BACKGROUND In the "one-stop-shop" stroke computed tomography (CT) scanning protocol, CT perfusion (CTP) can be performed either before or after CT angiography (CTA). This study analyzed the effect of different scanning strategies in one-stop-shop stroke CT on CTA image quality and perfusion parameters, aiming to optimize the scanning sequence of CTP and CTA in the one-stop-shop stroke CT protocol. MATERIAL AND METHODS We retrospectively analyzed 115 patients with suspected acute ischemic stroke admitted to our hospital between March and June 2024 and implemented 2 scanning strategies: CTP before CTA (group A, n=51) and CTA before CTP (group B, n=64) using 64-row CT equipment. The differences in CT values of the basilar artery, middle cerebral artery, superior sagittal sinus, and straight sinus, as well as craniocerebral perfusion parameter values and subjective scores of the CTA image quality, were compared between the 2 groups. The difference between venous CT values and the expert consensus-recommended intracranial venous CT value of 150 Hounsfield units (HU) was also compared. RESULTS There were no significant differences in arterial CT values or perfusion parameter values between groups A and B (P>0.0125). However, there was a significant difference in superior sagittal sinus CT values between the groups (P<0.0125). Group A showed more venous contamination (P<0.025), and its superior sagittal sinus CT value was significantly higher than the expert consensus-recommended value of 150 HU (P<0.0125). CONCLUSIONS CTA before CTP had no significant effect on perfusion parameters and was associated with reduced venous contamination. This strategy may serve as a practical alternative in similar 64-slice CT one-stop-shop stroke protocols.

Mounting evidence suggests CBC-derived hematological inflammatory ratios correlate with nutritional status, yet few studies explore their cross-sectional associations with GNRI-defined concurrent nutritional risk in elderly patients with acute ischemic stroke (AIS). This single-center, cross-sectional, observational study was designed to evaluate the correlation between routine admission hematological markers and nutritional risk in elderly patients with AIS. Twelve CBC-derived indices were analyzed: lymphocyte ratio (LR), red blood cell-to-lymphocyte ratio (RLR), hemoglobin-to-lymphocyte ratio (HLR), monocyte-to-lymphocyte ratio (MLR), monocyte-to-neutrophil ratio (MNR), neutrophil-to-lymphocyte ratio (NLR), NLR-to-platelet ratio (NLR/PLT100), MLR-to-platelet ratio (MLR/PLT), platelet-to-neutrophil ratio (PNR), platelet-to-lymphocyte ratio (PLR), mean platelet volume-to-lymphocyte ratio (MPVLR), serum albumin-to-lymphocyte ratio (ALBLR).

Between January 2022 and January 2024, 540 elderly AIS patients (≥60 years) were enrolled. All participants underwent admission GNRI assessment and were split into GNRI-defined nutritional risk group (GNRI≤98, n = 245, 45.4%) and non-nutritional risk group (GNRI>98, n = 295). Venous blood was collected within 24 h on admission. Univariate and multivariate logistic regression were applied to explore cross-sectional correlations, and an exploratory combined statistical model was built. ROC curve, DeLong's test, likelihood ratio test and AIC were used to evaluate model discrimination and fit.

Multiple indicators including age, hypertension, ALT, UA, TG, LR, RLR, MLR, NLR, NLR/PLT100, MLR/PLT, PLR and MPVLR showed univariate correlations with nutritional risk. Multivariate regression identified MLR and NLR/PLT100 as independent correlates within this cohort; MLR showed the strongest association in this dataset instead of robust correlative ability. Adding MLR alone or combining MLR + NLR/PLT100 to base clinical variables significantly improved C-statistic. The combined model reached an AUC of 0.735, representing only moderate discriminative capacity, and it was merely the superior exploratory model limited to the present sample without external generalizability.

Within this single-center cohort, MLR exhibited the strongest cross-sectional correlation with GNRI-defined nutritional risk among all tested CBC-derived hematological inflammatory ratios. The composite model combining baseline clinical indicators, MLR and NLR/PLT*100 demonstrated moderate discriminative ability within the study sample, but is not yet robust enough to serve as an effective tool for routine clinical risk stratification.

Neurological injury is common after cardiac arrest (CA), but early and accurate assessment remains challenging. Existing evaluation methods often lack sensitivity and specificity. This study aims to develop and validate an interpretable machine learning model for early and reliable assessment of brain injury and its prognostic relevance in ICU patients.

In this study, we analyzed 1,419 CA patients from the MIMIC-IV database, randomly split into training and validation cohorts. Six machine learning (ML) algorithms-logistic regression (LR), XGBoost, artificial neural network (ANN), random forest (RF), support vector machine (SVM), and k-nearest neighbors (KNN) were developed and evaluated. The top-performing model was interpreted using SHapley Additive exPlanations (SHAP), identifying eight key predictors of brain injury. Finally, clinical data from cardiac arrest patients at our hospital were collected for external validation to assess the model's generalizability and practical utility in an ICU setting.

