Background: While advanced age is a known risk factor for postoperative complications following hip arthroplasty, its role as an independent predictor versus a surrogate for comorbidity remains unclear, particularly in developing countries. This study aimed to investigate the independent impact of age on postoperative outcomes and explore the mediating role of key comorbidities in a resource-limited setting. Methods: We retrospectively reviewed 769 adult patients undergoing hip arthroplasty at a Vietnamese tertiary hospital (2021–2024), categorized into three groups: younger adults (18–64 years), older adults (65–79 years), and oldest old (≥80 years). The primary outcome was a composite of major postoperative complications. Multivariable logistic regression and structural equation modeling were used to identify independent predictors and assess mediation effects. Results: Among 769 patients, 363 were younger (47.2%), 241 older adults (31.3%), and 165 oldest old (21.5%). Complication rates increased significantly with age (18.7%, 36.9%, and 60.0%, respectively; p<0.001). However, multivariable adjustment showed that age was not an independent predictor. Instead, heart failure (adjusted odds ratio [aOR]=5.49, 95% confidence interval [CI] 2.19–13.74) and preoperative anemia (aOR=1.77, 95% CI 1.21– 2.59) were identified as independent risk factors. Mediation analysis revealed that the effect of age on complications was significantly mediated through preoperative anemia. Conclusion Increased postoperative risk in older adults is driven by comorbidity burden rather than chronological age. Preoperative anemia and heart failure are critical, independent predictors, with anemia acting as a key mediator for the effects of age. Individualized correction of modifiable comorbidities may be more beneficial than using age alone to assess surgical risk.

Background: In the targeted therapy era, the indication for stereotactic radiosurgery (SRS) has ex-panded to include patients with multiple brain metastases (BMs). This study aimed to compare treatment outcomes in epidermal growth factor receptor (EGFR)-mutant non-small cell lung cancer (NSCLC) patients with 1–4 versus 5–10 BMs, all treated with tyrosine kinase inhibitors (TKIs) and upfront Gamma Knife radiosurgery. Methods: We retrospectively reviewed 74 consecutive EGFR-mutant NSCLC patients with 1–10synchronous BMs treated with first-line EGFR-TKIs and upfront Gamma Knife SRS at Vietnam National Cancer Hospital from 2021 to 2024. Patients were divided into 1–4 BMs (n=39) and 5–10 BMs (n=35) groups. Primary endpoints were intracranial progression-free survival (iPFS) and overall survival (OS). Results: Baseline characteristics were balanced between the two groups. Median iPFS wasnot reached in the 1–4 BMs group and 19 months in the 5–10 BMs group (hazard ratio [HR] 1.06, 95% confidence interval [CI] 0.95–1.17; p=0.31). Median OS was not reached in the 1–4 BMs group and was 23 months in the 5–10 BMs group (HR 1.03, 95% CI 0.91–1.16; p=0.41). Multivariate analysis revealed extracranial response (HR 4.30, p<0.01 for iPFS; HR 7.29, p<0.01 for OS) and presence of extracranial metastases (HR 3.20, p=0.01 for iPFS) as the only independent prognostic factors; number of BMs was not prognostic. Radionecrosis occurred in 6.8%, of which 2.7% were symptomatic. Conclusion In EGFR-mutant NSCLC patients receiving TKIs and upfront Gamma Knife radiosur-gery, the survival time in patients with 5–10 BMs was comparable to that with 1–4 BMs. The number of BMs should not be regarded as a contraindication for SRS in this subgroup.

Endovascular thrombectomy for acute large-vessel occlusion in patients with active cancer remains a difficult clinical decision. Multiple cohort studies and meta-analyses indicate that, when standard imaging and clinical criteria are applied, reperfusion success is high and symptomatic intracranial hemorrhage is broadly comparable with non-cancer populations, arguing against categorical exclusion. At the same time, registries show lower 90-day functional independence and higher 90-day mortality in active-cancer cohorts—effects likely driven by malignancy-related systemic factors and pre-existing functional compromise rather than procedural harm. This narrative review synthesizes efficacy and safety signals, highlights decision-grade outcomes that are seldom reported—early neurological change, performance status around 90 days, and whether systemic anticancer therapy is started or resumed. It sets out a clinical–ethical–economic framework to support selection, consent, and aftercare, including a pragmatic pathway for under-resourced settings based on non-contrast computed tomography (CT) or single-phase CT angiography where advanced perfusion imaging or magnetic resonance imaging are unavailable. We outline an Asia–Pacific collaborative program designed to identify subgroups that may benefit from reperfusion and initiation of active cancer care.

