BackgroundIschemic stroke (IS) is the most common and life-threatening arterial manifestation of antiphospholipid syndrome (APS). It is related to high mortality and severe permanent disability in survivors. Thus, it is essential to identify patients with APS at high risk of IS and adopt individual-level preventive measures. This study was conducted to identify risk factors for IS in patients with APS and to develop a nomogram specifically for IS prediction in these patients by combining the adjusted Global Anti-Phospholipid Syndrome Score (aGAPSS) with additional clinical and laboratory data.MethodsA total of 478 consecutive patients with APS were enrolled retrospectively. All patients were randomly assigned to the training and validation cohorts. Univariate and multivariate binary logistic analyses were conducted to identify predictors of IS in the training cohort. Then, a nomogram was developed based on these predictors. The predictive performance of the nomogram for the training and validation cohorts was evaluated by determining areas under the receiver operating characteristic curve (AUROC) and creating calibration plots. A decision curve analysis (DCA) was conducted to compare the potential net benefits of the nomogram with those of the aGAPSS.ResultsDuring a mean follow-up period of 2.7 years, 26.9% (129/478) of the patients were diagnosed with IS. Binary logistic regression analysis revealed that five risk factors were independent clinical predictors of IS: age (P < 0.001), diabetes (P = 0.030), hyperuricemia (P < 0.001), the platelet count (P = 0.001), and the aGAPSS (P = 0.001). These predictors were incorporated into the nomogram, named the aGAPSS-IS. The nomogram showed satisfactory performance in the training [AUROC = 0.853 (95% CI, 0.802–0.896] and validation [AUROC = 0.793 (95% CI, 0.737–0.843)] cohorts. Calibration curves showed good concordance between observed and nomogram-predicted probability in the training and validation cohorts. The DCA confirmed that the aGAPSS-IS provided more net benefits than the aGAPSS in both cohorts.ConclusionAge, diabetes, hyperuricemia, the platelet count, and the aGAPSS were risk factors for IS in patients with APS. The aGAPSS-IS may be a good tool for IS risk stratification for patients with APS based on routinely available data.

BackgroundStroke-associated pneumonia (SAP) commonly complicates acute ischemic stroke (AIS) and significantly worsens outcomes. Type 2 diabetes mellitus (T2DM) may contribute to malnutrition, impair innate immunity function, and increase the probability of SAP occurrence in AIS patients. We aimed to determine early predictors of SAP in AIS patients with T2DM and to construct a nomogram specifically for predicting SAP in this population by combining the A2DS2 score with available nutrition-related parameters.MethodsA total of 1,330 consecutive AIS patients with T2DM were retrospectively recruited. The patients were randomly allocated to the training (n = 887) and validation groups (n = 443). Univariate and multivariate binary logistic regression analyses were applied to determine the predictors of SAP in the training group. A nomogram was established according to the identified predictors. The areas under the receiver operating characteristic curve (AUROC) and calibration plots were performed to access the predictive values of the nomogram. The decision curve was applied to evaluate the net benefits of the nomogram.ResultsThe incidence of SAP was 9% and 9.7% in the training and validation groups, respectively. The results revealed that the A2DS2 score, stroke classification, Geriatric Nutritional Risk Index, hemoglobin, and fast blood glucose were independent predictors for SAP. A novel nomogram, A2DS2-Nutrition, was constructed based on these five predictors. The AUROC for A2DS2-Nutrition (0.820, 95% CI: 0.794–0.845) was higher than the A2DS2 score (0.691, 95% CI: 0.660–0.722) in the training group. Similarly, it showed a better predictive performance than the A2DS2 score [AUROC = 0.864 (95% CI: 0.828–0.894) vs. AUROC = 0.763 (95% CI: 0.720–0.801)] in the validation group. These results were well calibrated in the two groups. Moreover, the decision curve revealed that the A2DS2-Nutrition provided an additional net benefit to the AIS patients with T2DM compared to the A2DS2 score in both groups.ConclusionThe A2DS2 score, stroke classification, Geriatric Nutritional Risk Index, hemoglobin, and fast blood glucose were independent predictors for SAP in AIS patients with T2DM. Thus, the proposed A2DS2-Nutrition may be a simple and reliable prediction model for SAP occurrence in AIS patients with T2DM.

