Novel Risk Score to Predict Pneumonia After Acute Ischemic Stroke

Development and validation of radiology-clinical statistical and machine learning model for stroke-associated pneumonia after first intracerebral haemorrhage

BACKGROUND

Society is burdened with stroke-associated pneumonia (SAP) after intracerebral haemorrhage (ICH). Cerebral small vessel disease (CSVD) complicates clinical manifestations of stroke. In this study, we redefined the CSVD burden score and incorporated it into a novel radiological-clinical prediction model for SAP.

MATERIALS AND METHODS

A total of 1278 patients admitted to a tertiary hospital between 1 January 2010 and 31 December 2019 were included. The participants were divided into training and testing groups using fivefold cross-validation method. Four models, two traditional statistical models (logistic regression and ISAN) and two machine learning models (random forest and support vector machine), were established and evaluated. The outcomes and baseline characteristics were compared between the SAP and non-SAP groups.

RESULTS

Among the of 1278 patients, 281(22.0%) developed SAP after their first ICH. Multivariate analysis revealed that the logistic regression (LR) model was superior in predicting SAP in both the training and testing groups. Independent predictors of SAP after ICH included total CSVD burden score (OR, 1.29; 95% CI, 1.03-1.54), haematoma extension into ventricle (OR, 2.28; 95% CI, 1.87-3.31), haematoma with multilobar involvement (OR, 2.14; 95% CI, 1.44-3.18), transpharyngeal intubation operation (OR, 3.89; 95% CI, 2.7-5.62), admission NIHSS score ≥ 10 (OR, 2.06; 95% CI, 1.42-3.01), male sex (OR, 1.69; 95% CI, 1.16-2.52), and age ≥ 67 (OR, 2.24; 95% CI, 1.56-3.22). The patients in the SAP group had worse outcomes than those in the non-SAP group.

CONCLUSION

This study established a clinically combined imaging model for predicting stroke-associated pneumonia and demonstrated superior performance compared with the existing ISAN model. Given the poor outcomes observed in patients with SAP, the use of individualised predictive nomograms is vital in clinical practice.

Comparison of the Clinical Outcomes Between Reperfusion and Non-Reperfusion Therapy in Elderly Patients with Acute Ischemic Stroke

Purpose

To investigate the benefit (90-day mRS score) and rate of major complications (early symptomatic intracranial hemorrhage-SICH) after reperfusion therapy (RT) (including intravenous thrombolysis -IVT and mechanical thrombectomy -MT) in patients over 80 years with acute ischemic stroke (AIS).

Patients and Methods

AIS patients aged over 80 admitted to Huizhou Central People's Hospital from September 2018 to 2023 were included in this study. Data on SICH, NIHSS, and mRS were analyzed. A good prognosis was defined as a mRS ≤ 2 or recovery to pre-stroke status at 90 days.

Results

Of 209 patients, 80 received non-RT, 100 received IVT and 29 underwent MT. The non-RT group had the lowest baseline NIHSS while the MT group had the highest (non-RT 6.0 vs IVT 12.0 vs MT 18.0, P <0.001). Higher NIHSS was associated with increased SICH risk (OR 1.083, P=0.032), while RT was not (OR 5.194, P=0.129). The overall SICH rate in the RT group was higher but not significantly different after stratification by stroke severity. Poor prognosis was associated with higher admission NIHSS, stroke due to large artery atherosclerosis (LAA) combined with cardioembolism (CE), and stroke-associated pneumonia (SAP) (OR 0.902, P<0.001; OR 0.297, P=0.029; OR 0.103, P<0.001, respectively). The RT group showed a greater reduction in NIHSS (delta NIHSS) than the non-RT group (non-RT 2.0 vs IVT 4.0 vs MT 6.0, P<0.005). For severe AIS, the IVT group had a better prognosis at 90 days (non-RT 0% vs IVT 38.2%, P=0.039). No 90-day mortality difference was found between groups after stratification.

Conclusion

Stroke severity, rather than RT, is an independent risk factor for SICH in AIS patients over 80. RT in severe stroke patients improves NIHSS at 90 days, suggesting RT is safe and effective in this demographic. Further studies with larger samples are required to confirm these findings.

Association of follow-up neutrophil-to-lymphocyte ratio and systemic inflammation response index with stroke-associated pneumonia and functional outcomes in cerebral hemorrhage patients: a case-controlled study

BACKGROUND

The neutrophil-to-lymphocyte ratio (NLR) and systemic inflammation response index (SIRI) at admission are independent diagnostic biomarkers in stroke-associated pneumonia (SAP). Our study aimed to investigate the association between NLR, SIRI, specifically follow-up NLR and SIRI, and SAP, as well as their relationship with functional outcomes.

PATIENTS AND METHODS

We retrospectively included 451 consecutive intracerebral hemorrhage patients from May 2017 to May 2019. We conducted univariate and multivariable analyses to identify the factors independently associated with SAP and poor functional outcomes.

RESULTS

Compared to 127 (28.16%) patients diagnosed with SAP, those without SAP had both lower baseline and follow-up NLR and SIRI values ( P <0.001). After adjustments, we found that baseline NLR [OR, 1.039 (95% CI, 1.003-1.077); P =0.036] and follow-up NLR [OR, 1.054 (95% CI, 1.011-1.098); P =0.012] were independently associated with SAP. The follow-up NLR was also associated with a higher mRS [OR, 1.124 (95% CI, 1.025-1.233); P =0.013] and lower ADL-MBI score [OR, 1.167 (95% CI, 1.057-1.289); P =0.002] at discharge. Multivariable analysis indicated that advanced age and nasogastric tube feeding were independently associated with SAP ( P <0.05). We constructed a dynamic nomogram to identify SAP risk. Further subgroup analysis revealed that baseline NLR [OR, 1.062 (95% CI, 1.007-1.120); P =0.026] is independently associated with SAP in the nasogastric feeding group, while follow-up NLR [OR, 1.080 (95% CI, 1.024-1.139); P =0.005] was associated with the occurrence of SAP in non-nasogastric feeding patients.

CONCLUSIONS

We found elevated baseline and follow-up NLR values were associated with SAP occurrence, and increasing follow-up NLR indicated poor functional outcomes. Inflammatory markers at different stages may offer individualized guidance for patients receiving various treatments.

A systematic review and meta-analysis of acupuncture in aspiration caused by post-stroke dysphagia

Objective

This systematic review and meta-analysis aims to systematically evaluate the effectiveness and safety of acupuncture in the treatment of aspiration caused by post-stroke dysphagia.

Methods

A computer search was conducted in nine databases, including the China National Knowledge Infrastructure (CNKI), China Science and Technology Journal (VIP), Wan-fang Database, China Biomedical Literature Database (CBM), PubMed, Web of Science, Cochrane Library, Embase, and Chinese Clinical Trial Registry (ChiCTR), from their inception until April 2024. Clinical randomized controlled trials comparing acupuncture combined therapy or single therapy with control interventions for the treatment of aspiration caused by post-stroke dysphagia were included. The primary outcome measure was the Penetration Aspiration Scale (PAS), and secondary outcome measures included the overall effective rate, video fluoroscopic swallowing study (VFSS), and hyoid bone displacement. The statistical analysis was performed using RevMan 5.3 and Stata 16.0.

Results

A total of 16 articles involving 1,284 patients were included. The meta-analysis results showed that acupuncture combined therapy or single therapy was more effective in improving PAS scores compared to conventional rehabilitation therapy or balloon dilation of the catheter [WMD = -1.05, 95% CI (-1.30, -0.80), Z = 0.82, p = 0.00 < 0.05]. It was also more effective in improving VFSS scores [WMD = 1.32, 95% CI (0.08, 2.55), Z = 2.09, p = 0.04 < 0.05] and hyoid bone displacement [WMD = 2.02, 95% CI (0.86, 3.18), Z = 3.41, p = 0.00 < 0.05]. Additionally, acupuncture had a higher overall effective rate [WMD = 1.21, 95% CI (1.14, 1.29), Z = 5.76, p = 0.00 < 0.05] and a lower incidence of adverse events. Sensitivity analysis indicated that the literature had minimal impact on the results, and bias tests showed no publication bias.

Conclusion

Acupuncture combined therapy and acupuncture single therapy can effectively improve aspiration caused by post-stroke dysphagia with a low incidence of adverse events. However, due to the low quality of the included literature, more high-quality randomized controlled trials are still needed to confirm the effectiveness and safety of acupuncture in the treatment of aspiration caused by post-stroke dysphagia.

Systematic review registration

https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42023462707, identifier CRD42023462707.

Nomogram to predict ventilator-associated pneumonia in large vessel occlusion stroke after endovascular treatment: a retrospective study

Background

Ventilator-Associated Pneumonia (VAP) severely impacts stroke patients' prognosis after endovascular treatment. Hence, this study created a nomogram to predict the occurrence of VAP after endovascular treatment.

Methods

The individuals with acute ischemic stroke and large vessel occlusion (AIS-LVO) who received mechanical ventilation and endovascular therapy between July 2020 and August 2023 were included in this retrospective study. The predictive model and nomogram were generated by performing feature selection optimization using the LASSO regression model and multifactor logistic regression analysis and assessed the evaluation, verification and clinical application.

Results

A total of 184 individuals (average age 61.85 ± 13.25 years, 73.37% male) were enrolled, and the rate of VAP occurrence was found to be 57.07%. Factors such as the Glasgow Coma Scale (GCS) score, duration of stay in the Intensive Care Unit (ICU), dysphagia, Fazekas scale 2 and admission diastolic blood pressure were found to be associated with the occurrence of VAP in the nomogram that demonstrating a strong discriminatory power with AUC of 0.862 (95% CI, 0.810-0.914), and a favorable clinical net benefit.

Conclusion

This nomogram, comprising GCS score, ICU duration, dysphagia, Fazekas scale 2 and admission diastolic blood pressure, can aid clinicians in predicting the identification of high-risk patients for VAP following endovascular treatment in large vessel occlusion stroke.

Serial ASPECTS to predict stroke-associated pneumonia after thrombolysis in patients with acute ischemic stroke

Background

Stroke-associated pneumonia (SAP) is a serious complication in stroke patients, significantly increasing mortality. The Alberta Stroke Program Early CT Score (ASPECTS) is a recognized predictor of acute ischemic stroke outcomes. We aimed to investigate the performance of serial ASPECTS assessments (baseline ASPECTS, 24-h ASPECTS, and change in ASPECTS) for predicting SAP in patients with thrombolyzed acute anterior circulation ischemic stroke (AACIS).

