Objectives: Clinical situations that make it challenging to differentiate odontogenic cysts from non-odontogenic cysts and benign tumors of the jaw include cases with cystic conditions accompanied by secondary infection, impacted teeth, cortical thinning and expansion, or external root resorption.This study aimed to identify risk factors for complications in patients undergoing cyst enucleation of the jaw, propose a clinical model, and determine the necessary indications for preoperative root canal of adjacent teeth. Materials and Methods: A review of surgical, pathological, and radiological reports, as well as medical records, was conducted. Pathological diagnosis, lesion size, history of preoperative endodontic treatment of the adjacent tooth, operator details, surgical procedures, age, gender, and complications (with severity) were analyzed. Results: This study involved 77 patients (55 men, 22 women) and found 10 complications. Procedure type (cyst enucleation only, apicoectomy and bone graft, or bone graft only) and lesion size were significant risk factors. Preoperative root canal therapy and men gender also tended to positively correlate with complications, while age was not a factor. Conclusion Within the limitations of our study, additional procedures contributed to lower risk of complications with the exception of bone graft.A large cyst size was also associated with a higher risk of complications. It is important to consider the possibility of a second procedure and take thorough precautions to prevent infection when performing bone grafts. Patients should be informed of these risks in advance, scheduled for regular follow-up, and provided additional treatment when necessary.

Background and Objectives: Voice disorders can significantly impact quality of life. This study evaluates the feasibility of using deep learning models to detect voice disorders using an opensource dataset.Materials and Method We utilized the Saarbrücken Voice Database, which contains 1231 voice recordings of various pathologies. Datasets were used for training (n=1036) and validation (n=195). Key vocal parameters, including fundamental frequency (F0), formants (F1, F2), harmonics-to-noise ratio, jitter, and shimmer, were analyzed. A convolutional neural network (CNN) was designed to classify voice recordings into normal, vox senilis, and laryngocele. Performance was assessed using precision, recall, F1-score, and accuracy. Results: The CNN model demonstrated high classification performance, with precision, recall, and F1-scores of 1.00 for normal and 0.99 for vox senilis and laryngocele. Accuracy reached 1.00 after 50 epochs and remained stable through 100 epochs. Time-frequency analysis supported the model’s ability to differentiate between classes. Conclusion This study highlights the potential of deep learning for voice disorder detection, achieving high accuracy and precision. Future research should address dataset diversity and realworld integration for broader clinical adoption.

Objectives: Clinical situations that make it challenging to differentiate odontogenic cysts from non-odontogenic cysts and benign tumors of the jaw include cases with cystic conditions accompanied by secondary infection, impacted teeth, cortical thinning and expansion, or external root resorption.This study aimed to identify risk factors for complications in patients undergoing cyst enucleation of the jaw, propose a clinical model, and determine the necessary indications for preoperative root canal of adjacent teeth. Materials and Methods: A review of surgical, pathological, and radiological reports, as well as medical records, was conducted. Pathological diagnosis, lesion size, history of preoperative endodontic treatment of the adjacent tooth, operator details, surgical procedures, age, gender, and complications (with severity) were analyzed. Results: This study involved 77 patients (55 men, 22 women) and found 10 complications. Procedure type (cyst enucleation only, apicoectomy and bone graft, or bone graft only) and lesion size were significant risk factors. Preoperative root canal therapy and men gender also tended to positively correlate with complications, while age was not a factor. Conclusion Within the limitations of our study, additional procedures contributed to lower risk of complications with the exception of bone graft.A large cyst size was also associated with a higher risk of complications. It is important to consider the possibility of a second procedure and take thorough precautions to prevent infection when performing bone grafts. Patients should be informed of these risks in advance, scheduled for regular follow-up, and provided additional treatment when necessary.

