Objective To investigate the risk factors for early neurological deterioration in mild acute ischemic stroke，to construct a clinical predictive model，and to perform internal validation of this model. Methods A retrospective analysis was performed for 739 patients with mild acute ischemic stroke who were admitted to Department of Neurology，Kuntong Hospital of Zunhua，from October 2020 to December 2023，and they were randomly divided into a training set with 534 patients （72.3%） and a validation set with 205 patients （27.7%） at a ratio of 7∶3. Univariate and multivariate logistic regression analyses were performed for the training set to determine the risk factors for early neurological deterioration in mild acute ischemic stroke. A clinical predictive model was constructed，and internal validation was performed in terms of discriminatory ability，calibration，and clinical decision making. A nomogram was plotted. Results The multivariate logistic regression analysis showed that female sex （OR=1.87，95% CI 1.14~3.09，P=0.014），time window ≤6 hours （OR=3.10，95%CI 1.56~6.19，P=0.001），a baseline NIHSS score of 2 points （OR=3.72，95%CI 1.30~10.61，P=0.014），a baseline NIHSS score of 3 points （OR=4.24，95%CI 1.45~12.35，P=0.008），a TOAST classification of large artery atherosclerosis （OR=3.88，95%CI 2.20~6.83，P<0.001），and the responsible arteries of the basilar artery，the middle cerebral artery，and the internal carotid artery （OR=8.39，95%CI 2.28~30.85，P=0.001； OR=6.22，95%CI 1.78~21.71，P=0.004； OR=5.38，95%CI 1.15~25.13，P=0.032） were independent risk factors for early neurological deterioration in mild acute ischemic stroke. The clinical predictive model constructed showed a moderate discriminatory ability （AUC>0.7），good calibration （P>0.05） in the Hosmer-Lemeshow goodness-of-fit test），and good clinical benefits in both the training set and the validation set. Conclusion This clinical predictive model can effectively predict the onset of early neurological deterioration in mild acute ischemic stroke and guide clinicians to make decisions，and therefore，it holds promise for clinical application.
Nomograms

Human ; Communication ; Counseling ; Family ; Genetic Counseling ; Risk

OBJECTIVE

This study aimed to investigate the determinants linked to stunting among infants and young children aged 0-23 months in the Fourth District of Camarines Sur.

An analytical cross-sectional study was conducted among 628 primary caregivers with infants and young children aged 0-23 months in four municipalities of the Fourth District of Camarines Sur, Philippines, using a two stage stratified random sampling design. Data on sociodemographic and economic factors were collected through face-to-face interviews. Infant and young child feeding (IYCF) indicators were assessed using a list-based approach, while weight and length were evaluated using the World Health Organization Anthro Plus software. Descriptive statistics and multiple logistic regression were done using R statistical software version 4.3.1.

The study revealed that the prevalence of stunting was of significant public health concern, reaching 42.8%. Holding other variables constant, age of the child (OR=0.77; 95% CI: 0.63-0.94), having college undergraduate mothers (OR=0.26; 95% CI: 0.05-1.28), and belonging to a poor income household (OR=0.40; 95% CI: 0.14-0.88) were associated with stunting among infants aged 0.01-6.00 months. Moreover, after controlling for the confounding effects of other variables, age (OR=1.09; 95% CI: 1.05-1.14) and sex of the child (OR=1.55; 95% CI: 1.05-2.28) were associated with stunting among older children aged 6.00-23.99 months.

This study emphasizes the challenge of stunting in the Fourth District of Camarines Sur. None of the IYCF indicators were associated with stunting; however, maternal education, the child’s age, sex, and socioeconomic status were identified as significant factors influencing stunting. Addressing these determinants through targeted interventions focusing on improving maternal education and enhancing socio-economic conditions were crucial to reducing stunting in the study areas.

