The pneumonia score: a simple grading scale for prediction of pneumonia after acute stroke

Individualized prediction of stroke-associated pneumonia for patients with acute ischemic stroke

Background

Stroke-associated pneumonia (SAP) remains a neglected area despite its high morbidity and mortality. We aimed to establish an easy-to-use model for predicting SAP.

Methods

Two hundred seventy-five acute ischemic stroke (AIS) patients were enrolled, and 73 (26.55%) patients were diagnosed with SAP. T-test, Chi-square test and Fisher's exact test were used to investigate the associations of patient characteristics with pneumonia and its severity, and multivariable logistic regression models were used to construct a prediction scale.

Results

Three variables with the most significant associations, including age, NGT placement, and right cerebral hemisphere lesions combined with gender, were used to construct a stroke-associated pneumonia prediction scale with high accuracy (AUC = 0.93). Youden index of our SAP prediction model was 0.77. The sensitivity and specificity of our SAP prediction model were 0.89 and 0.88, respectively.

Conclusion

We identified the best predictive model for SAP in AIS patients. Our study aimed to be as clinically relevant as possible, focusing on features that are routinely available. The contribution of selected variables is visually displayed through SHapley Additive exPlanations (SHAP). Our model can help to distinguish AIS patients of high-risk, provide specific management, reduce healthcare costs and prevent life-threatening complications and even death.

The Efficacy of the Collaborative Respiratory Assessment Score (CoRAS) in Predicting Pneumonia Among Stroke Patients in Kaifukuki Rehabilitation Wards

Objective This study aims to assess the predictive accuracy and clinical utility of the Collaborative Respiratory Assessment Score (CoRAS) in identifying pneumonia risk among stroke patients in Kaifukuki Rehabilitation Wards (KRWs). CoRAS, developed by a multidisciplinary team, incorporates eight clinical parameters to quantify respiratory risk. The study retrospectively applies CoRAS to a cohort of stroke patients and evaluates its predictive performance using statistical methods, including logistic regression and receiver operating characteristic (ROC) curve analysis. Additionally, the study compares CoRAS with traditional risk factors such as age and pre-stroke care level to determine its unique contribution to pneumonia prediction. The findings aim to validate CoRAS as an effective tool for early risk stratification, supporting multidisciplinary collaboration and targeted interventions in KRWs. Methods We devised CoRAS as a scoring system based on eight clinical parameters: consciousness level, SpO₂, need for suctioning, history of respiratory diseases, FILS (Food Intake Level Scale), Hoffer criteria, nutritional status, and OHAT-J (Oral Health Assessment Tool - Japanese version). These parameters were weighted proportionally to sum up to a total score of 100. Assessments were independently conducted by seven multidisciplinary professionals, and the score was retrospectively applied to data from 629 stroke patients admitted to our hospital. Data on pneumonia occurrence were collected and analyzed. Results Pneumonia was observed in 48 (7.6%) of the 629 patients. The highest variance inflation factor (VIF) among the eight parameters was 2.11, validating the application of a linear combination model. ROC analysis showed an area under the curve of 0.860. Logistic regression revealed that CoRAS had an adjusted odds ratio of 1.06 per point for predicting pneumonia. Conclusion CoRAS demonstrated satisfactory predictive validity for pneumonia onset among stroke patients in the KRW, suggesting its utility as an assessment tool for multidisciplinary teams.

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

Background

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

Methods and Results

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

Conclusion

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

Prevalence and Risk Factors of Poststroke Dysphagia: A Meta-Analysis

INTRODUCTION

In patients with stroke, poststroke dysphagia (PSD) is a common complication that plays an important role in morbidity and mortality. The aim of this paper was to assess the prevalence and risk factors of PSD using a systemic review and meta-analysis.

METHODS

PubMed, Embase, Cochrane Library, and Web of Science databases were systematically searched for potentially eligible studies published until September 2023. Further, the pooled incidence and risk factors for PSD were determined using a random-effects model. Overall, 58 studies involving 37,404 patients with acute stroke were selected for the meta-analysis.

RESULTS

The pooled incidence of PSD in patients with acute stroke was 42% (95% confidence interval [CI]: 36-48%), which is the highest in South America (47%) and lowest in Asia (37%). Notably, older age (odds ratio [OR]: 2.13; 95% CI: 1.53-2.97; p < 0.001), hypertension (OR: 1.23; 95% CI: 1.06-1.44; p = 0.007), diabetes mellitus (OR: 1.22; 95% CI: 1.04-1.44; p = 0.014), stroke history (OR: 1.26; 95% CI: 1.04-1.53; p = 0.019), and atrial fibrillation (OR: 1.58; 95% CI: 1.02-2.44; p = 0.039) were found to be associated with an increased risk of PSD. Conversely, sex differences, smoking, alcoholism, obesity, hyperlipidemia, ischemic heart disease, stroke type, and the hemisphere affected were not associated with the risk of PSD.

CONCLUSION

The abstract reports the prevalence of PSD in patients with acute stroke and identified potential risk factors for PSD, including older age, hypertension, diabetes mellitus, stroke history, and atrial fibrillation.

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.

Predictors and impact of aspiration pneumonia in patients undergoing esophagogastroduodenoscopy: national inpatient sample 2016-2020

OBJECTIVES

Aspiration pneumonia is a rare but feared complication among patients undergoing esophagogastroduodenoscopy (EGD). Our study aims to assess the incidence as well as risk factors for aspiration pneumonia in patients undergoing EGD.

METHODS

National Inpatient Sample 2016-2020 was used to identify adult patients undergoing EGD. Patients were stratified into two groups based on the presence of aspiration pneumonia. Multivariate logistic regression analysis was performed to identify the risk factors associated with aspiration pneumonia. We adjusted for patient demographics, Elixhauser comorbidities and hospital characteristics.

RESULTS

Of the 1.8 million patients undergoing EGD, 1.9% of the patients developed aspiration pneumonia. Patients with aspiration pneumonia were mostly males (59.54%), aged >65 years old (66.19%), White (72.2%), had Medicare insurance (70.5%) and were in the lowest income quartile (28.7%). On multivariate analysis, the age >65 group, White race, congestive heart failure (CHF), neurological disorders and chronic obstructive pulmonary disease were associated with higher odds of aspiration pneumonia. This complication was associated with higher in-hospital mortality (9% vs. 0.8%; P  < 0.001) and longer length of stay (10.54 days vs. 4.85 days; P  < 0.001).

CONCLUSION

Our study found that rates of post-EGD aspiration pneumonia are increasing. We found a significant association between various comorbidities and aspiration pneumonia. Our data suggests that we need to optimize these patients before EGD, as the development of aspiration is associated with worsened outcomes. Further prospective studies are needed to clarify these associations.

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.

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.

Schizophrenia, but not depression or bipolar affective disorder, adds additional risk of aspiration pneumonia among stroke survivors: A national cohort study in Taiwan

OBJECTIVE

Few studies have assessed the sex-specific and age-specific risk of aspiration pneumonia (AP) in patients with stroke and evaluated whether mental disorders may increase this risk. In this population-based cohort study, we investigated the sex-specific and age-specific risk of AP in association with stroke and the joint effects of stroke and mental disorders on the risk of AP.