Background and Objectives: Voice disorders can significantly impact quality of life. This study evaluates the feasibility of using deep learning models to detect voice disorders using an opensource dataset.Materials and Method We utilized the Saarbrücken Voice Database, which contains 1231 voice recordings of various pathologies. Datasets were used for training (n=1036) and validation (n=195). Key vocal parameters, including fundamental frequency (F0), formants (F1, F2), harmonics-to-noise ratio, jitter, and shimmer, were analyzed. A convolutional neural network (CNN) was designed to classify voice recordings into normal, vox senilis, and laryngocele. Performance was assessed using precision, recall, F1-score, and accuracy. Results: The CNN model demonstrated high classification performance, with precision, recall, and F1-scores of 1.00 for normal and 0.99 for vox senilis and laryngocele. Accuracy reached 1.00 after 50 epochs and remained stable through 100 epochs. Time-frequency analysis supported the model’s ability to differentiate between classes. Conclusion This study highlights the potential of deep learning for voice disorder detection, achieving high accuracy and precision. Future research should address dataset diversity and realworld integration for broader clinical adoption.

Objectives: Clinical situations that make it challenging to differentiate odontogenic cysts from non-odontogenic cysts and benign tumors of the jaw include cases with cystic conditions accompanied by secondary infection, impacted teeth, cortical thinning and expansion, or external root resorption.This study aimed to identify risk factors for complications in patients undergoing cyst enucleation of the jaw, propose a clinical model, and determine the necessary indications for preoperative root canal of adjacent teeth. Materials and Methods: A review of surgical, pathological, and radiological reports, as well as medical records, was conducted. Pathological diagnosis, lesion size, history of preoperative endodontic treatment of the adjacent tooth, operator details, surgical procedures, age, gender, and complications (with severity) were analyzed. Results: This study involved 77 patients (55 men, 22 women) and found 10 complications. Procedure type (cyst enucleation only, apicoectomy and bone graft, or bone graft only) and lesion size were significant risk factors. Preoperative root canal therapy and men gender also tended to positively correlate with complications, while age was not a factor. Conclusion Within the limitations of our study, additional procedures contributed to lower risk of complications with the exception of bone graft.A large cyst size was also associated with a higher risk of complications. It is important to consider the possibility of a second procedure and take thorough precautions to prevent infection when performing bone grafts. Patients should be informed of these risks in advance, scheduled for regular follow-up, and provided additional treatment when necessary.

Background and Objectives: Voice disorders can significantly impact quality of life. This study evaluates the feasibility of using deep learning models to detect voice disorders using an opensource dataset.Materials and Method We utilized the Saarbrücken Voice Database, which contains 1231 voice recordings of various pathologies. Datasets were used for training (n=1036) and validation (n=195). Key vocal parameters, including fundamental frequency (F0), formants (F1, F2), harmonics-to-noise ratio, jitter, and shimmer, were analyzed. A convolutional neural network (CNN) was designed to classify voice recordings into normal, vox senilis, and laryngocele. Performance was assessed using precision, recall, F1-score, and accuracy. Results: The CNN model demonstrated high classification performance, with precision, recall, and F1-scores of 1.00 for normal and 0.99 for vox senilis and laryngocele. Accuracy reached 1.00 after 50 epochs and remained stable through 100 epochs. Time-frequency analysis supported the model’s ability to differentiate between classes. Conclusion This study highlights the potential of deep learning for voice disorder detection, achieving high accuracy and precision. Future research should address dataset diversity and realworld integration for broader clinical adoption.

Background: While Korea maintains a low prevalence of human immunodeficiency virus (HIV), the number of newly diagnosed cases has been steadily rising, reaching approximately 1,000 annually in recent years. The 2022 annual report from the Korea Disease Control and Prevention Agency revealed that women living with HIV (WLWH) constitute 6.4% of the total confirmed people living with the HIV population, totaling 1,219 individuals. Despite this, only a few studies have focused on WLWH in Korea. This study aims to analyze the epidemiological and clinical characteristics of WLWH in Korea. Materials and Methods: We retrospectively collected data by reviewing the medical records of all WLWH who visited 10 urban referral hospitals across Korea between January 2005 and May 2023. Results: A total of 443 WLWH were enrolled in this study. The predominant risk exposure was heterosexual contact, with 235 (53%) participants either married or cohabiting with a male partner at their initial clinic visit. Among the participants, 334 (77.7%) were Korean, 27 (6.1%) were Southeast Asian, and 19 (4.3%) were African. Antiretroviral therapy was initiated by 404 WLWH (91.2%). We observed 118 pregnancies in WLWH following their HIV diagnosis, resulting in 78 live births (66.1%), 18 induced abortions (15.2%), 10 pre-viable fetal losses (8.5%), and four stillbirths (3.4%). Over a cumulative follow-up duration of 3,202.1 years, the incidence rates of breast and cervical cancers were both 2.18 per 1,000 person-years. Additionally, the incidence rates of pelvic inflammatory disease, cervical intraepithelial neoplasm (above grade II), and osteoporosis were 4.67, 11.21, and 13.39 per 1,000 patient-years, respectively. Conclusion This is the first multicenter study to investigate the clinical and epidemiological characteristics of WLWH in Korea. The incidence and prevalence of diseases in women, including breast cancer, cervical cancer, and chronic comorbidities, are high in WLWH in Korea; therefore, further research and efforts are needed to manage these diseases.

