BACKGROUND

Graduating student nurses are crucial to healthcare delivery, yet concerns about their clinical performance persist. They often face challenges translating theoretical knowledge into practice, leading to a theory-practice gap. Clinical competence is essential for ensuring safe and effective nursing care.

This study assessed the clinical competence of graduating student nurses in HEIs within Baguio City. It specifically evaluated their proficiency in professional behavior, general performance, core nursing competency, and advanced nursing skills. Additionally, it examined whether significant differences in clinical competence existed based on sex, area of duty, and accreditation status.

A descriptive-quantitative non-experimental research design was employed. The study surveyed 285 graduating student nurses from six HEIs in Baguio City, selected through fishbowl sampling. Data was collected using the Clinical Competence Questionnaire (CCQ), a 47-item questionnaire with an I-CVI rating of 1.0 and a Cronbach’s Alpha of 0.94. Data analysis included descriptive statistics, Welch's T-test, One-way ANOVA, and Welch's ANOVA.

Students demonstrated high competence with the following means: 4.42 in nursing professional behaviors, 4.32 in general performance, 4.35 in core nursing skills, and 3.92 in advanced nursing skills. While the results were interpreted as high competence, specific advanced nursing skills require further enhancement. No significant differences (p-value < 0.05) in clinical competence were found concerning sex (0.38), duty area (0.92), or accreditation status (0.07).

Graduating student nurses show high competency upon entering level IV, emphasizing ongoing skill development for quality patient care. Both genders exhibit proficiency, indicating fair training and effective education regardless of duty area exposure and accreditation status.

INTRODUCTION

Ventricular tachycardia (VT) storm is a condition characterized by recurrent ventricular arrhythmias within a 24-hour period, requiring a device or pharmacologic intervention. Despite its clinical significance, data on VT storm prevalence and treatment outcomes in the Filipino population remain limited

We present a 69-year-old male with heart failure from non-ischemic cardiomyopathy and an implantable cardioverter-defibrillator (ICD), who experienced multiple VT episodes unresponsive to amiodarone, lidocaine and mechanical cardioversion. He was initially admitted for catheter ablation but later developed a left ventricular thrombus precluding the procedure. Mexiletine was introduced and successfully suppressed arrhythmia recurrence

This case emphasized the complexity of managing ES, especially in patients with contraindications to ablation. Mexiletine, a class IB antiarrhythmic agent structurally similar to lidocaine, has shown efficacy in refractory VT, especially when standard therapies are ineffective or are contraindicated. Limited data exists on its safety for such cases, particularly in patients with intracardiac thrombus.

Mexiletine may offer a viable treatment option for VT storm in patients ineligible for ablation due to left ventricular thrombus. While it was effective in this case, further studies are needed to validate its safety and long-term outcomes in similar high-risk populations.

BACKGROUND

Generative artificial intelligence (GenAI) is increasingly integrated into healthcare, including occupational therapy (OT), with potential applications in its service delivery and clinical decision-making. While GenAI offers promising educational and clinical support, its generative nature introduces risks related to contextual accuracy, transparency, and ethical use, particularly within supervised clinical training settings where professional judgment is still developing. Empirical research examining GenAI integration in OT clinical training remains limited, especially within the Philippine context.

This is a protocol for a study which aims to explore the perceptions of OT interns in Manila, Philippines, regarding GenAI integration in clinical training, including perceived benefits, challenges, and ethical considerations, guided by Rogers’ Diffusion of Innovations Theory

This qualitative study protocol describes an exploratory design that will be used to gather rich and contextualized insights from 24 to 32 OT interns enrolled in universities in Manila with established institutional AI-use policies. Data will be collected through semi-structured online focus group discussions (FGD). Thematic analysis will be used with assistance from atlas.ti. 

