Predictors of mortality and disability in stroke-associated pneumonia

Functional outcomes of minimally invasive surgery treatment for patients with small supratentorial spontaneous intracerebral haematoma less than 30 mL: a propensity score matching study

BACKGROUND

This study investigated the efficacy of frameless robot-assisted stereotactic aspiration coupled with catheter thrombolysis (SA-CT) in treating supratentorial spontaneous intracerebral haemorrhage (sICH) with small haematoma volumes (<30 mL).

METHODS

We analysed the clinical and long-term outcome data for patients who had haematoma volumes <30 mL and underwent SA-CT between August 2019 and June 2023. Then, we matched the patients receiving conservative treatment during the same period from a multicentre intracerebral haemorrhage database using propensity score matching. The outcomes included the restoration of independent standing ability and mortality within 1 year after onset.

RESULTS

340 patients were included in the final analysis. A greater proportion of patients in the surgery group regained the ability to stand independently within 1 year (89.1% vs 78.1%, p=0.049). The Kaplan-Meier curve showed that the cumulative standing rate in the surgery group was higher than that in the conservative group (90.4% vs 82.0%, p=0.007) within 1 year, and the median time to regain standing was shorter in the surgery group (30 days vs 34 days). The mortality rates were lower in the surgery group (p<0.05). Multivariate Cox regression analysis revealed that frameless robot-guided SA-CT (adjusted HR 1.80; 95% CI 1.37 to 2.38; p<0.001), age, haematoma volume, the severe Glasgow Coma Scale scores and pneumonia were independent factors associated with standing recovery within 1 year after onset.

CONCLUSIONS

Frameless robot-guided SA-CT for small supratentorial haematoma with contralateral hemiplegia seems safe and potentially facilitates the recovery of independent standing ability and reduces the mortality rates.

Safety, Functional Disability, Healthcare Utilization, and Quality-of-Life Outcomes in Elderly Receiving Alteplase and Tenecteplase: A Secondary Analysis From the AcT Trial

BACKGROUND

Older age has been associated with overall poorer outcomes in acute ischemic stroke. We compared (1) outcomes in various health-related domains among patients <80 years and ≥80 years presenting with acute ischemic stroke and (2) whether outcomes differ between intravenous TNK (tenecteplase) versus alteplase.

METHODS

Data are from patients included in AcT (Alteplase Compared to Tenecteplase in Patients With Acute Ischemic Stroke), a pragmatic, registry-linked, phase 3 randomized controlled trial comparing TNK with alteplase. Outcomes included functional disability (per 90-day modified Rankin Scale), safety (24-hour symptomatic intracerebral hemorrhage, 90-day mortality rates), health care utilization (discharge destination, length of stay, thrombectomy rate), and quality of life measures (EQ-5D-5L). With an a priori plan, patients aged <80 years were compared with those ≥80 years at symptom onset. Mixed effects Poisson regression was used to assess (1) the association of age with outcomes and (2) if these associations were modified by thrombolytic administered (TNK versus alteplase), after adjusting for sex, and baseline stroke severity.

RESULTS

Of the 1577 patients, 1034 (65.6%; 520: TNK and 514: alteplase) were <80 years and 543 (34.4%; 286: TNK and 257: alteplase) were ≥80 years of age. Baseline characteristics in the 2 groups were similar except for sex 40% female in <80 years group versus 62.8% female in ≥80 years. There was no difference in rates of symptomatic intracranial hemorrhage (3.5% versus 3.1%). Patients in the ≥80 years group had significantly lower rates of excellent functional outcome, return to baseline status, higher mortality, and lower quality-of-life outcomes as compared with the <80 years group. Length of hospital stay was similar between the 2 groups but, patients in the ≥80 years age group had significantly lower rates of endovascular treatment utilization. Type of thrombolytic agent (TNK versus alteplase) did not modify the association between age and primary clinical outcome (Pinteraction=0.22).

CONCLUSIONS

Similar to alteplase, increasing age was associated with poorer functional outcomes with TNK. Rates of angiographic and bleeding outcomes were similar between patients <80 and ≥80 years.

REGISTRATION

URL: https://www.clinicaltrials.gov; Unique identifier: NCT03889249.

Predictive Value of Serum Inflammatory Factors and FT 3 for Stroke-Associated Pneumonia in Patients With Acute Ischemic Stroke

OBJECTIVE

The ability of serum inflammatory factors and free triiodothyronine (FT 3 ) in predicting the occurrence of stroke-associated pneumonia (SAP) in patients with acute ischemic stroke (AIS) was assessed in this study.

METHODS

A retrospective analysis was conducted on 285 consecutive patients with AIS initially diagnosed and admitted to our hospital from January to December 2022. Patients were categorized into SAP and non-SAP groups based on the presence of SAP. Both groups were compared in terms of baseline characteristics, including National Institute of Health Stroke Scale (NIHSS) score, SAP risk assessment (A 2 DS 2 ), TOAST classification. Independent risk factors for SAP were identified using multivariate logistic regression analysis, and the predictive value of inflammatory markers was evaluated through ROC curves.