METHODS

We included 23,288 patients with incident stroke admitted between 2005 and 2017 and 68,675 matched nonstroke controls. Information on mental disorders was obtained from medical claims data within the 3 years before the stroke incidence. Cox proportional hazards models considering death as a competing risk event were constructed to estimate the hazard ratio of AP incidence by the end of 2018 associated with stroke and selected mental disorders.

RESULTS

After ≤14 years of follow-up, AP incidence was higher in the patients with stroke than in the controls (11.30/1000 vs. 1.51/1000 person-years), representing a covariate-adjusted subdistribution hazard ratio (sHR) of 3.64, with no significant sex difference. The sHR significantly decreased with increasing age in both sexes. Stratified analyses indicated schizophrenia but not depression or bipolar affective disorder increased the risk of AP in the patients with stroke.

CONCLUSION

Compared with their corresponding counterparts, the patients with schizophrenia only, stroke only, and both stroke and schizophrenia had a significantly higher sHR of 4.01, 5.16, and 8.01, respectively. The risk of AP was higher in younger stroke patients than those older than 60 years. Moreover, schizophrenia was found to increase the risk of AP in patients with stroke.

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.

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.

Braden scale for predicting pneumonia after spontaneous intracerebral hemorrhage

OBJECTIVE

Stroke-associated pneumonia is an infection that commonly occurs in patients with spontaneous intracerebral hemorrhage and causes serious burdens. In this study, we evaluated the validity of the Braden scale for predicting stroke-associated pneumonia after spontaneous intracerebral hemorrhage.

METHODS

Patients with spontaneous intracerebral hemorrhage were retrospectively included and divided into pneumonia and no pneumonia groups. The admission clinical characteristics and Braden scale scores at 24 h after admission were collected and compared between the two groups. Receiver operating characteristic curve analysis was performed to assess the predictive validity of the Braden scale. Multivariable analysis was conducted to identify the independent risk factors associated with pneumonia after intracerebral hemorrhage.

RESULTS

A total of 629 intracerebral hemorrhage patients were included, 150 (23.8%) of whom developed stroke-associated pneumonia. Significant differences were found in age and fasting blood glucose levels between the two groups. The mean score on the Braden scale in the pneumonia group was 14.1±2.4, which was significantly lower than that in the no pneumonia group (16.5±2.6), p<0.001. The area under the curve for the Braden scale for the prediction of pneumonia after intracerebral hemorrhage was 0.760 (95%CI 0.717-0.804). When the cutoff point was 15 points, the sensitivity was 74.3%, the specificity was 64.7%, the accuracy was 72.0%, and the Youden's index was 39.0%. Multivariable analysis showed that a lower Braden scale score (OR 0.696; 95%CI 0.631-0.768; p<0.001) was an independent risk factor associated with stroke-associated pneumonia after intracerebral hemorrhage.

CONCLUSION

The Braden scale, with a cutoff point of 15 points, is moderately valid for predicting stroke-associated pneumonia after spontaneous intracerebral hemorrhage.

Prevalence of dysphagia and risk of pneumonia and mortality in acute stroke patients: a meta-analysis

Background

Post-stroke dysphagia (PSD) has been associated with high risk of aspiration pneumonia and mortality. However, limited evidence on pooled prevalence of post-stroke dysphagia and influence of individual, disease and methodological factors reveals knowledge gap. Therefore, to extend previous evidence from systematic reviews, we performed the first meta-analysis to examine the pooled prevalence, risk of pneumonia and mortality and influence of prognostic factors for PSD in acute stroke.

Methods

Our search was conducted in CINAHL, Cochrane Library, EMBASE, Ovid-Medline, PubMed, and Web of Science an initial search in October 2020 and a follow-up search in May 2021. Data synthesis was conducted using the Freeman-Tukey double-arcsine transformation model for the pooled prevalence rate and the DerSimonian-Lard random-effects model for prognostic factors and outcomes of PSD.

Results

The pooled prevalence of PSD was 42% in 42 studies with 26,366 participants. PSD was associated with higher pooled odds ratio (OR) for risk of pneumonia 4.08 (95% CI, 2.13–7.79) and mortality 4.07 (95% CI, 2.17–7.63). Haemorrhagic stroke 1.52 (95% CI, 1.13–2.07), previous stroke 1.40 (95% CI, 1.18–1.67), severe stroke 1.38 (95% CI, 1.17–1.61), females 1.25 (95% CI, 1.09–1.43), and diabetes mellitus 1.24 (95% CI, 1.02–1.51) were associated with higher risk of PSD. Males 0.82 (95% CI, 0.70–0.95) and ischaemic stroke 0.54 (95% CI, 0.46–0.65) were associated with lower risk of PSD. Haemorrhagic stroke, use of instrumental assessment method, and high quality studies demonstrated to have higher prevalence of PSD in the moderator analysis.

Conclusions

Assessment of PSD in acute stroke with standardized valid and reliable instruments should take into account stroke type, previous stroke, severe stroke, diabetes mellitus and gender to aid in prevention and management of pneumonia and thereby, reduce the mortality rate.

Trial registration

https://osf.io/58bjk/?view_only=26c7c8df8b55418d9a414f6d6df68bdb.

Supplementary information

The online version contains supplementary material available at 10.1186/s12877-022-02960-5.

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.

The Relationship Between Dysphagia and Pneumonia in Acute Stroke Patients: A Systematic Review and Meta-Analysis

Background

Dysphagia is a common complication after stroke and is associated with the development of pneumonia. This study aimed to summarize the relationship between dysphagia and pneumonia in post-stroke patients.

Materials and Methods

Articles published up to November 2021 were searched in the PubMed, Embase, Cochrane library, and Scopus databases. Studies that investigated the development of pneumonia in acute stroke patients with and without dysphagia were included. The methodological quality of individual studies was evaluated using the Risk Of Bias In Non-randomized Studies-of Interventions tool, and publication bias was evaluated using a funnel plot and Egger's test.

Results

Of 5,314 studies, five studies were included in the meta-analysis. The results revealed that the incidence of pneumonia was significantly higher in the dysphagia group than in the non-dysphagia group (OR 9.60; 95% CI 5.75–16.04; p &lt; 0.0001; I2 = 78%). There was no significant difference in the mortality rate between the two groups (OR 5.64; 95% CI 0.83–38.18; p = 0.08; I2 = 99%).

Conclusion

Dysphagia is a significant risk factor for pneumonia after stroke. The early diagnosis and treatment of dysphagia in stroke patients are important to prevent stroke-associated pneumonia.

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.

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.

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.

SDL Index Predicts Stroke-Associated Pneumonia in Patients After Endovascular Therapy

Objective: This study aimed to develop and validate a novel index to predict SAP for AIS patients who underwent endovascular treatment.