Among the six machine learning models, the Random Forest model achieved the highest numerical performance in both the internal test and external validation cohorts. In the internal test cohort, Random Forest achieved an ACC of 88.7%, sensitivity of 80.0%, specificity of 90.6%, F1 score of 0.714, NPV of 95.5%, PPV of 64.5%, and AUC of 0.901. In the external validation cohort, Random Forest achieved an ACC of 88.8%, sensitivity of 77.8%, specificity of 90.8%, F1 score of 0.677, NPV of 95.8%, PPV of 60.0%, and AUC of 0.889. SHAP analysis identified eight influential predictors: age, hemoglobin, OASIS, temperature, blood urea nitrogen, white blood cell count, non-invasive diastolic pressure, and non-invasive systolic pressure.

Machine learning offers strong potential for early prediction of acute brain injury in in-hospital cardiac arrest patients. Our interpretable model addresses the "black box" concern by providing transparent insights into key predictive features.

Although physical restraint causes mental and physical harm to patients, such practice occurs worldwide to ensure patient safety. It is non-standard practice for a number of reasons, including the lack of education, training, and protocol.

This study aims to determine the experiences of nurses who apply physical restraint to patients.

A descriptive phenomenological method was employed in this study, wherein semi-structured interviews were the data collection method. In this qualitative study, the data consisted of semi-structured individual interviews with nurses (n = 20). The data were analysed phenomenologically and were arranged with MAXqda 22 analysis software. The study complies with the COREQ checklist.

Six main themes were found from the data. The themes were (i) experiences related to nurses' physical restraint procedures, (ii) ethical balance in nursing, (iii) nurses' emotions, (iv) the meaning of physical restraint, (v) nurses' observations regarding patients' reactions to physical restraints, and (vi) the experience of ethical dilemmas. The nurses perceived physical restraint as being uncomfortable, a necessity or an obligation, as beneficial for patients, and a practice seen as punishment.

The findings showed that physical restraint elicited diverse thoughts and emotions among nurses, who reported difficulties in coping with these emotions and insufficient knowledge of restraint procedures. Nurses also described the need to protect patient safety while preserving patient autonomy, highlighting the ethical balance involved in decisions concerning physical restraint.

This study has provided insight that can guide clinician nurses, educators, and policy-makers in improving physical restraint administration. The lack of knowledge held among nurses as to physical restraint procedures emphasizes the importance of education and training on this topic and can suggest areas of development for pertinent policies and guidelines.

No patient or public contribution.

Period poverty (a lack of access to menstrual products, sanitation, and education), affects over a billion people worldwide, posing threats to physical, mental, and emotional well-being. Effective messaging is critical to combating this public health issue. This study investigated how message format (narrative versus non-narrative) and narrative focus (individual versus collective narrative) shape audience members' processing of and responses to Period poverty messaging. In a between-subjects online experiment withU.S. adults (N = 1104), participants were randomly assigned to one of three message conditions. Results revealed no significant effects of message format or narrative focus in the full sample. However, subgroup estimates revealed significant indirect effects. Within the male subsample, the individual narrative (vs. non-narrative) increased policy support and donation intention through transportation and anger. Additionally, the individual (vs. collective) narrative enhanced policy support via compassion and anger. Within the female subsample, persuasive outcomes were not shaped by message format or narrative focus. Overall, these patterns suggest that audience gender identity may warrant further investigation as a potential boundary condition in communicating period poverty. The results highlight the importance of tailoring period poverty messages to audiences with different genders and advancing theory on identity-contingent narrative persuasion.

Over a third of U.S. adults struggle with health literacy, which broadly describes the ability to access, understand, and use health-related information. Conceptual models highlight the importance of cognitive functions in health literacy, but limited empirical work has carefully examined the extent to which various aspects of cognition uniquely contribute to different dimensions of health literacy.

Participants in this retrospective, harmonized study included 312 healthy adults who completed a battery of well-validated cognitive tests that measured their general fund of knowledge, attention, declarative memory, and executive functions (;). Participants also completed a performance-based measure of health-related numeracy (i.e., Expanded Numeracy Scale) and questionnaires assessing self-perceived health literacy in applied contexts (i.e., Brief Health Literacy Screening and eHealth Literacy Scale).

After accounting for the influence of sociodemographics and general fund of knowledge parallel hierarchical regressions showed that measures of executive functions and memory explained a significant amount of variance in health-related numeracy and measures of executive functions explained a significant, but modest, amount of variance in self-perceived health literacy in applied contexts after accounting for the influence of sociodemographics and general fund of knowledge.

Findings suggest that executive functions (i.e. generativity and cognitive flexibility) play a unique role in some aspects of personal health literacy among healthy adults. Future experimental studies might further dissect the role of executive functions in the expression and management of health literacy in at-risk clinical populations.

