OBJECTIVE: To explore the application value of artificial intelligence (AI)-assisted chromosomal karyotype analysis in the diagnosis of prenatal chromosomal mosaicism. METHODS: A retrospective analysis was conducted on 172 pregnant women who underwent amniocentesis at the Department of Medical Genetics and Prenatal Diagnosis, the Third Affiliated Hospital of Zhengzhou University between January 2019 and December 2024. All cases whose fetuses were diagnosed with chromosomal mosaicism via karyotype analysis and stratified into two groups based on the analytical software employed: the conventional analysis group (n = 70), which utilized Leica analysis software for karyotype image recognition and cell counting; and the AI-assisted analysis group (n = 102), which utilized AI-assisted software for the same procedures. The clinical performance of AI-assisted karyotype analysis in diagnosing chromosomal mosaicism was comprehensively evaluated by comparing the types of mosaic karyotypes, distribution of mosaic ratios, and verification outcomes of different detection modalities between the two groups. This study was approved by the Medical Ethics Committee of the Third Affiliated Hospital of Zhengzhou University (Ethics No.: 2024-406-01). RESULTS: No statistically significant difference was observed in baseline characteristics (maternal age, gestational week, and indications for prenatal diagnosis) between the two groups. Regarding the detection efficacy for numerical and structural mosaicisms, no significant difference was found in the detection of numerical mosaicism. However, the conventional analysis group exhibited a significantly higher detection rate of autosomal structural mosaicism compared to the AI-assisted group (11.43% vs. 0.98%, P < 0.05). Numerical mosaicism cases were further verified using copy number variation sequencing (CNV-seq) and/or fluorescence in situ hybridization (FISH). The AI-assisted group demonstrated a significantly lower inconsistency rate (5.56% vs. 20.41%, P < 0.05) compared to the conventional group. For low-proportion (< 10%) chromosomal mosaicism, the AI-assisted group had a significantly lower detection rate (13.25% vs. 29.69%, P < 0.05). Subsequent validation of low-proportion mosaicism by CNV-seq and/or FISH showed a higher consistency rate in the AI-assisted group (81.82% vs. 54.55%), though the difference did not reach statistical significance (P = 0.360). CONCLUSION For the karyotyping analysis of prenatal chromosomal mosaicism, AI-assisted karyotype analysis shows high accuracy and consistency in identifying numerical chromosomal mosaicism, particularly in reducing the detection of low-proportion (< 10%) mosaicism while improving verification accuracy. AI-assisted analysis can significantly improve the detection accuracy of numerical mosaicism and mitigate the risk of misclassification for low-proportion (< 10%) mosaicism, thereby providing more precise clinical evidence for the prenatal diagnosis of chromosomal mosaicisms.
Humans ; Female ; Mosaicism ; Pregnancy ; Karyotyping/methods* ; Artificial Intelligence ; Prenatal Diagnosis/methods* ; Adult ; Retrospective Studies ; Chromosome Disorders/genetics* ; Amniocentesis

OBJECTIVE: To explore the efficacy of a Thalassemia risk assessment software for the screening of thalassemia mutation carriers and distribution of thalassemia genotypes detected by screening. METHODS: A total of 6 040 individuals were evaluated at Leshan Maternal and Child Health Care Hospital between 2022 and 2024 using the commonly used clinical thalassemia risk assessment method and the thalassemia screening software, respectively, and the performance indicators of the two methods were compared and analyzed against the result of thalassemia gene testing. This study was approved by the Ethics Committee of our hospital (Ethics No.: LfyLL[2022]005). RESULTS: The high-risk rate by the thalassemia screening software was 11.19%, with a sensitivity of 95.12%, specificity of 93.28%, positive predictive value of 43.20%, negative predictive value of 99.72%, and the area under the ROC curve (AUC) was 0.942. The thalassemia gene detection rate of the high-risk samples screened was 4.83%. The high-risk screening rate of the conventional method was 2.50%, with a sensitivity of 51.22%, specificity of 93.28%, positive predictive value of 80.79%, negative predictive value of 97.40%, and the AUC was 0.754. The thalassemia gene detection rate of the high-risk samples was 2.02%. CONCLUSION The software can effectively detect thalassemia carriers and significantly reduce the missed detection compared with conventional method, thereby significantly improve the efficacy of screening.
Humans ; Thalassemia/diagnosis* ; Software ; Female ; Genetic Testing/methods* ; Male ; Mutation ; Adult ; Genotype ; ROC Curve ; Risk Assessment

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.