Impact of national health insurance and socioeconomic disparities on newborn hearing screening performance in South Korea: A nationwide population-based evaluation.

OBJECTIVES: This study aimed to assess the impact of national health insurance coverage on newborn hearing screening (NHS) outcomes by analyzing hearing questionnaires from the National Infant Health Check-up Program (NIHCP) in South Korea. METHODS: This study evaluated the performance and referral rates of NHS using nationwide data from 814,875 infants enrolled in the 4-month NIHCP from January 2017 to December 2019. This period encompasses the periods before and after the National Health Insurance in South Korea began covering NHS expenses in October 2018. The study also investigated household income levels to determine their relationship with participation in the NIHCP and NHS outcomes. RESULTS: The performance of NIHCP increased year-on-year, with NHS performance rates increasing from 88.5 % in 2017 to 91.5 % in 2019. Analysis by household income level revealed that the medical benefit recipients' group had the lowest NHS performance rate of 81.9 % in 2019, whereas that of the higher income level group exceeded 90 %. The NHS referral rate remained consistent at 0.9 % nationally during the study period. CONCLUSION: The inclusion of NHS in national insurance coverage positively influenced its performance rates across South Korea. Nevertheless, the data indicate the need for more focused and customized support for low-income families to enhance early hearing detection and interventions in newborns and infants.

Genetic Inactivation of the ß1 adrenergic receptor prevents Cerebral Cavernous Malformations in zebrafish.

Propranolol reduces experimental murine cerebral cavernous malformations (CCMs) and prevents embryonic caudal venous plexus (CVP) lesions in zebrafish that follow mosaic inactivation of ccm2 . Because morpholino silencing of the ß1 adrenergic receptor ( adrb1 ) prevents the embryonic CVP lesion, we proposed that adrb1 plays a role in CCM pathogenesis. Here we report that adrb1 -/- zebrafish exhibited 86% fewer CVP lesions and 87% reduction of CCM lesion volume relative to wild type brood mates at 2dpf and 8-10 weeks stage, respectively. Treatment with metoprolol, a ß1 selective antagonist, yielded a similar reduction in CCM lesion volume. Adrb1 -/- zebrafish embryos exhibited reduced heart rate and contractility and reduced CVP blood flow. Similarly, slowing the heart and eliminating the blood flow in CVP by administration of 2,3-BDM suppressed the CVP lesion. In sum, our findings provide genetic and pharmacological evidence that the therapeutic effect of propranolol on CCM is achieved through ß1 receptor antagonism.

Reinforcement of a Subcutaneous Pocket for Implantable Cardioverter Defibrillator Insertion Using Acellular Dermal Matrix: A Case Report.

Pediatric patients who undergo implant insertion into the chest wall face a high risk of implant exposure to the external environment. Five months after an 8-year-old boy underwent implantable cardioverter-defibrillator (ICD) implantation in a subcutaneous pocket in the left anterolateral chest wall to manage long QT syndrome, ICD replacement became necessary owing to exposure risk from distal and lateral thinning of the ICD pocket. Pocket rupture and exposure would increase the risk of infection; therefore, we performed ICD removal and primary pocket closure. Two weeks later, a new suprafascial pocket was created, an acellular dermal matrix (ADM) was attached to the inner wall to prevent ICD protrusion, and a new ICD was inserted. One year postoperatively, the ADM was engrafted, and no complications were observed. A thin subcutaneous layer increases the risk of ICD implantation complications. Inner wall strengthening with an ADM can help prevent pocket rupture.

Immune Cells Are Differentially Affected by SARS-CoV-2 Viral Loads in K18-hACE2 Mice.

Viral load and the duration of viral shedding of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are important determinants of the transmission of coronavirus disease 2019. In this study, we examined the effects of viral doses on the lung and spleen of K18-hACE2 transgenic mice by temporal histological and transcriptional analyses. Approximately, 1×105 plaque-forming units (PFU) of SARS-CoV-2 induced strong host responses in the lungs from 2 days post inoculation (dpi) which did not recover until the mice died, whereas responses to the virus were obvious at 5 days, recovering to the basal state by 14 dpi at 1×102 PFU. Further, flow cytometry showed that number of CD8+ T cells continuously increased in 1×102 PFU-virus-infected lungs from 2 dpi, but not in 1×105 PFU-virus-infected lungs. In spleens, responses to the virus were prominent from 2 dpi, and number of B cells was significantly decreased at 1×105 PFU; however, 1×102 PFU of virus induced very weak responses from 2 dpi which recovered by 10 dpi. Although the defense responses returned to normal and the mice survived, lung histology showed evidence of fibrosis, suggesting sequelae of SARS-CoV-2 infection. Our findings indicate that specific effectors of the immune response in the lung and spleen were either increased or depleted in response to doses of SARS-CoV-2. This study demonstrated that the response of local and systemic immune effectors to a viral infection varies with viral dose, which either exacerbates the severity of the infection or accelerates its elimination.