Background: Although the criteria for follicular-pattern thyroid tumors are well-established, diagnosing these lesions remains challenging in some cases. In the recent World Health Organization Classification of Endocrine and Neuroendocrine Tumors (5th edition), the invasive encapsulated follicular variant of papillary thyroid carcinoma was reclassified as its own entity. It is crucial to differentiate this variant of papillary thyroid carcinoma from low-risk follicular pattern tumors due to their shared morphological characteristics. Proteomics holds significant promise for detecting and quantifying protein biomarkers. We investigated the potential value of a protein biomarker panel defined by machine learning for identifying the invasive encapsulated follicular variant of papillary thyroid carcinoma, initially using formalin- fixed paraffin-embedded samples. Methods: We developed a supervised machine-learning model and tested its performance using proteomics data from 46 thyroid tissue samples. Results: We applied a random forest classifier utilizing five protein biomarkers (ZEB1, NUP98, C2C2L, NPAP1, and KCNJ3). This classifier achieved areas under the curve (AUCs) of 1.00 and accuracy rates of 1.00 in training samples for distinguishing the invasive encapsulated follicular variant of papillary thyroid carcinoma from non-malignant samples. Additionally, we analyzed the performance of single-protein/gene receiver operating characteristic in differentiating the invasive encapsulated follicular variant of papillary thyroid carcinoma from others within The Cancer Genome Atlas projects, which yielded an AUC >0.5. Conclusions We demonstrated that integration of high-throughput proteomics with machine learning can effectively differentiate the invasive encapsulated follicular variant of papillary thyroid carcinoma from other follicular pattern thyroid tumors.

Background: Although the criteria for follicular-pattern thyroid tumors are well-established, diagnosing these lesions remains challenging in some cases. In the recent World Health Organization Classification of Endocrine and Neuroendocrine Tumors (5th edition), the invasive encapsulated follicular variant of papillary thyroid carcinoma was reclassified as its own entity. It is crucial to differentiate this variant of papillary thyroid carcinoma from low-risk follicular pattern tumors due to their shared morphological characteristics. Proteomics holds significant promise for detecting and quantifying protein biomarkers. We investigated the potential value of a protein biomarker panel defined by machine learning for identifying the invasive encapsulated follicular variant of papillary thyroid carcinoma, initially using formalin- fixed paraffin-embedded samples. Methods: We developed a supervised machine-learning model and tested its performance using proteomics data from 46 thyroid tissue samples. Results: We applied a random forest classifier utilizing five protein biomarkers (ZEB1, NUP98, C2C2L, NPAP1, and KCNJ3). This classifier achieved areas under the curve (AUCs) of 1.00 and accuracy rates of 1.00 in training samples for distinguishing the invasive encapsulated follicular variant of papillary thyroid carcinoma from non-malignant samples. Additionally, we analyzed the performance of single-protein/gene receiver operating characteristic in differentiating the invasive encapsulated follicular variant of papillary thyroid carcinoma from others within The Cancer Genome Atlas projects, which yielded an AUC >0.5. Conclusions We demonstrated that integration of high-throughput proteomics with machine learning can effectively differentiate the invasive encapsulated follicular variant of papillary thyroid carcinoma from other follicular pattern thyroid tumors.

Background: Although the criteria for follicular-pattern thyroid tumors are well-established, diagnosing these lesions remains challenging in some cases. In the recent World Health Organization Classification of Endocrine and Neuroendocrine Tumors (5th edition), the invasive encapsulated follicular variant of papillary thyroid carcinoma was reclassified as its own entity. It is crucial to differentiate this variant of papillary thyroid carcinoma from low-risk follicular pattern tumors due to their shared morphological characteristics. Proteomics holds significant promise for detecting and quantifying protein biomarkers. We investigated the potential value of a protein biomarker panel defined by machine learning for identifying the invasive encapsulated follicular variant of papillary thyroid carcinoma, initially using formalin- fixed paraffin-embedded samples. Methods: We developed a supervised machine-learning model and tested its performance using proteomics data from 46 thyroid tissue samples. Results: We applied a random forest classifier utilizing five protein biomarkers (ZEB1, NUP98, C2C2L, NPAP1, and KCNJ3). This classifier achieved areas under the curve (AUCs) of 1.00 and accuracy rates of 1.00 in training samples for distinguishing the invasive encapsulated follicular variant of papillary thyroid carcinoma from non-malignant samples. Additionally, we analyzed the performance of single-protein/gene receiver operating characteristic in differentiating the invasive encapsulated follicular variant of papillary thyroid carcinoma from others within The Cancer Genome Atlas projects, which yielded an AUC >0.5. Conclusions We demonstrated that integration of high-throughput proteomics with machine learning can effectively differentiate the invasive encapsulated follicular variant of papillary thyroid carcinoma from other follicular pattern thyroid tumors.

Background: Anaplastic lymphoma kinase (ALK) mutations have been identified as a prominent cause of some familial and sporadic neuroblastoma (NB). ALK expression in NB and its relationship with clinical and histopathological features remains controversial. This study investigated ALK expression and its potential relations with these features in NB. Methods: Ninety cases of NB at the Department of Pathology, University of Medicine and Pharmacy at Ho Chi Minh City, Viet Nam from 01/01/2018 to 12/31/2021, were immunohistochemically stained with ALK (D5F3) antibody. The ALK expression and its relations with some clinical and histopathological features were investigated. Results: The rate of ALK expression in NB was 91.1%. High ALK expression (over 50% of tumor cells were positive with moderate-strong intensity) accounted for 65.6%, and low ALK expression accounted for 34.4%. All the MYCN-amplified NB patients had ALK immunohistochemistry positivity, most cases had high ALK protein expression. The undifferentiated subtype of NB had a lower ALK-positive rate than the poorly differentiated and differentiated subtype. The percentages of ALK positivity were significantly higher in more differentiated histological types of NB (p = .024). There was no relation between ALK expression and: age group, sex, primary tumor location, tumor stage, MYCN status, clinical risk, Mitotic-Karyorrhectic Index, prognostic group, necrosis, and calcification. Conclusions ALK was highly expressed in NB. ALK expression was not related to several clinical and histopathological features. More studies are needed to elucidate the association between ALK expression and ALK gene status and to investigate disease progression, especially the oncogenesis of ALK-positive NB.

