Purpose: To evaluate the clinical outcomes of myopic choroidal neovascularization (CNV) and atrophic and tractional changes according to the ATN (A: atrophy, T: traction, N: neovascularization) classification system. Methods: This was a retrospective review of the medical records of myopic CNV patients treated with intravitreal anti-vascular endothelial growth factor (anti-VEGF) injections and followed up for at least 3 years. Atrophic and tractional components were graded according to the ATN system at baseline and the last visit. Results: The study included 21 eyes in 21 patients. The mean age was 52.29 ± 14.6 years, the mean follow-up duration was 57.65 ± 18.8 months, and the mean number of injections was 2.9 ± 1.9. Recurrence occurred in seven eyes (33.3%). Five patients (23.8%) developed myopic CNV in the contralateral eye. The mean initial and final logarithm of the minimum angle of resolution (logMAR) visual acuities were 0.44 ± 0.30 and 0.33 ± 0.39, respectively. Visual acuity was maintained or improved compared to baseline in 15 eyes (71.4%). Baseline visual acuity was significantly associated with the final visual acuity (p = 0.026). Based on the ATN classification system, the atrophic component progressed in four eyes (19.0%), while the tractional component improved in one eye (4.8%) and progressed in five eyes (23.8%). Conclusions Intravitreal anti-VEGF injection therapy effectively preserved long-term vision in myopic CNV patients. Evaluation of the atrophic and tractional components should not be neglected during the follow-up.

Purpose: To report the efficacy of frontalis suspension using a silicone rod or preserved fascia lata for patients with blepharospasm who exhibit persistent symptoms and visual dysfunction unresponsive to botulinum injections. Methods: The clinical records of five patients (10 eyes) with essential blepharospasm who underwent frontalis suspension were reviewed. Patients who continued to report eyelid-opening difficulties despite prior administration of botulinum toxin were included. Results: The mean patient age was 60.2 years; and 40% of the patients were women. The frontalis was suspended using silicone rods (n = 3) or preserved fascia lata (n = 2). Blepharospasm frequency and severity were measured using the Jankovic Rating Scale (JRS). Compared with preoperative scores, the summed JRS scores decreased 1 week, 1 month, and 3 months after surgery. Postoperatively, two patients (40%) did not require further botulinum toxin injections. In three patients, the intervals between injections were increased after surgery. No patient experienced any significant complication. Conclusions Frontalis suspension is safe and effective for patients with blepharospasm and apraxia of eyelid opening, who have not responded to botulinum toxin injections.

This study compared the predictive models for the growth kinetics of Staphylococcus aureus in ham rice balls. In addition, a semi-quantitative risk assessment of S. aureus on ham rice balls was conducted using FDA-iRISK 4.0. The rice was rounded with chopped ham, which was mixed with mayonnaise (SHM), soy sauce (SHS), or gochujang (SHG), and was contaminated artificially with approximately 2.5 log CFU·g⁻¹ of S. aureus. The inoculated rice balls were then stored at 7℃, 15℃, and 25℃, and the number of viable S. aureus was counted. The lag phases duration (LPD) and maximum specific growth rate (SGR) were calculated using a Baranyi model as a primary model. The growth parameters were analyzed using the polynomial equation as a function of temperature. The LPD values of S. aureus decreased with increasing temperature in SHS and SHG. On the other hand, those in SHM did not show any trend with increasing temperature. The SGR positively correlated with temperature. Equations for LPD and SGR were developed and validated using R² values, which ranged from 0.9929 to 0.9999. In addition, the total DALYs (disability adjusted life years) per year in the ham rice balls with soy sauce and gochujang was greater than mayonnaise. These results could be used to calculate the expected number of illnesses, and set the hazard management method taking the DALY value for public health into account.
Hand ; Kinetics ; Methods ; Public Health ; Risk Assessment ; Safety Management ; Soy Foods ; Staphylococcus aureus ; Staphylococcus

Background: and Purpose The prevalence of Alzheimer’s dementia (AD) is increasing as populations age, causing immense suffering for patients, families, and communities. Unfortunately, no treatments for this neurodegenerative disease have been established. Predicting AD is therefore becoming more important, because early diagnosis is the best way to prevent its onset and delay its progression. Methods: Mild cognitive impairment (MCI) is the stage between normal cognition and AD, with large variations in its progression. The disease can be effectively managed by accurately predicting the probability of MCI progressing to AD over several years. In this study we used the Alzheimer’s Disease Neuroimaging Initiative dataset to predict the progression of MCI to AD over a 3-year period from baseline. We developed and compared various recurrent neural network (RNN) models to determine the predictive effectiveness of four neuropsychological (NP) tests and magnetic resonance imaging (MRI) data at baseline. Results: The experimental results confirmed that the Preclinical Alzheimer’s Cognitive Composite score was the most effective of the four NP tests, and that the prediction performance of the NP tests improved over time. Moreover, the gated recurrent unit model exhibited the best performance among the prediction models, with an average area under the receiver operating characteristic curve of 0.916 Conclusions Timely prediction of progression from MCI to AD can be achieved using a series of NP test results and an RNN, both with and without using the baseline MRI data.