Materials

A retrospective observational cohort study of adult patients with thrombolyzed AACIS was conducted. Baseline and 24-h ASPECTS using non-contrast computed tomography (NCCT), complications of stroke, including SAP and swallowing dysfunction using the Modified Water Swallowing test, were collected. Baseline and 24-h ASPECTS were evaluated by a certified neurologist and neuroradiologist. The predictive performance was determined based on the receiver operating characteristic curve (ROC). Multivariable logistic regression analyses were employed to assess the impact of serial ASPECTS assessment on predicting SAP.

Results

Of the 345 patients with thrombolyzed AACIS in our study, 18.4% (64/345) experienced SAP. The patients' median age was 62 years [interquartile range (IQR): 52-73], with 53.4% being male. The median NIHSS score was 11 points (IQR: 8-17). The ROC analysis revealed areas under the curve for predicting SAP with baseline ASPECTS, 24-h ASPECTS, and change in ASPECTS were 0.75 (95% CI, 0.69-0.82), 0.84 (95% CI, 0.79-0.89), and 0.82 (95% CI, 0.76-0.87), respectively. Of the three measures, 24-h ASPECTS was a better predictor of SAP (odds ratio: 5.33, 95%CI: 2.08-13.67, p < 0.001) and had a higher sensitivity (0.84 [95%CI, 0.74-0.92]) and specificity (0.79 [95%CI, 0.74-0.84]) than both baseline ASPECTS and change in ASPECTS.

Conclusion

24-h NCCT-ASPECTS outperformed both baseline ASPECTS and change in ASPECTS for predicting SAP. Notably, 24-h ASPECTS, with a cut-off value of ≤6, exhibited good predictive performance and emerged as the better predictor for SAP.

Development and validation of a predictive model for stroke associated pneumonia in patients after thrombectomy for acute ischemic stroke

Objective

This study aims to identify the risk factors associated with stroke-associated pneumonia (SAP) in patients who have undergone thrombectomy for acute ischemic stroke and to develop a nomogram chart model for predicting the occurrence of pneumonia.

Methods

Consecutive patients who underwent thrombectomy for acute ischemic stroke were enrolled from three hospitals at Taizhou Enze Medical Center. They were randomly divided into a training group and a validation group in a 7:3 ratio. The training group data was used to screen for effective predictive factors using LASSO regression. Multiple logistic regression was then conducted to determine the predictive factors and construct a nomogram chart. The model was evaluated using the validation group, analyzing its discrimination, calibration, and clinical decision curve. Finally, the newly constructed model was compared with the AIS-APS, A2DS2, ISAN, and PANTHERIS scores for acute ischemic stroke-associated pneumonia.

Results

Out of 913 patients who underwent thrombectomy, 762 were included for analysis, consisting of 473 males and 289 females. The incidence rate of SAP was 45.8%. The new predictive model was constructed based on three main influencing factors: NIHSS ≥16, postoperative LMR, and difficulty swallowing. The model demonstrated good discrimination and calibration. When applying the nomogram chart to threshold probabilities between 7 and 90%, net returns were increased. Furthermore, the AUC was higher compared to other scoring systems.

Conclusion

The constructed nomogram chart in this study outperformed the AIS-APS, A2DS2 score, ISAN score, and PANTHERIS score in predicting the risk of stroke-associated pneumonia in patients with acute ischemic stroke after thrombectomy. It can be utilized for clinical risk prediction of stroke-associated pneumonia in patients after thrombectomy for acute ischemic stroke.

A clinically actionable and explainable real-time risk assessment framework for stroke-associated pneumonia

The current medical practice is more responsive rather than proactive, despite the widely recognized value of early disease detection, including improving the quality of care and reducing medical costs. One of the cornerstones of early disease detection is clinically actionable predictions, where predictions are expected to be accurate, stable, real-time and interpretable. As an example, we used stroke-associated pneumonia (SAP), setting up a transformer-encoder-based model that analyzes highly heterogeneous electronic health records in real-time. The model was proven accurate and stable on an independent test set. In addition, it issued at least one warning for 98.6 % of SAP patients, and on average, its alerts were ahead of physician diagnoses by 2.71 days. We applied Integrated Gradient to glean the model's reasoning process. Supplementing the risk scores, the model highlighted critical historical events on patients' trajectories, which were shown to have high clinical relevance.

Risk Factors for the Development of Pneumonia in Stroke Patients: A Systematic Review and Meta-Analysis

Pneumonia is one of the most prevalent medical complications post-stroke. It can have negative impacts on the prognosis of stroke patients. This study aimed to determine the predictors of pneumonia in stroke patients. The authors devised, reviewed, and enhanced the search strategy in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Studies were gathered from various electronic databases, including Medline, CINAHL, Cochrane, Embase, and Web of Science, from January 1st, 2011, to February 25th, 2024. The review encompassed studies involving patients aged 18 years and older who were hospitalized for acute stroke care. Inclusion criteria required patients to have received a clinical diagnosis of stroke, confirmed via medical imaging (CT or MRI), hospital primary diagnosis International Classification of Diseases 10th Revision discharge codes, or pathology reporting. A total of 35 studies met the criteria and were included in our pooled analysis. Among them, 23 adopted a retrospective design, while the remaining 12 were prospective. The pooled incidence of pneumonia among patients with stroke was found to be 14% (95% confidence interval = 13%-15%). The pooled analysis reported that advancing age, male gender, a history of chronic obstructive pulmonary disease (COPD), the presence of a nasogastric tube, atrial fibrillation, mechanical ventilation, stroke severity, dysphagia, and a history of diabetes were identified as significant risk factors for pneumonia development among stroke patients. Our results underscore the importance of proactive identification and management of these factors to mitigate the risk of pneumonia in stroke patients.

Construction and comparison of short-term prognosis prediction model based on machine learning in acute ischemic stroke

Objective

To construct and compared the short-term prognosis prediction models of acute ischemic stroke (AIS) by machine learning (ML).

Methods

Retrospectively study. The group W (mRS≤3) was clustered, and combined with group P (mRS>3) to form the post-clustering dataset for modeling. The "glmnet", "rpart", "xgboost", "randomForest", "neuralnet" packages were used to construct ML models. The accuracy, sensitivity, specificity, positive predict value (PPV), negative predict value (NPV) among the models were compared. Four external clinical datasets were used for external clinical validation. The optimal prediction model was determined by variable screening ability, model visualization, and external clinical validation performance.

Results

The post-clustering dataset contains 139 patients (group W) and 122 patients (group P). The neutrophil multiplied by D-dimer (NDM) has predictive value in all ML prediction models in this study. In the decision tree model, NDMQ occupies the first tree node, When NDM≤5.62 and the age<74.5, the probability of poor prognosis of AIS is less than 20 %. When NDM>5.62 and accompanied by pneumonia, the incidence of poor prognosis of AIS is about 90 %. In the Random Forest (RF) model, NDMQ had the highest Gini index. The variable combination screened by the RF model had the best performance in the neural network, and the accuracy, sensitivity, specificity, PPV, and NPV of the external validation were 0.800, 0.774, 0.833, 0.857, and 0.741, respectively. The RF model had the best performance in the external clinical validation datasets, with accuracies of 0.646, 0.697, 0.695, and 0.713, respectively.

Conclusions

NDM shows predictive value for AIS short-term prognosis in all ML models in this study. The optimal model in screening characteristic variables and the performance of in external clinical datasets was RF model. In the analysis of medical data with small sample size and outcome as categorical variables, RF could be used as the main algorithm to build a model.

Prevalence of Stroke-Associated Pneumonia and Its Predictors Among Hyperglycaemia Patients During Acute Ischemic Stroke

BACKGROUND

Hyperglycaemia (HG) during an acute ischemic stroke (AIS) is not only associated with unfavourable functional outcomes but also associated with stroke-associated pneumonia (SAP). This study aimed to determine the prevalence of SAP among Malaysian patients with AIS and the predictors of SAP among patients with HG during AIS.

METHODS

This is a retrospective cross-sectional study that included patients with AIS admitted to Hospital Sultanah Nur Zahirah, Malaysia from 2017 to 2020. SAP was defined as infection with pneumonia during the first seven days after IS. HG was defined as a blood glucose level > 7.8 mmol/L within 72 h after admission. Patients with SAP were divided into two groups according to HG status. Multivariate logistic regression analysis was performed using SPSS software, version 22 (IBM Corp., Armonk, NY) to identify SAP predictors among patients with HG. Kaplan-Meier log-rank test was used to compare the survival rate from unfavourable functional outcomes between hyperglycaemic patients with and without SAP.

RESULTS

Among 412 patients with AIS, 69 (16.74%) had SAP. The prevalence of SAP among patients with HG and normoglycemia during AIS was 20.98%, and 10.65%, respectively. Age above 60 years, leucocytosis, and National Institute of Health Stroke Scale (NIHSS) > 14 on admission were independent predictors of SAP with aOR of 2.08 (95% CI;1.01-4.30), 2.83 (95% CI; 1.41-5.67), and 3.67 (95% CI; 1.53-8.80), respectively. No significant difference in unfavourable functional outcomes survival was found among patients with and without SAP (p = 0.653).

CONCLUSION

This study demonstrated the prevalence of SAP was higher among patients with HG compared to normoglycemia during AIS. The patient being old, leucocytosis and severe stroke upon admission predict the occurrence of SAP among patients with HG during AIS.

Construction and evaluation of a nomogram prediction model for aspiration pneumonia in patients with acute ischemic stroke

Background

Aspiration Pneumonia (AP) is a leading cause of death in patients with Acute Ischemic Stroke (AIS). Early detection, diagnosis and effective prevention measures are crucial for improving patient prognosis. However, there is a lack of research predicting AP occurrence after AIS. This study aimed to identify risk factors and develop a nomogram model to determine the probability of developing AP after AIS.