Methods: A study was conducted in an advanced comprehensive stroke center from January 2013 to December 2019 aiming to develop and validate a novel index to predict SAP for AIS patients who underwent endovascular treatment. This cohort consisted of a total of 407 consecutively registered AIS patients who underwent endovascular therapy, which was divided into derivation and validation cohorts. Multiple blood parameters as well as demographic features, vascular risk factors, and clinical features were carefully evaluated in the derivation cohort. The independent predictors were obtained using multivariable logistic regression. The scoring system was generated based on the β-coefficients of each independent risk factor.

Results: Ultimately, a novel predictive model: the SDL index (stroke history, dysphagia, lymphocyte count < 1.00 × 10³/μL) was developed. The SDL index showed good discrimination both in the derivation cohort (AUROC: 0.739, 95% confidence interval, 0.678–0.801) and the validation cohort (AUROC: 0.783, 95% confidence interval, 0.707–0.859). The SDL index was well-calibrated (Hosmer–Lemeshow test) in the derivation cohort (P = 0.389) and the validation cohort (P = 0.692). We therefore divided our population into low (SDL index = 0), medium (SDL index = 1), and high (SDL index ≥ 2) risk groups for SAP. The SDL index showed good discrimination when compared with two existing SAP prediction models.

Conclusions: The SDL index is a novel feasible tool to predict SAP risk in acute ischemic stroke patients post endovascular treatment.

External Validation of Five Scores to Predict Stroke-Associated Pneumonia and the Role of Selected Blood Biomarkers

BACKGROUND AND PURPOSE

Several clinical scoring systems as well as biomarkers have been proposed to predict stroke-associated pneumonia (SAP). We aimed to externally and competitively validate SAP scores and hypothesized that 5 selected biomarkers would improve performance of these scores.

METHODS

We pooled the clinical data of 2 acute stroke studies with identical data assessment: STRAWINSKI and PREDICT. Biomarkers (ultrasensitive procalcitonin; mid-regional proadrenomedullin; mid-regional proatrionatriuretic peptide; ultrasensitive copeptin; C-terminal proendothelin) were measured from hospital admission serum samples. A literature search was performed to identify SAP prediction scores. We then calculated multivariate regression models with the individual scores and the biomarkers. Areas under receiver operating characteristic curves were used to compare discrimination of these scores and models.

RESULTS

The combined cohort consisted of 683 cases, of which 573 had available backup samples to perform the biomarker analysis. Literature search identified 9 SAP prediction scores. Our data set enabled us to calculate 5 of these scores. The scores had area under receiver operating characteristic curve of 0.543 to 0.651 for physician determined SAP, 0.574 to 0.685 for probable and 0.689 to 0.811 for definite SAP according to Pneumonia in Stroke Consensus group criteria. Multivariate models of the scores with biomarkers improved virtually all predictions, but mostly in the range of an area under receiver operating characteristic curve delta of 0.05.

CONCLUSIONS

All SAP prediction scores identified patients who would develop SAP with fair to strong capabilities, with better discrimination when stricter criteria for SAP diagnosis were applied. The selected biomarkers provided only limited added predictive value, currently not warranting addition of these markers to prediction models. Registration: URL: https://www.clinicaltrials.gov. Unique identifier: NCT01264549 and NCT01079728.

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

Stroke has been a leading cause of mortality in China. Stroke-associated infections (SAI) are common complications, occurring in 5–65% of stroke patients. Faced with SAI, clinicians often are placed in a considerable dilemma. On the one hand, preventive overuse of antibiotics will lead to the emergence of drug-resistant bacteria. On the other hand, treatment delay of the infection will likely result in a poor outcome. Therefore, it is necessary to determine the early predictors of post-stroke infection to screen patients with high infection risk for early clinical intervention, thereby promoting and improving survival rates. We assessed 257 patients with acute ischemic stroke from a consecutive retrospective cohort. Data of these patients were obtained from three hospitals (TongJi Hospital and its two branches) between August 2018 and June 2019. Of these patients, 59 (23.0%) developed SAI. SAI was defined according to the modified Centers for Disease Control and Prevention criteria. There were 38 patients (64.4%) who developed pneumonia, 11 with urinary tract infections (18.6%), and 10 with other infections (16.9%). We found that a higher neutrophil-to-lymphocyte ratio (adjusted odds ratio [aOR] = 1.16; 95% confidence interval [CI], 1.01–1.33; P = 0.034), National Institutes of Health Stroke Scale score (aOR = 1.18; CI, 1.09–1.27; p < 0.001), and dysphagia (aOR = 2.95; CI, 1.40–6.22; P = 0.004) were risk factors for SAI. Of note, hypertriglyceridemia (aOR = 0.35; CI, 0.13–0.90; P = 0.029) was a protective factor, lowering the risk of SAI. To this end, a reliable nomogram was constructed for the prediction of SAI in our study (mean C-index value ± standard deviation = 0.821 ± 0.03). It has the potential to be widely used and may help identify patients at high risk for SAI and make timely clinical decisions. Given our study was based on relatively small dataset, the results should be interpreted with care and external validation in independent datasets is very necessary.

A Comparison of the National Institutes of Health Stroke Scale and the Gugging Swallowing Screen in Predicting Stroke-Associated Pneumonia

Background

There have been many scales to predict pneumonia in stroke patients, but they are so complex, making it difficult to apply in practice. Therefore, we conducted this study to assess the role of the National Institutes of Health Stroke Scale (NIHSS) and the Gugging Swallowing Screen (GUSS) in predicting stroke-associated pneumonia (SAP). These scales are routinely used in stroke patients. Therefore, their application in predicting SAP risk will be of high value in clinical practice. There has been no previous study evaluating the effectiveness of SAP risk prediction for each of these scales.

Aim

This study aimed to compare the value of NIHSS and GUSS in SAP prediction and their convenience in clinical practice.

Methods

It was a cohort study. The receiver operating characteristics (ROC) curves were constructed to assess the sensitivity (Se) and specificity (Sp) of the scales. Area under the curves (AUC) were calculated, and we compared them.

Results

NIHSS had a medium value of predictor of SAP with AUC 0.764 (95% CI 0.735–0.792), 65.4% Se, 76.5% Sp. GUSS had good value in predicting SAP with AUC 0.858 (95% CI 0.833–0.880), 80.5% Se, 80.1% Sp. Pairwise comparison of ROCs curves demonstrated that the difference between two AUCs was significant (p < 0.01). Performing GUSS required 24.5 ± 6.7 minutes, 2.5 times longer than NIHSS (9.9 ± 2.0 minutes).

Conclusion

GUSS had a better predictive value of SAP than NIHSS. But NIHSS was more convenient in clinical practice because of its simple instrument and quick performance.