RESULTS

Among 285 patients with AIS, 40 (14.03%) were found to have developed SAP. Higher NIHSS and A 2 DS 2 scores, elevated serum IL-1β, IL-8, and IL-33 levels, increased age, atrial fibrillation, swallowing difficulties, and a higher proportion of patients with low FT 3 levels were observed in the SAP group compared with the non-SAP group (all P <0.05). Significant risk factors for SAP in patients with AIS were identified through multivariate logistic regression analysis, including age, swallowing difficulties, NIHSS, A 2 DS 2 , IL-1β, IL-8, IL-33, and FT 3 ( P <0.05). The highest predictive values were observed for A 2 DS 2 , FT 3 , and IL-8 with AUC values of 0.854, 0.844, and 0.823, respectively.

CONCLUSION

SAP can be highly predicted by A 2 DS 2 , FT 3 , and IL-8, enabling the early identification of patients with high-risk SAP and facilitating timely intervention and treatment.

Machine learning-based prediction of one-year mortality in ischemic stroke patients

BACKGROUND

Accurate prediction of mortality following an ischemic stroke is essential for tailoring personalized treatment strategies. This study evaluates the effectiveness of machine learning models in predicting one-year mortality after an ischemic stroke.

METHODS

Five machine learning models were trained using data from a national stroke registry, with logistic regression demonstrating the highest performance. The SHapley Additive exPlanations (SHAP) analysis explained the model's outcomes and defined the influential predictive factors.

RESULTS

Analyzing 8183 ischemic stroke patients, logistic regression achieved 83% accuracy, 0.89 AUC, and an F1 score of 0.83. Significant predictors included stroke severity, pre-stroke functional status, age, hospital-acquired pneumonia, ischemic stroke subtype, tobacco use, and co-existing diabetes mellitus (DM).

DISCUSSION

The model highlights the importance of predicting mortality in enhancing personalized stroke care. Apart from pneumonia, all predictors can serve the early prediction of mortality risk which supports the initiation of early preventive measures and in setting realistic expectations of disease outcomes for all stakeholders. The identified tobacco paradox warrants further investigation.

CONCLUSION

This study offers a promising tool for early prediction of stroke mortality and for advancing personalized stroke care. It emphasizes the need for prospective studies to validate these findings in diverse clinical settings.

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

BACKGROUND AND PURPOSE

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

MATERIALS AND METHODS

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

RESULTS

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

CONCLUSIONS

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

Evaluation of Physiological Variables Determining Time-to-Mortality after Stroke-Associated Pneumonia

INTRODUCTION

Stroke-associated pneumonia (SAP) frequently complicates stroke and is associated with significant mortality. Clinicians often use physiological variables within the National Early Warning Score (NEWS) when diagnosing and prescribing antibiotics for SAP, but little is known of its association with mortality. We investigated the relationship of the NEWS 2 score and its components (respiratory rate, heart rate, temperature, oxygen requirement, oxygen saturation, and alertness level) prior to antibiotic initiation, with time-to-mortality in SAP.

METHODS

We included patients with SAP (n = 389) from a single hyperacute stroke unit. Diagnosis of SAP was made if pneumonia occurred within 7 days of hospital admission. Kaplan-Meier survival curves were generated to assess NEWS 2 parameters influencing survival at pre-defined time periods (1 year and 5 years). The association of these parameters on time-to-mortality were analysed using multivariable Cox-regression models to account for a set of pre-specified potential confounders.

RESULTS

The median age was 80 years (71-87 years) and median NIHSS was 7 (IQR 4-17). Mortality within 1 year was 52.4% and 65.8% within 5 years. In the multivariable analyses, time-to-mortality was independently associated with respiratory rate (heart rate [HR] 1.04, 95% confidence intervals [CI] 1.01-1.08, p = 0.009) and total NEWS 2 score (HR 1.13, 95% CI 1.06-1.21, p < 0.001).

CONCLUSIONS

In patients with SAP, higher respiratory rate and total NEWS 2 score prior to antibiotic initiation were independently associated with time-to-mortality. Further studies are warranted to identify potential opportunities for intervention and ultimately guide treatment to improve outcomes in SAP patients.

Association between lymphocyte-to-monocyte ratio and stroke-associated pneumonia: a retrospective cohort study

Background

Stroke-associated pneumonia (SAP) is a common complication of acute ischemic stroke (AIS) and is associated with increased mortality and prolonged hospital stays. The lymphocyte-to-monocyte ratio (LMR) is a novel inflammatory marker that has been shown to be associated with various diseases. However, the relationship between the LMR and SAP in patients with AIS remains unclear.

