. Age, NIHSS score, comorbid atrial fibrillation, dysphagia, PLR, and GNRI were identified as independent factors influencing the occurrence of SAP in AIS patients. A web-based dynamic nomogram was developed based on these six variables. The training set showed an AUC-ROC of 0.864 (95% CI: 0.828-0.892), while the validation set showed an AUC-ROC of 0.825 (95% CI: 0.772-0.882), indicating good predictive ability and discrimination of the model. The calibration curve demonstrated good calibration of the model, and the DCA curve showed its clinical value. This model can be accessed and utilized by anyone on the website (https://moonlittledoctor.shinyapps.io/ANADPG/).

Conclusion

PLR and GNRI are independent factors influencing the occurrence of SAP in AIS patients, and a dynamic nomogram was constructed to predict the risk of SAP in AIS patients. It can guide clinical decision-making and improve patient prognosis.

The assessment of dysphagia after stroke: state of the art and future directions

Dysphagia is a major complication following an acute stroke that affects the majority of patients. Clinically, dysphagia after stroke is associated with increased risk of aspiration pneumonia, malnutrition, mortality, and other adverse functional outcomes. Pathophysiologically, dysphagia after stroke is caused by disruption of an extensive cortical and subcortical swallowing network. The screening of patients for dysphagia after stroke should be provided as soon as possible, starting with simple water-swallowing tests at the bedside or more elaborate multi-consistency protocols. Subsequently, a more detailed examination, ideally with instrumental diagnostics such as flexible endoscopic evaluation of swallowing or video fluoroscopy is indicated in some patients. Emerging diagnostic procedures, technical innovations in assessment tools, and digitalisation will improve diagnostic accuracy in the future. Advances in the diagnosis of dysphagia after stroke will enable management based on individual patterns of dysfunction and predisposing risk factors for complications. Progess in dysphagia rehabilitation are essential to reduce mortality and improve patients' quality of life after a stroke.

Development and validation of a nomogram model for predicting unfavorable functional outcomes in ischemic stroke patients after acute phase

Introduction

Prediction of post-stroke functional outcome is important for personalized rehabilitation treatment, we aimed to develop an effective nomogram for predicting long-term unfavorable functional outcomes in ischemic stroke patients after acute phase.

Methods

We retrospectively analyzed clinical data, rehabilitation data, and longitudinal follow-up data from ischemic stroke patients who underwent early rehabilitation at multiple centers in China. An unfavorable functional outcome was defined as a modified Rankin Scale (mRS) score of 3-6 at 90 days after onset. Patients were randomly allocated to either a training or test cohort in a ratio of 4:1. Univariate and multivariate logistic regression analyses were used to identify the predictors for the development of a predictive nomogram. The area under the receiver operating characteristic curve (AUC) was used to evaluate predictive ability in both the training and test cohorts.

Results

A total of 856 patients (training cohort: n = 684; test cohort: n = 172) were included in this study. Among them, 518 patients experienced unfavorable outcomes 90 days after ischemic stroke. Trial of ORG 10172 in Acute Stroke Treatment classification (p = 0.024), antihypertensive agents use [odds ratio (OR) = 1.86; p = 0.041], 15-day Barthel Index score (OR = 0.930; p < 0.001) and 15-day mRS score (OR = 13.494; p < 0.001) were selected as predictors for the unfavorable outcome nomogram. The nomogram model showed good predictive performance in both the training (AUC = 0.950) and test cohorts (AUC = 0.942).

Conclusion

The constructed nomogram model could be a practical tool for predicting unfavorable functional outcomes in ischemic stroke patients underwent early rehabilitation after acute phase.

Correlation between nutritional status screening by MNA-SF and acute stroke-associated infections in older adults

PURPOSE

This study aimed to explore the correlation between nutritional status screening using the MNA-SF and stroke-associated infections (SAI) in older adults.

METHODS

A retrospective study of patients aged over 70 years with acute stroke was conducted. The patients were divided into normal nutritional status, malnutrition risk, and malnutrition groups depending on their baseline MNA-SF scores. The correlation between nutritional status and SAI was identified using multivariate logistic regression. The receiver operating characteristic (ROC) curve was used to demonstrate the predicted value of MNA-SF.