The study is expected to generate meaningful themes that describe the perceptions of OT interns regarding the integration of GenAI within supervised clinical training contexts. Results are expected to reflect how interns perceive the role of GenAI in supporting clinical decision-making, as well as its perceived challenges and ethical concerns related to institutional policies, data privacy, reliability, and variability in AI-generated outputs.

Effective discharge planning is crucial for ensuring safe transitions and sustained occupational participation as clients transition from professional care to their desired community settings. Despite its importance, current discharge practices in occupational therapy remain inconsistent, often relying on informal communication, variable team coordination, and unstructured decision-making. These gaps contribute to client–caregiver unpreparedness, fragmented services, and increased readmissions. This manuscript presents the Building Rehabilitation Into Discharge Goals and Engagement (BRIDGE) Framework, a client-centered, occupation-focused conceptual model designed to structure and support the discharge planning process in occupational therapy.

The BRIDGE framework was developed through an iterative process of literature review, theoretical grounding, and integration of clinical experience. It synthesizes principles from the Canadian Practice Process Framework, Person–Environment–Occupation frameworks, the Kawa Model, and Bioecological Systems Theory. The framework outlines six discharge planning steps, ranging from goal and timeline setting to follow-up and monitoring, supported by four foundational pillars: patient and family factors, occupational therapy factors, interdisciplinary team factors, and environmental or system influences. Together, these components provide a comprehensive guide for clinical reasoning, collaborative planning, caregiver preparation, and transitional support.

The framework clarifies the role of occupational therapy, enhances interprofessional coordination, and promotes consistent transition planning. Future work should include empirical testing, case-based application, and population-specific adaptations.

Introduction: Glucagon-like peptide-1 receptor agonists (GLP-1 RAs) improve glycemic control, promote weight loss, reduce insulin requirements, and confer cardiometabolic benefits in type 2 diabetes mellitus (T2DM). This audit evaluated glycemic and metabolic outcomes of GLP-1 RAs in T2DM patients at a single-centre diabetes clinic. Methodology: This audit included T2DM patients who initiated GLP1 RAs between January 2022 and March 2025 at Hospital Sultan Abdul Halim. Primary outcomes were changes in hemoglobin A1c (HbA1c), body weight, and body mass index (BMI) at 3 and 12 months. Secondary outcomes included percentage weight loss, changes in systolic blood pressure (SBP), insulin total daily dose (TDD), low-density lipoprotein (LDL) cholesterol, gastrointestinal adverse effects, and treatment discontinuation. Results: Sixteen patients were included; median age was 58.5 years (interquartile range [IQR] 47.5–65), and 56.3% were female. Median diabetes duration was 15 years (IQR 11.5–20.3). Median HbA1c decreased from 9.7% (IQR 8.6–10.4) at baseline to 8.8% (IQR 7.7–9.1) at 3 months and 7.8% (IQR 7.0–8.5) at 12 months. Body weight decreased from 88.1 kg (IQR 79.5–122.1) at baseline to 85.0 kg (IQR 75.9–113.7) at 3 months and 82.0 kg (IQR 74.8–117.3) at 12 months. BMI decreased from 37.8 kg/m² (IQR 31.7–47.1) to 37.3 kg/m² (IQR 30.7–45.5) at 3 months and 36.0 kg/m² (IQR 30.1–45.6) at 12 months. At 12 months, weight loss was 5.8% (IQR 3.0–8.0), with 56.5% achieving >5% weight reduction. In all, 93.8% achieved >1% HbA1c reduction. Mean SBP decreased by 10 ± 20 mmHg, LDL cholesterol 0.29 mmol/L (IQR -0.77 to 0.07), and insulin TDD 8 units/day (IQR -13 to 10). No gastrointestinal adverse effects reported. Three patients (18.8%) discontinued treatment due to excessive weight loss, treatment plateau, and limited drug availability. Conclusion From our single-centre experience, the observed improvements in glycemic and metabolic outcomes support the benefits of GLP-1 RAs in managing T2DM.
Diabetes Mellitus, Type 2 ; Glucagon-Like Peptide-1 Receptor Agonists ; Clinical Audit