Methods

A retrospective cohort study was conducted on 1,063 patients with AIS admitted to our hospital within 72 hours of symptom onset. Patients were divided into two groups: the SAP group (n = 99) and the non-SAP group (n = 964). The LMR was measured within 24 hours of admission, and the primary outcome was the incidence of SAP. We used univariate and multivariate logistic regression analyses to assess the relationship between the LMR and SAP. Additionally, curve-fitting techniques and subgroup analyses were conducted.

Result

The incidence of SAP was 9.31%. We found that the LMR was significantly lower in the SAP group than in the non-SAP group (2.46 ± 1.44 vs. 3.86 ± 1.48, P < 0.001). A nonlinear relationship was observed between the LMR and the incidence of SAP. Subgroup analysis revealed that an elevated LMR was associated with a reduced incidence of SAP in individuals with an LMR below 4. Multivariate logistic regression analysis demonstrated that LMR was an independent predictor of SAP (OR = 0.37, 95% CI [0.27-0.53]).

Conclusion

Our study suggests that the LMR is an independent predictor of SAP in patients with AIS, particularly when the LMR is less than 4. The LMR may serve as a promising biomarker for the early identification of patients with AIS at a high risk of SAP.

From Editorial Board of Special Issue Entitled "Post-Stroke Rehabilitation"

Diseases affecting the nervous system are diverse [...].

Bacterial stroke-associated pneumonia: microbiological analysis and mortality outcome

BACKGROUND

Stroke-associated pneumonia (SAP) considerably burden healthcare systems. This study aimed to identify predictors of developing SAP in acute ischemic stroke patients admitted to the Stroke Unit at Manial Specialized Hospital factors with microbiological causality and impact on 30-day mortality.

METHODS

This was a retrospective cohort study. All patients with acute ischemic stroke admitted to the Stroke Unit at Manial Specialized Hospital (from February 2021 to August 2023) were divided into the SAP and non-SAP groups. Detailed clinical characteristics and microbiological results were recorded.

RESULTS

Five hundred twenty-two patients diagnosed with acute ischemic stroke (mean age of 55 ± 10) were included. One hundred sixty-nine (32.4%) of stroke patients developed SAP; Klebsiella pneumoniae was the most commonly detected pathogen (40.2%), followed by Pseudomonas aeruginosa (20.7%). Bacteremia was identified in nine cases (5.3%). The number of deaths was 11, all of whom were diagnosed with SAP, whereas none from the non-SAP group died (P < 0.001). The binary logistic regression model identified three independent predictors of the occurrence of SAP: previous history of TIA/stroke (OR = 3.014, 95%CI = 1.281-7.092), mechanical ventilation (OR = 4.883, 95%CI = 1.544-15.436), and bulbar dysfunction (OR = 200.460, 95%CI = 80.831-497.143).

CONCLUSIONS

Stroke-associated pneumonia was reported in one-third of patients with acute ischemic stroke, adversely affecting mortality outcomes. Findings showed that the main predictors of SAP were bulbar dysfunction, the use of mechanical ventilation and previous history of TIA/stroke. More attention to these vulnerable patients is necessary to reduce mortality.

The clinical value of nutritional and inflammatory indicators in predicting pneumonia among patients with intracerebral hemorrhage

Immunosuppression and malnutrition play pivotal roles in the complications of intracerebral hemorrhage (ICH) and are intricately linked to the development of stroke-associated pneumonia (SAP). Inflammatory markers, including NLR (neutrophil-to-lymphocyte ratio), SII (systemic immune inflammation index), SIRI (systemic inflammatory response index), and SIS (systemic inflammation score), along with nutritional indexes such as CONUT (controlling nutritional status) and PNI (prognostic nutritional index), are crucial indicators influencing the inflammatory state following ICH. In this study, our objective was to compare the predictive efficacy of inflammatory and nutritional indices for SAP in ICH patients, aiming to determine and explore their clinical utility in early pneumonia detection. Patients with severe ICH requiring ICU admission were screened from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. The outcomes included the occurrence of SAP and in-hospital death. Receiver operating characteristic (ROC) analysis, multivariate logistic regression, smooth curve analysis, and stratified analysis were employed to investigate the relationship between the CONUT index and the clinical outcomes of patients with severe ICH. A total of 348 patients were enrolled in the study. The incidence of SAP was 21.3%, and the in-hospital mortality rate was 17.0%. Among these indicators, multiple regression analysis revealed that CONUT, PNI, and SIRI were independently associated with SAP. Further ROC curve analysis demonstrated that CONUT (AUC 0.6743, 95% CI 0.6079-0.7408) exhibited the most robust predictive ability for SAP in patients with ICH. Threshold analysis revealed that when CONUT < 6, an increase of 1 point in CONUT was associated with a 1.39 times higher risk of SAP. Similarly, our findings indicate that CONUT has the potential to predict the prognosis of patients with ICH. Among the inflammatory and nutritional markers, CONUT stands out as the most reliable predictor of SAP in patients with ICH. Additionally, it proves to be a valuable indicator for assessing the prognosis of patients with ICH.

