Chulabhorn Hospital

To evaluate the cost-utility and budget impact of biosimilar trastuzumab plus paclitaxel versus paclitaxel monotherapy for HER2-positive metastatic breast cancer in Thailand and to explore policy implications for access and affordability. A Markov model was developed from a societal perspective over a lifetime horizon, simulating 3 health states: stable disease, progressive disease, and death, in 3-week cycles. Two trastuzumab-based strategies were evaluated: (1) fixed-duration treatment for 1 year and (2) continuous treatment until disease progression. All costs were updated to 2024 values using local data. Clinical effectiveness was measured in quality-adjusted life-years (QALYs). A probabilistic sensitivity analysis and a 5-year budget impact analysis were performed. Compared with paclitaxel monotherapy, trastuzumab plus paclitaxel increased life-years by 0.31 and QALYs by 0.27. The incremental cost-effectiveness ratios were Thai Baht (THB) 195 541/QALY for the 1-year regimen and THB 231 119/QALY for the continuous regimen, both exceeding Thailand's cost-effectiveness threshold of THB 160 000/QALY. The 5-year budget impact was estimated at THB 166.3 million and THB 199.3 million, respectively. Price reductions would be required for trastuzumab to achieve cost-effectiveness under the Thai threshold. Although biosimilar trastuzumab has improved affordability, it remains not cost-effective at current prices. However, the relatively modest budget impact supports the feasibility of expanding access through targeted price negotiation and policy interventions. Threshold analysis indicated that price reductions to approximately THB 3700 per vial (1-year regimen) and THB 2950 per vial (until-progression regimen) would be required for trastuzumab to achieve cost-effectiveness under the Thai threshold.

This study evaluated Apis mellifera brood fat extracts as a sustainable alternative to beeswax for anti-inflammatory topical delivery, including their formulation into nanostructured lipid carriers (NLCs). Brood fat was extracted using acetone, ethyl acetate (EA), and hexane, and the resulting extracts were characterized for fatty acid composition and physicochemical properties. Safety was assessed using the hen's egg chorioallantoic membrane test and cytotoxicity testing in RAW 264.7 macrophages. Anti-inflammatory activity was assessed by inhibition of lipopolysaccharide-induced interleukin-6 (IL-6) and tumor necrosis factor-alpha (TNF-α) production. The most suitable extract was formulated into NLCs using sugar squalane as liquid lipid, and the effects of lipid ratio and preparation method were investigated. The results showed that the ethyl acetate extract had the highest yield. Compared with beeswax, all fat extracts exhibited a favorable oleic acid-rich fatty acid profile with comparable crystallinity and thermal behavior, while showing significantly enhanced anti-inflammatory activity (p < 0.05). All extracts and their NLCs were non-irritating and non-cytotoxic. Ethyl acetate extract-based NLCs exhibited favorable particle sizes (72.1 ± 0.3 nm) and narrow polydispersity (0.14 ± 0.00), with high-pressure homogenization producing smaller particles compared to probe sonication without affecting IL-6 or TNF-α inhibition. Therefore, A. mellifera brood fat extract is a sustainable anti-inflammatory lipid source with strong potential as an alternative to beeswax in topical nano-formulations.