RESULTS

497 patients were included, 101 (20.32%) developed SAI. 32.29% of patients with malnutrition developed SAI, while 25.14% of those with malnutrition risk developed SAI. Malnutrition (aOR 4.58, 95% CI 2.34-8.96, p < 0.001) and risk of malnutrition (aOR 3.70, 95%CI 2.01-6.85, p < 0.001) were independent risk factors for SAI in older stroke patients. The area under the curve (AUC) value of MNA-SF was 0.713.

CONCLUSION

MNA-SF is a simple and effective nutritional screening tool for predicting the occurrence of SAI in older patients with acute stroke.

Optimal time point for neutrophil-to-lymphocyte ratio to predict stroke-associated pneumonia

PURPOSE

This study aimed at the population receiving thrombolytic therapy and to explore the optimal time point for neutrophil-to-lymphocyte ratio (NLR) in predicting stroke-associated pneumonia (SAP).

METHODS

We assessed patients undergoing intravenous thrombolysis (IVT) for acute ischemic stroke. Blood parameters were sampled before thrombolysis (within 30 min after admission) and within 24-36 h after thrombolysis, respectively. The primary outcome measure was the occurrence of SAP. Multivariate logistic regression analysis was performed to analyze the association between admission blood parameters and the event of SAP. We also used receiver operating characteristic (ROC) curve analysis to assess the discriminative ability of blood parameters measured at different times in predicting SAP.

RESULTS

Among the 388 patients, SAP occurred in 60 (15%) patients. Multivariate logistic regression analysis showed that NLR was significantly associated with SAP (NLR before IVT: aOR = 1.288; 95%CI = 1.123-1.476; p < 0.001; NLR after IVT: (aOR = 1.127, 95%CI = 1.017-1.249; p = 0.023). The ROC curve showed that the predictive ability of NLR after IVT was better than NLR before IVT, not only in predicting the occurrence of SAP but also in predicting short-term and long-term functional outcomes, hemorrhagic transformation, and 1-year mortality.

CONCLUSION

Increased NLR measured within 24-36 h after IVT has a significant predictive effect on the occurrence of SAP and can be used to predict short-term and long-term poor functional outcomes, hemorrhagic transformation, and 1-year mortality.

Swallowing function after acute ischemic stroke: Development and validation of a novel clinical prognostic model

Background

Predicting the duration of dysphagia after acute ischemic stroke (AIS) is important for clinical treatment decisions.

Objective

The purpose of this study is to assess the swallowing function of AIS patients and to develop and validate a prognostic model for the need for nasogastric tube (NGT) in these patients.

Materials and methods

We included 554 AIS patients during 2018–2019 as the development group and had 186 AIS patients as the external validation group. The primary end point of the study was the retention of NGT in patients 1 week after admission (Functional Oral Intake Scale ≤ 4). Swallowing function and stroke-associated pneumonia (SAP) at 1 month post-onset were also the objectives of this study. The volume-viscosity swallow test (V-VST) was used to assess the patient’s impaired swallowing function. The Predictive model was built by logistic regression.

Results

Overall, a total of 104 patients required indwelling NGT at 1 week of AIS onset in development group. The final prognostic model includes 5 variables: age (OR: 1.085, 95%CI: 1.049–1.123), neutrophil-to-lymphocyte ratio (NLR) (OR: 1.332, 95%CI: 1.090–1.626), NIHSS (OR: 1.092, 95%CI: 1.025–1.164), history of drinking (OR: 2.532, 95%CI: 1.452–4.417) and stroke location (Subtentorial vs. Supratentorial, OR: 1.954, 95%CI: 1.088–3.509). The prediction model had an AUC of 0.810, while the external validation group was 0.794.

Conclusion

In stroke patients, it is very important to decide early whether to indwell a NGT. The nomogram will support decision making for NGT insertion and help these patients recover from their condition.

Prolonged increased neutrophil-to-lymphocyte ratio is associated with mortality after successful revascularization for treatment of acute ischemic stroke

Background

To determine the association between dynamic neutrophil-to-lymphocyte ratio (NLR) during hospitalization and mortality 1 month after ischemia reperfusion in patients undergoing endovascular treatment (EVT) with successful revascularization for acute large vessel occlusion stroke.