Method

A total of 3258 AIS patients admitted to Jinshan Hospital of Fudan University between January 1, 2016, and August 20, 2022, were included. Among them, 307 patients were diagnosed with AP (AP group), while 2951 patients formed the control group (NAP group). Univariate and multivariate logistic regression analyses were conducted to identify relevant risk factors for AP after AIS. These factors were used to establish a scoring system and develop a nomogram model using R software.

Results

Univariate analysis revealed 20 factors significantly associated (P < 0.05) with the development of AP after AIS. These factors underwent multivariate logistic regression analysis, which identified age (elderly), National Institute of Health Stroke Scale (NIHSS) score, dysphagia, atrial fibrillation, cardiac insufficiency, renal insufficiency, hepatic insufficiency, elevated Fasting Blood Glucose (FBG), elevated C-Reactive Protein (CRP), elevated Neutrophil percentage (NEUT%), and decreased prealbumin as independent risk factors. A nomogram model incorporating these 11 risk factors was constructed, with a C-index of 0.872 (95 % CI: 0.845-0.899), indicating high accuracy. Calibration and clinical decision analyses demonstrated the model's reliability and clinical value.

Conclusion

A nomogram model incorporating age, NIHSS score, dysphagia, atrial fibrillation, cardiac insufficiency, renal insufficiency, hepatic insufficiency, FBG, CRP, NEUT%, and prealbumin effectively predicts AP risk in AIS patients. This model provides guidance for early intervention strategies, enabling the identification of high-risk individuals for timely preventive measures.

Development and validation of a nomogram model for prediction of stroke-associated pneumonia associated with intracerebral hemorrhage

BACKGROUND

We aimed to establish risk factors for stroke-associated pneumonia (SAP) following intracerebral hemorrhage (ICH) and develop an efficient and convenient model to predict SAP in patients with ICH.

METHODS

Our study involved 1333 patients consecutively diagnosed with ICH and admitted to the Neurology Department of the First Affiliated Hospital of Wenzhou Medical University. The 1333 patients were randomly divided (3:1) into the derivation cohort (n = 1000) and validation Cohort (n = 333). Variables were screened from demographics, lifestyle-related factors, comorbidities, clinical symptoms, neuroimaging features, and laboratory tests. In the derivation cohort, we developed a prediction model with multivariable logistic regression analysis. In the validation cohort, we assessed the model performance and compared it to previously reported models. The area under the receiver operating characteristic curve (AUROC), GiViTI calibration belt, net reclassification index (NRI), integrated discrimination index (IDI) and decision curve analysis (DCA) were used to assess the prediction ability and the clinical decision-making ability.

RESULTS

The incidence of SAP was 19.9% and 19.8% in the derivation (n = 1000) and validation (n = 333) cohorts, respectively. We developed a nomogram prediction model including age (Odds Ratio [OR] 1.037, 95% confidence interval [CI] 1.020-1.054), male sex (OR 1.824, 95% CI 1.206-2.757), multilobar involvement (OR 1.851, 95% CI 1.160-2.954), extension into ventricles (OR 2.164, 95% CI 1.456-3.215), dysphagia (OR 3.626, 95% CI 2.297-5.725), disturbance of consciousness (OR 2.113, 95% CI 1.327-3.362) and total muscle strength of the worse side (OR 0.93, 95% CI 0.876-0.987). Compared with previous models, our model was well calibrated and showed significantly higher AUROC, better reclassification ability (improved NRI and IDI) and a positive net benefit for predicted probability thresholds between 10% and 73% in DCA.

CONCLUSIONS

We developed a simple, valid, and clinically useful model to predict SAP following ICH, with better predictive performance than previous models. It might be a promising tool to assess the individual risk of developing SAP for patients with ICH and optimize decision-making.

Health Care-Associated Infection in Elderly Patients With Cerebrovascular Disease in Intensive Care Units: A Retrospective Cohort Study in Taizhou, China

BACKGROUND

Cerebrovascular diseases are associated with high incidence of health care-associated infections (HAIs) and poor prognosis in elderly patients. This study aimed to investigate the incidence and clinical characteristics of HAIs in elderly patients with cerebrovascular disease in the intensive care unit (ICU).

METHODS

Patients admitted with cerebrovascular disease, aged ≥65 years, were included. The clinical data of the patients were retrospectively analyzed to determine the risk factors, infection type, distribution, and pathogenic characteristics of HAIs in the context of cerebrovascular diseases.

RESULTS

Out of 381 ICU inpatients monitored, 79 (20.73%) developed HAIs. Risk analysis revealed number of ventilator days as significant risk factors for HAIs in elderly patients with cerebrovascular diseases in the comprehensive ICU. In the HAI group, 56 patients (70.89%) had respiratory tract infection (RTI). Sixty-five patients (82.28%) were infected with Gram-negative bacteria (GNB), and 42 (53.16%) with multi-drug-resistant organism (MDRO). The length of hospitalization days, ventilator days, and overall hospitalization costs were higher in the HAI group than in the non-HAI group (P < 0.05), but there was no significant difference between groups in the treatment outcome of patients. Patients with MDRO infection had longer duration and higher cost of hospitalization than those infected with non-MDRO (P < 0.05), but there was no significant difference between the groups in the treatment outcome of patients.

CONCLUSIONS

HAIs occurred mostly due to RTI and GNB infection. The hospitalization cost and duration, as well as the length of ventilator days, were higher for cerebrovascular patients with HAIs than for non-HAIs patients.

The Potential of Gut Microbiota in Prediction of Stroke-Associated Pneumonia

BACKGROUND

Stroke-associated pneumonia (SAP) is a common stroke complication, and the changes in the gut microbiota composition may play a role. Our study aimed to evaluate the predictive ability of gut microbiota for SAP.

METHODS

Acute ischemic stroke patients were prospectively enrolled and divided into two groups based on the presence or absence of SAP. The composition of gut microbiota was characterized by the 16S RNA Miseq sequencing. The gut microbiota that differed significantly between groups were incorporated into the conventional risk scores, the Acute Ischemic Stroke-Associated Pneumonia Score (AIS-APS), and the Age, Atrial fibrillation, Dysphagia, Sex, Stroke Severity Score (A2DS2). The predictive performances were assessed in terms of the area under the curve (AUC), the Net Reclassification Improvement (NRI), and the Integrated Discrimination Improvement (IDI) indices.

RESULTS

A total of 135 patients were enrolled, of whom 43 had SAP (31%). The short-chain fatty acids (SCFAs)-producing bacteria, such as Bacteroides, Fusicatenibacter, and Butyricicoccus, were decreased in the SAP group. The integrated models showed better predictive ability for SAP (AUC = 0.813, NRI = 0.333, p = 0.052, IDI = 0.038, p = 0.018, for AIS-APS; AUC = 0.816, NRI = 0.575, p < 0.001, IDI = 0.043, p = 0.007, for A2DS2) in comparison to the differential genera (AUC = 0.699) and each predictive score (AUCAISAPS = 0.777; AUCA2DS2 = 0.777).

CONCLUSIONS

The lower abundance of SCFAs-producing gut microbiota after acute ischemic stroke was associated with SAP and may play a role in SAP prediction.

Prevalence of Electrolyte Imbalance in Patients With Acute Stroke: A Systematic Review

Electrolyte abnormalities are common in acute stroke patients and have a substantial impact on the course and prognosis of the disease. Electrolyte imbalances such as hyponatremia, hypokalemia, hypocalcemia, hypomagnesemia, and phosphate abnormalities are frequently seen in this patient population. The incidence, root causes, and medical ramifications of electrolyte abnormalities in acute stroke patients are investigated in this comprehensive study. According to our research, hyponatremia is the most prevalent electrolyte imbalance. The most common reason for hyponatremia in stroke patients is the syndrome of inappropriate antidiuretic hormone secretion (SIADH). Higher mortality rates, longer hospital admissions, and less favorable functional outcomes are all linked to hyponatremia. Acute stroke patients also typically experience hypokalemia, which affects the severity of the stroke and the recovery of functional abilities. The review furthermore emphasizes the incidence and clinical consequences of hypercalcemia, hypomagnesemia, hypophosphatemia, and hypocalcemia in patients with acute stroke. The results highlight the significance of early electrolyte imbalance detection and treatment in acute stroke patients. To better comprehend therapeutic approaches, evaluate their influence on stroke outcomes, and analyze prognostic implications, more research is required.

Post-stroke dysphagia: Clinical characteristics and evolution in a single-primary stroke center

BACKGROUND

Dysphagia is a common manifestation after stroke and seems to play a major role in clinical and functional outcomes.

OBJECTIVES

To identify clinical predictors of higher degrees of dysphagia, as well as assess its burden in our hospital, in order to understand how to improve the approach to this symptom.

METHODS

We included 311 patients admitted in an acute stroke unit in a year-long period. The relationship of dysphagia with different outcomes, both in acute phase and within the first year after stroke, were investigated.

RESULTS

Using the Pearson Correlation Coefficient, NIHSS score at admission was positively correlated with the degree of dysphagia (r = 0,783; p <  0,001) and total anterior circulation infarcts and age (>  70 years) were also associated with higher risk of dysphagia (p <  0.001). During hospitalization both respiratory infections and mortality occurred at significantly higher rates for dysphagic patients (p <  0.001) and we observed an increasing trend towards a higher mortality rate, the higher the degree of dysphagia. These patients stayed longer in the stroke unit, with less chance to be discharged home and more frequently transferred to inpatient rehabilitation care. One year after admission, dysphagic patients were more frequently readmitted due to pneumonia and we observed a higher mortality rate compared to patients without dysphagia (p <  0.001).

CONCLUSION

The presence of the above-mentioned dysphagia predictive factors should alert us to the need for an early approach, starting in the stroke unit, but also after discharge, taking into account its impact on clinical outcomes, mortality and healthcare costs.

