UNASSIGNED: Stroke-associated pneumonia (SAP) usually complicates stroke and is linked to adverse prognoses. Triglycerides, total cholesterol, and body weight index (TCBI) is a new and simple calculated nutrition index. This study seeks to investigate the association between TCBI and SAP incidence, along with its predictive value.
UNASSIGNED: Nine hundred and sixty-two patients with acute ischemic stroke were divided into SAP group and Non-SAP group. The TCBI was divided into three layers: T1, TCBI < 948.33; T2, TCBI 948.33-1647.15; T3, TCBI > 1647.15. Binary Logistic regression analysis was used to determine the relationship between TCBI levels and the incidence of SAP. Furthermore, restricted cubic splines (RCS) analysis was utilized to evaluate the influence of TCBI on the risk of SAP.
UNASSIGNED: TCBI in the SAP group was markedly lower compared to that in the Non-SAP group (P < 0.001). The Logistic regression model revealed that, using T3 layer as the reference, T1 layer had the highest risk for SAP prevalence (OR = 2.962, 95% CI: 1.600-5.485, P = 0.001), with confounding factors being controlled. The RCS model found that TCBI had a linear relationship with SAP (P for nonlinear = 0.490, P for overall = 0.004). Moreover, incorporating TCBI into the A2DS2 (Age, atrial fibrillation, dysphagia, sex, and severity) model substantially enhanced the initial model\'s predictive accuracy.
UNASSIGNED: Low TCBI was associated with a higher risk of SAP. In clinical practice, TCBI has shown predictive value for SAP, contributing to early intervention and treatment of SAP.

OBJECTIVE: Futile reperfusion (FR) is becoming a major challenge in the treatment of patients with acute ischaemic stroke (AIS) undergoing endovascular thrombectomy. This study aims to determine the dose-response relationship between low-density lipoprotein cholesterol (LDL-C) levels and the risk of FR in patients with AIS undergoing endovascular thrombectomy and to investigate potential mediators.
METHODS: A total of 614 patients with AIS undergoing endovascular thrombectomy were enrolled and divided into five groups according to quintiles of LDL-C levels: Q1(≤2.27 mmol/l), Q2 (2.27-2.5 mmol/l), Q3 (2.5-2.59 mmol/l), Q4 (2.59-2.97 mmol/l) and Q5 (≥2.97 mmol/l). Associations between LDL-C levels and the risk of FR and stroke-associated pneumonia (SAP) were estimated using multivariate logistic regression models. Restricted cubic spline curves were used to describe the dose-response relationship between LDL-C levels and the risk of FR and SAP. Mediation effect analysis was performed in R software with 100 bootstrap samples.
RESULTS: After adjustment for confounders, both low and high LDL-C levels were significantly associated with a higher risk of FR compared with the reference group (Q3). We observed a U-shaped association between LDL-C levels and the risk of FR (P for nonlinear =0.012). Mediation analysis showed that the association between LDL-C levels and the risk of FR was 29.7 % (95 % CI: 2.96 %-75.0 %, P=0.02) mediated by SAP.
CONCLUSIONS: We found a U-shaped association between LDL-C levels and the risk of FR that was mediated by SAP. Clinicians should note that in AIS patients undergoing endovascular thrombectomy, lower LDL-C levels are not always better.

