Hatyai Hospital

Autochthonous leishmaniasis has become increasingly recognized in Thailand, with Leishmania (Mundinia) martiniquensis identified as the predominant species, particularly among immunocompromised individuals. Infected immunosuppressed patients often present with complex clinical features, which can delay diagnosis and complicate treatment. Given the limited clinical data available and emerging reports of resistant infections, improved awareness, prompt diagnosis, and optimized management strategies are urgently needed to address this underrecognized pathogen in Thailand. We report two patients with advanced HIV disease (AHD) from Songkhla Province, Southern Thailand, who developed chronic diffuse cutaneous leishmaniasis characterized by widespread non-ulcerative papulonodular lesions that progressed to visceral involvement. Histopathological examination of the skin nodules showed prominent dermal fibrosis with infiltration by macrophages heavily parasitized with kinetoplast-containing amastigotes, consistent with cutaneous leishmaniasis. Molecular analyses identified L. martiniquensis as the causative agent in both cases. The parasite strains (WHO codes: MHOM/TH/2022/CULE7.1 and MHOM/TH/2022/CULE7.2) were successfully isolated from the bone marrow and cutaneous biopsy of the second patient before treatment. Furthermore, the parasite was isolated again from a cutaneous biopsy of the same patient after relapse, designated MHOM/TH/2023/CULE8. Due to the high costs of liposomal amphotericin B and the unavailability of miltefosine in Thailand, contrary to the WHO guideline recommending these as first-line therapy, patients received intravenous amphotericin B deoxycholate (AmB-D) combined with oral itraconazole. Despite repeated treatment with AmB-D and itraconazole, both patients relapsed, and Case 1 died. This raises concerns about drug resistance. These cases illustrate complex cutaneous manifestations and therapeutic challenges of relapsing diffuse cutaneous and visceral leishmaniasis caused by L. martiniquensis in patients with AHD from Southern Thailand. The persistence and relapse despite AmB-D therapy raise concerns about emerging drug-resistant strains and underscore the need for enhanced surveillance, parasite isolation, and optimized treatment strategies for this neglected pathogen. Moreover, this report expands the understanding of the cutaneous spectrum of L. martiniquensis in patients with AHD, emphasizing the importance of including leishmaniasis in the differential diagnosis of complex skin diseases among immunosuppressed individuals, particularly in endemic areas.

Dengue severity prediction models are usually developed using hospitalized patient data, but triage and hospital admission are mainly evaluated in outpatient settings. This study developed models using clinical and laboratory data from patients in outpatient settings during the febrile phase. Data from two cohort studies in Vietnam and Thailand were used to develop and validate six models: logistic regression with warning signs, Lasso-selected logistic regression, random forest, extreme gradient boosted classification, support vector machine, and artificial neural network. Models predicted dengue shock syndrome (DSS) as the primary endpoint and moderate plasma leakage and/or DSS as the secondary endpoint. We assessed model performance, discrimination, and calibration, using sensitivity, specificity, accuracy, Brier score, AUROC, CITL, calibration slope, calibration plots, and decision curve analysis. The optimal model was the Lasso-selected logistic regression for predicting DSS and the combined endpoint of moderate plasma leakage and/or DSS (Brier score: 0.044 [95% CI 0.043, 0.044] and 0.104 [95% CI 0.104, 0.105]; AUROC: 0.789 [95% CI 0.787, 0.791] and 0.741 [95% CI 0.740, 0.742]). We identified hematocrit, platelet count, lymphocyte count, and aspartate aminotransferase as predictors for DSS, and abdominal pain or tenderness, vomiting, mucosal bleeding, white blood cell count, lymphocyte count, platelet count, aspartate aminotransferase, and serum albumin as predictors for the secondary endpoint. Logistic regression and machine learning models using clinical and laboratory data during the febrile phase can support early prediction of severe disease in outpatient settings. Integrating risk prediction models into a decision support system could improve triage and optimize healthcare and resource allocation in endemic and resource-limited areas.

