Suratthani Cancer Hospital

Abstract Background Thailand has yet to include any pneumococcal vaccines in its National Immunization Program (NIP) as of 2025, contributing to low vaccine uptake and a persistently high burden of pneumococcal diseases. This study aims to update the incidence of pneumococcal diseases in Thai hospitalized adults using time-series analysis of data from sentinel hospitals across the country to generate evidence supporting its inclusion in the NIP. Methods A quasi-experimental, interrupted time-series analysis was conducted using sentinel-based, prospective surveillance of adults aged ≥18 years hospitalized with invasive pneumococcal disease (IPD) or pneumococcal pneumonia (PP) in Thailand from 2010 to 2024. Serotype distribution was assessed through parallel prospective surveillance. The study period was divided into four phases based on PCV13 licensing and the COVID-19 pandemic. Segmented linear regression with autoregressive adjustment was used for time-series analysis. Results A total of 2,069 adults hospitalized with pneumococcal diseases were enrolled, including 61.0% aged >65 years, 15.2% aged 50–65 years, and 23.5% aged 18–50 years. PP accounted for 72.8% of cases and IPD for 27.2%. IPD incidence was stable from 2010 to 2022 (1.0–1.45 per 100,000; p = 0.47) but rose significantly during the recent COVID-19 pandemic (3.1 per 100,000; p < 0.001) (Figure 1), similar trends in PP. The highest incidence was among those aged >65 years (9.2 per 100,000). Overall in-hospital mortality was 23.4%, with higher mortality in IPD cases (p < 0.01). Vaccine serotype coverage for PP was 82% for PCV13/15 and 88–91% for PCV20; for IPD, coverage was 79%, 81%, and 94–95%, respectively. The predominant serotypes were 6A/B and 3 (Figure 2). Conclusion The burden of pneumococcal diseases in Thailand remains substantial, with a notable increase observed during the COVID-19 pandemic. Adults aged >65 years were the most affected group. The majority of disease-causing serotypes remained vaccine-type strains. Given that PCV13 and PCV15 provide coverage for approximately 80% of circulating serotypes, their inclusion in the Thai adult NIP should be prioritized to reduce the disease burden. Disclosures All Authors: No reported disclosures

Background: Postoperative pain following laparoscopic cholecystectomy (LC) is complex and influenced by multiple factors. Dexamethasone has been investigated for its potential to reduce postoperative pain and nausea, but its efficacy remains controversial. Materials and Methods: This prospective, randomized, double-blind, controlled trial included 108 patients undergoing elective LC. Patients were randomly assigned to receive either 5 mg dexamethasone (study group) or 1 ml normal saline (control group) 1–2 hours before surgery. Postoperative pain was assessed using the Visual Analog Scale (VAS) at 0, 2, 6, 12, and 24 hours. Data on analgesic use, postoperative nausea and vomiting (PONV), complications, and length of hospital stay were also collected. Statistical analyses were conducted using SPSS, with a p-value < 0.05 considered significant. Results: No statistically significant differences in VAS scores were observed between the dexamethasone and control groups at any time point. Morphine use was similarly low in both groups (2.0 ± 2.9 mg vs. 2.2 ± 3.6 mg, p > 0.05), with about half of the patients requiring no morphine. PONV was less frequent in the dexamethasone group (5.7% vs. 11.1%), but the difference was insignificant. Length of hospital stay was identical in both groups (2.3 ± 0.5 days). Conclusion: Dexamethasone did not significantly reduce postoperative pain or morphine use in LC patients with low baseline pain scores. Although PONV was less frequent in the dexamethasone group, the difference was not statistically significant. Future studies with larger sample sizes and standardized postoperative care are needed to clarify its role in LC pain management.