: This study aimed to identify risk factors associated with problematic mealtime behaviors in Filipino children aged 3-11 years diagnosed with ASD and to validate the Filipino-translated Brief Autism Mealtime Behavior Inventory (BAMBI) for clinical use. The study examined demographics, socioeconomic status, and clinical characteristics of children with ASD in relation to feeding difficulties. MATERIALS AND METHODS: A cross-sectional study was conducted with 166 caregivers of Filipino children with ASD at the Philippine Children’s Medical Center. The BAMBI questionnaire, translated and validated into Filipino, was administered among patients evaluated under the Section of Neurodevelopmental Pediatrics. Content validity was established through neurodevelopmental pediatric experts, while face validity was achieved with feedback from 17 caregivers during the pilot test. Descriptive statistics and logistic regression were performed to identify the factors. RESULTS: The Filipino-translated BAMBI demonstrated good content and face va- lidity based on reviews and pilot testing. The tool showed acceptable internal consistency with a Cronbach’s alpha of 0.75, indicating good reliability. Seventy-seven percent (77%) of participants scored above the threshold for problematic mealtime behaviors, with multivariate analysis revealing a significant association between these behaviors and sensory sensitivities (OR = 3.0, 95% CI: 1.2 to 7.3, p = 0.0150). Additional factors, such as dietary habits and family structure, also showed trends toward significance but did not reach statistical significance. CONCLUSIONS AND RECOMMENDATIONS This study validates the Filipino BAMBI as a reliable tool for assessing mealtime behaviors in children with ASD, highlighting the high prevalence of feeding problems in this population. Sensory sensitivities emerged as a significant factor contributing to problematic mealtime behaviors, underscoring the importance of incorporating sensory processing strategies in interventions. Further research should explore other contributing factors, such as dietary habits and family dynamics, to develop more comprehensive, tailored interventions for children with ASD and their families.
Autism spectrum disorder ; mealtime behaviors ; feeding difficulties ; BAMBI ; parent questionnaire ; risk factors

INTRODUCTION

Cardiovascular diseases (CVD) are a leading global health concern. Modifiable behavioral risk factors are increasingly recognized in young adults, especially among medical students who often live independently. This study investigated the association between living alone and modifiable cardiovascular risk factors—sleep quality, sodium intake, physical activity, and body mass index (BMI)—among medical students at UERMMMCI during the 2022-2023 academic year.

Researchers conducted an analytical cross-sectional study among 220 medical students. Validated tools were used: Pittsburgh Sleep Quality Index (PSQI), Scored Sodium Questionnaire, International Physical Activity Questionnaire (IPAQ), and BMI classification. Researchers performed statistical analyses using Chi-square tests and calculated relative risks (RR) with 95% confidence intervals.

A significant positive association was found between living alone and poor sleep quality (RR 2.132 p = 0.047). No significant associations were observed between living alone and sodium intake (RR 0.96 p = 0.6868), physical activity (RR 1.18 p = 0.2239), or BMI (RR 1.03 p = 0.7367).

Among the studied cardiovascular risk factors, only poor sleep quality was significantly more prevalent among students living alone. These findings highlight the importance of interventions targeting sleep hygiene in this demographic.

INTRODUCTION

This retrospective cohort study investigated the quality of care provided to patients with acute myocardial infarction (AMI) at a non-PCI capable tertiary hospital. We employed validated quality indicators (QIs) endorsed by the European Society of Cardiology (ESC) to assess adherence to evidence-based guidelines for AMI care.

This retrospective cohort study aims to comprehensively evaluate the quality of acute myocardial infarction (AMI) care provided at a non-PCI capable tertiary hospital by utilizing validated quality indicators (QIs). The study assesses adherence to evidence-based guidelines, identifies areas of improvement, and explores the association between care processes and patient outcomes.

This retrospective cohort study analyzed patients admitted with acute myocardial infarction (AMI) to a non-percutaneous coronary intervention (PCI) capable tertiary hospital between January 2021 and December 2022. Data on quality indicators were systematically extracted from medical records to assess adherence to clinical guidelines and patient outcomes. Logistic regression was used to identify predictors of mortality, while controlling for potential confounders such as demographic and clinical characteristics. Ethical approval was granted, and patient data was anonymized in compliance with national regulations.

The study identified a patient population consistent with established cardiovascular risk factors. Adherence rates to QIs varied across different domains. Notably, the risk-adjusted 30-day mortality rate was 29.09%, highlighting the need for further investigation into factors influencing patient outcomes.

Our study highlights both strengths and gaps in adherence to AMI quality indicators at a non-PCI hospital. While key treatments such as P2Y12 inhibitor use and anticoagulation were well implemented, areas like reperfusion protocols, LVEF measurement, and data collection require improvement. These findings reinforce the importance of evidence-based practices and the need for targeted quality improvement initiatives to address disparities in care. Future efforts should focus on enhancing data collection and exploring the reasons behind regional variations to optimize outcomes for AMI patients in resource-limited settings.