Post-Stroke Pneumonia in Real-World Practice: Background, Microbiological Examination, and Treatment

Post-stroke pneumonia (PSP) has an impact on acute ischemic stroke (AIS). Although predictive scores for PSP have been developed, it is occasionally difficult to predict. Clarifying how PSP was treated after its onset in clinical practice is important. Admitted patients with AIS over a 2-year period were retrospectively reviewed. Of 281 patients with AIS, 24 (8.5%) developed PSP. The integer-based pneumonia risk score was higher in patients with PSP. The onset of PSP was frequently seen up to the 4th day of hospitalization. Of patients with PSP, sputum examination yielded Geckler 4 or 5 in only 8.3%. Angiotensin-converting enzyme inhibitor (ACE-I) was more frequently administered to patients with PSP; however, all these cases were started with ACE-I following PSP onset. Nasogastric tubes (NGTs) were inserted in 16 of the patients with PSP, of whom 11 were inserted following PSP onset. Multivariate analysis showed that PSP onset was a poor prognostic factor independent of the female sex, urinary tract infection, and National Institutes of Health Stroke Scale. PSP treatment would benefit from the administration of antimicrobials and ACE-I, as well as NGT insertion. To select effective agents for PSP and evaluate the indications for NGT insertion, further case studies are needed.

Systemic Immune-Inflammation Index and Long-Term Mortality in Patients with Stroke-Associated Pneumonia

Background

Systemic immune inflammation has been investigated as a prognostic marker of different diseases. This study is designed to assess the association of systemic immune-inflammation index (SII) with long-term mortality of stroke-associated pneumonia (SAP) patients.

Methods

Patients aged ≥18 years with SAP were selected from the Nanjing Stroke Registry Program in China. We retrospectively evaluated systemic immune-inflammation response with SII and pneumonia severity with the pneumonia severity index and the confusion, uremia, elevated respiratory rate, hypotension, and aged 65 years or older score. To explore the correlation between SII and mortality in SAP patients, multivariable Cox regressions and competing risk regressions were conducted. Mediation analysis was also performed to assess the role of pneumonia severity.

Results

Among 611 patients in the SAP population, death occurred in 164 patients (26.8%) during the median follow-up of 3.0 (1.2-4.6) years. In multivariate analysis, higher SII scores could predict increased mortality in patients with SAP (adjusted hazard ratio 2.061; 95% confidence interval, 1.256-3.383; P = 0.004), and the association was mediated by pneumonia severity. Moreover, adding SII to traditional models improved their predictive ability for mortality.

Conclusion

Our study displayed that SII was characterized in SAP patients with different prognoses. Elevated SII scores increased the risk of mortality. Further research is required for the clinical practice of the index among SAP patients.

A Clinical Prediction Model Based on Post Large Artery Atherosclerosis Infarction Pneumonia

BACKGROUND AND PURPOSE

Stroke-associated pneumonia (SAP) has been found as a common complication in acute ischemic stroke (AIS) patients. Large artery atherosclerosis (LAA) infarct is a major subtype of AIS. This study aimed to build a clinical prediction model for SAP of LAA type AIS patients.

METHODS

This study included 295 patients with LAA type AIS. Univariate analyses and logistic regression analyses were conducted to determine the independent predictors for the modeling purpose. Nomogram used receiver operating characteristics to assess the accuracy of the model, and the calibration plots were employed to assess the fitting degree between the model and the practical scenario. One hundred and five patients were employed for the external validation to test the stability of the model.

RESULTS

From the univariate analysis, patients' ages, neutrophil-to-lymphocyte ratios, National Institute of Health Stroke scale (NIHSS) scores, red blood cell, sex, history of coronary artery disease, stroke location and volume-viscosity swallow test showed statistical difference in the development group for the occurrence of SAP. By incorporating the factors above into a multivariate logistic regression analysis, patients' ages, neutrophil-to-lymphocyte ratios, NIHSS, and volume-viscosity swallow test emerged as the independent risk factors of the development of SAP. The nomogram based on the mentioned 4 variables above achieved a receiver operating characteristic of 0.951 and a validation group of 0.946.

CONCLUSIONS

The proposed nomogram is capable of predicting predict the occurrence of SAP in LAA type AIS patients, and it may identify high-risk patients in time and present information for in-depth treatment.

Hospital-acquired pneumonia is more frequent and lethal in stroke patients: A nationwide 4-year study

We report a higher incidence of hospital-acquired pneumonia (HAP) in patients admitted with stroke (odds ratio, 5.6; 95% CI, 5.4-5.8). Patients with HAP and stroke had an elevated risk of death (odds ratio, 1.2; 95% CI, 1.1-1.3). The incidence and mortality of HAP in stroke patients increased across all age groups.

Effects of nurse-led hierarchical management care on acute stroke patients: A pilot study to promote stroke-associated pneumonia management

Background

Stroke-related pneumonia (SAP) is a common complication in acute ischemic stroke (AIS) patients, and it has adverse effects on the clinical outcomes and increases the burden on patients' families and society. Early identification and individualized care are necessary to reduce the incidence of SAP.

Objective

The present study aimed to explore the effect of nurse-led hierarchical management care based on the acute ischemic stroke-associated pneumonia score (AIS-APS) scale in AIS patients.

Methods

A quasi-intervention pilot study design was adopted for the present study. A total of 120 AIS patients were enrolled and assigned to the intervention group and the control group, with 60 subjects in each group in a tertiary hospital in Guangzhou, China. The control group received routine care, whereas the intervention group was given nurse-led hierarchical management care based on the AIS-APS scale. The intervention duration was more than 7 days, and the incidence of SAP, neurological function, swallowing function, and activities of daily living (ADLs) at discharge were observed. The outcomes were assessed at baseline and at outpatient time.

Results

A total of 120 participants were enrolled in our study. A significant decrease was found in the incidence of SAP in the intervention group (18.3%) compared with that in the control group (41.7%). Positive outcomes were shown in neurology function, swallowing function, and ADL in the intervention group.

Conclusion

Nurse-led hierarchical management care based on AIS-APS can reduce the incidence of SAP, promote AIS patients' neurological function, and maintain patients' ADL. The results of our study indicated that nurse-led hierarchical management care is feasible for AIS patients and provides individualized interventions for patients with different levels of SAP risk. Nurse-led hierarchical management care could be incorporated into routine nursing practice. Further study is needed and expected to solve more clinical problems.

A Novel Index in the Prediction of Pneumonia Following Acute Ischemic Stroke

BACKGROUND

The aim of our study was to search for predictive factors and to develop a model (index) for the risk of pneumonia following acute ischemic stroke.

MATERIAL AND METHODS

This study is an analysis of prospectively collected data from the neurology department of a district general hospital in Poland, comprising 1001 patients suffering from an acute ischemic stroke. Based on the medical data, the formula for the prediction of pneumonia was calculated.

RESULTS

Multivariate assessment for pneumonia occurrence was performed using the new PNEUMOINDEX. The study showed a significant increase in pneumonia risk with an increasing PNEUMOINDEX (OR non-adjusted = 2.738, p < 0.001). After accounting for age and comorbidities as confounders, the effect of the Index on pneumonia changed marginally (OR = 2.636, p < 0.001).

CONCLUSIONS

This study presents factors that show a significant association with the occurrence of pneumonia in patients with acute ischemic stroke. The calculated PNEUMOINDEX consists of data obtained at admission, namely NYHA III and IV heart failure, COPD, generalized atherosclerosis, NIHHS score on admission, and CRP/Hgb ratio, and shows high prediction accuracy in predicting hospital-acquired pneumonia in ischemic stroke patients.

Low triiodothyronine syndrome is associated with stroke-associated pneumonia

OBJECTIVE

Stroke-associated pneumonia (SAP) is the most common early consequence in patients suffering from an acute ischaemic stroke (AIS). The purpose of this study was to explore the possible relationship between low triiodothyronine (T3) syndrome and SAP in stroke patients.

METHODS

This study recruited 2460 consecutive AIS patients. SAP was defined according to the modified Centers for Disease Control and Prevention criteria for hospital-acquired pneumonia. The thyroid hormones levels were measured within 24 h after admission. Low T3 syndrome was characterized as T3 below the lower limit of the reference interval accompanied by normal TSH levels.

RESULTS

Among the total patients, 336 (13.7%) patients were diagnosed with SAP. SAP in individuals with low T3 syndrome was substantially greater (p < .001) as compared to those without low T3 syndrome. After adjusting for possible confounders, low T3 syndrome (adjusted odds ratio [aOR] = 1.59; 95% confidence interval [CI], 1.20-2.09; p = .001) remained significant in our logistic model. Patients with low T3 syndrome had a higher risk of severe SAP (aOR = 2.17, 95% confidence interval [CI] 1.38-3.44; p = .001).

CONCLUSION

Low T3 syndrome, independent of recognized risk factors, is a possible risk factor for in-hospital SAP, which can help clinicians in the early detection and treatment of high-risk patients.

A nomogram based on nutritional status and A2DS2 score for predicting stroke-associated pneumonia in acute ischemic stroke patients with type 2 diabetes mellitus: A retrospective study

Background

Stroke-associated pneumonia (SAP) commonly complicates acute ischemic stroke (AIS) and significantly worsens outcomes. Type 2 diabetes mellitus (T2DM) may contribute to malnutrition, impair innate immunity function, and increase the probability of SAP occurrence in AIS patients. We aimed to determine early predictors of SAP in AIS patients with T2DM and to construct a nomogram specifically for predicting SAP in this population by combining the A²DS² score with available nutrition-related parameters.

Methods

A total of 1,330 consecutive AIS patients with T2DM were retrospectively recruited. The patients were randomly allocated to the training (n = 887) and validation groups (n = 443). Univariate and multivariate binary logistic regression analyses were applied to determine the predictors of SAP in the training group. A nomogram was established according to the identified predictors. The areas under the receiver operating characteristic curve (AUROC) and calibration plots were performed to access the predictive values of the nomogram. The decision curve was applied to evaluate the net benefits of the nomogram.

Results

The incidence of SAP was 9% and 9.7% in the training and validation groups, respectively. The results revealed that the A²DS² score, stroke classification, Geriatric Nutritional Risk Index, hemoglobin, and fast blood glucose were independent predictors for SAP. A novel nomogram, A²DS²-Nutrition, was constructed based on these five predictors. The AUROC for A²DS²-Nutrition (0.820, 95% CI: 0.794–0.845) was higher than the A²DS² score (0.691, 95% CI: 0.660–0.722) in the training group. Similarly, it showed a better predictive performance than the A²DS² score [AUROC = 0.864 (95% CI: 0.828–0.894) vs. AUROC = 0.763 (95% CI: 0.720–0.801)] in the validation group. These results were well calibrated in the two groups. Moreover, the decision curve revealed that the A²DS²-Nutrition provided an additional net benefit to the AIS patients with T2DM compared to the A²DS² score in both groups.

