To investigate the surgical outcomes of patients with chronic angle-closure glaucoma (CACG) treated with phacoemulsification (phaco)/endocyclophotocoagulation (ECP) with and without endoscopic goniosynechialysis (E-GSL). A retrospective, nonrandomized, comparative case series was conducted. Patients with CACG who underwent phaco in combination with either ECP alone (ECP group) or GSL with ECP (E-GSL group) from 2018 to 2019 were followed for 12mo and reviewed. Clinical features and outcomes were identified and analyzed. The ECP and E-GSL groups were matched in age and baseline intraocular pressure (IOP). Changes in IOP, mean of visual acuity (VA), peripheral anterior synechiae (PAS) formation, and the number of glaucoma medications was examined. The ECP group included 32 eyes of 27 patients, and the E-GSL group included 32 eyes of 26 patients. The preoperative baseline IOP was 22.18±6.48 mm Hg in the ECP group and 22.95±6.71 mm Hg in the E-GSL group (P=0.644). The mean IOP reduction was 26.2% in the ECP group and 41.6% in the E-GSL group at 12mo. The mean postoperative VA (logMAR units) at 12mo was 0.47 in the ECP group and 0.36 in the E-GSL group. The reduction in PAS formation and the number of glaucoma medications was also higher in the ECP group than E-GSL group at 12mo. The phaco/ECP and phaco/E-GSL groups both achieve a significant reduction in IOP without complications associated with traditional glaucoma filtration surgeries.

Background: Digital health tools, such as mobile apps and wearable devices, have been widely adopted to support self-management of health behaviors. However, user engagement remains inconsistent, particularly among populations with varying BMI. While digital health technologies have the potential to promote healthier behaviors, little is known about how psychological and behavioral factors interact with BMI to influence use patterns. Objective: This study aimed to explore the relationship between BMI and digital health technology use and to examine how factors such as health awareness, self-efficacy, and health motivation contribute to technology engagement. Methods: A cross-sectional online survey was conducted from January 2024 to April 2024. A total of 184 valid questionnaire participants were included in this study. The questionnaire was measured on a 5-point Likert scale. Descriptive statistics, chi-square tests, and multiple regression analyses were applied. Results: Of the participants, 38.6% (71/184) had a BMI<24 kg/m2, 42.4% (78/184) had a BMI between 24 and 29.9 kg/m2, and 19% (35/184) had a BMI≥30 kg/m2. Significant BMI differences were observed based on sex (P<.001) and age (P<.001) but not based on prior digital health tool use. Use rates for Bluetooth or Wi-Fi devices, wearables, and mobile apps were 32.1% (59/184), 38.6% (71/184), and 39.1% (72/184), respectively. A negative correlation between BMI and mobile app use frequency was identified (P=.02). Multiple regression analysis indicated that health motivation significantly predicted digital health use (P<.001), whereas health awareness, lifestyle, and self-efficacy did not. Conclusions: Individuals with higher BMI reported a lower frequency of digital health tool use, potentially due to lower health motivation in the studied population. Health motivation was the strongest predictor of digital health engagement. Integrating personalized medical records into apps may enhance health motivation, thereby improving user engagement and promoting healthier behaviors in individuals with higher BMI.

BACKGROUND Digital health tools, such as mobile apps and wearable devices, have been widely adopted to support self-management of health behaviors. However, user engagement remains inconsistent, particularly among populations with varying BMI. While digital health technologies have the potential to promote healthier behaviors, little is known about how psychological and behavioral factors interact with BMI to influence use patterns. OBJECTIVE This study aimed to explore the relationship between BMI and digital health technology use and to examine how factors such as health awareness, self-efficacy, and health motivation contribute to technology engagement. METHODS A cross-sectional online survey was conducted from January 2024 to April 2024. A total of 184 valid questionnaire participants were included in this study. The questionnaire was measured on a 5-point Likert scale. Descriptive statistics, chi-square tests, and multiple regression analyses were applied. RESULTS Of the participants, 38.6% (71/184) had a BMI<24 kg/m2, 42.4% (78/184) had a BMI between 24 and 29.9 kg/m2, and 19% (35/184) had a BMI≥30 kg/m2. Significant BMI differences were observed based on sex (P<.001) and age (P<.001) but not based on prior digital health tool use. Use rates for Bluetooth or Wi-Fi devices, wearables, and mobile apps were 32.1% (59/184), 38.6% (71/184), and 39.1% (72/184), respectively. A negative correlation between BMI and mobile app use frequency was identified (P=.02). Multiple regression analysis indicated that health motivation significantly predicted digital health use (P<.001), whereas health awareness, lifestyle, and self-efficacy did not. CONCLUSIONS Individuals with higher BMI reported a lower frequency of digital health tool use, potentially due to lower health motivation in the studied population. Health motivation was the strongest predictor of digital health engagement. Integrating personalized medical records into apps may enhance health motivation, thereby improving user engagement and promoting healthier behaviors in individuals with higher BMI.

Background: Rhinolaryngoscopes are one of the most widely used tools by otolaryngologists and speech-language pathologists in current clinical practice. However, there is limited data on adverse events associated with or caused by the use of rhinolaryngoscopes. Objective: In this study, we used the Manufacturer and User Facility Device Experience (MAUDE) database with the aim of providing insights that may assist otolaryngologists in better understanding the limitations of these devices and selecting appropriate procedures for their specific clinical setting. Methods: We characterized complications associated with the postmarket use of rhinolaryngoscope devices from the US Food and Drug Administration MAUDE database from 2016 through 2023. Results: A total of 2591 reports were identified, including 2534 device malfunctions, 56 injuries, and 1 death, from 2016 through 2023. The most common device problem with rhinolaryngoscopes was breakage (n=1058 reports, 40.8%), followed by fluid leaks (n=632 reports, 24.4%). The third most common problem was poor image quality (n=467 reports, 18%). Other device issues included contamination or device reprocessing problems (n=127 reports, 4.9%), material deformation or wear (n=125 reports, 4.8%), and device detachment (n=73 reports, 2.8%). Of the 63 reported adverse events, the most common patient-related adverse event was hemorrhage or bleeding, accounting for 18 reports, with the root causes including material deformation or wear, breakage, wrinkled rubber, or improper operation. Conclusions: Our study offers valuable insights for endoscopists and manufacturers to recognize potential issues and adverse events associated with the use of rhinolaryngoscopes. It emphasizes the need for improving device reliability, training, and procedural protocols to enhance patient safety during diagnostic procedures.