Pneumonia risk factors in stroke patients

ABSTRACT Purpose: to assess the demographic and clinical characteristics associated with the development of pneumonia in post-stroke patients hospitalized in a tertiary hospital, located in the Vale do São Francisco, that covers the states of Pernambuco and Bahia, Brazil. Methods: a unicentric, observational, analytical, cross-sectional study, based on the medical records of patients diagnosed with stroke and included in the Stroke Registry (RAVESS study). The statistical analysis was made with the chi-square test, Fisher’s exact test, and the analysis of variance, with the Bonferroni’s post-test, and P≤0.05. Results: data from 69 patients presented with acute stroke were collected, aged 63.2±16.8 years; 37 (53.6%) were females; the prevalence of pneumonia during hospital stay was estimated at 31.9% (95% confidence interval: 21.2-44.2%). In the univariate analysis of predictors for post-stroke pneumonia, the following were identified: older age (72.6±17.9 vs. 58.8±14.5; P = 0.001), lower response signal to the Glasgow Coma Scale at admission (11.3±1.8 vs. 13.3±2.1; P = 0.001), and higher frequency of dysarthria at admission (61.9% vs. 27.9%; P = 0.009). Conclusion: pneumonia was a prevalent complication in post-stroke patients at a Brazilian tertiary hospital. It was related to the patient’s older age and the severity of the cerebral event.

Risk stratification model for post-stroke pneumonia in patients with acute ischemic stroke

BACKGROUND

Post-stroke pneumonia (PSP) has been implicated in the morbidity, mortality, and increased medical costs after acute ischemic stroke.

AIM

The aim of this study was to develop a prediction model for PSP in patients with acute ischemic stroke.

METHODS

A retrospective, case-control, secondary analysis study was conducted using data for 10,034 patients with ischemic stroke who presented to the hospital within 24 hours of onset of stroke symptoms. The predictive factors for PSP were analyzed using multivariate logistic regression and classification and regression tree (CART) analyses.

RESULTS

Among the study population, 546 patients (5.4%) had PSP. Multivariate logistic regression revealed that age, atrial fibrillation, smoking habit, body temperature at admission, pulse rate at admission, National Institute of Health Stroke Scale (NIHSS) score upon admission, white blood cell count, and blood urea nitrogen level were major predictive factors of PSP. CART analysis identified NIHSS score at admission, pulse rate at admission, and percentage of lymphocyte as important factors for PSP to stratify the patients into subgroups. The subgroup of patients with an NIHSS score >14 at admission and pulse rate >111 beats per minute at admission and those with an NIHSS score >14, pulse rate ⩽111 beats per minute at admission, and percentage of lymphocyte ⩽9.2% had a relatively high risk of PSP (39.6% and 35.5%, respectively).

CONCLUSIONS

In this study, CART analysis has a similar predictive value of PSP as compared with a logistic regression model. In addition, decision rules generated by CART can easily be interpreted and applied in clinical practice.

Braden scale for assessing pneumonia after acute ischaemic stroke

Background

The prevention of pneumonia is critical for patients with acute ischaemic stroke (AIS). The six subscales in the Braden Scale seem to be related to the occurrence of pneumonia. We aimed to evaluate the feasibility of using the Braden Scale to predict the occurrence of pneumonia after AIS.

Methods

We studied a series of consecutive patients with AIS who were admitted to the hospital. The cohort was subdivided into pneumonia and no pneumonia groups. The scores on the Braden Scale, demographic characteristics and clinical characteristics were obtained and analysed by statistical comparisons between the two groups. We investigated the predictive validity of the Braden Scale by receiver operating characteristic (ROC) curve analysis.

Results

A total of 414 patients with AIS were included in this study. Of those 414 patients, 57 (13.8%) patients fulfilled the criteria for post-stroke pneumonia. There were significant differences in age and histories of chronic obstructive pulmonary disease (COPD), dysphagia and Glasgow Coma Scale (GCS) score between the two groups, and the National Institutes of Health Stroke Scale (NIHSS) score in the pneumonia group was significantly higher than that in the no pneumonia group (P < 0.01). The mean score on the Braden Scale in the pneumonia group was significantly lower than that in the no pneumonia group (P < 0.01). The six subscale scores on the Braden Scale were all significantly different between the two groups. The area under the curve (AUC) for the Braden Scale for the prediction of pneumonia after AIS was 0.883 (95% CI = 0.828–0.937). With 18 points as the cutoff point, the sensitivity was 83.2%, and the specificity was 84.2%.

Conclusion

The Braden Scale with 18 points as the cutoff point is likely a valid clinical grading scale for predicting pneumonia after AIS at presentation. Further studies on the association of the Braden Scale score with stroke outcomes are needed.

Predicting post-stroke pneumonia using deep neural network approaches

BACKGROUND AND PURPOSE

Pneumonia is a common complication after stroke, causing an increased length of hospital stay and death. Therefore, the timely and accurate prediction of post-stroke pneumonia would be highly valuable in clinical practice. Previous pneumonia risk score models were often built on simple statistical methods such as logistic regression. This study aims to investigate post-stroke pneumonia prediction models using more advanced machine learning algorithms, specifically deep learning approaches.

METHODS

Using a hospital's electronic health record(EHR) data from 2007-2017, 13,930 eligible patients with acute ischaemic stroke (AIS) were identified to build and evaluate the models (85% of the patients were used for training, and 15% were used for testing). In total, 1012 patients (7.23%) contracted pneumonia during hospitalization. A number of machine learning methods were developed and compared to predict pneumonia in the stroke population in China. In addition to the classic methods (i.e., logistic regression (LR), support vector machines (SVMs), extreme gradient boosting (XGBoost)), methods based on multiple layer perceptron (MLP) neural networks and recurrent neural network (RNNs) (i.e., attention-augmented gated recurrent unit (GRU)) are also implemented to make use of the temporal sequence information in electronic health record (EHR) systems. Prediction models for pneumonia were built for two time windows, i.e., within 7 days and within 14 days after stroke onset. In particular, pneumonia occurring within the 7-day window is considered highly associated with stroke (stroke-associated pneumonia, SAP).

MAIN FINDINGS

The attention-augmented GRU model achieved the best performance based on an area under the receiver operating characteristic curve (AUC) of 0.928 for pneumonia prediction within 7 days and an AUC of 0.905 for pneumonia prediction within 14 days. This method outperformed the other machine learning-based methods and previously published pneumonia risk score models. Considering that pneumonia prediction after stroke requires a high sensitivity to facilitate its prevention at a relatively low cost (i.e., increasing the nursing level), we also compared the prediction performance using other evaluation criteria by setting the sensitivity to 0.90. The attention-augmented GRU achieved the optimal performance, with a specificity of 0.85, a positive predictive value (PPV) of 0.32 and a negative predictive value (NPV) of 0.99 for pneumonia within 7 days and a specificity of 0.82, a PPV of 0.29 and an NPV of 0.99 for pneumonia within 14 days.

CONCLUSIONS

The deep learning-based predictive model is feasible for stroke patient management and achieves the optimal performance compared to many classic machine learning methods.

Men Experience Higher Risk of Pneumonia and Death After Intracerebral Hemorrhage

BACKGROUND

Infectious complications worsen outcome after intracerebral hemorrhage (ICH). We investigated the impact of sex on post-ICH infections and mortality.

METHODS

Consecutive ICH patients (admitted to a single hospital between 1994 and 2015) were retrospectively assessed via chart review to ascertain the following in-hospital infections: urinary tract infection (UTI), pneumonia, and sepsis. Adjusted logistic regression was performed to identify associations between sex, infection, and mortality at 90 days.