Methods

This retrospective study included patients who had undergone successful EVT. Information was collected regarding patients’ clinical characteristics, imaging data, and mortality at 1 month. Univariate and multivariate logistic regression models were applied to assess the association between NLR and mortality. We used a generalized additive model and a generalized additive mixed model to compare trends in NLR over time between survivors and nonsurvivors.

Results

A total of 237 patients were included. During the 1-month follow-up, 42 of these patients (17.7%) died. The multivariate analysis demonstrated that NLR obtained within 12 to 24 hours (odds ratio [OR] = 1.18; 95% confidence interval [CI]: 1.04, 1.33; P = 0.008), 24 to 48 hours (OR = 1.16; 95% CI: 1.01, 1.35; P = 0.044), and 48 to 72 hours (OR = 1.23; 95% CI: 1.03, 1.47; P = 0.021) after EVT were independently associated with mortality at 1 month. In addition, there was a trend for NLR to decrease gradually over time for both survivors and nonsurvivors; however, NLR in survivors decreased by an average of 0.29 daily than in nonsurvivors.

Conclusions

Increased NLR in the early period after EVT was associated with an increased risk of mortality, and a continued trend toward higher NLR over time was also linked with a higher mortality risk.

The Neutrophil to Lymphocyte Ratio in Poststroke Infection: A Systematic Review and Meta-Analysis

Ischemic and hemorrhagic strokes have multiple downstream consequences for patients. One of the most critical is poststroke infection (PSI). The goal of this systematic review and meta-analysis was to critically evaluate the literature regarding the use of the neutrophil to lymphocyte ratio (NLR) as a reliable means to detect early PSI development, particularly poststroke pneumonia (PSP) development to help clinicians institute early interventions and improve outcomes. The following were the inclusion criteria: (1) cross-sectional, case-control, and cohort studies; (2) studies comparing NLR data from PSI or PSP patients to controls; and (3) studies with a control group of stroke patients without infection. There was not any language or publication preference. The Newcastle-Ottawa Scale was used by two writers to assess the quality of the included studies. We assessed the certainty of the associations with GRADE methods. Web of Science, PubMed, and Scopus were searched, and 25 studies were included in the qualitative review. Among them, 15 studies were included in the meta-analysis. Standardized mean difference (SMD) was reported with a 95% confidence interval (CI) for the NLR levels. Patients with PSI had significantly higher NLR levels than stroke patients without infection (SMD = 1.08; CI 95% = 0.78-1.39, P value < 0.001). In addition, the NLR levels of the stroke patients with pneumonia were significantly higher than those without pneumonia (SMD = 0.98; CI 95% = 0.81-1.14, P value < 0.001). However, data extracted from the qualitative review suggested that NLR could not predict urinary tract infection, sepsis, or ventriculitis in stroke patients. Our study indicated that NLR could be recommended as an inexpensive biomarker for predicting infection, particularly pneumonia, in stroke patients. It can help clinicians institute early interventions that can reduce PSI and improve outcomes.

Risk Estimation of Infectious and Inflammatory Disorders in Hospitalized Patients With Acute Ischemic Stroke Using Clinical-Lab Nomogram

Background: Infections after acute ischemic stroke are common and likely to complicate the clinical course and negatively affect patient outcomes. Despite the development of various risk factors and predictive models for infectious and inflammatory disorders (IAID) after stroke, more objective and easily obtainable predictors remain necessary. This study involves the development and validation of an accessible, accurate nomogram for predicting in-hospital IAID in patients with acute ischemic stroke (AIS).

Methods: A retrospective cohort of 2,257 patients with AIS confirmed by neurological examination and radiography was assessed. The International Statistical Classification of Diseases and Health related Problem's definition was used for IAID. Data was obtained from two hospitals between January 2016 and March 2020.

Results: The incidence of IAID was 19.8 and 20.8% in the derivation and validation cohorts, respectively. Using an absolute shrinkage and selection operator (LASSO) algorithm, four biochemical blood predictors and four clinical indicators were optimized from fifty-five features. Using a multivariable analysis, four predictors, namely age (adjusted odds ratio, 1.05; 95% confidence interval [CI], 1.038–1.062; p < 0.001), comatose state (28.033[4.706–536.403], p = 0.002), diabetes (0.417[0.27–0.649], p < 0.001), and congestive heart failure (CHF) (5.488[2.451–12.912], p < 0.001) were found to be risk factors for IAID. Furthermore, neutrophil, monocyte, hemoglobin, and high-sensitivity C-reactive protein were also found to be independently associated with IAID. Consequently, a reliable clinical-lab nomogram was constructed to predict IAID in our study (C-index value = 0.83). The results of the ROC analysis were consistent with the calibration curve analysis. The decision curve demonstrated that the clinical-lab model added more net benefit than either the lab-score or clinical models in differentiating IAID from AIS patients.

