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

BACKGROUND AND OBJECTIVE

The Philippines has significant potential as a clinical trial hub but faces a shortage of skilled clinical research professionals (CRPs). In 2022, a cross-sectional study assessed the self-assessed competencies of CRPs in four countries (Thailand, Vietnam, Congo, Philippines) using the Joint Task Force for Clinical Trial Competency (JTF) framework. This paper presents findings on the self-assessed competency and training needs of Filipino CRPs.

METHODS

We conducted a cross-sectional online survey among Filipino clinical research professionals from March to April 2022. We asked for their self-assessed competency, relevance to their roles, and training needs in the competency domains according to the JTF framework. We also asked for the skills in community engagement and research grant application of the investigators. Results were summarized and analyzed according to their primary roles.

RESULTS

One hundred seventy-five (175) Filipino CRPs participated in the survey. They described themselves as “skilled” across all competency domains in conducting clinical research but did not rate themselves at an advanced level. They reported the lowest confidence in their skills related to study management, investigational product development and regulation, and data management. They exhibited greater confidence in competencies such as ethical considerations, professionalism, and communication. Notably, surveyed investigators had the lowest ratings in research design.

CONCLUSION

This study provides a comprehensive assessment of the self-perceived competencies of a sample of Filipino CRPs using the JTF Clinical Research Competency Framework. It highlights key areas for capacity building, particularly in operational and regulatory competencies. However, due to the non-probability sampling and reliance on self-assessment, findings should be interpreted with caution.

Human ; Research Personnel ; Professional Competence ; Self-assessment ; Needs Assessment ; Philippines

BACKGROUND

Early-stage endometrial cancer often presents with favorable survival rates, but high-risk factors, including TP53 mutations and high-grade serous pathology, can lead to recurrence and poor prognosis. The standard primary treatment for endometrial cancer is surgical staging, and lymph node metastases significantly impact adjuvant therapy decisions. The subgroup of p53-abnormal (p53abn) indicates the worst prognosis and potential benefits from adjuvant chemotherapy. Molecular classification, while recommended, faces practical challenges due to resource constraints.

OBJECTIVES

The study aimed to assess the incidence of p53 abnormal expression in clinical stage 1 endometrial cancer cases that underwent surgery at a government tertiary hospital, and assess its relationship with clinicopathologic factors and pelvic and paraaortic lymph node metastasis (LNM).

METHODS

A cross-sectional retrospective analysis was conducted on clinical early-stage endometrial cancer cases that underwent surgical primary treatment between January 2018 and December 2022. Patient records were reviewed to gather demographics, surgical information, and pathological evaluations. Preoperative clinical staging was determined through imaging, and surgical staging involved comprehensive lymphadenectomy. Immunohistochemistry studies for p53 were carried out on formalin-fixed paraffin-embedded tissue samples.

RESULTS

A total of 233 endometrial cancer cases were included. The mean age at diagnosis was 53.7 years. Common comorbidities included hypertension (47.2%) and dyslipidemia (20.6%). Most cases were endometrioid histology (82.8%) and low-grade tumors (85.8%). Tumor grade (p=0.010), myometrial invasion (p<0.001) and lymphovascular space invasion (p<0.001) significantly correlated with lymph node metastasis. However, tumor size and p53abn were not significantly associated with lymph node metastasis. p53abn overexpression was significantly associated with non-endometrioid histology at 33% and Grade 3 tumors at 23%. Preoperative grading demonstrated moderate reliability (0.51) with postoperative grading, with an agreement of 65.4%.

CONCLUSION

Tumor grade, myometrial invasion, and LVSI were all significantly associated with lymph node involvement. While p53 immunohistochemical stains show promise in predicting metastasis and has been associated with tumor aggressiveness, this should still be correlated with clinicopathological parameters to carry out a more accurate risk stratification of early-stage patients.