Conclusion

The A²DS² score, stroke classification, Geriatric Nutritional Risk Index, hemoglobin, and fast blood glucose were independent predictors for SAP in AIS patients with T2DM. Thus, the proposed A²DS²-Nutrition may be a simple and reliable prediction model for SAP occurrence in AIS patients with T2DM.

Comparison of six risk scores for stroke-associated pneumonia in patients with acute ischemic stroke: A systematic review and Bayesian network meta-analysis

Background

Stroke-associated pneumonia (SAP) is one of the major causes of death after suffering a stroke. Several scoring systems have been developed for the early prediction of SAP. However, it is unclear which scoring system is more suitable as a risk prediction tool. We performed this Bayesian network meta-analysis to compare the prediction accuracy of these scoring systems.

Methods

Seven databases were searched from their inception up to April 8, 2022. The risk of bias assessment of included study was evaluated by the QUADAS-C tool. Then, a Bayesian network meta-analysis (NMA) was performed by R 4.1.3 and STATA 17.0 software. The surface under the cumulative ranking curve (SUCRA) probability values were applied to rank the examined scoring systems.

Results

A total of 20 cohort studies involving 42,236 participants were included in this analysis. The results of the NMA showed that AIS-APS had excellent performance in prediction accuracy for SAP than Chumbler (MD = 0.030, 95%CI: 0.004, 0.054), A2DS2 (MD = 0.041, 95% CI: 0.023, 0.059), ISAN (MD = 0.045, 95% CI: 0.022, 0.069), Kwon (MD = 0.077, 95% CI: 0.055, 0.099) and PANTHERIS (MD = 0.082, 95% CI: 0.049, 0.114). Based on SUCRA values, AIS-APS (SUCRA: 99.8%) ranked the highest.

Conclusion

In conclusion, the study found that the AIS-APS is a validated clinical tool for predicting SAP after the onset of acute ischemic stroke.

Systematic review registration

https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=292375, identifier: CRD42021292375.

Neutrophil count multiplied by D-dimer combined with pneumonia may better predict short-term outcomes in patients with acute ischemic stroke

Objective

To investigate the predictive value of neutrophil, D-dimer and diseases associated with stroke for short-term outcomes of acute ischemic stroke (AIS).

Methods

By collecting the subitems of laboratory data especially routine blood and coagulation test in AIS patients, and recording their clinical status, the correlation, regression and predictive value of each subitem with the short-term outcomes of AIS were analyzed. The predict model was constructed.

Results

The neutrophil count multiplied by D-dimer (NDM) had the best predictive value among the subitems, and the area under the receiver operating characteristic (ROC) curve reached 0.804. When clinical information was not considered, the Youden index of NDM was calculated to be 0.48, corresponding to an NDM value of 7.78, a diagnostic sensitivity of 0.79, specificity of 0.69, negative predictive value of 96%. NDM were divided into 5 quintiles, the five grade of NDM (quintile) were < = 1.82, 1.83–2.41, 2.42–3.27, 3.28–4.49, 4.95+, respectively. The multivariate regression analysis was conducted between NDM (quintile), Babinski+, pneumonia, cardiac disease and poor outcomes of AIS. Compared with the first grade of NDM (quintile), the second grade of NDM (quintile) was not significant, but the third grade of NDM (quintile) showed 7.061 times, the fourth grade of NDM (quintile) showed 11.776 times, the fifth grade of NDM (quintile) showed 23.394 times in short-term poor outcomes occurrence. Babinski sign + showed 1.512 times, pneumonia showed 2.995 times, cardiac disease showed 1.936 times in short-term poor outcomes occurrence compared with those negative patients.

Conclusions

NDM combined with pneumonia may better predict short-term outcomes in patients with AIS. Early prevention, regular examination and timely intervention should be emphasized for patients, which may reduce the risk of short-term poor outcomes.

Reduced plasma levels of RGM-A predict stroke-associated pneumonia in patients with acute ischemic stroke: A prospective clinical study

Background

Stroke-induced immunodepression syndrome is considered the major etiology of stroke-associated pneumonia (SAP). Repulsive guidance molecule A (RGM-A) is an immunomodulatory protein that is closely related to inflammation and immune responses. To explore the relationship between RGM-A and SAP and facilitate the early identification of patients at high risk of developing SAP, we investigated the predictive value of RGM-A in SAP.

Methods

We enrolled 178 patients with acute ischemic stroke (AIS) and finally analyzed 150 patients, among whom 69 had SAP and 81 had non-SAP. During the same period, 40 patients with community-acquired pneumonia and 40 healthy participants were included as controls. SAP was defined according to the modified US Centers for Disease Control and Prevention criteria. Blood samples were collected at 24 h, 48 h, 3 days, 4 to 7 days, and 8 to 14 days after stroke onset. An enzyme-linked immunosorbent assay was used to detect the plasma levels of RGM-A and interleukin-6.

Results

The plasma RGM-A levels were significantly decreased in both patients with community-acquired pneumonia and those with AIS, and the decline was most pronounced in patients with SAP (P < 0.001). RGM-A started to decline within 24 h after stroke in the SAP group, and the lowest levels were detected on day 3 and days 4 to 7 (P < 0.001). The RGM-A levels in the SAP group were lower than those in the non-SAP group at all blood collection time points (P < 0.05). In the logistic regression analyses, RGM-A was a protective factor for SAP after adjusting for confounders (adjusted odds ratio = 0.22, 95% confidence interval = 0.091–0.538, P = 0.001). Receiver operating characteristic curve analysis showed that the area under the curve for RGM-A was 0.766 (0.091–0.538; P = 0.001), the cutoff value was 4.881 ng/mL, and the sensitivity and specificity were 80.00 and 76.36%, respectively.

Conclusions

We demonstrated that reduced plasma levels of RGM-A might help in the early identification of high-risk patients with SAP and predict the occurrence of SAP in patients with AIS. RGM-A might provide new clues to a potential alternative therapy for SAP.

Nutritional risk screening 2002 scale and subsequent risk of stroke-associated infection in ischemic stroke: The REMISE study

Background and aim

Stroke-associated infection (SAI) is a common and serious complication in patients with IS. This study aimed to evaluate the impact of nutritional status at admission assessed on SAI, explore the predictive value of the Nutritional Risk Screening 2002 (NRS-2002 for SAI.

Methods

This study included patients with IS who were admitted to five major hospitals in Chengdu from January 2017 to February 2019. The nutritional status was assessed using the NRS-2002 tool. Logistic regression analysis was performed to explore the predictive value of NRS-2002 for SAI.

Results

A total of 594 patients with IS were included in this study; among them, 215 (36.20%) patients were at risk of malnutrition, and 216 (36.36%) patients developed SAI. The area under the curve of the NRS-2002 scores was smaller than A2DS2 (0.644 vs. 0.779), and NRS-2002 improved the predictive values of the A²DS² score(Age, Atrial fibrillation, Dysphagia, Sex, Stroke Severity) for SAI (P < 0.001). Logistic regression analysis showed that patients with NRS-2002 score ≥ 3 had significantly higher risks of SAI (NRS-2002: odds ratios (OR) = 1.450, 95% confidence interval (CI): 1.184–1.692, P < 0.001).

Conclusion

NRS-2002 is a useful and simple tool for identifying the risk of SAI. Malnutrition is related to the development of SAI. Malnourished patients with stroke may benefit from further nutritional supplements and management.

Novel machine learning models to predict pneumonia events in supratentorial intracerebral hemorrhage populations: An analysis of the Risa-MIS-ICH study

Background

Stroke-associated pneumonia (SAP) contributes to high mortality rates in spontaneous intracerebral hemorrhage (sICH) populations. Accurate prediction and early intervention of SAP are associated with prognosis. None of the previously developed predictive scoring systems are widely accepted. We aimed to derive and validate novel supervised machine learning (ML) models to predict SAP events in supratentorial sICH populations.

Methods

The data of eligible supratentorial sICH individuals were extracted from the Risa-MIS-ICH database and split into training, internal validation, and external validation datasets. The primary outcome was SAP during hospitalization. Univariate and multivariate analyses were used for variable filtering, and logistic regression (LR), Gaussian naïve Bayes (GNB), random forest (RF), K-nearest neighbor (KNN), support vector machine (SVM), extreme gradient boosting (XGB), and ensemble soft voting model (ESVM) were adopted for ML model derivations. The accuracy, sensitivity, specificity, and area under the curve (AUC) were adopted to evaluate the predictive value of each model with internal/cross-/external validations.

Results

A total of 468 individuals with sICH were included in this work. Six independent variables [nasogastric feeding, airway support, unconscious onset, surgery for external ventricular drainage (EVD), larger sICH volume, and intensive care unit (ICU) stay] for SAP were identified and selected for ML prediction model derivations and validations. The internal and cross-validations revealed the superior and robust performance of the GNB model with the highest AUC value (0.861, 95% CI: 0.793–0.930), while the LR model had the highest AUC value (0.867, 95% CI: 0.812–0.923) in external validation. The ESVM method combining the other six methods had moderate but robust abilities in both cross-validation and external validation and achieved an AUC of 0.843 (95% CI: 0.784–0.902) in external validation.

Conclusion

The ML models could effectively predict SAP in sICH populations, and our novel ensemble model demonstrated reliable robust performance outcomes despite the populational and algorithmic differences. This attempt indicated that ML application may benefit in the early identification of SAP.