Background: Community-dwelling older adults with type 2 diabetes mellitus (T2DM) and mild cognitive impairment (MCI) often report poor sleep, which may aggravate metabolic control and functional decline; yet sleep problems and their biopsychosocial drivers are underrecognized in primary care. Objectives: To describe sleep quality, examine biopsychosocial correlates, and identify significant predictors of sleep quality in older adults with T2DM and MCI. Methods: A cross-sectional study was conducted in 6 primary care units in Suphan Buri province, Thailand. Sleep quality was measured using the Pittsburgh Sleep Quality Index (PSQI). Biological factors included age, sex, body mass index, glycated hemoglobin (HbA1c), diabetes duration, hypertension, comorbidities, and probable obstructive sleep apnea (OSA). Psychological factors were depressive symptoms (TGDS-15), diabetes-related distress (DDS-17), and diabetes self-efficacy. Social/environmental factors included perceived social support and environmental disturbance. Behavioral factors were diabetes self-care behaviors (SDSCA). Pearson’s correlations and hierarchical multiple regression were performed. Results: Poor sleep was common (82.3%; PSQI &gt; 5). Sleep quality correlated with depressive symptoms (r = 0.46), diabetes distress (r = 0.39), self-efficacy (r = -0.41), environmental disturbance (r = 0.34), and self-care (r = -0.32) (all P &lt; .001). In the final model, HbA1c (β = 0.11), probable OSA (β = 0.14), depressive symptoms (β = 0.28), diabetes distress (β = 0.17), self-efficacy (β = -0.22), environmental disturbance (β = 0.19), and self-care (β = -0.12) independently predicted PSQI, explaining 47% of variance (adjusted R² = 0.45). Conclusions: Sleep quality in older adults with T2DM and MCI reflects a biopsychosocial profile dominated by psychological, environmental, and behavioral factors, with selected biological risks. Primary care nurses should integrate sleep screening with assessment of mood, diabetes distress, self-efficacy, OSA risk, and home sleep conditions to guide multicomponent interventions.

<title>Abstract</title> Background The complexity of osteoporosis risk stratification often leads to substantial knowledge-to-practice gaps and diagnostic variability. This study evaluates the efficacy of a deterministic rule-based clinical decision support system (CDSS) in operationalizing the 2021 Thai Osteoporosis Foundation (TOPF) guidelines to standardize clinical decision-making. Methods A within-subject randomized experimental study was conducted with 65 physicians (22 juniors, 43 seniors) who evaluated 20 clinical vignettes. Participants were randomized to assess cases under manual and CDSS-supported conditions. Primary outcomes included decision accuracy compared to an expert consensus gold standard, decision time, and system usability, analyzed using paired statistical tests. Results The CDSS significantly improved overall risk classification accuracy from 70.3% to 84.8% ( <italic>p</italic> &lt; 0.001) and treatment selection accuracy from 78.5% to 85.4% ( <italic>p</italic> = 0.003). Crucially, the intervention demonstrated a robust "equalizing effect": junior physicians achieved a 22.3% accuracy gain ( <italic>p</italic> &lt; 0.001), effectively eliminating the baseline expertise gap compared to senior physicians. Decision efficiency was maintained, with no statistically significant increase in processing time ( <italic>p</italic> = 0.322). The system usability score was 69.1, indicating good potential for workflow integration. Conclusion Implementing a transparent, rule-based logic engine successfully mitigates cognitive biases and neutralizes experience-based performance variability. This study confirms that operationalizing clinical guidelines through digital analytics is a scalable strategy to bridge the expertise gap and ensure guideline-concordant management in primary care.

Klebsiella pneumoniae is a major cause of bloodstream infections worldwide and is increasingly associated with multidrug resistance, particularly to carbapenems and colistin, which severely limits treatment options. This study investigated the genomic epidemiology of K. pneumoniae bloodstream infection (BSI) isolates collected in Thailand between 2020 and 2024. A total of 227 K. pneumoniae BSI isolates collected nationwide through the National Antimicrobial Resistance Surveillance Center, Thailand were subjected to antimicrobial susceptibility testing and whole-genome sequencing, followed by multilocus sequence typing, AMR gene detection, plasmid profiling, virulence scoring, phylogenetic analysis, and genotype-phenotype correlation. Among the isolates, 199 were resistant to carbapenems, seven were resistant only to colistin, and 21 were not resistant to either carbapenems or colistin. Three high-risk sequence types (ST) (ST16, ST147, and ST231) predominated in most regions, whereas the south showed greater clonal diversity. ST16 isolates commonly co-harbored blaNDM-1 and blaOXA-232 and had high rates of carbapenem and colistin co-resistance. ST231 isolates exhibited carbapenem resistance along with rmtF1-mediated aminoglycoside resistance, whereas ST147 isolates demonstrated high genomic plasticity and resistance diversity. Rare ST isolates carrying mcr genes and hypervirulent ST23 and ST268 lineages were also identified, with ST268 resistant to all carbapenems tested. These findings highlight the dissemination of high-risk clones in Thailand and underscore the need for real-time genomic surveillance and molecular diagnostics to inform infection control and national AMR strategies.