Therapeutics ; Survival Rate ; Risk Factors ; Recurrence ; Prognosis ; Pathology ; Endometrial Neoplasms ; Immunohistochemistry ; Tumor Suppressor Protein P53 ; Lymph Node Excision ; Risk Assessment

Abstract Background: Important determinants of dialysis adequacy are blood flow rate (BFR) and dialysis time. This study aimed to evaluate the impact of BFR and duration of dialysis session on nutritional status and quality of life (QoL) in hemodialysis (HD) patients. Methods: Real-world evidence studies (RWE) of 3 HD units that differ in BFR and/or dialysis time. Group I, HD 5 hours and BFR 200-250 mL/minute; group II, HD 4 hours and BFR 270-320 mL/minute, and group III, HD 4 hours and BFR 200-250 mL/minute. All HD units use the same dialysate flow and dialysis frequency. The 3-point Subjective Global Assessment (SGA) scale is used to assess nutritional status, while QOL is assessed using the SF-36. Results: There were 291 chronic HD patients with an average age of 51 (12.3) years, 50.5% were male. The proportion of SGA classes between groups did not differ significantly. Group I was associated with significantly higher PF and RP domain scores of PC and VT domain scores of MC compared to Group III. On the other hand, Group II was associated with significantly lower VT and MH domain scores of MC compared to Group I, while the other domains were not significantly different. In general, Group III had the lowest SF-36 scores compared to the other 2 groups. Conclusion: Duration of HD was not associated with nutritional status. Compared with 4-hour HD but with a faster BFR, 5-hour HD was associated with higher Mental Component QOL scores, but not Physical Component scores.
subjective global assessment ; SF-36 questionnaire ; blood flow rate ; dialysis time

Introduction: Metabolic dysfunction–associated steatotic liver disease (MASLD) is common among patients with type 2 diabetes (T2D) and increases the risk of cirrhosis, yet fibrosis often remains clinically silent until hepatic decompensation occurs. Current diabetes guidelines recommend noninvasive fibrosis risk stratification, such as the fibrosis-4 index (FIB-4), during routine diabetes care, but real-world adoption remains unclear. This study aimed to evaluate the implementation of FIB-4 as a risk stratification tool in patients with T2D. Methodology: This was a retrospective study of consecutive patients with T2D who were seen in the Diabetes Clinic of University of Malaya Medical Centre in 2023. Patients were identified as having a higher risk of future cirrhosis based on elevated FIB-4 ≥1.3. Results: The data for 1,009 patients were analyzed, median age 62 (52–71) years, 40.7% male. Elevated FIB-4 was seen in 28.8% (291/1,009). Only 12.0% (35/291) with elevated FIB-4 were referred for further hepatology evaluation, whereas 3.3% (24/718) with low FIB-4 were referred. Among the patients with elevated FIB-4, those referred were more likely known to have hepatic steatosis, had higher alanine aminotransferase, aspartate aminotransferase, gammaglutamyl transferase, and lower low-density lipoprotein cholesterol and platelet count. Over a median follow-up of 1.71 (0.99–1.95) years, totaling 1,440 person-years, two liverrelated events (0.2%) occurred (one each in the elevated and low FIB-4 group, respectively). Sixteen patients (4.0%) experienced cardiovascular events, including one patient (0.6%) in the elevated FIB-4 group and 15 (2.9%) in the low FIB-4 group. Conclusion Despite automated FIB-4 reporting, this risk stratification tool was underutilized in T2D, resulting in missed opportunities for early identification and management of more severe liver disease. Integration of FIB-4 into diabetes care workflows, alongside structured referral pathways and clinician education, may improve early detection and reduce long-term hepatic complications in T2D.
Diabetes Mellitus, Type 2 ; Risk Assessment ; Liver Diseases ; Referral and Consultation

Introduction: The 2021 IDF-DAR risk calculator had been previously evaluated in multiple studies and subsequently widely accepted and applied in clinical practice as a practical standardized tool for patient risk stratification. Recently updated, the 2026 IDF-DAR Risk calculator enables a more individualized, evidence-related evaluation of patientrelated and disease-related risk factors, incorporating modern diabetes technologies, including continuous glucose monitoring (CGM), automated insulin delivery (AID) systems, and advanced insulin formulations to enhance risk stratification. This tool allows medical professionals to tailor Ramadan practices based on overall factors toward promoting safe fasting. Methodology: This prospective multicentre observational study recruited adults with Type 1 and Type 2 diabetes attending public hospitals nationwide. People with diabetes (PwD) intending to perform Ramadan fasting were invited to participate and assessed using the 2026 IDF-DAR Risk Calculator in the 6-week pre-Ramadan period between 30th January and 19th March 2026. Results: A total of 458 PwD were evaluated and stratified into low (15.7%), moderate (41%), and high risk (43.3%) categories. Most participants had Type 2 diabetes (83.6%), with 60.3% having a disease duration exceeding 10 years and 43% exhibiting poor glycemic control (hemoglobin A1c >9%). Insulin therapy was used by 76.4% of participants, including two individuals with Type 1 diabetes using AID systems. Most participants reported no recent hypoglycemia (76.4%), 81.0% performed glucose monitoring, and 3.3% used CGM. Severe comorbidities were uncommon, with 1.1% having unstable macrovascular disease and 4.4% advanced chronic kidney disease (estimated glomerular filtration rate <30). Notably, 72.2% received structured Ramadan education. Conclusion Majority of PwD attending tertiary diabetes clinics were in the moderate- to high-risk category and intended to fast despite medical advice against fasting in some cases. Although most participants were on insulin therapy, hypoglycemia was low in the pre-Ramadan period. Integration of modern technologies, advanced insulin therapies, and structured education may support safer fasting practices.
Risk Assessment ; Diabetes Mellitus ; Hospitals ; Fasting