Factors associated with stroke associated pneumonia among adult stroke patients admitted to university of Gondar hospital, Northwest Ethiopia

Stroke is the major cause of disability and death in sub-Saharan African countries. The presence and severity of complications play a major role in the outcome of stroke. Stroke associated pneumonia is often noticed post stroke infection that has been linked to an increased risk of hospital mortality, a longer hospital stay and higher healthcare expenses. Report on details of stroke-associated pneumonia has never been documented in countries of sub-Saharan Africa. This study aimed to determine the incidence and risk factors of stroke-associated pneumonia among adult stroke patients in hospital settings, Northwest Ethiopia. The study was undertaken at a stroke care unit, University of Gondar hospital between January 1, 2020 and December 31, 2020. A convenience sampling method was used to recruit study subjects. Relevant clinical history was taken, focused physical examination was done, and brain imaging (CT scan or MRI) was performed to settle the diagnosis of stroke. A modified Centre for Disease Control and Prevention (CDC) criteria was used to diagnose stroke-associated pneumonia. All patients with stroke-associated pneumonia were treated according to the 2016 Infectious Diseases Society of America/American Thoracic Society Clinical Practice Guidelines. The Data were cleaned in Epi Info version 4.6.0.2, and analyzed using SPSS version 26. Variables associated with stroke-associated pneumonia were computed using logistic regression analysis. P value < 0.05 was considered to declare statistical significance. The study comprised a total of 325 adult stroke patients. The mean age of study subjects was 65.2 years (SD ± 15.7). The most prevalent type of stroke was ischemic stroke, which accounted for 68% of all cases. Hemiparesis (94%), facial palsy (87%), and swallowing disturbance (51%) were the frequently noticed neurological findings. Stroke-associated pneumonia complicated 116/325 (36%) of stroke patients. Multi-variate regression analysis revealed that patients who were elderly (age > 75 years) (AOR = 3.910, CI 1.181-12.936, P = 0.026), had swallowing disturbance (AOR = 4.656, CI 2.356-9.202, P-value < 0.001), epileptic seizures (AOR = 2.678, 95% CI 1.253-5.721, P-value < 0.001) and moderate to severe stroke (NIHSS score = 16-21) (AOR = 5.994, 95% CI 2.043-17.585, P-value < 0.001) were at risk of developing stroke-associated pneumonia. SAP was a substantial medical complication among stroke patients. Early identification and prompt intervention measures for the identified risk factors might address the burden of SAP.

Hypersensitive C-reactive protein-albumin ratio is associated with stroke-associated pneumonia and early clinical outcomes in patients with acute ischemic stroke

OBJECTIVES

We aimed to explore the association between the baseline hypersensitive C-reactive protein-albumin ratio (CAR) and stroke-associated pneumonia (SAP) during hospitalization and the short-term prognosis in patients with acute ischemic stroke (AIS).

METHODS

We enrolled 766 patients with AIS and collected their admission baseline characteristics, including their National Institutes of Health Stroke Scale score, CAR, age, atrial fibrillation, dysphagia, sex, stroke severity (A² DS² ) score, and other information. The occurrence of SAP within 7 days after stroke, length of hospital stay, and physical condition at discharge were also recorded. The patients' Modified Rankin Scale (mRS) scores and mortality 3 months after AIS were further evaluated at follow-up. All patients were divided into four groups based on the quartiles of the admission CAR (Q1 <1.3, Q2 1.3-3.7, Q3 3.7-9.3, Q4 ≥9.3).

RESULTS

During hospitalization, 92 (11.9%) patients were diagnosed with SAP. The patients with SAP had a higher CAR than the non-SAP patients (p < .001). In the multivariate-adjusted model, the patients in the Q3 and Q4 groups had a higher SAP risk (aOR was 5.21 and 17.72, p-trend < .001) than those in the lowest quartile. The area under the curve for the CAR's ability to predict SAP was 0.810 in the receiver operating characteristic curve analysis and had a similar predictive efficacy as the A² DS²  score (p <.05). The length of stay in the SAP group was almost the same as that in the non-SAP group, but the clinical outcomes were worse at discharge and at the 3-month follow-up in the SAP group. In addition, the patients in the higher CAR quartiles at admission were more likely to have poorer clinical outcomes.

CONCLUSIONS

Patients with AIS with a high CAR at admission are more likely to develop SAP during hospitalization and have poor short-term clinical outcomes. These findings might help to timely identify patients at high risk of SAP and provide a basis for further research on prophylactic antibiotic therapy.

ICH-LR2S2: a new risk score for predicting stroke-associated pneumonia from spontaneous intracerebral hemorrhage

Purpose

We develop a new risk score to predict patients with stroke-associated pneumonia (SAP) who have an acute intracranial hemorrhage (ICH).

Method

We applied logistic regression to develop a new risk score called ICH-LR2S2. It was derived from examining a dataset of 70,540 ICH patients between 2015 and 2018 from the Chinese Stroke Center Alliance (CSCA). During the training of ICH-LR2S2, patients were randomly divided into two groups – 80% for the training set and 20% for model validation. A prospective test set was developed using 12,523 patients recruited in 2019. To further verify its effectiveness, we tested ICH-LR2S2 on an external dataset of 24,860 patients from the China National Stroke Registration Management System II (CNSR II). The performance of ICH-LR2S2 was measured by the area under the receiver operating characteristic curve (AUROC).

Results

The incidence of SAP in the dataset was 25.52%. A 24-point ICH-LR2S2 was developed from independent predictors, including age, modified Rankin Scale, fasting blood glucose, National Institutes of Health Stroke Scale admission score, Glasgow Coma Scale score, C-reactive protein, dysphagia, Chronic Obstructive Pulmonary Disease, and current smoking. The results showed that ICH-LR2S2 achieved an AUC = 0.749 [95% CI 0.739–0.759], which outperforms the best baseline ICH-APS (AUC = 0.704) [95% CI 0.694–0.714]. Compared with the previous ICH risk scores, ICH-LR2S2 incorporates fasting blood glucose and C-reactive protein, improving its discriminative ability. Machine learning methods such as XGboost (AUC = 0.772) [95% CI 0.762–0.782] can further improve our prediction performance. It also performed well when further validated by the external independent cohort of patients (n = 24,860), ICH-LR2S2 AUC = 0.784 [95% CI 0.774–0.794].

Conclusion

ICH-LR2S2 accurately distinguishes SAP patients based on easily available clinical features. It can help identify high-risk patients in the early stages of diseases.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12967-022-03389-5.

Association of Platelet-to-Lymphocyte Ratio with Stroke-Associated Pneumonia in Acute Ischemic Stroke

A common consequence of acute ischemic stroke (AIS), stroke-associated pneumonia (SAP), might result in a poor prognosis after stroke. Based on the critical position of inflammation in SAP, this study aimed to explore the correlation between platelet-to-lymphocyte ratio (PLR) and the occurrence of SAP. We included 295 patients with acute ischemic stroke, 40 with SAP, and 255 without SAP. The area under the receiver operating characteristic curve was used to determine the diagnostic value of SAP risk factors using binary logistic regression analysis. The comparison between the two groups showed that age, the baseline National Institutes of Health Stroke Scale (NIHSS) score, and the proportion of dysphagia, atrial fibrillation, and total anterior circulation infarct were higher, and the proportion of lacunar circulation infarct was lower in the SAP group (P < 0.001). In terms of laboratory data, the SAP group had considerably greater neutrophil counts and PLR, while the non-SAP group (P < 0.001) had significantly lower lymphocyte counts and triglycerides. Binary logistic regression analysis revealed that older age (aOR = 1.062, 95% CI: 1.023–1.102, P = 0.002), atrial fibrillation (aOR = 3.585, 95% CI: 1.605–8.007, P = 0.019), and PLR (aOR = 1.003, 95% CI: 1.001–1.006, P = 0.020) were independent risk factors associated with SAP after adjusting for potential confounders. The sensitivity and specificity of PLR with a cutoff value of 152.22 (AUC: 0.663, 95% CI: 0.606–0.717, P = 0.0006) were 57.5% and 70.6%, respectively. This study showed that high PLR is an associated factor for SAP in AIS patients. Increased systemic inflammation is linked to SAP in ischemic stroke. Inflammatory biomarkers that are easily accessible may aid in the diagnosis of high-risk SAP patients.

Predicting Poststroke Pneumonia in Patients With Anterior Large Vessel Occlusion: A Prospective, Population-Based Stroke Registry Analysis

Objective

To assess predictive factors for poststroke pneumonia (PSP) in patients with acute ischemic stroke (AIS) due to large vessel occlusion (LVO) of the anterior circulation, with special regard to the impact of intravenous thrombolysis (IVT) and endovascular treatment (EVT) on the risk of PSP. As a secondary goal, the validity of the A²DS², PNEUMONIA, and ISAN scores in LVO will be determined.

Methods

Analysis was based on consecutive data for the years 2017 to 2019 from the prospective inpatient stroke registry covering the entire federal state of Hesse, Germany, using the Kruskal-Wallis test and binary logistic regression.

Results

Data from 4,281 patients with LVO were included in the analysis (54.8% female, median age = 78 years, range = 18–102), of whom 66.4% (n = 2,843) received recanalization therapy (RCT). In total, 19.4% (n = 832) of all LVO patients developed PSP. Development of PSP was associated with an increase in overall in-hospital mortality of 32.1% compared with LVO patients without PSP (16.4%; p < 0.001). Incidence of PSP was increased in 2132 patients with either EVT (n = 928; 25.9% PSP incidence) or combined EVT plus IVT (n = 1,204; 24.1%), compared with 2,149 patients with IVT alone (n = 711; 15.2%) or conservative treatment only (n = 1,438; 13.5%; p < 0.001). Multivariate analysis identified EVT (OR 1.5) and combined EVT plus IVT (OR 1.5) as significant independent risk factors for PSP. Furthermore, male sex (OR 1.9), age ≥ 65 years (OR 1.7), dysphagia (OR 3.2) as well as impaired consciousness at arrival (OR 1.7) and the comorbidities diabetes (OR 1.4) and atrial fibrillation (OR 1.3) were significantly associated risk factors (each p < 0.001). Minor stroke (NIHSS ≤ 4) was associated with a significant lower risk of PSP (OR 0.5). Performance of risk stratification scores varied between A²DS² (96.1% sensitivity, 20.7% specificity), PNEUMONIA (78.2% sensitivity and 45.1% specificity) and ISAN score (98.0% sensitivity, 20.0% specificity).

Conclusion

Nearly one in five stroke patients with LVO develops PSP during acute care. This risk of PSP is further increased if an EVT is performed. Other predictive factors are consistent with those previously described for all AIS patients. Available risk stratification scores proved to be sensitive tools in LVO patients but lack specificity.

A2DS2 Score Combined With Clinical and Neuroimaging Factors Better Predicts Stroke-Associated Pneumonia in Hyperacute Cerebral Infarction

Objective

To investigate the predictors of stroke-associated pneumonia (SAP) and poor functional outcome in patients with hyperacute cerebral infarction (HCI) by combining clinical factors, laboratory tests and neuroimaging features.