Introduction: Diabetic retinopathy (DRP) is the most common microvascular complication of diabetes, affecting approximately 30% of patients with type 2 diabetes and over half of those with type 1 diabetes. It remains a leading cause of preventable blindness among adults worldwide. Early stages are frequently asymptomatic, making regular diabetic eye screening essential to detect sight-threatening changes before irreversible vision loss occurs. In Malaysia, where diabetes prevalence has reached 15.6% among adults (NHMS 2023), the effective implementation of annual retinal screening is crucial. Malaysian National Clinical Practice Guidelines recommend an annual retinal screening among type 2 diabetes mellitus (T2DM) patients. This clinical audit evaluated adherence to DRP screening. Methodology: A retrospective clinical audit was conducted at Pusat Perubatan Angkatan Tentera (PPAT), Kem Sungai Besi, to evaluate compliance with national DR screening standards among adults with T2DM. Thirty eligible patient records were reviewed. Three key indicators were assessed: (1) documentation of visual acuity at diagnosis, (2) annual fundoscopy, and (3) referral for fundus photography within the preceding 12 months. Performance was benchmarked against the 80% standard. Data were analyzed descriptively. Results: The median age group was 55–59 years, with equal gender distribution. Screening adherence was substantially below target: visual acuity assessment at diagnosis, 23.3%; annual fundoscopy, 26.7%; and fundus imaging referral, 36.7%. All screening indicators were below the recommended standard. Conclusion This audit reveals a significant implementation gap between national guidelines and routine practice. Structured workflow integration and documentation reinforcement strategies need to be emphasized. Additional measures include strengthening patient education and reinforcing guideline-based practice through regular CME sessions. However, a re-audit has not yet been conducted at the time of clinical audit reporting. An ongoing evaluation will be essential to determine the effectiveness and sustainability of these interventions in reducing preventable diabetic vision loss at PPAT Sungai Besi.
Humans ; iabetes Mellitus, Type 2 ; Diabetic Retinopathy ; Clinical Audit

Artificial intelligence (AI) technology enhances the function of acupuncture clinical decision support system (CDSS) by promoting the accuracy of its diagnosis, assisting the formulation of personalized therapeutic regimen, and realizing the scientific and precise evaluation of its therapeutic effect. This paper deeply analyzes the unique advantages of AI-based acupuncture CDSS, including the intelligence and high efficiency. Besides, it points out the challenges of data security, the lack of model interpretation and the complexity of interdisciplinary cooperation in the development of acupuncture CDSS. With the continuous development and improvement of AI technology, acupuncture CDSS is expected to play a more important role in the fields of personalized medicine, telemedicine and disease prevention, and to further advance the efficiency and effect of acupuncture treatment, drive the modernization of acupuncture, and enhance its position and influence in the global healthcare system.
Humans ; Acupuncture Therapy ; Artificial Intelligence ; Decision Support Systems, Clinical

The expert consensus on the clinical treatment of herpes zoster with fire needling was developed, and the commonly used fire needling treatment scheme verified by clinical research was selected to form a standardized diagnosis and treatment scheme for acute herpes zoster and postherpetic neuralgia (PHN), so as to answer the core problems in clinical application. The consensus focuses on patients with herpes zoster, and forms recommendations for 9 key clinical issues, covering simple fire needling and TCM comprehensive therapy based on fire needling, including fire needling combined with cupping, fire needling combined with Chinese herb, fire needling combined with cupping and Chinese herb, fire needling combined with filiform needling, fire needling combined with moxibustion, and provides specific recommendations and operational guidelines for various therapies.
Humans ; Herpes Zoster/therapy* ; Acupuncture Therapy/instrumentation* ; Consensus ; Clinical Protocols