Human ; Writing ; Artificial Intelligence

BACKGROUND AND OBJECTIVES

The drug problem in the Philippines is influenced by various factors, but research on the specific risk factors and onset of drug use—an early predictor of severe drug abuse—is limited. This crosssectional study aims to identify factors associated with the onset of illicit drug use, focusing on variables such as sex, perceived socioeconomic status, adverse life events (including physical, verbal, and sexual abuse, and bullying), adverse home environments (like family substance abuse and parental separation), and premorbidities (such as anxiety and depression). Understanding these factors is crucial since early drug use often predicts more severe abuse later.

This cross-sectional study involved 354 participants aged 7 to 34 years, all undergoing rehabilitation for at least three months. Data were collected through self-administered questionnaires at their rehabilitation centers. Regression analysis was used to examine the relationship between the onset of drug use and the identified risk factors.

Regression analysis revealed that, apart from premorbidities, all the examined factors were significantly correlated with the onset of drug use. Specifically, being male, having higher affluence, experiencing more adverse life events, and living in a more adverse home environment were associated with an earlier onset of drug use. Among these factors, adverse life events and home environment were the strongest predictors of the onset of illicit drug use, while premorbidities did not show a significant relationship with drug use onset.

The study highlights that sex, socioeconomic status, adverse life events, and home environment are significant in the early onset of drug use, while premorbidities are not. Early intervention should focus on these key risk factors. A risk-focused approach, guided by biopsychosocial perspectives, is recommended. Targeted interventions should address adverse life events and home environments to prevent early drug use and subsequent abuse effectively.

INTRODUCTION: Adolescent depression is prevalent, and teen suicide rates are on the rise locally. A systemic review to understand associated risk and protective factors is important to strengthen measures for the prevention and early detection of adolescent depression and suicide in Singapore. This systematic review aims to identify the factors associated with adolescent depression in Singapore. METHODS: A systematic search on the following databases was performed on 21 May 2020: PubMed, EMBASE and PsycINFO. Full texts were reviewed for eligibility, and the included studies were appraised for quality using the Newcastle Ottawa Scale. Narrative synthesis of the finalised articles was performed through thematic analysis. RESULTS: In total, eight studies were included in this review. The four factors associated with adolescent depression identified were: (1) sociodemographic factors (gender, ethnicity); (2) psychological factors, including childhood maltreatment exposure and psychological constructs (hope, optimism); (3) coexisting chronic medical conditions (asthma); and (4) lifestyle factors (sleep inadequacy, excessive internet use and pathological gaming). CONCLUSION The identified factors were largely similar to those reported in the global literature, except for sleep inadequacy along with conspicuously absent factors such as academic stress and strict parenting, which should prompt further research in these areas. Further research should focus on current and prospective interventions to improve mental health literacy, targeting sleep duration, internet use and gaming, and mitigating the risk of depression in patients with chronic disease in the primary care and community setting.
Humans ; Singapore/epidemiology* ; Adolescent ; Risk Factors ; Depression/etiology* ; Protective Factors ; Male ; Female ; Life Style ; Suicide

INTRODUCTION: Obstructive sleep apnoea (OSA) is a serious but underdiagnosed condition. Demand for the gold standard diagnostic polysomnogram (PSG) far exceeds its availability. More efficient diagnostic methods are needed, even in tertiary settings. Machine learning (ML) models have strengths in disease prediction and early diagnosis. We explored the use of ML with oximetry, demographic and anthropometric data to diagnose OSA. METHODS: A total of 2,996 patients were included for modelling and divided into test and training sets. Seven commonly used supervised learning algorithms were trained with the data. Sensitivity (recall), specificity, positive predictive value (PPV) (precision), negative predictive value, area under the receiver operating characteristic curve (AUC) and F1 measure were reported for each model. RESULTS: In the best performing four-class model (neural network model predicting no, mild, moderate or severe OSA), a prediction of moderate and/or severe disease had a combined PPV of 94%; one out of 335 patients had no OSA and 19 had mild OSA. In the best performing two-class model (logistic regression model predicting no-mild vs. moderate-severe OSA), the PPV for moderate-severe OSA was 92%; two out of 350 patients had no OSA and 26 had mild OSA. CONCLUSION Our study showed that the prediction of moderate-severe OSA in a tertiary setting with an ML approach is a viable option to facilitate early identification of OSA. Prospective studies with home-based oximeters and analysis of other oximetry variables are the next steps towards formal implementation.
Humans ; Oximetry/methods* ; Sleep Apnea, Obstructive/diagnosis* ; Male ; Female ; Middle Aged ; Machine Learning ; Polysomnography ; Adult ; Anthropometry ; ROC Curve ; Aged ; Algorithms ; Predictive Value of Tests ; Sensitivity and Specificity ; Neural Networks, Computer ; Demography