Alteration of multilayer network perspective on gray and white matter connectivity in obstructive sleep apnea.

PURPOSE: The objective of this research was to examine changes in the neural networks of both gray and white matter in individuals with obstructive sleep apnea (OSA) in comparison to those without the condition, employing a comprehensive multilayer network analysis. METHODS: Patients meeting the criteria for OSA were recruited through polysomnography, while a control group of healthy individuals matched for age and sex was also assembled. Utilizing T1-weighted imaging, a morphometric similarity network was crafted to represent gray matter, while diffusion tensor imaging provided structural connectivity for constructing a white matter network. A multilayer network analysis was then performed, employing graph theory methodologies. RESULTS: We included 40 individuals diagnosed with OSA and 40 healthy participants in our study. Analysis revealed significant differences in various global network metrics between the two groups. Specifically, patients with OSA exhibited higher average degree overlap and average multilayer clustering coefficient (28.081 vs. 23.407, p < 0.001; 0.459 vs. 0.412, p = 0.004), but lower multilayer modularity (0.150 vs. 0.175, p = 0.001) compared to healthy controls. However, no significant differences were observed in average multiplex participation, average overlapping strength, or average weighted multiplex participation between the patients with OSA and healthy controls. Moreover, several brain regions displayed notable differences in degree overlap at the nodal level between patients with OSA and healthy controls. CONCLUSION: Remarkable alterations in the multilayer network, indicating shifts in both gray and white matter, were detected in patients with OSA in contrast to their healthy counterparts. Further examination at the nodal level unveiled notable changes in regions associated with cognition, underscoring the effectiveness of multilayer network analysis in exploring interactions across brain layers.

Clinical usability of 3D gradient-echo-based ultrashort echo time imaging: Is it enough to facilitate diagnostic decision in real-world practice?

BACKGROUND: With recent advances in magnetic resonance imaging (MRI) technology, the practical role of lung MRI is expanding despite the inherent challenges of the thorax. The purpose of our study was to evaluate the current status of the concurrent dephasing and excitation (CODE) ultrashort echo-time sequence and the T1-weighted volumetric interpolated breath-hold examination (VIBE) sequence in the evaluation of thoracic disease by comparing it with the gold standard computed tomography (CT). METHODS: Twenty-four patients with lung cancer and mediastinal masses underwent both CT and MRI including T1-weighted VIBE and CODE. For CODE images, data were acquired in free breathing and end-expiratory images were reconstructed using retrospective respiratory gating. All images were evaluated through qualitative and quantitative approaches regarding various anatomical structures and lesions (nodule, mediastinal mass, emphysema, reticulation, honeycombing, bronchiectasis, pleural plaque and lymphadenopathy) inside the thorax in terms of diagnostic performance in making specific decisions. RESULTS: Depiction of the lung parenchyma, mediastinal and pleural lesion was not significant different among the three modalities (p > 0.05). Intra-tumoral and peritumoral features of lung nodules were not significant different in the CT, VIBE or CODE images (p > 0.05). However, VIBE and CODE had significantly lower image quality and poorer depiction of airway, great vessels, and emphysema compared to CT (p < 0.05). Image quality of central airways and depiction of bronchi were significantly better in CODE than in VIBE (p < 0.001 and p = 0.005). In contrast, the depiction of the vasculature was better for VIBE than CODE images (p = 0.003). The signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were significant greater in VIBE than CODE except for SNRlung and SNRnodule (p < 0.05). CONCLUSIONS: Our study showed the potential of CODE and VIBE sequences in the evaluation of localized thoracic abnormalities including solid pulmonary nodules.