UNASSIGNED: Absent in melanoma 2 (AIM2) is implicated in inflammatory processes. We measured serum AIM2 with intent to unveil its predictive significance for stroke-associated pneumonia (SAP) and functional prognosis following acute intracerebral hemorrhage (ICH).
UNASSIGNED: In this prospective cohort study, serum AIM2 concentrations of 163 ICH patients were gauged upon admission and 57 of them also consented for measurements at days 1, 3, 5, 7, 10 and 14. Coupled with 57 individuals without health conditions, dynamic change of serum AIM2 levels were uncovered. National Institutes of Health Stroke Scale (NIHSS) scores and hematoma volume were identified as the dual indicators of severity. Poststroke six-month modified Rankin Scale (mRS) scores ranging from 3 to 6 indicated an unfavorable outcome. SAP was observed during the first seven days after ICH. Sequential univariate and multivariate analyses were performed to discern predictors of SAP and adverse prognosis.
UNASSIGNED: The serum levels of AIM2 in patients exhibited a marked elevation upon admission, reaching peak levels on the third and fifth days, and remained notably elevated until day 14 compared to those of the control group. Serum AIM2 levels showed independent correlations with both NIHSS scores and the volume of hematoma. Additionally, AIM2 concentrations were independently associated with a poor prognosis and SAP at the six-month mark. Within the framework of restricted cubic spline analysis, serum AIM2 concentrations exhibited a linear correlation with the likelihood of developing SAP and experiencing a poor prognosis. In the context of receiver operating characteristic (ROC) curve analysis, serum AIM2 concentrations effectively differentiated risks of SAP and poor prognosis. By employing segmented analysis, serum AIM2 concentrations showed negligible interactions with several traditional variables, such as age, gender, smoking habits, alcohol consumption, and more. The integrated model incorporating serum AIM2, NIHSS scores, and the volume of hematoma was depicted by employing a nomogram and demonstrated strong predictive performance for poor prognosis or SAP across various evaluation metrics, including ROC curve analysis, calibration curve analysis, and decision curve analysis.
UNASSIGNED: Serum AIM2 levels show a marked increase shortly after intracerebral hemorrhage (ICH), which may accurately reflect stroke severity, and effectively predict SAP and poor neurological outcomes, and therefore serum AIM2 stands out as an encouraging predictive indicator for ICH.

UNASSIGNED: Stroke-associated pneumonia (SAP) is a serious complication in stroke patients, significantly increasing mortality. The Alberta Stroke Program Early CT Score (ASPECTS) is a recognized predictor of acute ischemic stroke outcomes. We aimed to investigate the performance of serial ASPECTS assessments (baseline ASPECTS, 24-h ASPECTS, and change in ASPECTS) for predicting SAP in patients with thrombolyzed acute anterior circulation ischemic stroke (AACIS).
UNASSIGNED: A retrospective observational cohort study of adult patients with thrombolyzed AACIS was conducted. Baseline and 24-h ASPECTS using non-contrast computed tomography (NCCT), complications of stroke, including SAP and swallowing dysfunction using the Modified Water Swallowing test, were collected. Baseline and 24-h ASPECTS were evaluated by a certified neurologist and neuroradiologist. The predictive performance was determined based on the receiver operating characteristic curve (ROC). Multivariable logistic regression analyses were employed to assess the impact of serial ASPECTS assessment on predicting SAP.
UNASSIGNED: Of the 345 patients with thrombolyzed AACIS in our study, 18.4% (64/345) experienced SAP. The patients\' median age was 62 years [interquartile range (IQR): 52-73], with 53.4% being male. The median NIHSS score was 11 points (IQR: 8-17). The ROC analysis revealed areas under the curve for predicting SAP with baseline ASPECTS, 24-h ASPECTS, and change in ASPECTS were 0.75 (95% CI, 0.69-0.82), 0.84 (95% CI, 0.79-0.89), and 0.82 (95% CI, 0.76-0.87), respectively. Of the three measures, 24-h ASPECTS was a better predictor of SAP (odds ratio: 5.33, 95%CI: 2.08-13.67, p < 0.001) and had a higher sensitivity (0.84 [95%CI, 0.74-0.92]) and specificity (0.79 [95%CI, 0.74-0.84]) than both baseline ASPECTS and change in ASPECTS.
UNASSIGNED: 24-h NCCT-ASPECTS outperformed both baseline ASPECTS and change in ASPECTS for predicting SAP. Notably, 24-h ASPECTS, with a cut-off value of ≤6, exhibited good predictive performance and emerged as the better predictor for SAP.

