Chulalongkorn Medical Journal

Identifying Pyle’s metaphyseal dysplasia: An incidental finding of skeletal pathology on a dental checkup

2026-07-13T12:48:46+07:00

Pyle’s disease, also known as familial metaphyseal dysplasia, is a rare autosomal recessive genetic disorder that primarily affects the skeletal system, particularly in children and adolescents. Furthermore, it is characterized by distinctive radiographic features, including Erlenmeyer flask deformity and metaphyseal widening. Pyle’s disease often goes underdiagnosed because of its mild clinical manifestations. This case report details a 15- year-old female patient presenting with retained milk teeth and unerupted permanent teeth, alongside notable skeletal abnormalities, including genu valgum and kyphosis. Clinical and radiographic evaluations revealed considerable dental anomalies, including multiple impacted permanent teeth and mild dysmorphic facial features. Although genetic testing was not performed in this case, a diagnosis of Pyle’s disease was made based on the clinical presentation and radiographic findings. This case highlights the importance of recognizing dental manifestations as potential indicators of underlying skeletal dysplasias or other systemic conditions. Prompt diagnosis and early intervention could enhance the quality of life and treatment outcomes in such cases.

Incidental leftward displacement of the appendix due to redundant sigmoid colon: A case report of anatomical variation

2026-06-17T09:07:20+07:00

A left-sided appendix is an uncommon clinical finding, often attributed to congenital anomalies, such as situs inversus or intestinal malrotation. However, it can also arise from anatomical displacement by other organs, such as redundant colonic loops. While rare, such variations may complicate the clinical and radiological diagnosis of abdominal pain and result in potentially serious consequences if not recognized. This case report highlights a left-sided appendix due to a redundant sigmoid colon incidentally discovered during the evaluation of right lower quadrant pain. A 22-year-old woman presented to the emergency department with right flank pain, which later localized to the right lower quadrant (RLQ). There was localized tenderness in the RLQ, with no systemic symptoms. A working diagnosis of acute appendicitis was considered. A noncontrast abdominal computed tomography scan revealed a 0.4 cm right lower pole nephrolithiasis without signs of appendiceal inflammation. Unexpectedly, the appendix was visualized at the mid-left lower quadrant due to displacement by a type C redundant sigmoid colon. The patient was referred to urology for further management. This report highlights the importance of recognizing anatomical variations. They may substantially alter the expected location of intra-abdominal organs and result in diagnostic confusion. Although the patient in this report did not have appendicitis, the displacement of the appendix into the left lower quadrant could have been misleading had inflammation occurred. Radiologists and clinicians should both be cognizant of atypical disease presentations, and accurate diagnosis and treatment are crucial for an optimal outcome, especially in emergency settings.

Opioid-free total intravenous anesthesia for valvular cardiac replacement surgery

2026-07-22T09:25:22+07:00

A 44-year-old woman with rheumatic heart disease with severe mitral stenosis, moderate–severe mitral regurgitation, and severe tricuspid regurgitation underwent mitral valve replacement and tricuspid repair under cardiopulmonary bypass using opioid-free total intravenous anesthesia (OF-TIVA) with propofol, ketamine, lidocaine, and dexmedetomidine, combined with a transversus thoracic plane (TTP) block. The patient’s intraoperative hemodynamics remained stable, and the patient was extubated six hours postoperatively with minimal pain and no complications. OF-TIVA with TTP block provided effective analgesia, hemodynamic stability, and early recovery, thus highlighting its potential as a safe alternative to opioid-based anesthesia in cardiac valve surgery.