Beyond measurement: a deep dive into the commonly used pain scales for postoperative pain assessment.

This review explores the essential methodologies for effective postoperative pain management, focusing on the need for thorough pain assessment tools, as underscored in various existing guidelines. Herein, the strengths and weaknesses of commonly used pain scales for postoperative pain-the Visual Analog Scale, Numeric Rating Scale, Verbal Rating Scale, and Faces Pain Scale-are evaluated, highlighting the importance of selecting appropriate assessment tools based on factors influencing their effectiveness in surgical contexts. By emphasizing the need to comprehend the minimal clinically important difference (MCID) for these scales in evaluating new analgesic interventions and monitoring pain trajectories over time, this review advocates recognizing the limitations of common pain scales to improve pain assessment strategies, ultimately enhancing postoperative pain management. Finally, five recommendations for pain assessment in research on postoperative pain are provided: first, selecting an appropriate pain scale tailored to the patient group, considering the strengths and weaknesses of each scale; second, simultaneously assessing the intensity of postoperative pain at rest and during movement; third, conducting evaluations at specific time points and monitoring trends over time; fourth, extending the focus beyond the intensity of postoperative pain to include its impact on postoperative functional recovery; and lastly, interpreting the findings while considering the MCID, ensuring that it is clinically significant for the chosen pain scale. These recommendations broaden our understanding of postoperative pain and provide insights that contribute to more effective pain management strategies, thereby enhancing patient care outcomes.

Correlation of diffusion tensor tractography with obstructive sleep apnea severity.

INTRODUCTION: Using correlation tractography, this study aimed to find statistically significant correlations between white matter (WM) tracts in participants with obstructive sleep apnea (OSA) and OSA severity. We hypothesized that changes in certain WM tracts could be related to OSA severity. METHODS: We enrolled 40 participants with OSA who underwent diffusion tensor imaging (DTI) using a 3.0 Tesla MRI scanner. Fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), radial diffusivity (RD), and quantitative anisotropy (QA)-values were used in the connectometry analysis. The apnea-hypopnea index (AHI) is a representative measure of the severity of OSA. Diffusion MRI connectometry that was used to derive correlational tractography revealed changes in the values of FA, MD, AD, RD, and QA when correlated with the AHI. A false-discovery rate threshold of 0.05 was used to select tracts to conduct multiple corrections. RESULTS: Connectometry analysis revealed that the AHI in participants with OSA was negatively correlated with FA values in WM tracts that included the cingulum, corpus callosum, cerebellum, inferior longitudinal fasciculus, fornices, thalamic radiations, inferior fronto-occipital fasciculus, superior and posterior corticostriatal tracts, medial lemnisci, and arcuate fasciculus. However, there were no statistically significant results in the WM tracts, in which FA values were positively correlated with the AHI. In addition, connectometry analysis did not reveal statistically significant results in WM tracts, in which MD, AD, RD, and QA values were positively or negatively correlated with the AHI. CONCLUSION: Several WM tract changes were correlated with OSA severity. However, WM changes in OSA likely involve tissue edema and not neuronal changes, such as axonal loss. Connectometry analyses are valuable tools for detecting WM changes in sleep disorders.

StrokeClassifier: ischemic stroke etiology classification by ensemble consensus modeling using electronic health records.

Determining acute ischemic stroke (AIS) etiology is fundamental to secondary stroke prevention efforts but can be diagnostically challenging. We trained and validated an automated classification tool, StrokeClassifier, using electronic health record (EHR) text from 2039 non-cryptogenic AIS patients at 2 academic hospitals to predict the 4-level outcome of stroke etiology adjudicated by agreement of at least 2 board-certified vascular neurologists' review of the EHR. StrokeClassifier is an ensemble consensus meta-model of 9 machine learning classifiers applied to features extracted from discharge summary texts by natural language processing. StrokeClassifier was externally validated in 406 discharge summaries from the MIMIC-III dataset reviewed by a vascular neurologist to ascertain stroke etiology. Compared with vascular neurologists' diagnoses, StrokeClassifier achieved the mean cross-validated accuracy of 0.74 and weighted F1 of 0.74 for multi-class classification. In MIMIC-III, its accuracy and weighted F1 were 0.70 and 0.71, respectively. In binary classification, the two metrics ranged from 0.77 to 0.96. The top 5 features contributing to stroke etiology prediction were atrial fibrillation, age, middle cerebral artery occlusion, internal carotid artery occlusion, and frontal stroke location. We designed a certainty heuristic to grade the confidence of StrokeClassifier's diagnosis as non-cryptogenic by the degree of consensus among the 9 classifiers and applied it to 788 cryptogenic patients, reducing cryptogenic diagnoses from 25.2% to 7.2%. StrokeClassifier is a validated artificial intelligence tool that rivals the performance of vascular neurologists in classifying ischemic stroke etiology. With further training, StrokeClassifier may have downstream applications including its use as a clinical decision support system.