Machine learning-based prognostication of mortality in stroke patients

Objectives

Predicting stroke mortality is crucial for personalized care. This study aims to design and evaluate a machine learning model to predict one-year mortality after a stroke.

Materials and methods

Data from the National Multiethnic Stroke Registry was utilized. Eight machine learning (ML) models were trained and evaluated using various metrics. SHapley Additive exPlanations (SHAP) analysis was used to identify the influential predictors.

Results

The final analysis included 9840 patients diagnosed with stroke were included in the study. The XGBoost algorithm exhibited optimal performance with high accuracy (94.5%) and AUC (87.3%). Core predictors encompassed National Institutes of Health Stroke Scale (NIHSS) at admission, age, hospital length of stay, mode of arrival, heart rate, and blood pressure. Increased NIHSS, age, and longer stay correlated with higher mortality. Ambulance arrival and lower diastolic blood pressure and lower body mass index predicted poorer outcomes.

Conclusions

This model's predictive capacity emphasizes the significance of NIHSS, age, hospital stay, arrival mode, heart rate, blood pressure, and BMI in stroke mortality prediction. Specific findings suggest avenues for data quality enhancement, registry expansion, and real-world validation. The study underscores machine learning's potential for early mortality prediction, improving risk assessment, and personalized care. The potential transformation of care delivery through robust ML predictive tools for Stroke outcomes could revolutionize patient care, allowing for personalized plans and improved preventive strategies for stroke patients. However, it is imperative to conduct prospective validation to evaluate its practical clinical effectiveness and ensure its successful adoption across various healthcare environments.

Acute ischaemic stroke in active cancer versus non-cancer patients: stroke characteristics, mechanisms and clinical outcomes

BACKGROUND AND PURPOSE

Demographics, clinical characteristics, stroke mechanisms and long-term outcomes were compared between acute ischaemic stroke (AIS) patients with active cancer (AC) versus non-cancer patients.

METHODS

Using data from 2003 to 2021 in the Acute STroke Registry and Analysis of Lausanne, a retrospective cohort study was performed comparing patients with AC, including previously known and newly diagnosed cancers, with non-cancer patients. Patients with inactive cancer were excluded. Outcomes were the modified Rankin Scale (mRS) score at 3 months, death and cerebrovascular recurrences at 12 months before and after propensity score matching.

RESULTS

Amongst 6686 patients with AIS, 1065 (15.9%) had a history of cancer. After excluding 700 (10.4%) patients with inactive cancer, there were 365 (5.5%) patients with AC and 5621 (84%) non-cancer AIS patients. Amongst AC patients, 154 (42.2%) strokes were classified as cancer related. In multivariable analysis, patients with AC were older (adjusted odds ratio [aOR] 1.02, 95% confidence interval [CI] 1.00-1.03), had fewer vascular risk factors and were 48% less likely to receive reperfusion therapies (aOR 0.52, 95% CI 0.35-0.76). Three-month mRS scores were not different in AC patients (aOR 2.18, 95% CI 0.96-5.00). At 12 months, death (adjusted hazard ratio 1.91, 95% CI 1.50-2.43) and risk of cerebrovascular recurrence (sub-distribution hazard ratio 1.68, 95% CI 1.22-2.31) before and after propensity score matching were higher in AC patients.

CONCLUSIONS

In a large institutional registry spanning nearly two decades, AIS patients with AC had less past cerebrovascular disease but a higher 1-year risk of subsequent death and cerebrovascular recurrence compared to non-cancer patients. Antithrombotic medications at discharge may reduce this risk in AC patients.

Association of composite dietary antioxidant index with prevalence of stroke: insights from NHANES 1999-2018

Background

There is a growing acknowledgment of the potential influence of antioxidative effects resulting from dietary decisions on the occurrence of stroke. The objective of this study was to elucidate the correlation between the composite dietary antioxidant index (CDAI) and the incidence of stroke in the general population of the United States.

Methods

We gathered cross-sectional data encompassing 40,320 participants from the National Health and Nutrition Examination Survey (NHANES) spanning the years 1999 to 2018. Employing weighted multivariate logistic regression, we assessed the correlation between CDAI and stroke, while also investigating potential nonlinear relationships through restricted cubic spline (RCS) regression. Further, the intake of CDAI components were then incorporated into a predictive nomogram model, subsequently evaluated for its discriminatory prowess in stroke risk assessment using the receiver operating characteristic (ROC) curve.

Results

Post-adjustment for confounding variables, we found that higher CDAI score were associated with a decreased risk of stroke, the odds ratio (OR) [95% CI] of CDAI associating with prevalence was 0.96 [0.94-0.98] (P< 0.001). Moreover, the adjusted OR [95% CI] for stroke across ascending CDAI quartiles stood at 0.90 [0.74-1.09], 0.74 [0.60-0.91], and 0.61 [0.50-0.76] compared to the reference quartile, respectively. The RCS analysis indicated a nonlinear yet negative correlation between CDAI and stroke. The nomogram model, constructed based the intake of antioxidants, exhibited a significant predictive capacity for stroke risk, boasting an area under the curve (AUC) of 77.4% (76.3%-78.5%).