BACKGROUND: Over 20 million colonoscopies are performed in China annually. An automatic clinical decision support system (CDSS) with accurate semantic recognition of colonoscopy reports and guideline-based is helpful to relieve the increasing medical burden and standardize the healthcare. In this study, the CDSS was built under a hierarchical-label interpretable classification framework, trained by a state-of-the-art transformer-based model, and validated in a multi-center style. METHODS: We conducted stratified sampling on a previously established dataset containing 302,965 electronic colonoscopy reports with pathology, identified 2041 patients' records representative of overall features, and randomly divided into the training and testing sets (7:3). A total of five main labels and 22 sublabels were applied to annotate each record on a network platform, and the data were trained respectively by three pre-training models on Chinese corpus website, including bidirectional encoder representations from transformers (BERT)-base-Chinese (BC), the BERT-wwm-ext-Chinese (BWEC), and ernie-3.0-base-zh (E3BZ). The performance of trained models was subsequently compared with a randomly initialized model, and the preferred model was selected. Model fine-tuning was applied to further enhance the capacity. The system was validated in five other hospitals with 3177 consecutive colonoscopy cases. RESULTS: The E3BZ pre-trained model exhibited the best performance, with a 90.18% accuracy and a 69.14% Macro-F1 score overall. The model achieved 100% accuracy in identifying cancer cases and 99.16% for normal cases. In external validation, the model exhibited favorable consistency and good performance among five hospitals. CONCLUSIONS The novel CDSS possesses high-level semantic recognition of colonoscopy reports, provides appropriate recommendations, and holds the potential to be a powerful tool for physicians and patients. The hierarchical multi-label strategy and pre-training method should be amendable to manage more medical text in the future.
Humans ; Colonoscopy/methods* ; Deep Learning ; Decision Support Systems, Clinical ; Female ; Male

BACKGROUND: Gluconeogenesis is a critical metabolic pathway for maintaining glucose homeostasis, and its dysregulation can lead to glycometabolic disorders. This study aimed to identify hub biomarkers of these disorders to provide a theoretical foundation for enhancing diagnosis and treatment. METHODS: Gene expression profiles from liver tissues of three well-characterized gluconeogenesis mouse models were analyzed to identify commonly differentially expressed genes (DEGs). Weighted gene co-expression network analysis (WGCNA), machine learning techniques, and diagnostic tests on transcriptome data from publicly available datasets of type 2 diabetes mellitus (T2DM) patients were employed to assess the clinical relevance of these DEGs. Subsequently, we identified hub biomarkers associated with gluconeogenesis-related glycometabolic disorders, investigated potential correlations with immune cell types, and validated expression using quantitative polymerase chain reaction in the mouse models. RESULTS: Only a few common DEGs were observed in gluconeogenesis-related glycometabolic disorders across different contributing factors. However, these DEGs were consistently associated with cytokine regulation and oxidative stress (OS). Enrichment analysis highlighted significant alterations in terms related to cytokines and OS. Importantly, osteomodulin ( OMD ), apolipoprotein A4 ( APOA4 ), and insulin like growth factor binding protein 6 ( IGFBP6 ) were identified with potential clinical significance in T2DM patients. These genes demonstrated robust diagnostic performance in T2DM cohorts and were positively correlated with resting dendritic cells. CONCLUSIONS Gluconeogenesis-related glycometabolic disorders exhibit considerable heterogeneity, yet changes in cytokine regulation and OS are universally present. OMD , APOA4 , and IGFBP6  may serve as hub biomarkers for gluconeogenesis-related glycometabolic disorders.
Machine Learning ; Humans ; Computational Biology/methods* ; Biomarkers/metabolism* ; Diabetes Mellitus, Type 2/genetics* ; Animals ; Mice ; Gluconeogenesis/physiology* ; Gene Expression Profiling ; Transcriptome/genetics* ; Gene Regulatory Networks/genetics* ; Clinical Relevance