Anh Hieu Bui

Background: Defensible standard setting is a cornerstone of competency-based medical education. However, many institutions still use arbitrary pass marks such as 50% without empirical justification. This study aimed to apply the Nedelsky method—a defensible, criterion-referenced standard setting approach—to determine the minimal passing score for the final examination of the Obstetrics and Gynecology (OBGYN) course at Pham Ngoc Thach University of Medicine, Vietnam, and to compare it with the conventional Cohen method. Method: A four-step Nedelsky procedure was implemented to establish a defensible passing standard for a 50-item multiple-choice examination administered to fourth-year medical students on December 3, 2022. Three trained assessors independently estimated the number of distractors that a minimally competent candidate (MCC) could eliminate for each question, from which the Minimal Passing Level (MPL) was calculated. Subsequently, a cross-sectional analysis was conducted on 808 students to determine the pass and fail rates using both Nedelsky and Cohen methods. Statistical comparison was performed using the McNemar’s test for paired categorical data. Results: The mean MPL derived from three assessors was 65%, corresponding to 33 correct answers as the passing score. According to this standard, 183 of 808 students (23%) passed the examination, while 625 (77%) failed. In contrast, using the Cohen method (cut-off = 55%), 416 students (51%) failed. McNemar’s test showed a statistically significant difference between the two methods (χ ² = 207.0, p < 0.001), with moderate agreement (Cohen’s κ = 0.47). Conclusion: The relative Cohen method underestimated the minimal competency threshold, resulting in a substantial “failure to fail” phenomenon. The Nedelsky method provided a more defensible, transparent, and evidence-based approach for setting pass standards in resource-limited medical education contexts. Adoption of defensible standard setting methods such as Nedelsky can enhance fairness, validity, and accountability in competency-based assessments.

Background: Febrile seizures (FS) are a common neurological emergency in early childhood and frequently raise concerns among caregivers regarding the likelihood of recurrence. Accurate risk stratification is important for counseling and follow‐up, particularly in resource‐limited settings. We aimed to estimate the incidence and identify prognostic factors for FS recurrence, and to propose a simple approach for clinical risk stratification. Methods: In this prospective cohort study conducted at the Children's Hospital 2 (Ho Chi Minh City, Vietnam), we enrolled 631 children aged 1 month to 6 years with a first FS and followed them for recurrence over a median follow‐up of 1.9 years. A simple count‐based approach to risk stratification was derived from independent predictors identified by multivariable Cox regression. Results: During follow‐up, 174 children (27.6%) experienced recurrence, corresponding to an incidence of 173 per 1000 person‐years. The predictors included: age < 21 months at first FS (adjusted HR: 2.02; 95% CI: 1.45, 2.81), family history of FS (adjusted HR: 1.83; 95% CI: 1.34, 2.49), and multiple seizures within the same febrile illness (adjusted HR: 1.60; 95% CI: 1.17, 2.21). Two‐year recurrence risk ranged from 13.8% (0 predictors) to 63.1% (3 predictors). Model discrimination was modest, with a bootstrap‐corrected AUC of 0.67 (95% CI: 0.62–0.72). Conclusions: Our findings provide contemporary data on the incidence and risk factors of FS recurrence and support a simple, clinically applicable approach to risk stratification. This information may assist clinicians in counseling families and planning follow‐up, particularly in resource‐limited settings.

Objective: Febrile seizures (FS) are common and usually self‐limited, yet a subset of children develop epilepsy. Early risk stratification remains challenging, particularly in resource‐limited settings with limited access to long‐term neurologic follow‐up. We aimed to estimate the incidence and identify the most robust predictors of epilepsy following FS in children. Methods: In this prospective cohort study at Children's Hospital 2 (Ho Chi Minh City, Vietnam), 631 children aged 1 month to 6 years with first FS were enrolled (March 2023–March 2024) and followed through July 2025. Children with any history of seizures prior to the index FS were excluded. Epilepsy was defined per the International League Against Epilepsy (ILAE) 2014 criteria. Predictor selection used clinical reasoning and Bayesian Model Averaging (BMA), followed by multivariable Cox regression. Discrimination was evaluated using Harrell's C‐index and time‐dependent AUC; internal validation was performed with bootstrap resampling. Results: Over a median follow‐up of 2.0 years, 35 children (5.5%) developed epilepsy, corresponding to an incidence of 29 per 1000 person‐years. After BMA, four independent predictors were retained: neurodevelopmental delay (HR = 8.78), family history of epilepsy (HR = 2.66), focal seizures (HR = 3.23), and each additional FS recurrence (HR = 1.50). The predictor set showed strong discrimination (C‐index: 0.87; AUC at 24 months: 0.89 with 95% CI: 0.82, 0.95). Significance: This parsimonious set of clinical predictors may support early counseling and targeted follow‐up of children with FS, especially where pediatric neurology resources are limited. Model development and validation are ongoing. Plain Language Summary: We followed 631 children after their first febrile seizure to see who might later develop epilepsy. About 5.5% of children developed epilepsy within 2 years. Children with developmental delay, focal seizures, a family history of epilepsy, or repeated FS were at higher risk. Using these four simple factors may help doctors give families clearer advice and closer follow‐up, especially where access to pediatric neurologists is limited.