Conclusion

Our investigation ascertained a nonlinear negative relationship between CDAI and stroke within the broader American population. However, given the inherent limitations of the cross-sectional design, further comprehensive research is imperative to establish the causative nature of this association.

Development and Validation of a Dynamic Nomogram for Predicting 3-Month Mortality in Acute Ischemic Stroke Patients with Atrial Fibrillation

Background

Acute ischemic stroke (AIS) in patients with atrial fibrillation (AF) carries a substantial risk of mortality, emphasizing the need for effective risk assessment and timely interventions. This study aimed to develop and validate a practical dynamic nomogram for predicting 3-month mortality in AIS patients with AF.

Methods

AIS patients with AF were enrolled and randomly divided into training and validation cohorts. The nomogram was developed based on independent risk factors identified by multivariate logistic regression analysis. The prediction performance of the nomogram was evaluated using the area under the receiver operating characteristic curve (AUC-ROC), calibration plots, decision curve analysis (DCA), and Kaplan-Meier survival analysis.

Results

A total of 412 patients with AIS and AF entered final analysis, 288 patients in the training cohort and 124 patients in the validation cohort. The nomogram was developed using age, baseline National Institutes of Health Stroke Scale score, early introduction of novel oral anticoagulants, and pneumonia as independent risk factors. The nomogram exhibited good discrimination both in the training cohort (AUC, 0.851; 95% CI, 0.802-0.899) and the validation cohort (AUC, 0.811; 95% CI, 0.706-0.916). The calibration plots, DCA and Kaplan-Meier survival analysis demonstrated that the nomogram was well calibrated and clinically useful, effectively distinguishing the 3-month survival status of patients with AIS and AF, respectively. The dynamic nomogram can be obtained at the website: https://yanxiaodi.shinyapps.io/3-monthmortality/.

Conclusion

The dynamic nomogram represents the first predictive model for 3-month mortality and may contribute to managing the mortality risk of patients with AIS and AF.

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

Objective

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

Methods

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

Results

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

Conclusion

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

Telestroke: A Novel Approach for Post-Stroke Rehabilitation

Despite the tremendous technologic advancements of recent years, the prevalence of stroke has increased significantly worldwide from 1990 to 2019 (a 70 [...].

Clinical and Demographic Characteristics, Mechanisms, and Outcomes in Patients With Acute Ischemic Stroke and Newly Diagnosed or Known Active Cancer

BACKGROUND AND OBJECTIVES

Patients with a new diagnosis of cancer carry an increased risk of acute ischemic stroke (AIS), and this risk varies depending on age, cancer type, stage, and time from diagnosis. Whether patients with AIS with a new diagnosis of neoplasm represent a distinct subset from those with a previously known active malignancy remains unclear. We aimed to estimate the rate of stroke in patients with newly diagnosed cancer (NC) and previously known active cancer (KC) and to compare the demographic and clinical features, stroke mechanisms, and long-term outcomes between groups.

METHODS

Using 2003-2021 data from the Acute STroke Registry and Analysis of Lausanne registry, we compared patients with KC with patients with NC (cancer identified during AIS hospitalization or within the following 12 months). Patients with inactive and no history of cancer were excluded. Outcomes were the modified Rankin scale (mRS) score at 3 months and mortality and recurrent stroke at 12 months. We used multivariable regression analyses to compare outcomes between groups while adjusting for important prognostic variables.

RESULTS

Among 6,686 patients with AIS, 362 (5.4%) had active cancer (AC), including 102 (1.5%) with NC. Gastrointestinal and genitourinary cancers were the most frequent cancer types. Among all patients with AC, 152 (42.5%) AISs were classified as cancer related, with nearly half of these cases attributed to hypercoagulability. In multivariable analysis, patients with NC had less prestroke disability (adjusted odds ratio [aOR] 0.62, 95% CI 0.44-0.86) and fewer prior stroke/transient ischemic attack events (aOR 0.43, 95% CI 0.21-0.88) than patients with KC. Three-month mRS scores were similar between cancer groups (aOR 1.27, 95% CI 0.65-2.49) and were predominantly driven by the presence of newly diagnosed brain metastases (aOR 7.22, 95% CI 1.49-43.17) and metastatic cancer (aOR 2.19, 95% CI 1.22-3.97). At 12 months, mortality risk was higher in patients with NC vs patients with KC (hazard ratio [HR] 2.11, 95% CI 1.38-3.21), while recurrent stroke risk was similar between groups (adjusted HR 1.27, 95% CI 0.67-2.43).

DISCUSSION

In a comprehensive institutional registry spanning nearly 2 decades, 5.4% of patients with AIS had AC, a quarter of which were diagnosed during or within 12 months after the index stroke hospitalization. Patients with NC had less disability and prior cerebrovascular disease, but a higher 1-year risk of subsequent death than patients with KC.