Previous randomized controlled trials (RCTs) investigating Botulinum toxin A (BoNT-A) for treatment of hemifacial spasm (HFS) have primarily focused on symptom relief and quality-of-life improvement. However, head-to-head comparisons of different BoNT-A formulations, particularly in terms of onset, duration of action, and efficacy, remain limited. We conducted a 12-week prospective, randomized controlled trial comparing the efficacy and safety of 33.33 units of Neubotulinum toxin A (Neu-BoNT-A) with 100 units of Abobotulinum toxin A (Abo-BoNT-A) in the treatment of HFS. A total of 87 patients were enrolled between September and December 2024. Neu-BoNT-A and Abo-BoNT-A exhibited similar onset and duration of action [5.0 ± 0.9 vs. 6.2 ± 0.7 days, respectively (p = 0.33)]. After 12 weeks of treatment, Neu-BoNT-A demonstrated superior efficacy in reducing the daily duration of HFS (2.00 ± 0.06 vs. 1.42 ± 0.10 h/day, p < 0.001) and improving sleep duration (1.37 ± 0.01 vs. 1.06 ± 0.01 h/day, p < 0.001). However, Abo-BoNT-A was associated with significantly lower absolute daily disability time compared to Neu-BoNT-A (11.4 vs. 1.2 min/day, p < 0.001). No serious adverse events were observed. Both Neu-BoNT-A and Abo-BoNT-A were safe and effective in treating HFS. However, Neu-BoNT-A was more effective in HFS with minimal symptoms without disability and Abo-BoNT-A more effective in HFS with greater duration of disability.

MicroRNAs (miRNAs), derived from extracellular vesicles (EVs) are circulating intercellular communicators which influence pathogenesis and could be used as potential diagnostic markers. In this study, plasma-derived EVs from Plasmodium knowlesi-infected patients (n = 13) and healthy individuals (n = 10) were isolated using size exclusion chromatography and ultracentrifugation. The presence of EVs was confirmed by transmission electron microscopy and Western immunoblotting, and quantified by nanoparticle tracking analysis. The EVs isolated from patients exhibited a larger size, accompanied by an elevated concentration of EVs. The relative expression levels of 8 human miRNAs were quantified using reverse transcriptase quantitative polymerase chain reaction. Compared to uninfected groups, hsa-miR-223-5p (P-value = 0.0002) and hsa-miR-486-5p (P-value = 0.025) were upregulated in P. knowlesi-infected patients. Bioinformatic analysis revealed that these miRNAs are predicted to target both human host and parasite genes, and they were found to be enriched in various malaria-related pathways. The areas under the receiver operating characteristic curve of hsa-miR-223-5p and hsa-miR-486-5p were 0.9154 and 0.8231, respectively, suggesting the potential of EV-miRNAs as diagnostic markers. Results revealed that EV-miRNAs may play a significant role in the progression of P. knowlesi infection. Further investigations should explore their potential impact on gene expression regulation as diagnostic biomarkers or targets for therapeutic interventions.

Acute retinal necrosis (ARN) is a profound infection of the retina, marked by acute panuveitis, retinal periarteritis, and widespread necrotizing retinitis. The etiology of ARN involves human herpesviruses, such as herpes simplex virus (HSV) and varicella-zoster virus (VZV), which can lead to severe visual impairment or even blindness. A diagnosis of ARN is based on clinical characteristics and disease progression according to the standard diagnostic criteria established by the American Uveitis Society (AUS) in 1994. The polymerase chain reaction(PCR) of aqueous specimens can enable identification of the type of virus. Early initiation of antiviral medication is essential for treatment efficacy to stop lesion progression, accelerate the healing process, and prevent contralateral eye involvement. Ocular complications of ARN include atrophic retina, multiple retinal breaks, rhegmatogenous retinal detachment (RRD), tractional retinal detachment (TRD), optic atrophy, macular edema, epiretinal membrane (ERM), and retinal and optic disc neovascularization. This review summarizes the clinical features, diagnostic criteria, and recently recommended ARN management.