Introduction: Obesity is a heterogeneous metabolic disease in which individuals with similar body weight may exhibit markedly different physiological risk profiles. Conventional monitoring using weight alone may fail to capture underlying metabolic and cellular changes during lifestyle intervention. Integrating body composition and biochemical markers may improve risk stratification in clinical practice. Methodology: A prospective observational analysis was conducted among participants enrolled in a structured lifestyle programme. Baseline and follow-up assessments included biochemical markers (fasting glucose, renal function, lipid profile, and liver enzymes) alongside body composition parameters derived from bioelectrical impedance analysis, including percent body fat, visceral fat area, skeletal muscle index (SMI), and phase angle (PhA). Changes over time and associations between metabolic and body composition variables were analyzed. Results: Metabolic responses varied substantially despite similar anthropometric profiles. Renal function improved significantly, with increased estimated glomerular filtration rate (eGFR) observed over time (p = 0.01), and was inversely associated with fasting glucose (r = −0.41, p <0.01). Lipid abnormalities persisted, although reductions in lowdensity lipoprotein cholesterol were noted (p = 0.04). Total cholesterol remained elevated and correlated positively with fasting glucose (r = 0.36, p = 0.02). Improvements in aspartate aminotransferase were observed (p = 0.03), while other liver markers remained stable. Notably, body composition parameters, including PhA and SMI, demonstrated variability independent of weight change, reflecting heterogeneous physiological adaptation. Conclusion Metabolic and physiological responses to lifestyle intervention are heterogeneous and not fully captured by changes in body weight alone. The integration of bioimpedance-derived parameters with biochemical markers provides a more comprehensive approach to metabolic risk stratification and may support more personalized clinical management in obesity care.
Biomarkers ; Risk Assessment ; Body Composition

Objective:To investigate the clinical characteristics of residual dizziness（RD） after repositioning in patients with benign paroxysmal positional vertigo（BPPV）, identify its potential risk factors, and develop a predictive risk model. Methods:A total of 137 patients diagnosed with BPPV at the First Affiliated Hospital of Xi'an Jiaotong University between January 2023 and June 2023 were enrolled. Based on the presence or absence of subjective discomfort within 3 months after successful repositioning, patients were divided into the non-RD group（NRD, n=93） and the RD group（n=44）. Differences in demographic characteristics, comorbidities, and disease-related features were compared between groups. Multivariate logistic regression analysis was used to identify independent risk factors for RD, and a nomogram was constructed based on these factors. The predictive performance of the model was assessed using the area under the curve（AUC）. Results:The RD group showed significantly higher values in body mass index, prevalence of diabetes and motion sickness history, dizziness duration before repositioning, history of repositioning at external hospitals, number of treatments, and recurrence（all P<0.001）. Multivariate logistic regression revealed that diabetes（adjusted OR=8.73, P=0.039）, motion sickness history（adjusted OR=23.08, P<0.001）, dizziness duration ≥30 days before repositioning（adjusted OR=15.16, P<0.001）, and recurrence（adjusted OR=15.72, P=0.001） were independent risk factors for RD. The nomogram model based on these variables demonstrated good predictive ability, with an AUC of 0.804（95%CI 0.684-0.924）. Conclusion:Diabetes, motion sickness history, dizziness duration ≥30 days, and recurrence are independent risk factors for RD after repositioning in patients with BPPV. The nomogram model based on these variables shows good predictive performance, with recurrence having the highest predictive value. This model can aid in early identification of high-risk patients and guide individualized intervention strategies.
Humans ; Nomograms ; Benign Paroxysmal Positional Vertigo/therapy* ; Dizziness/etiology* ; Risk Factors ; Risk Assessment ; Multivariate Analysis ; Male ; Female ; Logistic Models ; Middle Aged ; Patient Positioning ; Adult