RESULTS

Two thousand and four patients were investigated, 1071 (53.7%) males. Men were more likely to develop pneumonia (21.9 vs 15.5% p < 0.001) and sepsis (3.4 vs 1.6%, p = 0.009), whereas women had higher risk of UTI (19.9 vs 11.7% p < 0.001). Multivariate analyses confirmed association between male sex and pneumonia (Odds Ratio (OR) 1.37, 95% confidence interval (CI) 1.08-1.74, p = 0.011). Male sex (OR 1.40; CI 1.07-1.85; p = 0.015) and infection (OR 1.56; CI 1.11-1.85; p = 0.011) were independently associated with higher 90-day mortality.

CONCLUSIONS

Types and rates of infection following ICH differ by sex. Male sex independently increases pneumonia risk, which subsequently increases 90-day mortality. Sex-specific preventive strategies to reduce the risk of these complications may be one strategy to improve ICH outcomes.

Epidemiologic features and risk factors of sepsis in ischemic stroke patients admitted to intensive care: A prospective cohort study

BACKGROUND/OBJECTIVE

Stroke is the second leading cause of death globally that predisposed to sepsis. Therefore, this study was aimed to assess the risk factors and epidemiologic features of sepsis in ischemic stroke patients admitted to ICUs.

METHODS

Throughout this prospective study, we investigated all severe ischemic stroke patients admitted to ICUs of Namazi and Ali-Ashghar Hospitals in Shiraz. After ICU admission and diagnosing stroke by a neurologist according to NIHSS (National Institute of Health Stroke Scale) criteria, sepsis work-up was performed in all patients suspected to have sepsis. Then the incidence of sepsis and its risk factors in ICU admitted stroke patients were determined.

RESULTS

A total of 149 patients were screened in this study. The mean age of the participants was 65.37 ± 15.40 years old and 57.4% of them were male. Hypertension was the most common coexistent disease (74.6%) in stroke patients. Seventy-six patients (62.3%) were diagnosed with sepsis and pneumonia was the most common infection leading to sepsis in stroke patients. Our data showed significant differences between two groups in terms of APACHE-IV score (P < 0.001), NIHSS and APS (P < 0.001) before ICU admission (P < 0.001) and NIHSS at admission (P < 0.001); however, age (P = 0.07) and sex (P = 0.17) were not significantly different between the groups. Logistic regression analysis displayed that severe stroke (NIHSS = 21-42, OR = 49.09) and severe loss of consciousness (GCS < 8, OR = 27.95) at admission were the most essential predictive factors for sepsis after ischemic stroke.

CONCLUSIONS

This study showed that ICU patients with severe ischemic stroke were more susceptible to sepsis during the hospital course.

A 2 DS 2 Score to Predict the Risk of Stroke-Associated Pneumonia in Acute Stroke: An Indian Perspective

Background  Stroke-associated pneumonia (SAP) is an important cause of poststroke morbidity and mortality. Several clinical risk scores predict the risk of SAP. In this study, we used the A ² DS ² score (age, atrial fibrillation, dysphagia, sex, and stroke severity) to assess the risk of SAP in patients admitted with acute stroke. Methods  A high (5-10) and a low (0-4) A ² DS ² score was assigned to patients with acute stroke admitted to the neurology ward. Univariate binary logistic regression analysis was performed to find the strength of association of SAP and A ² DS ² score. Results  There were 250 patients with acute stroke of which 46 developed SAP. Forty-four patients developed SAP in high score as against 2 in low-score group (odds ratio [OR] = 0.03, 95% confidence interval [CI] = 0.01-0.15, p = 0.0001). A ² DS ² score >5 had sensitivity of 82.6% and specificity of 65.1% to predict SAP. The mean A ² DS ² score in patients with pneumonia was 7.02 ± 1.40 compared to 4.75 ± 1.92 in patients without pneumonia ( p = 0.0001). Conclusions  A ² DS ² score has a high sensitivity of 82% in predicting the risk of SAP and is a useful tool to monitor patients after acute stroke. A ² DS ² score can help in timely detection and prevention of SAP and reduction in caregiver's burden.

The effects of a standardized nursing intervention model on immobile patients with stroke: a multicenter study in China

BACKGROUND

Immobility complications, including pressure injuries (PIs), deep vein thrombosis (DVT), pneumonia, and urinary tract infections (UTIs), affect the clinical outcomes of stroke patients. A standardized nursing intervention model (SNIM) was constructed and implemented to improve the quality of care and clinical outcomes among immobile patients with stroke.

AIMS

To assess the benefit of SNIM for immobility complication rates, including PIs, DVT, pneumonia, and UTIs, and mortalities in immobile patients with stroke.

METHODS

A before and after study design was used. Patients were divided into a pre- and post-SNIM training original cohort and matched for socioeconomic, demographic, and disease characteristics using propensity score. We fitted logistic regression models to examine the effect of SNIM, and whether the benefit differed between tertiary and non-tertiary hospitals.

RESULTS

In the original cohort, the rate of pneumonia, UTIs, and mortality was lower after SNIM training. Furthermore, in the matched cohort, the difference in PI rates was significant. Logistic regression analysis revealed that the probability of PIs, pneumonia, UTIs, and mortality were significantly reduced after SNIM training in the original cohort and this estimated value changed little in the matched cohort. Our results show that the decreased rates of pneumonia, UTIs, and mortality were mainly among non-tertiary hospitals.

CONCLUSIONS

A structured and systematic SNIM benefited immobile stroke patients' clinical outcomes, but mainly in non-tertiary hospitals in China. Standardized nursing training is needed in non-tertiary hospitals.

Predictive Factors of Swallowing Disorders and Bronchopneumonia in Acute Ischemic Stroke

BACKGROUND

In stroke patients, early complications such as swallowing disorders (SD) and bronchopneumonia (BP) are frequent and may worsen outcome. The aim of this study was to evaluate the prevalence of SD in acute ischemic stroke (AIS) and the risk of BP, as well as to identify factors associated with these conditions.

METHODS

We retrospectively studied all AISs over a 12-month period in a single-center registry. We determined the frequency of SD in the first 7 days and of BP over the entire hospital stay. Associations of SD and BP with patient characteristics, stroke features, dental status, and presence of a feeding tube were analyzed in multivariate analyses.

RESULTS

In the 340 consecutive patients, the overall frequency of SD and BP was 23.8% and 11.5%, respectively. The multivariate analyses showed significant associations of SD with NIHSS scores >4, involvement of the medulla oblongata and wearing a dental prosthesis (area under the receiver-operator curve (AUC) of 76%). BP was significantly associated with NIHSS scores >4, male sex, bilateral cerebral lesions, the presence of SD, and the use of an enteral feeding tube (AUC 84%). In unadjusted analysis, unfavorable 12-month outcome and mortality were increased in the presence of SD.

CONCLUSION

In AIS, SD and BP are associated with stroke severity and localization and wearing a dental prosthesis increases the risk of SD. Given that patients with SD have an increased risk of poor outcome and mortality, high-risk patients warrant early interventions, including more randomized trials.