Conclusions: The clinical-lab nomogram predicted IAID in patients with acute ischemic stroke. As a result, this nomogram can be used for identification of high-risk patients and to further guide clinical decisions.

High Neutrophil Percentage-To-Albumin Ratio Can Predict Occurrence of Stroke-Associated Infection

Purpose: Stroke-associated infection (SAI) is associated with adverse outcomes in patients with acute ischemic stroke (AIS). In this study, we aimed to evaluate the association between neutrophil percentage-to-albumin ratio (NPAR) and SAI occurrence in patients with AIS. Methods: We retrospectively analyzed all AIS patients who were admitted to the Neurology ward of The Second Hospital of Tianjin Medical University from November 2018 to October 2020. The relationship between NPAR and SAI was analyzed by multivariable analysis. The receiver operating characteristic (ROC) curve was used to compare the predicted value of albumin, neutrophil percentage, neutrophil-to-lymphocyte ratio (NLR), and NPAR. Results: We included 379 AIS patients out of which 51 (13.5%) developed SAI. The NPAR was independently associated with increased risk of SAI adjusting for confounders [adjusted odds ratio (aOR) = 10.52; 95% confidence interval (CI), 3.33-33.28; P <0.001]. The optimal cutoff value of NPAR for predicting SAI incidence was 1.64, with sensitivity and specificity of 90.2 and 55.8%, respectively. The area under the curve (AUC) value of NPAR [0.771 (0.725-0.812)] was higher than that of albumin [0.640 (0.590-0.689)], neutrophil percentage [0.747 (0.700-0.790)], and NLR [0.736 (0.689-0.780)], though the statistical significance appeared only between NPAR and albumin. Conclusions: We demonstrated that a higher NPAR could predict the occurrence of SAI. Thus, NPAR might be a more effective biomarker to predict SAI compared with albumin, neutrophil percentage, and NLR.

Usefulness of the Neutrophil-to-Lymphocyte Ratio as a Predictor of Pneumonia and Urinary Tract Infection Within the First Week After Acute Ischemic Stroke

Background: A high Neutrophil-to-Lymphocyte ratio (NLR) in patients with acute ischemic stroke (AIS) has been associated with post-stroke infections, but it's role as an early predictive biomarker for post-stroke pneumonia (PSP) and urinary tract infection (UTI) is not clear.

Aim: To investigate the usefulness of NLR obtained within 24 h after AIS for predicting PSP and UTI in the first week.

Methods: Clinical and laboratory data were retrieved from the University Hospital Brussels stroke database/electronic record system. Patients were divided into those who developed PSP or UTI within the first week after stroke onset and those who didn't. Receiver operating characteristics (ROC) curves and logistic regression analysis were used to identify independent predictors.

Results: Five hundred and fourteen patients were included, of which 15.4% (n = 79) developed PSP and 22% (n = 115) UTI. In univariate analysis, NLR was significantly higher in patients who developed PSP (4.1 vs. 2.8, p < 0.001) but not in those who developed UTI (3.3 vs. 2.9, p = 0.074). Multiple logistic regression analysis for PSP showed that NLR, male gender, dysphagia, and stroke severity measured by the National Institutes of Health Stroke Scale (NIHSS), were independent predictors of PSP. For NLR alone, the area under the curve (AUC) in the ROC curve was 0.66 (95% CI = 0.59–0.73). When combining NLR ≥ 4.7 with age >75 years, male gender, NIHSS > 7, and dysphagia, the AUC increased to 0.84 (95% CI = 0.79–0.89).

Conclusion: The NLR within 24 h after AIS appears to have no predictive value for post-stroke UTI, and is only a weak predictor for identifying patients at high risk for PSP. Its predictive value for PSP appears to be much stronger when incorporated in a prediction model including age, gender, NIHSS score, and dysphagia.