BackgroundGrit refers to a combination of perseverance and passion, which is essential for long-term success. Grit is associated with higher education attainment and a lower likelihood of burnout. Understanding how grit evolves during internal medicine residency training is important for providing better support to residents. The primary objective of the current study was to evaluate potential changes in the level of grit throughout the training program and investigate the association between grit and stress levels, quality of life (QoL), and satisfaction of learning scores.MethodsWe conducted a prospective study involving internal medicine residents enrolled in training programs from July 2022 to July 2023, except for the second-third-year residents of dermatology and neurology programs and the third-year residents of haematology and oncology programs, which are not part of the same training regimen. Data collection was conducted using questionnaires at the beginning of the training year and every three months until the end. Collected data included age, gender, habitat, working experience, financial burden, marital status, rotations, grit scores, QoL, stress score, and satisfaction of learning score during each trimester. Changes in grit over the year were examined using repeated measures analysis of variance adjusted by training program, financial status, working experience, habitat, marital status, and age. We performed multivariable linear regression models to explore associations between grit and the following domains: QoL, ST-5, and SoLs.ResultsOf 122 internal medicine residents in all three years of training, one resident dropped out during training, and another declined to participate. A total of 120 residents were included. Grit did not significantly change over time. Subgroup analysis of the first-year resident group revealed that grit significantly decreased (P = 0.049). Multivariable analysis revealed that grit was positively associated with QoL (β = 0.01, P < 0.001) and satisfaction of learning score (β = 0.07, P < 0.001) but inversely associated with stress score (β = − 0.04, P < 0.001).ConclusionsOf all residents, grit did not change over a year. However, only the first-year residents reported a decrease in grit during a training year. Throughout first-year residents’ internal medicine residency training, grit was positively associated with QoL and satisfaction of learning score but negatively associated with stress level. These findings suggest the need for targeted interventions to support first-year residents and enhance their resilience throughout training.

RUOK was implemented to aid the screening protocol at rural Thai hospitals, addressing a shortage of radiologists. Various public Chest X-ray (CXR) datasets focus on radiological abnormalities rather than diseases, limiting their suitability for training disease screening models. To address this limitation, we collaborated with expert radiologists to reclassify the labels of public datasets into eight classes representing prevalent diseases in Thailand: No finding, Suspected active tuberculosis, Suspected lung malignancy, Abnormal heart, great vessels, and mediastinum, Intrathoracic abnormal findings, Pneumonia, COVID-19, and Extrathoracic abnormal findings. This innovative adaptation of public dataset labels enhances the optimization of the data-efficient image transformers model for practical common diseases screening protocols. The Area Under the Receiver Operating Characteristics evaluated on test set yielded the results of 93.06%, 89.21%, 68.66%, 90.46%, 66.88%, 73.45%, 75.13%, and 80.63%, respectively. This highlights the model's potential in advancing disease classification and improving healthcare outcomes, particularly in regions with a shortage of radiological expertise.

BackgroundOral cancer is a deadly disease and a major cause of morbidity and mortality worldwide. The purpose of this study was to develop a fuzzy deep learning (FDL)-based model to estimate the survival time based on clinicopathologic data of oral cancer.MethodsElectronic medical records of 581 oral squamous cell carcinoma (OSCC) patients, treated with surgery with or without radiochemotherapy, were collected retrospectively from the Oral and Maxillofacial Surgery Clinic and the Regional Cancer Center from 2011 to 2019. The deep learning (DL) model was trained to classify survival time classes based on clinicopathologic data. Fuzzy logic was integrated into the DL model and trained to create FDL-based models to estimate the survival time classes.ResultsThe performance of the models was evaluated on a test dataset. The performance of the DL and FDL models for estimation of survival time achieved an accuracy of 0.74 and 0.97 and an area under the receiver operating characteristic (AUC) curve of 0.84 to 1.00 and 1.00, respectively.ConclusionsThe integration of fuzzy logic into DL models could improve the accuracy to estimate survival time based on clinicopathologic data of oral cancer.