Proportion of Aspiration Pneumonia Cases Among Patients With Community-Acquired Pneumonia: A Single-Center Study in Korea

Objective

To investigate the proportion of aspiration pneumonia cases among patients with community-acquired pneumonia in Korea.

Methods

This retrospective study included patients with community-acquired pneumonia who had been admitted to the emergency department of a university-affiliated tertiary hospital in Gyeonggi Province, Korea between January 1, 2016 and December 31, 2016. Among these patients, those with aspiration pneumonia were identified using ICD-10 codes (J69.^*). Patients with recurrent pneumonia were excluded, as were those who were immunocompromised. The proportion of cases of aspiration pneumonia was calculated, and the characteristics and clinical outcomes of patients with aspiration pneumonia and non-aspiration pneumonia were compared.

Results

The proportion of aspiration pneumonia cases among patients with community-acquired pneumonia was 14.2%. Patients with aspiration pneumonia were significantly more likely to be older (p<0.001) and male (p<0.001), and to have a higher confusion, uremia, respiratory rate, blood pressure, and age ≥65 years (CURB-65) score (p<0.001) as compared to patients with non-aspiration pneumonia. They were also more likely to require admission to the intensive care unit (p<0.001) and a longer hospital stay (p<0.001).

Conclusion

Aspiration pneumonia accounts for 14.2% of all cases of community-acquired pneumonia in Korea. These data may contribute to the establishment of healthcare strategies for managing aspiration pneumonia among Korean adults.

Clopidogrel may decrease the risk of post-stroke infection after ischaemic stroke

BACKGROUND AND PURPOSE

The P2Y12 receptor, a well-known factor in the platelet activation pathway, plays a role in thrombosis as well as systemic inflammation. Clopidogrel, a prototype P2Y12 receptor antagonist, reportedly decreases inflammation and systemic infection. The aim of this study was to evaluate whether clopidogrel use decreases the risk of post-stroke infection following ischaemic stroke.

METHODS

A total of 1643 patients with acute ischaemic stroke (within 7 days after onset) were included for analysis between March 2010 and December 2015. Patients were categorized into two groups (clopidogrel users versus clopidogrel non-users), and clinical characteristics and risks of post-stroke infection were compared between the two groups. The inverse probability of treatment weighting using propensity scores for baseline imbalance adjustments was applied.

RESULTS

Of the included patients (mean age 67.7 years; men 60.6%), 670 (40.8%) patients were clopidogrel users and 164 (10.0%) patients had post-stroke infection. The proportion of patients with post-stroke infection was significantly lower in clopidogrel users compared to clopidogrel non-users (6.7% vs. 12.2%, P ≤ 0.001). Moreover, clopidogrel users were less likely to be admitted to the intensive care unit (13.3% vs. 35.3%, P = 0.006). A multivariate analysis with inverse probability of treatment weighting revealed that clopidogrel users exhibited a lower risk of post-stroke infection (odds ratio 0.56, 95% confidence interval 0.42-0.75) and intensive care unit admission (odds ratio 0.34, 95% confidence interval 0.22-0.53).

CONCLUSIONS

The study suggested that clopidogrel users exhibit a lower risk of infection and develop less severe infections after ischaemic stroke. Further prospective studies are needed.

Risk factors for the development of chest infections in acute stroke: a systematic review

BACKGROUND

Chest infections occur in approximately one-third of patients following acute stroke, and are associated with poor outcomes. Limitations in previous reviews restricted the accuracy of results.

OBJECTIVES

To perform a systematic review to reliably identify modifiable risk factors for chest infections following acute stroke.

METHODS

Ovid Medline, CINAHL, Cochrane, EMBASE and AMED were searched from 1946 to April 2017 for observational studies where risk factors for chest infections in patients hospitalized with acute stroke were reported. Key words used to identify included chest infection or pneumonia. Included studies were evaluated based on methodological criteria and scientific quality. Results were collated and separate meta-analyses were performed for risk factors examined in three or more studies where quality and homogeneity criteria were met.

RESULTS

3172 studies were identified, 15 were eligible for inclusion. Data collection methods included primary data collection, medical record audit and registry data. Chest infections were diagnosed 2-30 days following acute stroke in ten studies. Of the 39 risk factors identified, four were included in the meta-analysis. These were mechanical ventilation: 4 studies, OR: 3.83, 95%CI: 3.21, 4.57; diabetes: 4 studies, OR: 1.06, 95%CI: 1.04, 1.08; pre-existing respiratory conditions: 3 studies, OR: 1.48, 95%CI 1.21, 1.81 and atrial fibrillation: 3 studies, OR: 1.21, 95%CI: 1.17, 1.24. Common risk factors not eligible for meta-analysis were dysphagia and cardiac comorbidities.

CONCLUSION

Evidence has been comprehensively synthesized to provide reliable estimates of the association between important risk factors and chest infection. Monitoring patients meeting these criteria may promote early identification and treatment to improve long-term outcomes.

Predictors of post-stroke fever and infections: a systematic review and meta-analysis

Background

Fever after stroke is common, and often caused by infections. In the current study, we aimed to test the hypothesis that pneumonia, urinary tract infection and all-cause fever (thought to include at least some proportion of endogenous fever) have different predicting factors, since they differ regarding etiology.

Methods

PubMed was searched systematically for articles describing predictors for post-stroke pneumonia, urinary tract infection and all-cause fever. A total of 5294 articles were manually assessed; first by title, then by abstract and finally by full text. Data was extracted from each study, and for variables reported in 3 or more articles, a meta-analysis was performed using a random effects model.

Results

Fifty-nine articles met the inclusion criteria. It was found that post-stroke pneumonia is predicted by age OR 1.07 (1.04–1.11), male sex OR 1.42 (1.17–1.74), National Institutes of Health Stroke Scale (NIHSS) OR 1.07 (1.05–1.09), dysphagia OR 3.53 (2.69–4.64), nasogastric tube OR 5.29 (3.01–9.32), diabetes OR 1.15 (1.08–1.23), mechanical ventilation OR 4.65 (2.50–8.65), smoking OR 1.16 (1.08–1.26), Chronic Obstructive Pulmonary Disease (COPD) OR 4.48 (1.82–11.00) and atrial fibrillation OR 1.37 (1.22–1.55). An opposite relation to sex may exist for UTI, which seems to be more common in women.

Conclusions

The lack of studies simultaneously studying a wide range of predictors for UTI or all-cause fever calls for future research in this area. The importance of new research would be to improve our understanding of fever complications to facilitate greater vigilance, monitoring, prevention, diagnosis and treatment.

Development and internal validation of a prediction rule for post-stroke infection and post-stroke pneumonia in acute stroke patients

Introduction

Patients with acute stroke are at high risk for infection. These infections are associated with unfavourable outcome after stroke. A prediction rule can identify the patients at the highest risk for strategies to prevent infection. We aim to develop a prediction rule for post-stroke pneumonia and other infections in patients with acute stroke.