BackgroundStroke-associated infection (SAI) is a common complication after a stroke. The incidence of infection was higher in people with sarcopenia than in the general population. However, the relationship between pre-stroke sarcopenia risk and SAI in older patients has not been confirmed. This study aimed to investigate the association between pre-stroke sarcopenia risk and SAI in older patients with acute ischemic stroke (AIS).MethodsThis retrospective study was conducted by the Peking University People’s Hospital. We evaluated the pre-stroke sarcopenia risk by applying the SARC-F questionnaire. Multivariate logistic regression was applied to explore the association between pre-stroke sarcopenia risk and SAI.ResultsA total of 1,002 elder patients with AIS (592 men; 72.9 ± 8.6 years) were enrolled in our study. Pre-stroke sarcopenia risk was found in 29.1% of the cohort. The proportion of patients with pre-stroke sarcopenia risk was larger in the SAI group than in the non-SAI group (43.2 vs. 25.3%, p   < 0.001). In multivariate logistic analysis, pre-stroke sarcopenia risk was shown to be independently associated with SAI (OR = 1.454, 95% CI: 1.008–2.097, p = 0.045) after adjusting for potential factors. This association remained consistent across the subgroups based on age, sex, body mass index, smoking status, drinking status, diabetes, hypertension, and dyslipidemia.ConclusionPre-stroke sarcopenia risk was independently associated with SAI in older patients with AIS. Our findings highlight the significance of pre-stroke sarcopenia identification in the prevention and management of SAI in this population.

PurposeThis study aimed to determine the prognostic impact of the neutrophil-to-lymphocyte ratio (NLR) in critically ill trauma patients.MethodsThis retrospective study involved adult trauma patients from 335 intensive care units (ICUs) at 208 hospitals stored in the eICU database. The primary outcome was ICU mortality. The lengths of ICU and hospital stay were calculated as the secondary outcomes. The multivariable logistic regression model was used to identify independent predictors of mortality. To identify the effect of the NLR on survival, a 15-day survival curve was used.ResultsA total of 3,865 eligible subjects were enrolled in the study. Univariate analysis showed that patients in the group with a higher NLR were more likely to receive aggressive methods of care delivery: mechanical ventilation, vasopressor, and antibiotics ( P < 0.001 for all). The ICU, in-hospital, and 15-day mortality rates of the four groups increased in turn (P < 0.001 for all). The multivariable logistic Cox regression model indicated that a higher NLR was an independent risk factor of ICU mortality in trauma patients. ROC analysis showed that the NLR had better predictive capacity on the mortality of patients with traumatic brain injury (TBI) than those with trauma (AUC 0.725 vs. 0.681). An NLR > 7.44 was an independent risk factor for ICU death in patients with TBI (OR: 1.837, 95% CI: 1.045–3.229) and TBI victims whose NLR > 7.44 had a 15-day survival disadvantage (P = 0.005).ConclusionA high NLR is associated with a poor prognosis in trauma patients, even worse in patients with TBI. An NLR > 7.44 is an independent risk factor for death in patients with TBI.

BackgroundThe relationship between skeletal muscle mass index (SMI) and cirrhosis incidence in patients with non-cirrhotic acute-on-chronic (ACLF) has not been clarified. This study aimed to assess the predictive value of SMI on the incidence of long-term cirrhosis in male non-cirrhotic ACLF patients.Materials and methodsMale ACLF patients who were free of liver cirrhosis were retrospectively included in this study. Univariate and multivariate logistic analyses were conducted to determine the risk factors for the long-term (1-year) development of cirrhosis. The receiver operating characteristic curves (ROC) were used to assess the ability of SMI levels to predict the incidence of cirrhosis. Restricted triple spline (RCS) described the dose-response relationship between SMI and the risk of cirrhosis. Subgroup analysis was stratified by age (≤ 40 years and > 40 years).ResultsA total of 230 subjects were included in this study, of whom 45.2% (104/230) were diagnosed with cirrhosis within 360 days. Patients who progressed to cirrhosis had a lower SMI [46.1 ± 6.9 versus 49.2 ± 6.5 cm2/m2, P = 0.001] and a higher proportion of sarcopenia (19.2% versus 6.3%, P = 0.003). In multivariate logistic regression, SMI remained a protective agent against 360-days progression to cirrhosis in males with ACLF after adjustment (OR 0.950, 95% CI: 0.908–0.994, P < 0.05). SMI exerted a non-linear dose-dependent effect on the risk of cirrhosis. The area under the ROC curve (AUC) for the L3-SMI to predict the incidence of cirrhosis in male non-cirrhotic ACLF patients was 0.636 (P < 0.001). We observed significant differences in SMI among male ACLF patients in different age groups. Further subgroup analysis by age revealed that lower SMI was associated with the 1-year incidence of cirrhosis in male ACLF patients aged less than 40 years (OR 0.908, 95% CI: 0.842–0.979, P < 0.05), whereas SMI did not affect the 1-year risk of cirrhosis in older subjects (age > 40 years).ConclusionA higher SMI represents an independent protective factor for developing long-term cirrhosis in male ACLF patients who do not experience cirrhosis, especially in those under 40 years of age.