Stroke-associated infections in patients with and without cancer

Background

Cancer in stroke patients is associated with higher levels of inflammatory biomarkers and unfavorable poststroke outcomes. We thus explored whether there is a link between cancer and stroke-associated infections.

Methods

Medical records of patients with ischemic stroke in 2014-2016 registered in the Swiss Stroke Registry of Zurich were retrospectively analyzed. Incidence, characteristics, treatment, and outcome of stroke-associated infections diagnosed within 7 days after stroke onset were tested for an association with cancer.

Results

Among 1181 patients with ischemic stroke, 102 patients with cancer were identified. Stroke-associated infections occurred in 179 and 19 patients (17% and 19%) without and with cancer (P = .60), respectively, among them pneumonia in 95 and 10 patients (9% and 10%) and urinary tract infections in 68 and 9 patients (6% and 9%) (P = .74 and P = .32). Use of antibiotics was similar between groups. Levels of C-reactive protein (CRP) (P < .001), erythrocyte sedimentation rate (ESR) (P = .014) and procalcitonin (P = .015) were higher and levels of albumin (P = .042) and protein (P = .031) were lower in patients with cancer than without cancer. Among patients without cancer, higher CRP (P < .001), ESR (P < .001) and procalcitonin (P = .04) and lower albumin (P < .001) were associated with stroke-associated infections. Among cancer patients with or without infections, no significant differences in these parameters were observed. In-hospital mortality was associated with cancer (P < .001) and with stroke-associated infections (P < .001). However, among patients with stroke-associated infections, cancer was not associated with in-hospital mortality (P = .24) or 30-day mortality (P = .66).

Conclusions

Cancer does not represent a risk factor for stroke-associated infections in this patient cohort.

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

PURPOSE

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

METHODS

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

RESULTS

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

CONCLUSION

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

Dementia and acute care of ischemic stroke in Japan: A retrospective observational study using the Japanese Diagnosis Procedure Combination database

AIM

This study aimed to determine the impact of dementia on the implementation of intravenous thrombolysis and early rehabilitation as acute care for patients with acute ischemic stroke in Japan.

METHODS

This retrospective observational study used the Japanese Diagnosis Procedure Combination database. Patients aged ≥75 years with acute ischemic stroke (ICD-10 code: I63) were enrolled (n = 464 710). In this study, dementia was identified using the ICD-10 codes (F00, F01, F02, F03, G30, and G31) for comorbidity. A mixed-effects logistic regression analysis nested at the hospital level was conducted to examine the impact of dementia on the implementation of intravenous thrombolysis and early rehabilitation.

RESULTS

Overall, 57 905 patients with ischemic stroke had dementia. The group with dementia was less likely to receive intravenous thrombolysis (5.2% vs. 6.9%) and more likely to undergo early rehabilitation than the group without dementia (76.1% vs. 73.0%). In the mixed-effects logistic regression analysis, dementia was significantly associated with a lower probability of undergoing intravenous thrombolysis (adjusted odds ratio: 0.79, 95% confidence interval: 0.76-0.82, P < 0.001) and a higher probability of early rehabilitation (adjusted odds ratio: 1.06, 95% confidence interval: 1.04-1.09, P < 0.001).

CONCLUSIONS

We found that while dementia was associated with fewer opportunities for aggressive treatment, such as intravenous thrombolysis, it was also associated with increased opportunities to receive rehabilitation. It is necessary to examine the reasons why patients with dementia do not receive aggressive treatment and to establish a system that allows older adults with and without dementia to receive equal access to medical care. Geriatr Gerontol Int 2023; ••: ••-••.

Inflammatory response biomarkers nomogram for predicting pneumonia in patients with spontaneous intracerebral hemorrhage

Objectives

Inflammatory response biomarkers are promising prognostic factors to improve the prognosis of stroke-associated pneumonia (SAP) after ischemic stroke. This study aimed to investigate the prognostic significance of inflammatory response biomarkers on admission in SAP after spontaneous intracerebral hemorrhage (SICH) and establish a corresponding nomogram.

Methods

The data of 378 patients with SICH receiving conservative treatment from January 2019 to December 2021 at Taizhou People's Hospital were selected. All eligible patients were randomized into the training (70%, 265) and validation cohorts (30%, 113). In the training cohort, multivariate logistic regression analysis was used to establish an optimal nomogram, including inflammatory response biomarkers and clinical risk factors. The area under the receiver operating characteristic (ROC) curve (AUC), calibration curve, and decision curve analysis (DCA) were used to evaluate the nomogram's discrimination, calibration, and performance, respectively. Moreover, this model was further validated in a validation cohort.

