Analyzing prehospital delays in recurrent acute ischemic stroke: Insights from interpretable machine learning.

OBJECTIVE: This study investigates prehospital delays in recurrent Acute Ischemic Stroke (AIS) patients, aiming to identify key factors contributing to these delays to inform effective interventions. METHODS: A retrospective cohort analysis of 1419 AIS patients in Shenzhen from December 2021 to August 2023 was performed. The study applied the Extreme Gradient Boosting (XGBoost) algorithm and SHapley Additive exPlanations (SHAP) for identifying determinants of delay. RESULTS: Living with others and lack of stroke knowledge emerged as significant risk factors for delayed hospital presentation in recurrent AIS patients. Key features impacting delay times included residential status, awareness of stroke symptoms, presence of conscious disturbance, diabetes mellitus awareness, physical weakness, mode of hospital presentation, type of stroke, and presence of coronary artery disease. CONCLUSION: Prehospital delays are similarly prevalent among both recurrent and first-time AIS patients, highlighting a pronounced knowledge gap in the former group. This discovery underscores the urgent need for enhanced stroke education and management. PRACTICE IMPLICATION: The similarity in prehospital delay patterns between recurrent and first-time AIS patients emphasizes the necessity for public health initiatives and tailored educational programs. These strategies aim to improve stroke response times and outcomes for all patients.

Association among attention-deficit hyperactivity disorder, restless legs syndrome, and peripheral iron status: a two-sample Mendelian randomization study.

Background: Epidemiological evidence indicates a high correlation and comorbidity between Attention Deficit Hyperactivity Disorder (ADHD) and Restless Legs Syndrome (RLS). Objective: We aimed to investigate the causal relationship and shared genetic architecture between ADHD and RLS, as well as explore potential causal associations between both disorders and peripheral iron status. Methods: We performed two-sample Mendelian randomization (MR) analyses using summary statistics from genome-wide meta-analyses of ADHD, RLS, and peripheral iron status (serum iron, ferritin, transferrin saturation, and total iron binding capacity). Additionally, we employed linkage disequilibrium score regression (LDSC) to assess genetic correlations between ADHD and RLS using genetic data. Results: Our MR results supports a causal effect from ADHD (as exposure) to RLS (as outcome) (inverse variance weighted OR = 1.20, 95% CI: 1.08-1.34, p = 0.001). Conversely, we found no a causal association from RLS to ADHD (inverse variance weighted OR = 1.04, 95% CI: 0.99-1.09, p = 0.11). LDSC analysis did not detect a significant genetic correlation between RLS and ADHD (Rg = 0.3, SE = 0.16, p = 0.068). Furthermore, no evidence supported a causal relationship between peripheral iron deficiency and the RLS or ADHD onset. However, RLS may have been associated with a genetic predisposition to reduced serum ferritin levels (OR = 1.20, 95% CI: 1.00-1.04, p = 0.047). Conclusion: This study suggests that ADHD is an independent risk factor for RLS, while RLS may confer a genetic predisposition to reduced serum ferritin levels. Limitations: The GWAS summary data utilized originated from populations of European ancestry, limiting the generalizability of conclusions to other populations. Clinical implications: The potential co-occurrence of RLS in individuals with ADHD should be considered during diagnosis and treatment. Moreover, iron supplementation may be beneficial for alleviating RLS symptoms.

Record high external quantum efficiency of 20% achieved in fully solution-processed quantum dot light-emitting diodes based on hole-conductive metal oxides.

Poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS) has been widely used as a hole injection material in quantum dot (QD) light-emitting diodes (QLEDs). However, it degrades the organic materials and electrodes in QLEDs due to its strong hydroscopicity and acidity. Although hole-conductive metal oxides have a great potential to solve this disadvantage, it is still a challenge to achieve efficient and stable QLEDs by using these solution-processed metal oxides. Herein, the state-of-the-art QLEDs fabricated by using hole-conductive MoOx QDs are achieved. The α-phase MoOx QDs exhibit a monodispersed size distribution with clear and regular crystal lattices, corresponding to high-quality nanocrystals. Meanwhile, the MoOx film owns an excellent transmittance, suitable valence band, good morphology and impressive hole-conductivity, demonstrating that the MoOx film could be used as a hole injection layer in QLEDs. Moreover, the rigid and flexible red QLEDs made by MoOx exhibit peak external quantum efficiencies of over 20%, representing a new record for the hole-conductive metal oxide based QLEDs. Most importantly, the MoOx QDs afford their QLEDs with a longer T95 lifetime than these devices made by PEDOT:PSS. As a result, we believe that the MoOx QDs could be used as efficient and stable hole injection materials used in QLEDs.