Structural connectivity as a predictive factor for perampanel response in patients with epilepsy.

OBJECTIVES: This study aimed to identify clinical characteristics that could predict the response to perampanel (PER) and determine whether structural connectivity is a predictive factor. METHODS: We enrolled patients with epilepsy who received PER and were followed-up for a minimum of 12 months. Good PER responders, who were seizure-free or presented with more than 50 % seizure reduction, were classified separately from poor PER responders who had seizure reduction of less than 50 % or non-responders. A graph theoretical analysis was conducted based on diffusion tensor imaging to calculate network measures of structural connectivity among patients with epilepsy. RESULTS: 106 patients with epilepsy were enrolled, including 26 good PER responders and 80 poor PER responders. Good PER responders used fewer anti-seizure medications before PER administration compared to those by poor PER responders (3 vs. 4; p = 0.042). Early PER treatment was more common in good PER responders than poor PER responders (46.2 vs. 21.3 %, p = 0.014). Regarding cortical structural connectivity, the global efficiency was higher and characteristic path length was lower in good PER responders than in poor PER responders (0.647 vs. 0.635, p = 0.006; 1.726 vs. 1,759, p = 0.008, respectively). For subcortical structural connectivity, the mean clustering coefficient and small-worldness index were higher in good PER responders than in poor PER responders (0.821 vs. 0.791, p = 0.009; 0.597 vs. 0.560, p = 0.009, respectively). CONCLUSION: This study demonstrated that early PER administration can predict a good PER response in patients with epilepsy, and structural connectivity could potentially offer clinical utility in predicting PER response.

Geographic information system-based determination of priority monitoring areas for hazardous air pollutants in an industrial city.

Industrial cities are hotspots for many hazardous air pollutants (HAPs), which are detrimental to human health. We devised an identification method to determine priority HAP monitoring areas using a comprehensive approach involving monitoring, modeling, and demographics. The methodology to identify the priority HAP monitoring area consists of two parts: (1) mapping the spatial distribution of selected categories relevant to the target pollutant and (2) integrating the distribution maps of various categories and subsequent scoring. The identification method was applied in Ulsan, the largest industrial city in South Korea, to identify priority HAP monitoring areas. Four categories related to HAPs were used in the method: (1) concentrations of HAPs, (2) amount of HAP emissions, (3) the contribution of industrial activities, and (4) population density in the city. This method can be used to select priority HAP monitoring areas for intensive monitoring campaigns, cohort studies, and epidemiological studies.

Prevalence of Dysphonia and Dysphagia Among Adults in the United States in 2012 and 2022.

PURPOSE: The purpose of this study was to compare the prevalence of dysphonia and dysphagia among adults in the United States between 2012 and 2022. METHOD: A retrospective and cross-sectional design with national surveys was used. The 2012 and 2022 National Health Interview Surveys were utilized to estimate the number of adults reporting dysphonia and dysphagia in the past 12 months. Multivariate logistic regression models were used to examine associations between the survey year (2022 vs. 2012) and the prevalence rate of dysphonia and dysphagia while accounting for demographics and clinical characteristics. RESULTS: The population-estimated mean age was 46.63 years in 2012, which increased to 48.12 years in 2022. In 2012, adults reporting dysphonia and dysphagia were 17.89 million (7.62%) and 9.44 million (4.02%), respectively. In 2022, these estimates increased to 29.92 million adults (11.71%) and 15.10 million adults (5.91%), respectively. Adults in 2022 had significantly higher odds for reporting dysphonia (odds ratio [OR] = 1.602, 95% confidence intervals [CIs] [1.486, 1.726], p < .0001) and dysphagia (OR = 1.461, 95% CI [1.328, 1.606], p < .0001) in the past 12 months compared to adults in 2012. CONCLUSIONS: The population-estimates indicated that in 2022, dysphonia affected one in 8.5 adults and dysphagia affected one in 17 adults. The increase in prevalence of these disorders should serve as a call-to-action to improve access to care and research for voice and swallowing disorders.