UNASSIGNED: This study aims to identify the risk factors associated with stroke-associated pneumonia (SAP) in patients who have undergone thrombectomy for acute ischemic stroke and to develop a nomogram chart model for predicting the occurrence of pneumonia.
UNASSIGNED: Consecutive patients who underwent thrombectomy for acute ischemic stroke were enrolled from three hospitals at Taizhou Enze Medical Center. They were randomly divided into a training group and a validation group in a 7:3 ratio. The training group data was used to screen for effective predictive factors using LASSO regression. Multiple logistic regression was then conducted to determine the predictive factors and construct a nomogram chart. The model was evaluated using the validation group, analyzing its discrimination, calibration, and clinical decision curve. Finally, the newly constructed model was compared with the AIS-APS, A2DS2, ISAN, and PANTHERIS scores for acute ischemic stroke-associated pneumonia.
UNASSIGNED: Out of 913 patients who underwent thrombectomy, 762 were included for analysis, consisting of 473 males and 289 females. The incidence rate of SAP was 45.8%. The new predictive model was constructed based on three main influencing factors: NIHSS ≥16, postoperative LMR, and difficulty swallowing. The model demonstrated good discrimination and calibration. When applying the nomogram chart to threshold probabilities between 7 and 90%, net returns were increased. Furthermore, the AUC was higher compared to other scoring systems.
UNASSIGNED: The constructed nomogram chart in this study outperformed the AIS-APS, A2DS2 score, ISAN score, and PANTHERIS score in predicting the risk of stroke-associated pneumonia in patients with acute ischemic stroke after thrombectomy. It can be utilized for clinical risk prediction of stroke-associated pneumonia in patients after thrombectomy for acute ischemic stroke.

UNASSIGNED: The modified Centers for Disease Control and Prevention (mCDC) criteria have been proposed for diagnosing and managing stroke-associated pneumonia (SAP). The objective was to investigate the impact of SAP on stroke outcome depending on whether or not it conforms to mCDC criteria. Our secondary objective was to identify the responsible factors for antibiotic initiation in stroke patients.
UNASSIGNED: We conducted a prospective, multicenter, observational study of ischemic stroke patients with moderate to severe stroke (NIHSS≥4) admitted within 24 h. For 7 days, mCDC criteria were assessed daily, and infections and antibiotics were recorded. Pneumonias were divided into those fulfilling mCDC criteria (mCDC-SAP) or not (other pneumonias, OPn). The effect of each type of pneumonia on 3-month outcome was evaluated in separated logistic regression models. Factors associated with antibiotic initiation were explored using a random forest analysis.
UNASSIGNED: Of the 342 patients studied, infections were diagnosed in 72 (21.6%), including 39 (11.7%) cases of pneumonia. Of them, 25 (7.5%) fulfilled mCDC criteria. Antibiotics were used in 92% of mCDC-SAP and 64.3% of OPn. In logistic regression analysis, mCDC-SAP, but not OPn, was an independent predictor of poor outcome [OR, 4.939 (1.022-23.868)]. The random forest analysis revealed that fever had the highest importance for antibiotic initiation.
UNASSIGNED: The mCDC criteria might be useful for detecting clinically relevant SAP, which is associated with poor outcomes. Isolated signs of infection were more important for antibiotic initiation than compliance with pre-defined criteria. Therefore, adherence to mCDC criteria might result in antibiotic saving without compromising clinical outcome.

BACKGROUND: Hyperglycaemia (HG) during an acute ischemic stroke (AIS) is not only associated with unfavourable functional outcomes but also associated with stroke-associated pneumonia (SAP). This study aimed to determine the prevalence of SAP among Malaysian patients with AIS and the predictors of SAP among patients with HG during AIS.
METHODS: This is a retrospective cross-sectional study that included patients with AIS admitted to Hospital Sultanah Nur Zahirah, Malaysia from 2017 to 2020. SAP was defined as infection with pneumonia during the first seven days after IS. HG was defined as a blood glucose level > 7.8 mmol/L within 72 h after admission. Patients with SAP were divided into two groups according to HG status. Multivariate logistic regression analysis was performed using SPSS software, version 22 (IBM Corp., Armonk, NY) to identify SAP predictors among patients with HG. Kaplan-Meier log-rank test was used to compare the survival rate from unfavourable functional outcomes between hyperglycaemic patients with and without SAP.
RESULTS: Among 412 patients with AIS, 69 (16.74%) had SAP. The prevalence of SAP among patients with HG and normoglycemia during AIS was 20.98%, and 10.65%, respectively. Age above 60 years, leucocytosis, and National Institute of Health Stroke Scale (NIHSS) > 14 on admission were independent predictors of SAP with aOR of 2.08 (95% CI;1.01-4.30), 2.83 (95% CI; 1.41-5.67), and 3.67 (95% CI; 1.53-8.80), respectively. No significant difference in unfavourable functional outcomes survival was found among patients with and without SAP (p = 0.653).
CONCLUSIONS: This study demonstrated the prevalence of SAP was higher among patients with HG compared to normoglycemia during AIS. The patient being old, leucocytosis and severe stroke upon admission predict the occurrence of SAP among patients with HG during AIS.