Perinatal mental health (PMH) challenges impact numerous mothers in Canada, with disproportionate effects observed within racialised populations. Despite increasing awareness, disparities in access to care continue to persist. This study explores the lived experiences of racialised mothers accessing PMH care in the Greater Toronto Area (GTA), with a focus on contextual factors across the patient work system. Semi-structured interviews were conducted with sixteen racialised mothers within one-year postpartum. Data analysis employed an inductive thematic approach with emergent themes and contextual factors mapped across the patient work system. Findings underscored an interaction between micro- and macro-level, wherein varying levels of trust, comfort, and self-reliance corresponded with care that was fragmented, delayed, or absent. At the meso-level, emotionally engaged providers, multimodal services, and robust community-based support emerged as areas of resilience. Grounded in the patient work of racialised mothers, preliminary design recommendations are proposed for the design of proactive PMH care systems.

Given the impact of substance use disorder on public health and social development, synthesizing evidence can inform policies and programs tailored to Filipinos. This review included studies on substance-related disorders among Filipinos from 2006 to 2026. The search drew on four databases, namely PubMed, Scopus, ScienceDirect, and HERDIN, using keywords related to substance use and related outcomes and the Philippines. Data from eligible studies were extracted and compared using narrative synthesis and the biopsychosocial framework. A total of 338 publications were identified. After excluding duplicate records and conducting screening and eligibility assessments, the review included 28 study reports. The findings show that biological factors such as sex, age, smoking habits, and physical health were associated with substance use. Likewise, psychosocial factors, including mental health issues, psychological distress, maladaptive coping strategies, severity of drug use, recovery skills, peer substance use, family and peer support, school involvement, drug access, food insecurity, challenging home environments, and life stressors, were associated with substance use. These results support a biopsychosocial model for understanding substance use and a multi-level intervention ranging from improving individual mental health and coping skills to strengthening family, school, and peer support in the Philippines. Future research can focus on longitudinal and nationally representative studies.

Aperiodic electroencephalographic activity is proposed as a scalable marker of cortical population dynamics relevant to excitation-inhibition balance. However, it remains unclear whether aperiodic parameters represent disorder-specific abnormalities or context-sensitive indices of clinically relevant brain states. Consistent with systematic-review guidelines and a prospectively registered protocol, Ovid databases and PubMed were searched from inception through February 9, 2026, with updated manual searching conducted through July 14, 2026. Peer-reviewed studies reporting electroencephalography-derived aperiodic parameters in adults with schizophrenia-spectrum disorders, major depressive disorder, treatment-resistant depression, and/or bipolar disorder were eligible. Studies lacking aperiodic outcomes or separable findings for eligible diagnoses were excluded. Two reviewers independently conducted study screening, data extraction, and risk-of-bias assessments. Findings were synthesized narratively by diagnosis, recording context, and parameter. Thirty articles (N = 2298 aggregate participants) spanning cross-sectional, longitudinal, and interventional designs were included. Findings in schizophrenia-spectrum disorders were heterogeneous, with several studies reporting steeper slopes, higher offsets, or reduced temporal flexibility relative to healthy controls. Task-related and dynamic measures often showed greater clinical relevance than static resting-state parameters. Studies of major depressive disorder and treatment-resistant depression more consistently reported flatter slopes and reduced offsets, particularly in central and posterior regions, with evidence from sleep and intracranial recordings. Aperiodic parameters were sensitive to treatment-related modulation, although the direction of change differed across interventions. Bipolar disorder evidence was limited, and methodological heterogeneity precluded quantitative synthesis. Aperiodic electroencephalographic activity may be more informative as a context-sensitive, within-subject marker of cortical state and treatment-related change than a fixed diagnostic signature. Methodological harmonization and direct physiological validation remain necessary before clinical implementation.

The management of bradyarrhythmias requiring permanent pacing in pediatric patients and those with congenital heart disease (CHD) remains uniquely challenging due to continuous somatic growth, complex cardiac anatomy, limited vascular access, and long-term risks associated with conventional cardiac implantable electronic devices. Traditional transvenous endocardial and surgical epicardial pacing systems are associated with high rates of lead failure, venous occlusion, infection, and ventricular dyssynchrony. Leadless pacemakers and conduction system pacing have emerged as promising alternatives that overcome many of these historical limitations. This review provides a comprehensive, updated overview of the technical principles, clinical applications, advantages, limitations, and appropriate patient selection strategies for these two innovative modalities in the pediatric and CHD population. Critical clarifications are provided regarding venous access requirements, age-adjusted interpretation of QRS duration, ventricular dyssynchrony evaluation, and indications for device therapy according to pediatric-specific guidelines rather than adult-derived criteria. Clinical decision-making is integrated into a structured framework based on age, body size, clinical symptoms, ventricular synchrony, and arrhythmic risk stratification.