Clinical efficacy of prophylactic intravenous immunoglobulin for elderly DLBCL patients with hypogammaglobulinemia in the COVID-19 pandemic era.

Background: Elderly patients diagnosed with diffuse large B-cell lymphoma (DLBCL) undergoing reduced intensity R-CHOP therapy are at a heightened risk of acquiring infections, notably coronavirus disease 2019 (COVID-19) infection. This study aimed to evaluate the efficacy of intravenous immunoglobulin (IVIG) as prophylaxis against COVID-19 in this vulnerable population. Methods: A total of 125 elderly patients with DLBCL undergoing reduced intensity R-CHOP therapy were analyzed in this prospective, multicenter study. Patients with hypogammaglobulinemia were categorized into IVIG and non-IVIG groups, while those with normal immunoglobulin levels constituted the observation group. The study evaluated COVID-19 infection rates, therapy response, and safety outcomes. Results: Among the enrolled patients (median age: 77 years), 89 patients (71.2%) presented with hypogammaglobulinemia at diagnosis, and 56 patients enrolled in the IVIG administration group. IVIG administration remarkably reduced COVID-19 infection rates compared to non-IVIG recipients (8.9% vs. 24.6%; p =0.040). Notably, patients over 80 years old were more susceptible to COVID-19. Patients on IVIG exhibited good tolerance with manageable adverse events. Among patients with hypogammaglobulinemia who received IVIG, 40.5% of patients developed additional immunoglobulin deficiencies during chemotherapy. One or more new hypogammaglobulinemia occurred during chemotherapy in 72% of patients with hypogammaglobulinemia who did not receive IVIG, and in 61.3% of patients who did not have hypogammaglobulinemia at diagnosis. Conclusion: IVIG showed promise in reducing COVID-19 infections among elderly patients with DLBCL receiving reduced intensity R-CHOP therapy. This highlights IVIG's potential as a prophylactic measure, necessitating further investigation to optimize dosing, administration schedules, and potential interactions with vaccination strategies.

Ginseng-derived compounds as potential anticancer agents targeting cancer stem cells.

Cancer stem cells (CSCs) are a rare subpopulation of cancer cells that exhibit stem cell-like characteristics, including self-renewal and differentiation in a multi-stage lineage state via symmetric or asymmetric division, causing tumor initiation, heterogeneity, progression, and recurrence and posing a major challenge to current anticancer therapy. Despite the importance of CSCs in carcinogenesis and cancer progression, currently available anticancer therapeutics have limitations for eradicating CSCs. Moreover, the efficacy and therapeutic windows of currently available anti-CSC agents are limited, suggesting the necessity to optimize and develop a novel anticancer agent targeting CSCs. Ginseng has been traditionally used for enhancing immunity and relieving fatigue. As ginseng's long history of use has demonstrated its safety, it has gained attention for its potential pharmacological properties, including anticancer effects. Several studies have identified the bioactive principles of ginseng, such as ginseng saponin (ginsenosides) and non-saponin compounds (e.g., polysaccharides, polyacetylenes, and phenolic compounds), and their pharmacological activities, including antioxidant, anticancer, antidiabetic, antifatigue, and neuroprotective effects. Notably, recent reports have shown the potential of ginseng-derived compounds as anti-CSC agents. This review investigates the biology of CSCs and efforts to utilize ginseng-derived components for cancer treatment targeting CSCs, highlighting their role in overcoming current therapeutic limitations.

Dose-toxicity surface histogram-based prediction of radiation dermatitis severity and shapes.