Elevated systolic blood pressure (SBP) increases myocardial oxygen demand, whereas low diastolic blood pressure (DBP) can impair coronary perfusion. The prognostic impact of this high-SBP/low-DBP (HSLD) profile in patients with ST-elevation myocardial infarction (STEMI) remains unknown. We analyzed 696 consecutive patients with STEMI undergoing primary percutaneous coronary intervention (PCI) from a prospective 11-center registry in Japan. Patients were categorized based on pre-procedural SBP (≥ 120 mmHg) and DBP (< 70 mmHg) into four groups: high-SBP/low-DBP (HSLD) high-SBP/high-DBP (HSHD), low-SBP/high-DBP (LSHD), and low-SBP/low-DBP (LSLD). The primary endpoint was a 1-year composite of cardiovascular death, non-fatal myocardial infarction, or stroke. Median follow-up was 369 days. The 1-year cumulative incidence of the primary endpoint was 7 (9.5%) in the HSLD group, 19 (4.2%) in the HSHD group, 2 (2.8%) in the LSHD group, and 5 (6.0%) in the LSLD group (log-rank p = 0.007). In multivariable Cox regression, the HSLD was independently associated with the primary endpoint compared to the HSHD group (hazard ratio 3.20, 95% CI 1.04-9.87; p = 0.043). The prognostic value of HSLD was consistent across major subgroups. A pre-procedural blood pressure pattern of SBP ≥ 120 mmHg combined with DBP < 70 mmHg independently predicts a higher risk of adverse cardiovascular events at 1 year in patients with STEMI. This simple measurement at admission identifies a previously unrecognized high-risk phenotype and presents a valuable opportunity for early risk stratification.

From August to November 2023, a disease outbreak occurred in a research colony of 33 mixed-sex, five-month-old central bearded dragons obtained from a private breeder in the USA. Clinical presentation consisted primarily of dehydration, lethargy, inappetence, weight loss, neck extension, sporadic open mouth breathing indicating dyspnea, and sudden death. A total of six deaths occurred during this period. Pathological investigation followed by molecular diagnostics and whole-genome sequencing revealed Mycoplasma pogonae as the cause of disease. Pneumonia (5/6) was diagnosed from necropsy. Types of pneumonia included histiocytic (1/5), combined histiocytic and lymphocytic (2/5), histiocytic and granulocytic (1/5), and heterophilic pneumonia (1/5). Our results confirmed that M. pogonae infection is associated with sudden mortality in a colony of captive central bearded dragons in the USA and that M. pogonae has a potential pathogenic role as a primary infectious agent.