Lymphocyte to Monocyte Ratio is Independently Associated with Futile Recanalization in Acute Ischemic Stroke After Endovascular Therapy.

Background and Purpose: Acute ischemic stroke (AIS) caused by large artery occlusion (LAO) poses considerable risks in terms of mortality and disability. Endovascular treatment (EVT) has emerged as a primary intervention for this condition. However, the occurrence of futile recanalization (FR) following EVT remains common, necessitating the identification of predictive markers for treatment outcomes. Although the lymphocyte to monocyte ratio (LMR) has been linked to various diseases, its association with FR after EVT in AIS patients has not been investigated. Methods: An analysis was conducted on patients with AIS who underwent EVT within 24 hours of symptom onset. The success of reperfusion was evaluated using the modified Thrombolysis in Cerebral Infarction (mTICI) scale, with patients achieving an mTICI score of ≥2b being included in the study. Various clinical, radiological, and laboratory variables, including lymphocyte-to-monocyte ratio (LMR), neutrophil-to-lymphocyte ratio (NLR), and platelet-to-lymphocyte ratio (PLR), were collected. Logistic regression analysis was used to determine factors associated with FR, and receiver operating characteristic (ROC) analysis was performed to assess the predictive value of LMR. Results: Among the cohort of 101 patients, it was observed that 52.4% experienced FR. Upon admission, lower levels of lymphocyte-to-monocyte ratio (LMR) were found to be associated with older age, higher baseline NIHSS scores, lower ASPECTS, and poorer mRS scores at 90 days. Both univariate and multivariate logistic regression analyses indicated that low LMR independently predicted FR, with an adjusted odds ratio of 0.64 (95% CI = 0.412-0.984, p = 0.042). ROC analysis further demonstrated that LMR had an area under the curve (AUC) of 0.789 for predicting FR. Conclusion: This study establishes the potential value of the lymphocyte-to-monocyte ratio (LMR) as a prognostic marker for predicting FR in patients with AIS undergoing EVT. Decreased LMR levels are associated with unfavorable clinical outcomes.

Nomogram-Based Prediction of the Futile Recanalization Risk Among Acute Ischemic Stroke Patients Before and After Endovascular Therapy: A Retrospective Study.

Background and Purpose: Futile recanalization (FRC) is common among large artery occlusion (LAO) patients after endovascular therapy (EVT). We developed nomogram models to identify LAO patients at a high risk of FRC pre- and post-EVT to help neurologists select the optimal candidates for EVT. Methods: From April 2020 to July 2022, EVT and mTICI score ≥2b LAO patients were recruited. Nomogram models was developed by two-step approach for predicting the outcomes of LAO patients. First, the least absolute shrinkage and selection operator (LASSO) regression analysis was to optimize variable selection. Then, a multivariable analysis was to construct an estimation model with significant indicators from the LASSO. The accuracy of the model was verified using receiver operating characteristic (ROC), calibration curve, and decision curve analyses (DCA), along with validation cohort (VC). Results: Using LASSO, age, sex, hypertension history, baseline NIHSS, ASPECTS and baseline SBP upon admission were identified from the pre-EVT variables. Model 1 (pre-EVT) showed good predictive performance, with an area under the ROC curve (AUC) of 0.815 in the training cohort (TrC) and 0.904 in VC. Under the DCA, the generated nomogram was clinically applicable where risk cut-off was between 15%-85% in the TrC and 5%-100% in the VC. Moreover, age, ASPECTS upon admission, onset duration, puncture-to-recanalization (PTR) duration, and lymphocyte-to-monocyte ratio (LMR) were screened by LASSO. Model 2 (post-EVT) also demonstrated good predictive performance with AUCs of 0.888 and 0.814 for TrC and VC, respectively. Under the DCA, the generated nomogram was clinically applicable if the risk cut-off was between 13-100% in the TrC and 22-85% of VC. Conclusion: In this study, two nomogram models were generated that showed good discriminative performance, improved calibration, and clinical benefits. These nomograms can potentially accurately predict the risk of FRC in LAO patients pre- and post-EVT and help to select appropriate candidates for EVT.