Results

A logistic regression analysis showed that intraventricular hemorrhage (IVH), hypertension, dysphagia, Glasgow Coma Scale (GCS), National Institute of Health Stroke Scale (NIHSS), systemic inflammation response index (SIRI), and platelet/lymphocyte ratio (PLR) were correlated with SAP after SICH (P < 0.05). The nomogram was composed of all these statistically significant factors. The inflammatory marker-based nomogram showed strong prognostic power compared with the conventional factors, with an AUC of 0.886 (95% CI: 0.841-0.921) and 0.848 (95% CI: 0.799-0.899). The calibration curves demonstrated good homogeneity between the predicted risks and the observed outcomes. In addition, the model has a significant net benefit for SAP, according to DCA. Also, internal validation demonstrated the reliability of the prediction nomogram. The length of hospital stay was shorter in the non-SAP group than in the SAP group. At the 3-month follow-up, clinical outcomes were worse in the SAP group (P < 0.001).

Conclusion

SIRI and PLR at admission can be utilized as prognostic inflammatory biomarkers in patients with SICH in the upper brain treated with SAP. A nomogram covering SIRI and PLR can more accurately predict SAP in patients' supratentorial SICH. SAP can influence the length of hospital stay and the clinical outcome.

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.

In-hospital mortality and its predictors among adult stroke patients admitted in Debre Markos Comprehensive Specialized Hospital, Northwest Ethiopia

Introduction

Stroke is the second-leading global cause of death next to ischemic heart disease. The burden of stroke mortality, morbidity, and disability is increasing across the world. In Ethiopia, evidence on the survival status of adult stroke patients is insufficient. The purpose of this study is to estimate in-hospital mortality and its predictors among adult stroke patients.

Methods

Institution-based retrospective follow-up study was conducted on adult stroke patients who were admitted to Debre Markos Comprehensive Specialized Hospital from 1 November 2015 to 31 October 2020. Through simple random sampling, 382 patient charts were selected from 1125 stroke patients for 5 years follow-up period. Data were entered using EpiData™ version 4.1 and exported to Stata/SE™ version 14 for cleaning, coding, categorizing, and analysis. Predictor variables were selected using 95% confidence interval with a corresponding adjusted hazard ratio.

Results

In this study, 219 (57.33%) males and the mean (standard deviation) age of 57.65 ± 14.3 years. The in-hospital mortality rate of stroke was 12.8%; the median (interquartile range) time to mortality and Glasgow Coma Scale were 7 (4-13) days and 14 (11-15), respectively. The incidence of in-hospital mortality was 29/1000, 11/1000, 8/1000, and 13.6/1000 person-days in the first, second, third, and end of follow-up weeks, respectively. Pneumonia (adjusted hazard ratio = 3.51 (95% confidence interval = 1.86, 6.61)), hemorrhagic stroke (adjusted hazard ratio = 2.03 (95% confidence interval = 1.03, 3.99)), moderate impairment Glasgow Coma Scale (9-12) (adjusted hazard ratio = 2.16 (95% confidence interval = 1.08, 4.29)), severe impairment Glasgow Coma Scale (3-8) (adjusted hazard ratio = 2.38 (95% confidence interval = 1.01, 5.67)), history of hypertension (adjusted hazard ratio = 2.01 (95% confidence interval = 1.08, 3.74)), and increased intracranial pressure (adjusted hazard ratio = 2.12 (95% confidence interval = 1.10, 4.07)) were statistically significant predictors for in-hospital mortality.

Conclusion

In-hospital mortality of stroke was relatively high, and the median time to mortality was 8 days. Pneumonia, hemorrhagic stroke, Glasgow Coma Scale, history of hypertension, and increased intracranial pressure were identified predictors.

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.

Clinical significance of albumin to globulin ratio among patients with stroke-associated pneumonia

Background

It has been proven that the ratio of albumin to globulin (A/G) is a typical biomarker for monitoring inflammation and nutritional status. But the potential role of A/G in stroke-associated pneumonia (SAP) after acute ischemic stroke (AIS) remained unknown.

Patients and methods

Following inclusion criteria, 5,173 AIS patients were included and segmented into SAP (n = 897) and non-SAP (n = 4,276) groups. The differences in variables between groups were compared. The logistic regression model was used to determine the association between A/G and SAP, and a forest plot was drawn.

Results

Compared with the non-SAP group, the SAP group had a lower A/G level (P < 0.001). Then, A/G was divided into quartiles. In comparison to Q3 (A/G = 1.25–1.39), logistic regression revealed that patients with a lower A/G (A/G ≤ 1.09) had a higher risk of SAP (OR = 1.96, 95% CI, 1.56–2.46, P < 0.001). On the contrary, those with a higher A/G (A/G ≥ 1.4) had a lower SAP risk (OR = 0.73, 95% CI, 0.54–0.97, P = 0.029).

Conclusion

The study revealed that a low A/G level was associated with an increased SAP risk. Appropriate preventative measures for SAP should be taken in AIS patients with a low A/G level.