Background: Catheter-associated urinary tract infections (CAUTIs) account for a large proportion of healthcare-associated infections and have a significant impact on morbidity, length of hospital stay, and mortality. Adherence to the recommended infection prevention practices can effectively reduce the incidence of CAUTIs. This study aimed to assess the characteristics of CAUTIs and the efficacy of prevention programs across hospitals of various sizes. Methods: Intervention programs, including training, surveillance, and monitoring, were implemented. Data on the microorganisms responsible for CAUTIs, urinary catheter utilization ratio, rate of CAUTIs per 1,000 device days, and factors associated with the use of indwelling catheters were collected from 2017 to 2019. The incidence of CAUTIs and associated data were compared between university hospitals and small- and medium-sized hospitals. Results: Thirty-two hospitals participated in the study, including 21 university hospitals and 11 small- and medium-sized hospitals. The microorganisms responsible for CAUTIs and their resistance rates did not differ between the two groups. In the first quarter of 2018, the incidence rate was 2.05 infections/1,000 device-days in university hospitals and 1.44 infections/1,000 device-days in small- and medium-sized hospitals. After implementing interventions, the rate gradually decreased in the first quarter of 2019, with 1.18 infections/1,000 device-days in university hospitals and 0.79 infections/1,000 device-days in small- and medium-sized hospitals. However, by the end of the study, the infection rate increased to 1.74 infections/1,000 device-days in university hospitals and 1.80 infections/1,000 device-days in small- and medium-sized hospitals. Conclusion We implemented interventions to prevent CAUTIs and evaluated their outcomes. The incidence of these infections decreased in the initial phases of the intervention when adequate support and personnel were present. The rate of these infections may be reduced by implementing active interventions such as consistent monitoring and adherence to guidelines for preventing infections.

Background: The pathophysiological mechanisms underlying the post-acute sequelae of severe acute respiratory syndrome coronavirus 2 infection (PASC) are not well understood.Our study aimed to investigate various aspects of theses mechanisms, including viral persistence, immunological responses, and laboratory parameters in patients with and without PASC. Methods: We prospectively enrolled adults aged ≥ 18 years diagnosed with coronavirus disease 2019 (COVID-19) between August 2022 and July 2023. Blood samples were collected at three time-points: within one month of diagnosis (acute phase) and at 1 month, and 3 months post-diagnosis. Following a recent well-designed definition of PASC, PASC patients were defined as those with a questionnaire-based PASC score ≥ 12 persisting for at least 4 weeks after the initial COVID-19 diagnosis. Results: Of 57 eligible COVID-19 patients, 29 (51%) had PASC, and 28 (49%) did not. The PASC group had significantly higher nucleocapsid protein (NP) antigenemia 3 months after COVID-19 diagnosis (P = 0.022). Furthermore, several cytokines, including IL-2, IL-17A, VEGF, RANTES, sCD40L, IP-10, I-TAC, and granzyme A, were markedly elevated in the PASC group 1 and/or 3 month(s) after COVID-19 diagnosis. In contrast, the median values of several serological markers, including thyroid markers, autoimmune indicators, and stress-related hormones, were within the normal range. Conclusion Levels of NP antigen and of various cytokines involved in immune responses become significantly elevated over time after COVID-19 diagnosis in PASC patients compared to non-PASC patients. This suggests that PASC is associated with prolonged immune dysregulation resulting from heightened antigenic stimulation.