Pre-excited atrial fibrillation in a woman with minimal pre-excitation: A case report

2026-07-10T10:30:41+07:00

A 46-year-old Thai woman presented with palpitations. A 12-lead electrocardiogram (ECG) showed rapid preexcited atrial fibrillation (AF). The ECG following electrical cardioversion demonstrated minimal pre-excitation with a short PR interval and small apparent delta waves only in leads II, III, V4, and V5. An electrophysiologic study was performed and revealed sinus rhythm with a short H-V interval compatible with pre-excitation. A programmed electrical stimulation revealed orthodromic atrioventricular re-entrant tachycardia via the left lateral accessory pathway. Catheter ablation was successfully performed using a retrograde aortic approach to the left lateral accessory pathway. There was no recurrence of Wolff–Parkinson–White ECG pattern, supraventricular tachycardia, or AF during the 12-month follow-up visit. This is a rare case of minimal preexcitation presenting with pre-excited AF as the first presentation. This case report reflects that minimal preexcitation does not indicate a low risk of ventricular fibrillation and sudden cardiac arrest.

Machine learning-based gene signature detection highlights CXCL12 as a key marker for acute myeloid leukemia prediction

2026-07-14T08:58:03+07:00

Background: Acute myeloid leukemia (AML) is a severe hematologic malignancy that is marked by the uncontrolled proliferation and impaired differentiation of myeloid cells, which disrupts normal hematopoiesis and results in poor clinical outcomes. Conventional diagnostic approaches often lack the precision needed to accurately classify AML subtypes; therefore, integrating advanced computational methods is required to improve diagnostic and therapeutic strategies.

Objectives: This study aimed to apply machine learning (ML) techniques to transcriptomic data to identify a concise, informative gene signature that can distinguish AML cases from normal samples. In addition, the study sought to evaluate the performance of predictive models in supporting AML prediction and facilitating biomarker discovery.

Methods: Gene expression data were obtained from the TARGET-AML project via the Genomic Data Commons portal. Feature selection was performed using SelectKBest with chi-square scoring to identify the top 10 AML-associated genes. To address class imbalance, SMOTE was employed. Several ML models, including Random Forest, XGBoost, LightGBM, and a Stacking ensemble, were trained and optimized via hyperparameter tuning to classify AML vs. normal samples.

Results: The selected gene panel included CXCL12, SELENBP1, SLC4A1, IFIT1B, ALAS2, CAMP, OLFM4, DEFA3, CRISP3, and HBG1, which are functionally associated with immune response, inflammation, and hematopoietic processes. All models demonstrated robust classification performance: Random Forest (88.6%), XGBoost (88.8%), LightGBM (89.4%), and Stacking (89.4%). SMOTE effectively enhanced the model performance, particularly for underrepresented classes, thereby improving precision and recall.

Conclusion: This study identified a small, yet informative gene set that accurately differentiates AML from normal samples, with LightGBM revealing the highest predictive accuracy. The involvement of immune and inflammatory genes aligns with AML’s biological foundations. These findings suggest the clinical potential of ML-based tools for AML diagnostics. Future validation on independent cohorts and the integration of multi-omic data could further improve the model’s robustness and facilitate broader applications in precision medicine for hematologic malignancies.

Supervised learning algorithms for subject- and textlevel classification of depression-related context among Thai-language Facebook users

2026-07-21T13:08:50+07:00

Background: Depression is an increasing concern worldwide that requires urgent attention, particularly in Thailand. Without timely intervention, it can lead to serious consequences, such as health complications, reduced social participation, and even suicide. Consequently, research has increasingly focused on developing algorithms to identify and classify social media data into depression severity.

Objectives: This study aimed to examine label mismatches between self-assessment forms and social media behaviors and to evaluate the feasibility of using experts’ opinions to classify Thai Facebook text into depression categories.

Methods: The methodology involved data collection through surveys and Facebook scraping, followed by data preprocessing, feature engineering, and model training and validation. The models employed included the support vector machine, logistic regression, and decision tree, applied at the subject and text levels. Labels were derived from the Thai Depression Inventory (TDI) and experts’ evaluations.

Results: Only 30 out of 60 participants actively used Facebook during the study period, with substantial variation in posting behavior. Subject-level classification using TDI labels yielded better, more balanced performance metrics than classifications based on experts’ opinions at the subject and text levels. Part-ofspeech tagging showed slight correlations with depression severity, whereas emotions did not.