Patients and methods

We used data from the Preventive Antibiotics in Stroke Study, a multicentre randomised trial comparing preventive ceftriaxone vs. standard stroke care in patients with acute stroke. Possible predictors for post-stroke pneumonia or infection were selected from the literature. Backward elimination logistic regression analysis was used to construct prediction rules for pneumonia or infection. Internal validation was performed and a risk chart was constructed. We adjusted for preventive antibiotic use.

Results

Pneumonia was diagnosed in 159 of the 2538 included patients, and infection in 348. Pneumonia was predicted by higher age, male sex, pre-stroke disability, medical history of chronic obstructive pulmonary disease, more severe stroke, dysphagia and intracerebral haemorrhage (rather than ischaemic stroke). Infections were predicted by higher age, male sex, history of diabetes, chronic obstructive pulmonary disease, more severe stroke, dysphagia, use of bladder catheter, preventive antibiotic use and intracerebral haemorrhage. With the prediction rule developed, risks for pneumonia ranged from 0.4% to 56.2% and from 1.8% to 88.0% for infection. Discrimination of the score was good (C-statistic, 0.84; 95% CI: 0.81–0.87 and 0.82; 95% CI: 0.79–0.84 for pneumonia and infection).

Conclusions

The Preventive Antibiotics in Stroke Study pneumonia and infection rule identify patients at the highest risk for post-stroke pneumonia or infection and may be used for future studies and novel therapies, after confirmation in an external population.

Antibiotic therapy for preventing infections in people with acute stroke

BACKGROUND

Stroke is the main cause of disability in high-income countries and ranks second as a cause of death worldwide. Infections occur frequently after stroke and may adversely affect outcome. Preventive antibiotic therapy in the acute phase of stroke may reduce the incidence of infections and improve outcome. In the previous version of this Cochrane Review, published in 2012, we found that antibiotics did reduce the risk of infection but did not reduce the number of dependent or deceased patients. However, included studies were small and heterogeneous. In 2015, two large clinical trials were published, warranting an update of this Review.

OBJECTIVES

To assess the effectiveness and safety of preventive antibiotic therapy in people with ischaemic or haemorrhagic stroke. We wished to determine whether preventive antibiotic therapy in people with acute stroke:• reduces the risk of a poor functional outcome (dependency and/or death) at follow-up;• reduces the occurrence of infections in the acute phase of stroke;• reduces the occurrence of elevated body temperature (temperature ≥ 38° C) in the acute phase of stroke;• reduces length of hospital stay; or• leads to an increased rate of serious adverse events, such as anaphylactic shock, skin rash, or colonisation with antibiotic-resistant micro-organisms.

SEARCH METHODS

We searched the Cochrane Stroke Group Trials Register (25 June 2017); the Cochrane Central Register of Controlled Trials (CENTRAL; 2017, Issue 5; 25 June 2017) in the Cochrane Library; MEDLINE Ovid (1950 to 11 May 2017), and Embase Ovid (1980 to 11 May 2017). In an effort to identify further published, unpublished, and ongoing trials, we searched trials and research registers, scanned reference lists, and contacted trial authors, colleagues, and researchers in the field.

SELECTION CRITERIA

Randomised controlled trials (RCTs) of preventive antibiotic therapy versus control (placebo or open control) in people with acute ischaemic or haemorrhagic stroke.

DATA COLLECTION AND ANALYSIS

Two review authors independently selected articles and extracted data; we discussed and resolved discrepancies at a consensus meeting with a third review author. We contacted study authors to obtain missing data when required. An independent review author assessed risk of bias using the Cochrane 'Risk of bias' tool. We calculated risk ratios (RRs) for dichotomous outcomes, assessed heterogeneity amongst included studies, and performed subgroup analyses on study quality.

MAIN RESULTS

We included eight studies involving 4488 participants. Regarding quality of evidence, trials showed differences in study population, study design, type of antibiotic, and definition of infection; however, primary outcomes among the included studies were consistent. Mortality rate in the preventive antibiotic group was not significantly different from that in the control group (373/2208 (17%) vs 360/2214 (16%); RR 1.03, 95% confidence interval (CI) 0.87 to 1.21; high-quality evidence). The number of participants with a poor functional outcome (death or dependency) in the preventive antibiotic therapy group was also not significantly different from that in the control group (1158/2168 (53%) vs 1182/2164 (55%); RR 0.99, 95% CI 0.89 to 1.10; moderate-quality evidence). However, preventive antibiotic therapy did significantly reduce the incidence of 'overall' infections in participants with acute stroke from 26% to 19% (408/2161 (19%) vs 558/2156 (26%); RR 0.71, 95% CI 0.58 to 0.88; high-quality evidence). This finding was highly significant for urinary tract infections (81/2131 (4%) vs 204/2126 (10%); RR 0.40, 95% CI 0.32 to 0.51; high-quality evidence), whereas no preventive effect for pneumonia was found (222/2131 (10%) vs 235/2126 (11%); RR 0.95, 95% CI 0.80 to 1.13; high-quality evidence). No major side effects of preventive antibiotic therapy were reported. Only two studies qualitatively assessed the occurrence of elevated body temperature; therefore, these results could not be pooled. Only one study reported length of hospital stay.

AUTHORS' CONCLUSIONS

Preventive antibiotics had no effect on functional outcome or mortality, but significantly reduced the risk of 'overall' infections. This reduction was driven mainly by prevention of urinary tract infection; no effect for pneumonia was found.

[Risk factors for the onset of aspiration pneumonia among stroke patients in the recovery stage]

AIM

Post-stroke aspiration pneumonia is one of the most common complications among stroke patients. Although the onset of aspiration pneumonia is caused by a disruption of the balance between invasion (the type and amount of oral flora and aspiration) and host resistance (the protective airway reflex and immune function), several previous studies have focused on invasion, such as aspiration and dysphagia. In this study, we examined the importance of the host resistance to aspiration pneumonia among stroke patients with dysphagia.

METHODS

The study subjects included 76 stroke patients (mean age, 74.7±8.4 years) with dysphagia chosen from 175 stroke patients who were newly admitted to four rehabilitation hospitals. We divided the subjects into two groups based on the onset of pneumonia during the period of admission and compared their status.

RESULTS

Ten patients (13.2%) developed pneumonia at the hospital, and all of the affected patients were over 65 years old. Significant differences existed between the two groups with respect to the gender, activity level, albumin level, nutrition method and severity of dysphagia (p<0.05).

CONCLUSIONS

Our study revealed that recumbency, malnutrition, tube feeding, severe dysphagia and female sex were risk factors for pneumonia. In particular, dysphagia was closely associated with aspiration pneumonia. Moreover, host resistance factors, such as recumbency and malnutrition, also play important roles in the development of aspiration pneumonia.

External Validation of the Prestroke Independence, Sex, Age, National Institutes of Health Stroke Scale Score for Predicting Pneumonia After Stroke Using Data From the China National Stroke Registry

BACKGROUND AND PURPOSE

Pneumonia is an important risk factor for mortality and morbidity after stroke. The Prestroke Independence, Sex, Age, National Institutes of Health Stroke Scale (ISAN) score was shown to be a useful tool for predicting stroke-associated pneumonia based on UK multicenter cohort study. We aimed to externally validate the score using data from the China National Stroke Registry (CNSR).