Differentiation between leishmaniasis and histoplasmosis remains a significant diagnostic conundrum, especially in immunosuppressed patients, due to overlapping clinical presentations and histopathological features. We report a case of a 53-year-old Thai man with advanced HIV disease from Southern Thailand who presented in 2020 with a chronic palate ulcer and hard palate perforation, initially diagnosed as histoplasmosis and treated with itraconazole for a year. Three years later (2023), the patient developed systemic symptoms, and biopsies confirmed visceral leishmaniasis. Given the increasing number of autochthonous leishmaniasis cases, the patient's original diagnosis from 2020 was reexamined. Retrospective analysis of the original palate biopsy revealed amastigotes with kinetoplasts, whereas PAS and GMS staining were negative for fungi, excluding histoplasmosis. Molecular diagnostics, which combined PCR for Leishmania spp. and Histoplasma capsulatum with Sanger sequencing, confirmed Leishmania martiniquensis and ruled out Histoplasma capsulatum, leading to a corrected diagnosis of mucocutaneous leishmaniasis. This report documents the second case of mucocutaneous leishmaniasis caused by L. martiniquensis in Thailand, with primary mucocutaneous presentation that progressed to visceral involvement. This highlights diagnostic challenges due to morphological similarities between Leishmania amastigotes and Histoplasma capsulatum yeasts, emphasizing the need for integrative histopathological (including specific staining techniques) and molecular diagnostics for accurate diagnosis and effective treatment.

Background The optimal timing of elective cesarean section (ECS) remains controversial, requiring a balance between neonatal respiratory risk and maternal surgical safety. This study compared maternal morbidity and neonatal respiratory outcomes between early-term (< 39 weeks) and full-term (≥ 39 weeks) ECS. Methods A retrospective cohort study was conducted at a tertiary care hospital from January 2022 to December 2024. Women undergoing scheduled ECS were categorized as early-term (< 39 weeks; n = 1,326) or full-term (≥ 39 weeks; n = 473). Maternal characteristics, operative outcomes, and neonatal respiratory morbidity were analyzed using Chi-square and Wilcoxon rank-sum test. Multivariable logistic regression identified factors independently associated with composite neonatal respiratory morbidity. Results Of 13,745 deliveries, 5,188 (37.7%) were cesarean sections, including 1,799 eligible ECS cases (1,326 early-term and 473 full-term). The main ECS indication was the previous cesarean section (73.9%). Early-term ECS was associated with lower neonatal birth weight and a higher proportion of twin pregnancies. No significant differences were observed in operative outcomes, Apgar scores, or crude neonatal respiratory morbidity. After adjustment for maternal and neonatal factors, early-term ECS was not independently associated with composite respiratory morbidity (adjusted OR 0.77, 95% CI 0.56–1.07). Maternal obesity (adjusted OR 1.40, 95% CI 1.04–1.87), male sex (adjusted OR 1.94, 95% CI 1.44–2.61), and low birth weight < 2,500 g (adjusted OR 3.28, 95% CI 1.85–5.80) were independently associated with increased odds of respiratory morbidity. Conclusions Early-term ECS was not independently associated with neonatal respiratory morbidity. Neonatal characteristics and maternal obesity were stronger predictors than gestational age alone, suggesting individualized, risk-based decision-making for ECS timing.

Major disasters, particularly large-scale flooding, frequently paralyze urban infrastructure and isolate critical healthcare facilities, necessitating rapid, complex decision-making for hospital evacuation. This review examines the role of aeromedical evacuation as a logistical lifeline during internal hospital disasters, utilizing the November 2025 Hat Yai mega-flood in Southern Thailand as a case study. This study employs a retrospective case study approach combined with a narrative review. Data were derived from the academic literature, official operational reports, and relevant information from press releases between January 2016 and May 2026, as appropriate. Analysis followed a thematic framework aligned with the Hospital Incident Command System, focusing on strategic planning, operational decision schemes, and system elements. The November 2025 Hat Yai flood—the most intense precipitation event in 300 years—resulted in the inundation of critical medical facilities and compromised vital infrastructure. The study highlights the successful, phased evacuation of critically ill patients from Hatyai Hospital using governmental aviation assets, demonstrating the efficacy of the Thai Sky Doctor Service. However, the response also revealed significant systemic gaps, including delayed evacuation orders due to municipal communication failures and an over-reliance on premium aviation assets. Aeromedical transport serves as a critical force multiplier in disaster medicine, providing an essential vertical lifeline when ground infrastructure fails.