Methods

We included 205 patients with HCI from November 2018 to December 2019. The diagnostic criterion for SAP was occurrence within 7 days of the onset of stroke. Poor outcome was defined as a functional outcome based on a 3-months MRS score >3. The relationship of demographic, laboratory and neuroimaging variables with SAP and poor outcome was investigated using univariate and multivariate analyses.

Results

Fifty seven (27.8%) patients were diagnosed with SAP and 40 (19.5%) developed poor outcomes. A²DS² score (OR = 1.284; 95% CI: 1.048–1.574; P = 0.016), previous stroke (OR = 2.630; 95% CI: 1.122–6.163; P = 0.026), consciousness (OR = 2.945; 95% CI: 1.514–5.729; P < 0.001), brain atrophy (OR = 1.427; 95% CI: 1.040–1.959; P = 0.028), and core infarct volume (OR = 1.715; 95% CI: 1.163–2.528; P = 0.006) were independently associated with the occurrence of SAP. Therefore, we combined these variables into a new SAP prediction model with the C-statistic of 0.84 (95% CI: 0.78–0.90). Fasting plasma glucose (OR = 1.404; 95% CI: 1.202–1.640; P < 0.001), NIHSS score (OR = 1.088; 95% CI: 1.010–1.172; P = 0.026), previous stroke (OR = 4.333; 95% CI: 1.645–11.418; P = 0.003), SAP (OR = 3.420; 95% CI: 1.332–8.787; P = 0.011), basal ganglia-dilated perivascular spaces (BG-dPVS) (OR = 2.124; 95% CI: 1.313–3.436; P = 0.002), and core infarct volume (OR = 1.680; 95% CI: 1.166–2.420; P = 0.005) were independently associated with poor outcome. The C-statistic of the outcome model was 0.87 (95% CI: 0.81–0.94). Furthermore, the SAP model significantly improved discrimination and net benefit more than the A²DS² scale, with a C-statistic of 0.76 (95% CI: 0.69–0.83).

Conclusions

After the addition of neuroimaging features, the models exhibit good differentiation and calibration for the prediction of the occurrence of SAP and the development of poor outcomes in HCI patients. The SAP model could better predict the SAP, representing a helpful and valid tool to obtain a net benefit compared with the A²DS² scale.

The value of diffusion weighted imaging-alberta stroke program early CT score in predicting stroke-associated pneumonia in patients with acute cerebral infarction: a retrospective study

BACKGROUND

In this study, we aimed to investigate the value of Diffusion-Weighted Imaging-Alberta Stroke Program Early CT Score (DWI-ASPECTS) in predicting stroke-associated pneumonia (SAP) in patients with acute ischemic stroke.

METHODS

A total of 291 patients who suffered acute cerebral infarction for the first time were included in this retrospective study. DWI-ASPECTS was assessed and clinical data were collected in order to find the risk factors of SAP, and a logistic regression model was used to investigate the effect of predicting SAP. Furthermore, correlation analysis was used to explore the relationship between DWI-ASPECTS and the immume status of the body.

RESULTS

Among the 291 patients, 74 (25.4%) subjects were diagnosed with SAP. Compared with non-SAP, the patients with SAP were older and had a higher rate of atrial fibrillation (AF), National Institutes of Health Stroke Scale (NIHSS) scores. The SAP group also had a significantly lower DWI-ASPECTS than did the non-SAP group (P < 0.01). In the multivariable logistic regression analysis, the DWI-ASPECTS (adjusted odds ratio [aOR] = 1.438; 95% CI [1.158-1.787]; P < 0.01) remained significant after adjusting for confounders. What's more, the predictive ability of DWI-ASPECTS (AUC = 0.743 >0.7, 95% CI [0.678-0.800]) had acceptable discriminatory abilities. By the correlation analysis, DWI-ASPECTS was found to be negatively correlated with the count of white blood cell, neutrophils, monocytes, neutrophil-to-monocyte ratio and neutrophil-to-lymphocyte ratio, and positively correlated with the count of lymphocytes.

CONCLUSIONS

DWI-ASPECTS grades could predict stroke-associated pneumonia for patients with acute ischemic stroke, and combining grade with age, AF, or NIHSS could predict SAP events more accurately.

High Fibrinogen to Albumin Ratio: A Novel Marker for Risk of Stroke-Associated Pneumonia?

Background: Stroke-associated pneumonia (SAP) is associated with poor prognosis after acute ischemic stroke (AIS).

Purpose: This study aimed to describe the parameters of coagulation function and evaluate the association between the fibrinogen-to-albumin ratio (FAR) and SAP in patients with AIS.

Patients and methods: A total of 932 consecutive patients with AIS were included. Coagulation parameters were measured at admission. All patients were classified into two groups according to the optimal cutoff FAR point at which the sum of the specificity and sensitivity was highest. Propensity score matching (PSM) was performed to balance potential confounding factors. Univariate and multivariate logistic regression analyses were applied to identify predictors of SAP.

Results: A total of 100 (10.7%) patients were diagnosed with SAP. The data showed that fibrinogen, FAR, and D-dimer, prothrombin time (PT), activated partial thromboplastin time (aPTT) were higher in patients with SAP, while albumin was much lower. Patients with SAP showed a significantly increased FAR when compared with non-SAP (P < 0.001). Patients were assigned to groups of high FAR (≥0.0977) and low FAR (<0.0977) based on the optimal cut-off value. Propensity score matching analysis further confirmed the association between FAR and SAP. After adjusting for confounding and risk factors, multivariate regression analysis showed that the high FAR (≥0.0977) was an independent variable predicting the occurrence of SAP (odds ratio =2.830, 95% CI = 1.654–4.840, P < 0.001). In addition, the FAR was higher in the severe pneumonia group when it was assessed by pneumonia severity index (P = 0.008).

Conclusions: High FAR is an independent potential risk factor of SAP, which can help clinicians identify high-risk patients with SAP after AIS.

SNHG15 is a negative regulator of inflammation by mediating TRAF2 ubiquitination in stroke-induced immunosuppression

BACKGROUND

Abnormal expression of long noncoding RNAs (lncRNAs) has been reported in the acute stage of acute ischemic stroke (AIS). This study aimed to explore differential lncRNA expression in the subpopulations of peripheral blood mononuclear cells (PBMCs) from AIS patients and further evaluate its underlying mechanisms in stroke-induced immunosuppression.

METHODS

We reanalyzed lncRNA microarray data and investigated abnormally expressed lncRNAs in the subpopulations of PBMCs by magnetic cell sorting and real-time quantitative PCR. The potential mechanism of small nucleolar RNA host gene 15 (SNHG15) was explored through in vitro and in vivo approaches.

RESULTS

The stroke-induced SNHG15 acted as a checkpoint to inhibit peripheral inflammatory responses. Functional studies showed that SNHG15 promoted M2 macrophage polarization. Mechanistically, SNHG15 expression was dysregulated through the Janus kinase (JAK)-signal transducer and activator of transcription 6 (STAT6) signaling pathway. SNHG15, localized in the cytoplasm, interfered with K63-linked ubiquitination of tumor necrosis factor receptor-associated factor 2 and thereby repressed the activation of mitogen-activated protein kinase and nuclear factor kappa-B signaling pathways and prevented the production of proinflammatory cytokines. Administration of an adenovirus targeting SNHG15 improved stroke-induced immunosuppression in mice.

CONCLUSIONS

This study identified SNHG15 as a negative regulator of inflammation in stroke-induced immunosuppression, suggesting it as a novel biomarker and therapeutic target in stroke-associated infection. Trial registration ClinicalTrials.gov NCT04175691. Registered November 25, 2019, https://www.clinicaltrials.gov/ct2/show/NCT04175691 .

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.

Predictive value of monocyte to HDL cholesterol ratio for stroke-associated pneumonia in patients with acute ischemic stroke

Prior studies had reported monocyte to high-density lipoprotein cholesterol ratio (MHR) as a new inflammation marker and stroke-associated pneumonia (SAP) is common after stroke. We investigated the predictive value of MHR for SAP in patients with acute ischemic stroke (AIS). A total of 803 AIS patients within 72 h after stroke were enrolled from April 2012 to January 2016 in Zhangjiagang TCM Hospital affiliated to the Nanjing University of Chinese Medicine. MHR measurement within 24 h of hospital admission was divided into quartiles: Q1 (< 0.21), Q2 (0.21-0.30), Q3 (0.30-0.45), and Q4 (≥ 0.45). Monocyte count was also divided into categories. Clinical outcomes were post-stroke SAP and 3-month mortality. 121 patients (15.1%) experienced SAP during hospitalization, and 109 patients (13.6%) died from all causes within 3 months after AIS. Compared to the lowest quartile, having admission MHR level in the highest quartile was associated with SAP [adjusted odds ratio (aOR) 2.79, 95% confidence interval (CI) 1.44-5.42; P trend = 0.003]. Compared with the lowest category of monocyte, the highest category was associated with a 2.60-fold increase in the odds of SAP (aOR 2.60, 95% CI 1.28-5.30; P trend = 0.005). However, there was no significant association between MHR (P trend = 0.514) and monocyte count (P trend = 0.684) and all-cause mortality at 3 months. We demonstrated that both higher MHR and higher monocyte count at admission predicted SAP in patients with AIS.

Factors predicting non-ventilated hospital-acquired pneumonia: systematic review and meta-analysis

BACKGROUND

Hospital-acquired pneumonia (HAP) results in approximately 15-20% of all infections in hospitals, with more than two-thirds being in patients not using mechanical ventilation. The incidence of non-ventilated hospital-acquired pneumonia (NVHAP) is increasing, and it is associated with a longer length of stay, the need for intensive care unit hospitalization and mechanical ventilation use, and higher mortality.

AIM

To identify, quantify, and summarize predictive factors for NVHAP in adult patients admitted to non-intensive care units as determined by previous observational studies.

METHODS

PubMed, Embase, Scopus, and LILACS were systematically searched. Case-control and cohort studies were included, and a meta-analysis was performed for all factors studied more than once. National Institute of Health assessment tools were applied to assess the quality of the studies.

FINDINGS

Thirty-eight articles showing 204 predictive factors were included. A meta-analysis was performed for 58 factors, 32 of which were significantly associated with NVHAP. When the sensitivity analysis was performed without poor-quality studies, 24 factors remained associated with NVHAP.