Background: The identification of idiopathic inflammatory myopathies (IIMs) requires a comprehensive analysis involving clinical manifestations and histological findings. This study aims to provide insights into the histopathological and immunohistochemical aspects of IIMs. Methods: This retrospective case series involved 56 patients diagnosed with IIMs at the Department of Pathology, University of Medicine and Pharmacy at Ho Chi Minh City, from 2019 to 2023. The histology and immunohistochemical expression of HLA-ABC, HLA-DR, C5b-9, Mx1/2/3, and p62 were detected. Results: We examined six categories of inflammatory myopathy, including immunemediated necrotizing myopathy (58.9%), dermatomyositis (DM; 23.2%), overlap myositis (8.9%), antisynthetase syndrome (5.4%), inclusion body myositis (IBM; 1.8%), and polymyositis (1.8%). The average age of the patients was 49.7 ± 16.1 years, with a female-to-male ratio of 3:1. Inflammatory cell infiltration in the endomysium was present in 62.5% of cases, perifascicular atrophy was found in 17.8%, and fiber necrosis was observed in 42 cases (75.0%). Rimmed vacuoles were present in 100% of cases in the IBM group. Immunohistochemistry showed the following positivity rates: HLA-ABC (89.2%), HLA-DR (19.6%), C5b-9 (57.1%), and Mx1/2/3 (10.7%). Mx1/2/3 expression was high in DM cases. p62 vacuole deposits were noted in the IBM case. The combination of membrane attack complex and major histocompatibility complex I helped detect IIMs in 96% of cases. Conclusions The diagnosis of IIMs and their subtypes should be based on clinical features and histopathological characteristics. Immunohistochemistry plays a crucial role in the diagnosis and differentiation of these subgroups.

Objectives: The objective of this study was to characterize mental health issues among Vietnamese healthcare workers (HCWs) and to identify related factors. Methods: A cross-sectional study was conducted with 990 HCWs in 2021. Their mental health status was measured using the Depression, Anxiety, and Stress Scale. Results: In total, 49.9%, 52.3%, and 29.8% of respondents were found to have depression, anxiety, and stress, respectively. The multivariable linear regression model revealed that factors associated with increased anxiety scores included depression scores (β, 0.45; 95% confidence interval [CI], 0.39 to 0.51) and stress scores (β, 0.46; 95% CI, 0.41 to 0.52). Factors associated with increased depression scores included being frontline HCWs (β, 0.57; 95% CI, 0.10 to 1.10), stress scores (β, 0.50; 95% CI, 0.45 to 0.56), and anxiety scores (β, 0.41; 95% CI, 0.36 to 0.47), while working experience was associated with reduced depression scores (β, -0.08; 95% CI, -0.16 to -0.01). Factors associated with increased stress scores included working experience (β, 0.08; 95% CI, 0.00 to 0.16), personal protective equipment interference with daily activities (β, 0.55; 95% CI, 0.07 to 1.00), depression scores (β, 0.54; 95% CI, 0.48 to 0.59), and anxiety scores (β, 0.45; 95% CI, 0.39 to 0.50), while age was associated with reduced stress scores (β, -0.12; 95% CI, -0.20 to -0.05). Conclusions Specific interventions are necessary to enhance and promote the mental health of HCWs so they can successfully cope with the circumstances of the pandemic.

Objective: To investigate the cause of a foodborne outbreak that occurred in Dong Nai province, Viet Nam, in 2024, and implement control measures. Methods: An initial investigation was conducted to confirm the outbreak, which was followed by epidemiological and environmental investigations to find the plausible causative food item. Clinical specimens and food samples were tested to identify the pathogen. Results: A total of 547 symptomatic cases were recorded, of whom two were in severe condition requiring extracorporeal membrane oxygenation and ventilation, one of whom died. Among 99 interviewed cases, the mean incubation time was 9 hours (range 2–24 hours), with the main symptoms being fever, abdominal pain, diarrhoea and vomiting. All patients had eaten banh mi from a local bakery. Salmonella spp. were identified in food samples and clinical specimens. The bakery halted production, and the outbreak ended after 1 week. Discussion: All the patients were exposed to only one food in common, which facilitated the investigation process. This outbreak is a reminder to small retailers and take-away shops of the importance of food safety management in preventing similar future outbreaks. All food handlers must comply with food hygiene principles, especially in hot temperatures, which boosts bacterial growth.