OBJECTIVE: To explore the predictive value of radiomics in predicting stroke-associated pneumonia (SAP) in acute ischemic stroke (AIS) patients and construct a prediction model based on clinical features and DWI-MRI radiomics features.
METHODS: Univariate and multivariate logistic regression analyses were used to identify the independent clinical predictors for SAP. Pearson correlation analysis and the least absolute shrinkage and selection operator with ten-fold cross-validation were used to calculate the radiomics score for each feature and identify the predictive radiomics features for SAP. Multivariate logistic regression was used to combine the predictive radiomics features with the independent clinical predictors. The prediction performance of the SAP models was evaluated using receiver operating characteristics (ROC), calibration curves, decision curve analysis, and subgroup analyses.
RESULTS: Triglycerides, the neutrophil-to-lymphocyte ratio, dysphagia, the National Institutes of Health Stroke Scale (NIHSS) score, and internal carotid artery stenosis were identified as clinically independent risk factors for SAP. The radiomics scores in patients with SAP were generally higher than in patients without SAP (P < 0. 05). There was a linear positive correlation between radiomics scores and NIHSS scores, as well as between radiomics scores and infarct volume. Infarct volume showed moderate performance in predicting the occurrence of SAP, with an AUC of 0.635. When compared with the other models, the combined prediction model achieved the best area under the ROC (AUC) in both training (AUC = 0.859, 95% CI 0.759-0.936) and validation (AUC = 0.830, 95% CI 0.758-0.896) cohorts (P < 0.05). The calibration curves and decision curve analysis further confirmed the clinical value of the nomogram. Subgroup analysis showed that this nomogram had potential generalization ability.
CONCLUSIONS: The addition of the radiomics features to the clinical model improved the prediction of SAP in AIS patients, which verified its feasibility.

OBJECTIVE: To explore the predictive value of interleukin-6 (IL-6) combined with human neutrophil lipocalin (HNL) of stroke-associated pneumonia (SAP) in patients who were diagnosed with acute ischemic stroke (AIS).
METHODS: 108patients were divided into two groups: pneumonia group (52 cases) and non-pneumonia group (56 cases), according to whether the patients developed SAP within 7 days of admission. General information was compared between the two groups, like age, gender, history of hypertension, diabetes mellitus, cardiovascular disease, dysphagia, smoking and alcoholhistory. Clinical data were recorded and compared, including lipid profile, interleukin-6 (IL-6), homocysteine (Hcy), National Institutes of Health Stroke Scale (NIHSS) score, and HNL. Multivariate Logistic regression analysis was used to screen the risk factors of AIS-AP, and the predictive value of IL-6 and HNL alone and in combination was evaluated by receiver operating characteristic curve (ROC curve).
RESULTS: Logistic regression analysis showed that dysphagia (OR,0.018; 95% CI, 0.001 ~ 0.427; P = 0.013), increased NIHSS scores(OR,0.012; 95% CI, 0.000 ~ 0.434; P = 0.016), and high levels of IL-6 (OR,0.014; 95% CI, 0.000 ~ 0.695; P = 0.032)and HNL (OR,0.006; 95% CI, 0.000 ~ 0.280; P = 0.009) were independent risk factors for SAP with significant difference (all P < 0.05). According to the ROC curve analysis of IL-6, the area under the curve (AUC) was 0.881 (95% CI: 0.820 ~ 0.942), and the optimal cutoff value was 6.89 pg/mL with the sensitivity of 73.1% and specificity of 85.7%. As for the ROC curve analysis of HNL, the AUC was 0.896 (95% CI: 0.839 ~ 0.954), and the best cutoff value was 99.66ng/mL with the sensitivity of 76.9% and specificity of 89.3%. The AUC of the combination of IL-6 and HNL increased to 0.952 (95% CI: 0.914 ~ 0.989), and the sensitivity and specificity increased to 80.8% and 92.9%, respectively.
CONCLUSIONS: In this research, the levels of IL-6 ≥ 6.89 pg/mL and HNL ≥ 99.66ng/mL were considered as risk factors for AIS patients complicated with SAP. The combined detection had higher predictive value for patients with SAP, which may help to identify who were in highrisk.

UNASSIGNED: 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.
UNASSIGNED: 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.
UNASSIGNED: 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/).
UNASSIGNED: 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.