Conclusion: Subject-level classification using self-assessment labels performed better than expert-derived labels and text-level classification when compared to a dummy baseline model. This suggests a slight correlation between the self-assessment forms and social media behaviors. In contrast, the poor agreement between labeling approaches suggests that text data alone may be insufficient as a reliable clinical indicator of depression.

Ameliorative effect of the ethanolic extract of Nardostachys jatamansi against high-fat diet-induced dyslipidemia in Wistar albino rats

2026-07-09T14:26:08+07:00

Background: Dyslipidemia is a key contributor to metabolic disorders such as oxidative stress and is a major risk factor for cardiovascular diseases. Herbal interventions are increasingly preferred due to fewer side effects. Nardostachys jatamansi has demonstrated antioxidant and lipid-lowering properties, but its effects on high-fat diet (HFD)-induced dyslipidemia remain insufficiently studied.

Objective: The present study aimed to evaluate the antioxidant and hypolipidemic effects of the ethanol extract of N. jatamansi in an HFD-induced obesity model in male Wistar albino rats.

Methods: Thirty-six male Wistar albino rats were randomly divided into 6 groups, each comprising 6 animals. Group I received a normal diet for 9 weeks, whereas Group II was fed an HFD for the same period. Groups III– VI were also fed an HFD throughout the investigation period. From week 5, Group III received rosuvastatin (10 mg/kg), and Groups IV–VI were treated with N. jatamansi extract at 100, 200, and 300 mg/kg, respectively, for 4 weeks. All treatments were administered orally. At the end of the study, the animals were fasted overnight, anesthetized, and blood was collected for lipid and hematological analyses. In addition, the organs were excised for histological evaluation.

Results: N. jatamansi (100, 200, and 300 mg/kg) reversed HFD-induced increases in body weight, fat pad size, organ weight, total cholesterol, triglycerides, low-density lipoprotein, and very low-density lipoprotein levels while restoring high-density lipoprotein levels in a dose-dependent manner. Moreover, elevated white blood cells, lymphocyte counts, and serum urea, creatinine, and uric acid levels were normalized. Histological improvements in the liver suggest antioxidant and bioactive effects of N. jatamansi.

Conclusion: Our results revealed that the herbal drug N. jatamansi effectively ameliorates HFD-induced dyslipidemia through its potent antioxidant activity, thereby reducing oxidative stress and restoring lipid homeostasis.

Prevalence of stunting and environmental determinants among children under 5 years of age: A systematic review and meta-analysis

2026-07-09T14:08:17+07:00

Background: Stunting remains a major global public health issue, particularly in low- and middle-income countries. It is driven by inadequate nutrition and environmental factors, such as limited access to clean water, sanitation, and hygiene practices.

Objectives: This study aimed to estimate the prevalence of stunting among children under 5 years of age and to assess its correlation with environmental determinants.

Methods: This systematic review and meta-analysis followed PRISMA guidelines. Four international e-databases—Scopus, PubMed, ScienceDirect, and Springer—and reference lists were searched. In total, 20 studies involving 103,313 children met the inclusion criteria. A random-effects model was employed to estimate combined prevalence and associations; the I² statistic was used to assess heterogeneity.

Results: Stunting prevalence was 32.9% (95% CI: 28.6–37.8; I2 = 99.5%). Children from households with inadequate sources of drinking water were at a 1.2-times higher risk of stunting (adjusted odds ratio (AOR) = 1.2; 95% CI: 1.0–1.4; I2 = 78.5%). Inadequate toilet facilities increased the risk by 1.3 times (AOR = 1.3; 95% CI: 1.0–1.6; I2 = 86.5%), poor sanitation by 1.2 times (AOR = 1.2; 95% CI: 1.0–1.4; I2 = 75.0%), and poor handwashing practices by 2.3 times (AOR = 2.3; 95% CI: 1.0–5.5; I2 = 68.1%).

Conclusion: Stunting prevalence was significantly associated with environmental determinants. Integrating interventions for such factors with nutrition programs is essential to controlling stunting, particularly in rural areas. Policy efforts should prioritize improving access to safe drinking water, providing adequate sanitation facilities, conducting hygiene promotion programs, and community-based nutritional interventions to support child growth and development.