COMPERA 2.0 risk stratification has been demonstrated to be useful in patients with precapillary pulmonary hypertension (PH). However, its suitability for patients at risk for post-capillary PH or PH associated with left heart disease (PH-LHD) is unclear. To investigate the use of COMPERA 2.0 in patients with severe aortic stenosis (SAS) undergoing transcatheter aortic valve replacement (TAVR), who are at risk for post-capillary PH, a total of 327 eligible SAS patients undergoing TAVR at our institution between September 2015 and November 2020 were included in the study. Patients were classified into four strata before and after TAVR using the COMPERA 2.0 risk score. The primary endpoint was all-cause mortality. Survival analysis was performed using Kaplan-Meier curves, log-rank test, and Cox proportional hazards regression model. The study cohort had a median (interquartile range) age of 76 (70‒80) years and a pulmonary arterial systolic pressure of 33 (27‒43) mmHg (1 mmHg=0.133 kPa) before TAVR. The overall mortality was 11.9% during 26 (15‒47) months of follow-up. Before TAVR, cumulative mortality was higher with an increase in the risk stratum level (log-rank, both P<0.001); each increase in the risk stratum level resulted in an increased risk of death (hazard ratio (HR) 2.53, 95% confidential interval (CI) 1.54‒4.18, P<0.001), which was independent of age, sex, estimated glomerular filtration rate (eGFR), hemoglobin, albumin, and valve type (HR 1.76, 95% CI 1.01‒3.07, P=0.047). Similar results were observed at 30 d after TAVR. COMPERA 2.0 can serve as a useful tool for risk stratification in patients with SAS undergoing TAVR, indicating its potential application in the management of PH-LHD. Further validation is needed in patients with confirmed post-capillary PH by right heart catheterization.
Humans ; Aortic Valve Stenosis/complications* ; Aged ; Hypertension, Pulmonary/mortality* ; Male ; Female ; Transcatheter Aortic Valve Replacement ; Aged, 80 and over ; Risk Assessment/methods* ; Proportional Hazards Models ; Kaplan-Meier Estimate ; Retrospective Studies

OBJECTIVES: We propose a multi-feature fusion model based on manually extracted features and deep learning features from endoscopic images for grading rebleeding risk of peptic ulcers. METHODS: Based on the endoscopic appearance of peptic ulcers, color features were extracted to distinguish active bleeding (Forrest I) from non-bleeding ulcers (Forrest II and III). The edge and texture features were used to describe the morphology and appearance of the ulcers in different grades. By integrating deep features extracted from a deep learning network with manually extracted visual features, a multi-feature representation of endoscopic images was created to predict the risk of rebleeding of peptic ulcers. RESULTS: In a dataset consisting of 3573 images from 708 patients with Forrest classification, the proposed multi-feature fusion model achieved an accuracy of 74.94% in the 6-level rebleeding risk classification task, outperforming the experienced physicians who had a classification accuracy of 59.9% (P<0.05). The F1 scores of the model for identifying Forrest Ib, IIa, and III ulcers were 90.16%, 75.44%, and 77.13%, respectively, demonstrating particularly good performance of the model for Forrest Ib ulcers. Compared with the first model for peptic ulcer rebleeding classification, the proposed model had improved F1 scores by 5.8%. In the simplified 3-level risk (high-risk, low-risk, and non-endoscopic treatment) classification task, the model achieved F1 scores of 93.74%, 81.30%, and 73.59%, respectively. CONCLUSIONS The proposed multi-feature fusion model integrating deep features from CNNs with manually extracted visual features effectively improves the accuracy of rebleeding risk classification for peptic ulcers, thus providing an efficient diagnostic tool for clinical assessment of rebleeding risks of peptic ulcers.
Humans ; Deep Learning ; Peptic Ulcer ; Risk Assessment ; Peptic Ulcer Hemorrhage ; Recurrence