CONCLUSION

Although there is a lack of good-quality studies to establish predictive factors for NVHAP, the results of this study showed 24 factors associated with the development of this infectious complication. Knowledge of the significant predictive factors for NVHAP will enable the identification of patients most likely to develop it.

Ischemic stroke and infection: A brief update on mechanisms and potential therapies

Ischemic stroke triggers a multifaceted inflammatory response in the brain that contributes to secondary brain injury and infarct expansion. In parallel with brain inflammation, ischemic stroke also leads to post-stroke immunosuppression. Stroke-induced leukopenia then predisposes patients to opportunistic infections potentially leading to pneumonia or unrinary tract infections and a worsened stroke outcome. There is evidence that the hypothalamic-pituitaryadrenal axis plays an important role in the etiology of post-stroke immunosuppression, by which prolonged glucocorticoid signalling leads to changes in immune responses. While opportunistic microbes in hospitals have been thought to be the source of infection, recent studies have reported that gut flora may also be a cause of post-stroke infection as a consequence of compromised integrity of the gut barrier after stroke. While antimicrobial drugs would appear to be a rational form of treatment for bacterial infections in stroke patients, the rise in drug-resistant bacteria and possible adverse effects of disrupting beneficial gut flora represent major challenges with these drugs. Considering the prominent role of gut microbiota in modulating immune responses, protecting and restoring the post-stroke gut bacteriome may provide significant benefit in the context of post-stroke infection. With such broad aspects of post-stroke infection occurring together with an extensive inflammatory response in the brain, a carefully considered administration of therapies for ischemic stroke is warranted.

The Relationship Between Serum YKL-40 Levels on Admission and Stroke-Associated Pneumonia in Patients with Acute Ischemic Stroke

Background

Stroke-associated pneumonia (SAP) is a standout complication after acute ischemic stroke (AIS), with a prevalence of 7–38%. The aim of this prospective study was to investigate the relationship between serum YKL-40 levels at admission and SAP.

Methods

Between August 2020 and February 2021, consecutive AIS patients from two centers were enrolled prospectively. Serum YKL-40 concentrations were measured via enzyme-linked immunosorbent assay. We performed logistic regression analyses to explore the relationship between YKL-40 and SAP. Receiver operating characteristic curve was also used to assess the predictive ability of YKL-40 in predicting SAP.

Results

Ultimately, a total of 511 AIS patients were recruited. Multivariate logistic regression analysis showed that YKL-40 was independently related to SAP, whether as a continuous variable or as quartiles (P=0.001). The area under curve of YKL-40 to predict SAP was 0.765. The optimal cutoff value of YKL-40 as a predictor of SAP was determined to be 206.4 ng/mL, where the sensitivity was 63.1% and the specificity was 82.0%.

Conclusion

Our study demonstrated that YKL-40 might be considered as a useful biomarker to predict SAP in AIS patients.

Dysbiosis of Gut Microbiota Is an Independent Risk Factor of Stroke-Associated Pneumonia: A Chinese Pilot Study

Background and Purpose

Identifying risks of stroke-associated pneumonia (SAP) is important for clinical management. We aimed to evaluate the association between gut microbiome composition and SAP in patients with acute ischemic stroke (AIS).

Methods

A prospective observational study was conducted, and 188 AIS patients were enrolled as the training cohort. Fecal and serum samples were collected at admission. SAP was diagnosed by specialized physicians, and disease severity scores were recorded. Fecal samples were subjected to 16S rRNA V4 tag sequencing and analysed with QIIME and LEfSe. Associations between the most relevant taxa and SAP were analysed and validated with an independent cohort. Fecal short-chain fatty acid (SCFA), serum D-lactate (D-LA), intestinal fatty acid-binding protein (iFABP) and lipopolysaccharide binding protein (LBP) levels were measured.

Results

Overall, 52 patients (27.7%) had SAP in the training cohort. The gut microbiome differed between SAP and non-SAP patients; specifically, Roseburia depletion and opportunistic pathogen enrichment were noted in SAP patients, as confirmed in the validation cohort (n=144, 28 SAP [19.4%]). Based on multivariate analysis, Roseburia was identified as a protective factor against SAP in both cohorts (training, aOR 0.52; 95% CI, 0.30-0.90; validation, aOR 0.44; 95% CI, 0.23-0.85). The combination of these taxa into a microbial dysbiosis index (MDI) revealed that dysbiosis increased nearly 2 times risk of SAP (training, aOR 1.95; 95% CI, 1.19-3.20; validation, aOR 2.22; 95% CI, 1.15-4.26). Lower fecal SCFA levels and higher serum D-LA levels were observed in SAP patients. Furthermore, SAP was an independent risk factor of 30-day death and 90-day unfavorable outcome.

Conclusion

We demonstrate that a microbial community with depleted Roseburia and enriched opportunistic pathogens is associated with increased risk of SAP among AIS patients. Gut microbiota screening might be useful for identifying patients at high risk for SAP and provide clues for stroke treatment.

Monocyte-to-lymphocyte ratio as a predictor of stroke-associated pneumonia: A retrospective study-based investigation

BACKGROUND AND PURPOSE

Early prediction of stroke-associated pneumonia (SAP) is significant in clinical practice, as it is frequently challenging due to delays in typical clinical manifestations and radiological changes. The monocyte-to-lymphocyte ratio (MLR) has been proposed as an indicator of systemic inflammation and infection. However, none of these studies have focused on the predictive value of the MLR for SAP. We investigated the predictive value of MLR for SAP and investigated its relationship with disease severity.

METHODS

In this retrospective study, we assessed 399 consecutive patients with acute stroke. SAP was defined according to the modified Centers for Disease Control and Prevention criteria. The severity of pneumonia was rated using the pneumonia severity index (PSI). MLR was calculated by dividing absolute monocyte counts by absolute lymphocyte counts.

RESULTS

Among all the patients, SAP occurred in 116 patients (29.1%). White blood cell (WBC), neutrophil, monocyte, and MLR levels in the SAP group were higher than those in the non-SAP group, while lymphocyte levels were lower (p < .05). Multivariable regression analysis revealed that the MLR (OR = 7.177; 95% CI = 1.190-43.292, p = .032) remained significant after adjusting for confounders. The ROC curve showed that the AUC value of MLR for SAP was 0.779, the optimal cutoff value of MLR for SAP was 0.388, with a specificity of 64.7% and sensitivity of 81.3%. The MLR levels were significantly higher in the severe pneumonia group when assessed by PSI (p = .024) than in the mild group. The AUC value of MLR was 0.622 (95% CI = 0.520-0.724, p = .024) in the severe pneumonia group. The optimal cutoff value of MLR was 0.750, with a specificity of 91.0% and a sensitivity of 33.0%.

CONCLUSIONS

Our study shows that a high MLR is an independent risk factor for SAP and has a predictive value for severe pneumonia in patients with SAP.

Prediction of stroke-associated pneumonia by the A2DS2, AIS-APS, and ISAN scores: a systematic review and meta-analysis

Background: Different scoring systems (A2DS2, AISAPS, ISAN) have been designed to predict the risk of in-hospital stroke-associated pneumonia (SAP). Studies have assessed the accuracy of these scores for predicting SAP. We performed this meta-analysis to consolidate the evidence on the predictive accuracies for SAP of the A2DS2, AISAPS, and ISAN scores.Materials and methods: We conducted a systematic search for all studies reporting the SAP predictive accuracy of A2DS2, AISAPS, or ISAN scores in the databases of PubMed Central, SCOPUS, MEDLINE, Embase, and Cochrane from inception until December 2020. We used the STATA software for the meta-analysis.Results: We included 19 studies with 35 849 patients. The pooled score sensitivities were 78% (95% CI, 71%-83%) for A2DS2, 79% (95% CI, 77%-81%) for AISAPS, and 79% (95% CI, 77%-81%) for ISAN. The pooled score specificities were 73% (95% CI, 65%-80%) for A2DS2, 74% (95% CI, 69%-79%) for AISAPS, and 74% (95% CI, 69%-79%) for ISAN. We found significant heterogeneity for all the scoring systems based on the chi-square test results and an I² statistic > 75%. We performed meta-regression to explore the source of heterogeneity and found that patient selection (p< 0.05) and reference standards (p< 0.05) in the sensitivity model, index test standards (p< 0.05), flow and timing of tests (p< 0.01) in the specificity model, and mean age (p < 0.001) in the joint model were the source of heterogeneity.Conclusions: To summarize, we found that A2S2, AISAPS and ISAN have moderate predictive accuracy for SAP with A2S2 having a stable cutoff value.

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.

Variation of stroke-associated pneumonia in stroke units across England and Wales: A registry-based cohort study

Background

Pneumonia is common in stroke patients and is associated with worse clinical outcomes. Prevalence of stroke-associated pneumonia varies between studies, and reasons for this variation remain unclear. We aimed to describe the variation of observed stroke-associated pneumonia in England and Wales and explore the influence of patient baseline characteristics on this variation.

Methods

Patient data were obtained from the Sentinel Stroke National Audit Programme for all confirmed strokes between 1 April 2013 and 31 December 2018. Stroke-associated pneumonia was defined by new antibiotic initiation for pneumonia within the first seven days of admission. The probability of stroke-associated pneumonia occurrence within stroke units was estimated and compared using a multilevel mixed model with and without adjustment for patient-level characteristics at admission.

Results

Of the 413,133 patients included, median National Institutes of Health Stroke Scale was 4 (IQR: 2–10) and 42.3% were aged over 80 years. Stroke-associated pneumonia was identified in 8.5% of patients. The median within stroke unit stroke-associated pneumonia prevalence was 8.5% (IQR: 6.1–11.5%) with a maximum of 21.4%. The mean and variance of the predicted stroke-associated pneumonia probability across stroke units decreased from 0.08 (0.68) to 0.05 (0.63) when adjusting for patient admission characteristics. This difference in the variance suggests that clinical characteristics account for 5% of the observed variation in stroke-associated pneumonia between units.

Conclusions

Patient-level clinical characteristics contributed minimally to the observed variation of stroke-associated pneumonia between stroke units. Additional explanations for the observed variation in stroke-associated pneumonia need to be explored which could reduce variation in antibiotic use for stroke patients.