Hippocampal atrophy and hypometabolism are key neuroimaging biomarkers for early diagnosis of Alzheimer's Disease (AD). Artificial intelligence methods for quantitative automated volumetric analysis of brain magnetic resonance imaging (MRI) are enabling objective assessment of brain atrophy in a fast and accessible way. Thus, the objective of this work is to compare hippocampal volume derived from MRI with the hypometabolism observed in 18F-FDG positron emission tomography (PET) in the context of early diagnosis of AD. Twenty-two patients with AD (11 women, [51-84yo], mean age±SD: 69.91±9.51) and twenty-six normal individuals (16 women, age range [51-80yo], mean age±SD: 66.23±6.87) were enrolled in this study. Structural T1-weighted and 18F-FDG scans were acquired on a 3T MR-PET system (Biograph mMR, Siemens Healthineers, Forchheim, Germany). A deep-learning-based research application (MorphoBox) was used to derive brain volume normalized by the total intracranial volume from MRI (Figure 1), and p-mod software was applied to calculate standardized uptake value ratio (SUVR) from PET imaging. Pearson correlations between normalized brain volumes and SUVR, as well as visual interpretations from diagnostic radiologists, were assessed. Receiver operating characteristics (ROC) analyses were conducted to investigate the discrimination ability of hippocampus relative volume on one hand and SUVR on the other hand. A significant difference in SUVR normalized by cerebellar SUV was observed between the AD and control groups in the following brain regions: hippocampus (p<0.001), frontal lobe (p<0.001), parietal lobe (p<0.001), temporal lobe (p<0.001), occipital lobe (p=0.001), cingulate (p<0.001), caudate (p=0.002) and thalamus (p<0.001). There was a strong correlation between SUVR and normalized volume, particularly in hippocampus, frontal, parietal, and temporal regions (ρ=0.60, 0.64, 0.67, and 0.73, respectively). The ROC curve for hippocampal relative volume yielded an AUC of 0.79 indicating good discrimination abilities (Figure 2). Our study demonstrates a strong correlation between hippocampal volumetry from MRI and FDG PET brain imaging. The MorphoBox research application under study could serve as a valuable screening tool in centers with restricted access to PET imaging. Additionally, our findings indicate that hippocampal volumetry exhibits superior discrimination power in the sample under study. We recommend further evaluation with a larger sample size in future research.

BackgroundNutritional status constitutes a significant concern among individuals with cognitive impairment. A strong correlation exists between malnutrition and cognitive function. Nutritional status can be assessed through various methods, including questionnaire, biological indices, and biochemical markers. Individuals experiencing cognitive decline also exhibit swallowing and eating disturbance, which can adversely impact their nutritional status.MethodSixty‐two patients diagnosed with cognitive impairment were recruited from the memory clinic. Cognitive impairment severity was categorized based on the Clinical Dementia Rating scale Sum of Boxes (CDR‐SB). Participants underwent a comprehensive assessment including: Mini‐Nutritional Assessment (MNA) questionnaire, Body Mass Index (BMI) and Waist‐Hip Ratio (WHR) measurements, biochemical markers such as total protein, albumin, and hemoglobin levels, and a comprehensive questionnaire to evaluate swallowing and eating disturbances. This questionnaire consisted of five domains: swallowing disturbance, appetite change, food preference, eating habits, and other eating behaviors. The relationship between cognitive impairment severity and nutritional status was analyzed using logistic regression and chi‐square.ResultParticipants were classified into three groups: mild cognitive impairment (MCI) (n = 30), mild dementia (n = 22), and moderate dementia (n = 10). No significant differences were observed between the groups in terms of BMI, WHR, total protein, albumin, and hemoglobin levels. Based on the Mini‐Nutritional Assessment (MNA) score, the odds of malnutrition were found to increase with increasing severity of cognitive impairment. Moderate dementia patients exhibited a significantly higher risk of malnutrition compared to MCI patients (adjusted Odds Ratio [aOR] = 8.9; 95% Confidence Interval [CI] = 0.5 ‐ 3.9; p = 0.01). Furthermore, patients with dementia demonstrated a higher proportion of disturbances in eating habits: MCI (36.7%), mild dementia (50.0%), moderate dementia (90.0%); p = 0.01. Moderate dementia patients exhibited significantly higher odds of experiencing disturbances in eating habits compared to MCI patients (aOR = 15.5; 95% CI = 1.7 ‐ 139.7; p = 0.01).ConclusionThe severity of cognitive impairment emerged as a significant predictor of both malnutrition risk and the occurrence of eating disturbances.