Background: and Purpose The prevalence of Alzheimer’s dementia (AD) is increasing as populations age, causing immense suffering for patients, families, and communities. Unfortunately, no treatments for this neurodegenerative disease have been established. Predicting AD is therefore becoming more important, because early diagnosis is the best way to prevent its onset and delay its progression. Methods: Mild cognitive impairment (MCI) is the stage between normal cognition and AD, with large variations in its progression. The disease can be effectively managed by accurately predicting the probability of MCI progressing to AD over several years. In this study we used the Alzheimer’s Disease Neuroimaging Initiative dataset to predict the progression of MCI to AD over a 3-year period from baseline. We developed and compared various recurrent neural network (RNN) models to determine the predictive effectiveness of four neuropsychological (NP) tests and magnetic resonance imaging (MRI) data at baseline. Results: The experimental results confirmed that the Preclinical Alzheimer’s Cognitive Composite score was the most effective of the four NP tests, and that the prediction performance of the NP tests improved over time. Moreover, the gated recurrent unit model exhibited the best performance among the prediction models, with an average area under the receiver operating characteristic curve of 0.916 Conclusions Timely prediction of progression from MCI to AD can be achieved using a series of NP test results and an RNN, both with and without using the baseline MRI data.

Background: and Purpose The prevalence of Alzheimer’s dementia (AD) is increasing as populations age, causing immense suffering for patients, families, and communities. Unfortunately, no treatments for this neurodegenerative disease have been established. Predicting AD is therefore becoming more important, because early diagnosis is the best way to prevent its onset and delay its progression. Methods: Mild cognitive impairment (MCI) is the stage between normal cognition and AD, with large variations in its progression. The disease can be effectively managed by accurately predicting the probability of MCI progressing to AD over several years. In this study we used the Alzheimer’s Disease Neuroimaging Initiative dataset to predict the progression of MCI to AD over a 3-year period from baseline. We developed and compared various recurrent neural network (RNN) models to determine the predictive effectiveness of four neuropsychological (NP) tests and magnetic resonance imaging (MRI) data at baseline. Results: The experimental results confirmed that the Preclinical Alzheimer’s Cognitive Composite score was the most effective of the four NP tests, and that the prediction performance of the NP tests improved over time. Moreover, the gated recurrent unit model exhibited the best performance among the prediction models, with an average area under the receiver operating characteristic curve of 0.916 Conclusions Timely prediction of progression from MCI to AD can be achieved using a series of NP test results and an RNN, both with and without using the baseline MRI data.

Background: and Purpose The prevalence of Alzheimer’s dementia (AD) is increasing as populations age, causing immense suffering for patients, families, and communities. Unfortunately, no treatments for this neurodegenerative disease have been established. Predicting AD is therefore becoming more important, because early diagnosis is the best way to prevent its onset and delay its progression. Methods: Mild cognitive impairment (MCI) is the stage between normal cognition and AD, with large variations in its progression. The disease can be effectively managed by accurately predicting the probability of MCI progressing to AD over several years. In this study we used the Alzheimer’s Disease Neuroimaging Initiative dataset to predict the progression of MCI to AD over a 3-year period from baseline. We developed and compared various recurrent neural network (RNN) models to determine the predictive effectiveness of four neuropsychological (NP) tests and magnetic resonance imaging (MRI) data at baseline. Results: The experimental results confirmed that the Preclinical Alzheimer’s Cognitive Composite score was the most effective of the four NP tests, and that the prediction performance of the NP tests improved over time. Moreover, the gated recurrent unit model exhibited the best performance among the prediction models, with an average area under the receiver operating characteristic curve of 0.916 Conclusions Timely prediction of progression from MCI to AD can be achieved using a series of NP test results and an RNN, both with and without using the baseline MRI data.

OBJECTIVE: Chest pain is one of the most common complaints in the emergency department (ED). Cardiac computed tomography angiography (CCTA) is a frequently used tool for the early triage of patients with low- to intermediate-risk acute chest pain. We present a study protocol for a multicenter prospective randomized controlled clinical trial testing the hypothesis that a low-dose CCTA protocol using prospective electrocardiogram (ECG)-triggering and limited-scan range can provide sufficient diagnostic safety for early triage of patients with acute chest pain. METHODS: The trial will include 681 younger adult (aged 20 to 55) patients visiting EDs of three academic hospitals for acute chest pain or equivalent symptoms who require further evaluation to rule out acute coronary syndrome. Participants will be randomly allocated to either low-dose or conventional CCTA protocol at a 2:1 ratio. The low-dose group will undergo CCTA with prospective ECG-triggering and restricted scan range from sub-carina to heart base. The conventional protocol group will undergo CCTA with retrospective ECG-gating covering the entire chest. Patient disposition is determined based on computed tomography findings and clinical progression and all patients are followed for a month. The primary objective is to prove that the chance of experiencing any hard event within 30 days after a negative low-dose CCTA is less than 1%. The secondary objectives are comparisons of the amount of radiation exposure, ED length of stay and overall cost. RESULTS AND CONCLUSION: Our low-dose protocol is readily applicable to current multi-detector computed tomography devices. If this study proves its safety and efficacy, dose-reduction without purchasing of expensive newer devices would be possible.
Acute Coronary Syndrome ; Adult ; Angiography* ; Chest Pain ; Coronary Angiography ; Electrocardiography ; Emergencies* ; Emergency Service, Hospital ; Heart ; Humans ; Length of Stay ; Prospective Studies ; Radiation Exposure ; Retrospective Studies ; Thorax ; Triage