Objective: To present the indications associated with the increase in cesarean section rate at Thammasat University Hospital during the past three years.
Material And Method: This was a cross-sectional study. Pregnant women who underwent cesarean section between January 2003 and December 2005 at Thammasat University Hospital were recruited for the present study. Cases of fetal anomaly or intrauterine fetal death were excluded. Demographic and obstetric data including indications of cesarean section and pregnancy outcomes were collected and analyzed
Results: Among the 1328, 1402, and 1522 cases of cesarean section (27.31, 27.94, and 29.26%) in 2003, 2004 and 2005 respectively, the major indication was previous cesarean section (29%). Cephalopelvic disproportion (CPD), and elective cesarean section were second, and third most common indication (24.64%, 11.23%) respectively.
Conclusion: The increasing cesarean section rate was due to rising of elective cesarean section or patient's request. Cesarean section without obstetric indication should be reconsidered to lower the cesarean section rate.
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Eur J Dent
December 2024
Division of Restorative Dentistry, Faculty of Dentistry, Thammasat University, Pathum Thani, Thailand.
Objectives: This article compared the accuracy, reproducibility, and gap of crowns resulting from variations in print angulation of three-dimensional (3D)-printed VarseoSmile Crown (VS) and milled resin-ceramic hybrid materials (Cerasmart 270, CS, and Enamic, E).
Materials And Methods: A total of 60 specimens, consisting of VS printed at four different angulations (30, 45, 60, and 90 degrees), along with CS and E were investigated. External and internal accuracy and reproducibility were measured with the 3D deviation analysis.
Macromol Biosci
January 2025
Materials Chemistry Research Center, Department of Chemistry and Center of Excellence for Innovation in Chemistry, Faculty of Science, Khon Kaen University, Khon Kaen, 40002, Thailand.
To address the rising prevalence of bacterial infections and the need for innovative therapeutic solutions, this study has developed a novel antibacterial hydrogel composite composed of Aloe vera, gelatin, sodium alginate, and Sterculia monosperma-silver nanoparticles (SM-AgNPs) loaded curcumin-nanoliposomes (NLPs). The aloe vera/gelatin/sodium alginate hydrogels (AGS) are prepared using different weight ratios of Aloe vera, gelatin, and sodium alginate, aiming to optimize mechanical properties and biocompatibility for biomedical applications. The incorporation of SM-AgNPs and curcumin-loaded NLPs enhanced the hydrogels' antibacterial properties.
View Article and Find Full Text PDFImaging Sci Dent
December 2024
Department of Conservative Dentistry, Faculty of Dentistry, Universitas Sumatera Utara, Medan, Indonesia.
Purpose: This review aimed to explore the scientific literature concerning the methodologies and applications of artificial intelligence (AI) in the field of endodontics. The findings may equip dentists with the necessary technical knowledge to understand the opportunities presented by AI.
Materials And Methods: Articles published between 1992 and 2023 were retrieved through an electronic search of Medline via the PubMed, Scopus, and Google Scholar databases.
NPJ Sci Food
December 2024
International Joint Research Center on Food Security (IJC-FOODSEC), Khlong Luang, Pathum Thani, 12120, Thailand.
Co-occurrence of multiple mycotoxins is a growing global food safety concern due to their harmful effects on humans and animals. This study developed an eco-friendly sample preparation method and an innovative multiplex microarray-based lateral flow immunoassay, using a novel portable reader for on-site simultaneous determination of five regulated mycotoxins-aflatoxin B, T-2 toxin, zearalenone, deoxynivalenol, and fumonisin B in rice. The eco-friendly and ultrafast extraction procedure utilizes a bio-based solvent.
View Article and Find Full Text PDFPLoS One
December 2024
College of Interdisciplinary Studies, Thammasat University, Pathum Thani, Thailand.
This study aimed to evaluate the performance of a deep learning-based segmentation model for predicting outcomes of non-surgical endodontic treatment. Preoperative and 3-year postoperative periapical radiographic images of each tooth from routine root canal treatments performed by endodontists from 2015 to 2021 were obtained retrospectively from Thammasat University hospital. Preoperative radiographic images of 1200 teeth with 3-year follow-up results (440 healed, 400 healing, and 360 disease) were collected.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!