METHODS

Eligible patients with acute ischemic stroke (AIS) and intracerebral hemorrhage (ICH) in the CNSR from 2007 to 2008 were included. The area under the receiver operating characteristic (AUC) curve was used to evaluate discrimination. The Hosmer-Lemeshow goodness of fit test and Pearson correlation coefficient were performed to assess calibration of the model.

RESULTS

A total of 19,333 patients (AIS = 14400; ICH = 4933) were included and the overall pneumonia rate was 12.7%. The AUC was .76 (95% confidence interval [CI]: .75-.78) for the subgroup of AIS and .70 (95% CI: .68-.72) for the subgroup of ICH. The Hosmer-Lemeshow test showed the ISAN score with the good calibration for AIS and ICH (P = .177 and .405, respectively). The plot of observed versus predicted pneumonia rates suggested higher correlation for patients with AIS than with ICH (Pearson correlation coefficient = .99 and .83, respectively).

CONCLUSIONS

The ISAN score was a useful tool for predicting in-hospital pneumonia after acute stroke, especially for patients with AIS. Further validations need to be done in different populations.

The Efficacy of Prophylactic Antibiotics on Post-Stroke Infections: An Updated Systematic Review and Meta-Analysis

Post-stroke infections are common complications in acute stroke patients and are associated with an unfavorable functional outcome. However, reports on the effects of prophylactic antibiotics treatment on post-stroke infections are conflicting, especially those on post-stroke pneumonia and outcomes. We searched the PubMed, Embase, and Web of Knowledge databases up through March 11^th, 2016. Seven randomized controlled trials including 4261 patients were analyzed among this systematic review and meta-analysis. We found preventive antibiotics treatment at the time of stroke onset did reduce the incidence of infections in adults with acute stroke (OR = 0.57, 95% CI: 0.38–0.85, P = 0.005), including reducing the number of urinary tract infections (OR = 0.34, 95% CI: 0.26–0.46, P < 0.001), but did not significantly decrease the rate of post-stroke pneumonia (OR = 0.91, 95% CI: 0.73–1.13, P = 0.385). Importantly, antibiotics treatment also showed no significant effect on the number of fatalities among stroke patients (OR = 1.07, 95% CI: 0.90–1.26, P = 0.743) and functional outcome scores on the modified Rankin Scale (OR = 1.76, 95% CI: 0.86–3.63, p = 0.124). Our study indicated that preventive antibiotics treatment not reduced the rate of post-stroke pneumonia or mortality, even though decreased the risk of infections, especially urinary tract infections. Thus, preventive antibiotics treatment may not be recommended for acute stroke patients.

Stroke-Associated Pneumonia Risk Score: Validity in a French Stroke Unit

BACKGROUND

Stroke-associated pneumonia is a leading cause of in-hospital death and post-stroke outcome. Screening patients at high risk is one of the main challenges in acute stroke units. Several screening tests have been developed, but their feasibility and validity still remain unclear.

OBJECTIVE

The aim of our study was to evaluate the validity of four risk scores (Pneumonia score, A2DS2, ISAN score, and AIS-APS) in a population of ischemic stroke patients admitted in a French stroke unit.

METHODS

Consecutive ischemic stroke patients admitted to a stroke unit were retrospectively analyzed. Data that allowed to retrospectively calculate the different pneumonia risk scores were recorded. Sensitivity and specificity of each score were assessed for in-hospital stroke-associated pneumonia and mortality. The qualitative and quantitative accuracy and utility of each diagnostic screening test were assessed by measuring the Youden Index and the Clinical Utility Index.

RESULTS

Complete data were available for only 1960 patients. Pneumonia was observed in 8.6% of patients. Sensitivity and specificity were, respectively, .583 and .907 for Pneumonia score, .744 and .796 for A2DS2, and .696 and .812 for ISAN score. Data were insufficient to test AIS-APS. Stroke-associated pneumonia risk scores had an excellent negative Clinical Utility Index (.77-.87) to screen for in-hospital risk of pneumonia after acute ischemic stroke.

CONCLUSION

All scores might be useful and applied to screen stroke-associated pneumonia in stroke patients treated in French comprehensive stroke units.

Validation of risk scoring models for predicting stroke-associated pneumonia in patients with ischaemic stroke

Objective

Various risk scoring models have been developed to predict stroke-associated pneumonia (SAP). We aim to determine whether these risk models could effectively predict SAP in Chinese patients with ischaemic stroke (IS).

Methods

Consecutive patients with IS in West China hospital between January 2011 and September 2013 were included to assess the predictive performance of risk scoring models, including Chumbler's score, A²DS² and AISAPS. The area under the receiver operating characteristic curve (AUROC) was used to evaluate the performance of each risk model in predicting pneumonia.

Results

A total of 1569 consecutive patients with IS within 30 days of onset in West China hospital were included. The incidence of pneumonia is 15.3%. The AUROC of Chumbler's score, A²DS² and AISAPS was 0.659, 0.728 and 0.758, respectively, and AISAPS had the highest AUROC.

Conclusions

A²DS² and AISAPS had acceptable discriminatory abilities to predict SAP in Chinese patients with IS within 30 days of onset.

External validation of the A2SD2 and ISAN scales for predicting infectious respiratory complications of ischaemic stroke

BACKGROUND AND PURPOSE

Pneumonia as a complication of stroke is associated with poor outcomes. The A2DS2 and ISAN scales were developed by German and English researchers, respectively, to predict in-hospital stroke-associated pneumonia. We conducted an external validation study of these scales in a series of consecutive patients admitted to our hospital due to ischaemic stroke.

METHOD

These predictive models were applied to a sample of 340 consecutive patients admitted to hospital in 2015 due to stroke. Discrimination was assessed by calculating the area under the ROC curve for diagnostic efficacy. Calibration was assessed using the Hosmer-Lemeshow goodness-of-fit test and graphing the corresponding curve. Logistic regression analysis was performed to determine the independent predictors of respiratory infection secondary to stroke.

RESULTS

We included 285 patients, of whom 45 (15.8%) had respiratory infection after stroke according to the study criteria. Mean age was 71.01±12.62 years; men accounted for 177 of the patients (62.1%). Seventy-two patients (25.3%) had signs or symptoms of dysphagia, 42 (14.7%) had atrial fibrillation, and 14 (4.9%) were functionally dependent before stroke; the median NIHSS score was 4 points. Mean scores on A2DS2 and ISAN were 3.25±2.54 and 6.49±3.64, respectively. Our analysis showed that higher A2DS2 scores were associated with an increased risk of infection (OR=1.576; 95% CI: 1.363-1.821); the same was true for ISAN scores (OR=1.350; 95% CI: 1.214-1.501).

CONCLUSION

High scores on A2DS2 and ISAN were found to be a strong predictor of respiratory infection associated with acute stroke in a cohort of consecutive patients with stroke. These easy-to-use scales are promising tools for predicting this complication in routine clinical practice.