Immunodepression, Infections, and Functional Outcome in Ischemic Stroke

Stroke remains one of the main causes of mortality and morbidity worldwide. Immediately after stroke, a neuroinflammatory process starts in the brain, triggering a systemic immunodepression mainly through excessive activation of the autonomous nervous system. Manifestations of immunodepression include lymphopenia but also dysfunctional innate and adaptive immune cells. The resulting impaired antibacterial defenses render patients with stroke susceptible to infections. In addition, other risk factors like stroke severity, dysphagia, impaired consciousness, mechanical ventilation, catheterization, and older age predispose stroke patients for infections. Most common infections are pneumonia and urinary tract infection, both occur in ≈10% of the patients. Especially pneumonia increases unfavorable outcome and mortality in patients with stroke; systemic effects like hypotension, fever, delay in rehabilitation are thought to play a crucial role. Experimental and clinical data suggest that systemic infections enhance autoreactive immune responses against brain antigens and thus negatively affect outcome but convincing evidence is lacking. Prevention of poststroke infections by preventive antibiotic therapy did not improve functional outcome after stroke. Immunomodulatory approaches counteracting immunodepression to prevent stroke-associated pneumonia need to account for neuroinflammation in the ischemic brain and avoid further tissue damage. Experimental studies discovered interesting targets, but these have not yet been investigated in patients with stroke. A better understanding of the pathobiology may help to develop optimized approaches of preventive antibiotic therapy or immunomodulation to effectively prevent stroke-associated pneumonia while improving long-term outcome after stroke. In this review, we aim to characterize epidemiology, risk factors, cause, diagnosis, clinical presentation, and potential treatment of poststroke immunosuppression and associated infections.

Pharmacotherapy Pattern and Treatment Outcomes of Stroke Patients Admitted to Jimma University Medical Center, Ethiopia

Background

Despite the fact that stroke has been reported as one of the top three leading causes of death and morbidity in Ethiopia, there are limited data regarding the management of stroke and clinical outcomes. Hence, the present study aimed to evaluate the pharmacotherapy of stroke and factors associated with poor treatment outcomes.

Methods

A retrospective cross-sectional study was conducted at Jimma University Medical Center (JUMC) among adult stroke patients managed from 2014 to 2017. Clinical characteristics, treatment, and outcomes data were analyzed by using SPSS version 21. Multivariable logistic regression was performed to identify the predictors of poor treatment outcomes. Two-sided P < 0.05 was accepted as statistically significant.

Results

A total of 153 illegible patient cases were included in this study. The majority, 111 (72.5%), were male and the mean age of the patients was 57±13.7 years. Among 153 stroke patients, 112 (73.2%) patients presented with ischemic stroke. Aspirin and statins (78.6%) were the most commonly used treatment among ischemic stroke patients, whereas enalapril was used in about (43%) of stroke patients to treat high blood pressure. About 61 (40%) stroke patients had poor treatment outcomes; of this, 36 (23.5%) died in hospital. Older age (AOR = 1.034; 95% CI: 1.003–1.069), history of heart failure (AOR = 4.26; 95% CI: 1.58–11.48), loss of consciousness diabetes (AOR = 3.05 95% CI: 1.25–7.44), and aspiration pneumonia (AOR = 5.94; 95% CI: 2.46–14.32) were significantly associated with poor treatment outcomes.

Conclusion

Overall, treatment of stroke patients was sub-optimal and almost half of the patients had poor treatment outcomes. Availing of thrombolytic therapy, devising appropriate preventive measures of risk factors (hypertension), and decreasing preventable complication such as aspiration pneumonia could improve patient outcomes.

Oral Health, Oral Microbiota, and Incidence of Stroke-Associated Pneumonia-A Prospective Observational Study

Stroke-associated pneumonia is a major cause for poor outcomes in the post-acute phase after stroke. Several studies have suggested potential links between neglected oral health and pneumonia. Therefore, the aim of this prospective observational study was to investigate oral health and microbiota and incidence of pneumonia in patients consecutively admitted to a stroke unit with stroke-like symptoms. This study involved three investigation timepoints. The baseline investigation (within 24 h of admission) involved collection of demographic, neurological, and immunological data; dental examinations; and microbiological sampling (saliva and subgingival plaque). Further investigation timepoints at 48 or 120 h after baseline included collection of immunological data and microbiological sampling. Microbiological samples were analyzed by culture technique and by 16S rRNA amplicon sequencing. From the 99 patients included in this study, 57 were diagnosed with stroke and 42 were so-called stroke mimics. From 57 stroke patients, 8 (14%) developed pneumonia. Stroke-associated pneumonia was significantly associated with higher age, dysphagia, greater stroke severity, embolectomy, nasogastric tubes, and higher baseline C-reactive protein (CRP). There were trends toward higher incidence of pneumonia in patients with more missing teeth and worse oral hygiene. Microbiological analyses showed no relevant differences regarding microbial composition between the groups. However, there was a significant ecological shift over time in the pneumonia patients, probably due to antibiotic treatment. This prospective observational study investigating associations between neglected oral health and incidence of SAP encourages investigations in larger patient cohorts and implementation of oral hygiene programs in stroke units that may help reducing the incidence of stroke-associated pneumonia.

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.