OBJECTIVE: This study aimed to develop a new approach to predict radiation dermatitis (RD) by using the skin dose distribution in the actual area of RD occurrence to determine the predictive dose by grade. Approach: Twenty-three patients with head and neck cancer treated with volumetric modulated arc therapy were prospectively and retrospectively enrolled. A framework was developed to segment the RD occurrence area in skin photography by matching the skin surface image obtained using a 3D camera with the skin dose distribution. RD predictive doses were generated using the dose-toxicity surface histogram (DTH) calculated from the skin dose distribution within the segmented RD regions classified by severity. We then evaluated whether the developed DTH-based framework could visually predict RD grades and their occurrence areas and shapes according to severity. Main results: The developed framework successfully generated the DTH for three different RD severities: faint erythema (grade 1), dry desquamation (grade 2), and moist desquamation (grade 3); 48 DTHs were obtained from 23 patients: 23, 22, and 3 DTHs for grades 1, 2, and 3, respectively. The RD predictive doses determined using DTHs were 28.9 Gy, 38.1 Gy, and 54.3 Gy for grades 1, 2, and 3, respectively. The estimated RD occurrence area visualized by the DTH-based RD predictive dose showed acceptable agreement for all grades compared with the actual RD region in the patient. The predicted RD grade was accurate, except in two patients. Significance: The developed DTH-based framework can classify and determine RD predictive doses according to severity and visually predict the occurrence area and shape of different RD severities. The proposed approach can be used to predict the severity and shape of potential RD in patients and thus aid physicians in decision making.

Overview of AlphaFold2 and breakthroughs in overcoming its limitations.

Predicting three-dimensional (3D) protein structures has been challenging for decades. The emergence of AlphaFold2 (AF2), a deep learning-based machine learning method developed by DeepMind, became a game changer in the protein folding community. AF2 can predict a protein's three-dimensional structure with high confidence based on its amino acid sequence. Accurate prediction of protein structures can dramatically accelerate our understanding of biological mechanisms and provide a solid foundation for reliable drug design. Although AF2 breaks through the barriers in predicting protein structures, many rooms remain to be further studied. This review provides a brief historical overview of the development of protein structure prediction, covering template-based, template-free, and machine learning-based methods. In addition to reviewing the potential benefits (Pros) and considerations (Cons) of using AF2, this review summarizes the diverse applications, including protein structure predictions, dynamic changes, point mutation, integration of language model and experimental data, protein complex, and protein-peptide interaction. It underscores recent advancements in efficiency, reliability, and broad application of AF2. This comprehensive review offers valuable insights into the applications of AF2 and AF2-inspired AI methods in structural biology and its potential for clinically significant drug target discovery.

Current Health Data Standardization Project and Future Directions to Ensure Interoperability in Korea.

OBJECTIVES: The need for interoperability at the national level was highlighted in Korea, leading to a consensus on the importance of establishing national standards that align with international technological standards and reflect contemporary needs. This article aims to share insights into the background of the recent national health data standardization policy, the activities of the Health Data Standardization Taskforce, and the future direction of health data standardization in Korea. METHODS: To ensure health data interoperability, the Health Data Standardization Taskforce was jointly organized by the public and private sectors in December 2022. The taskforce operated three working groups. It reviewed international trends in interoperability standardization, assessed the current status of health data standardization, discussed its vision, mission, and strategies, engaged in short-term standardization activities, and established a governance system for standardization. RESULTS: On September 15, 2023, the notice of "Health Data Terminology and Transmission Standards" in Korea was thoroughly revised to improve the exchange of health information between information systems and ensure interoperability. This notice includes the Korea Core Data for Interoperability (KR CDI) and the Korea Core Data Transmission Standard (HL7 FHIR KR Core), which are outcomes of the taskforce's efforts. Additionally, to reinforce the standardized governance system, the Health-Data Standardization Promotion Committee was established. CONCLUSIONS: Active interest and support from medical informatics experts are needed for the development and widespread adoption of health data standards in Korea.

Clinical Outcomes of Secondary Duodenal Self-Expandable Metallic Stenting for Duodenal Stent Dysfunction in Patients with Malignant Duodenal Obstruction: A Retrospective Multicenter Study.

Background/Aims: Malignant duodenal obstruction has become more common with the development of palliative therapies.The outcomes of endoscopic ultrasound-guided gastrojejunostomy (EUS-GJ) are comparable to those of surgical gastrojejunostomy or duodenal stenting. However, EUS-GJ is technically challenging. Duodenal self-expandable metallic stent (SEMS) placement is popular; however, obstructions are common. Duodenal SEMS obstruction can be managed with the insertion of a second SEMS in a stent-in-stent manner. Therefore, we aimed to analyze the clinical outcomes of secondary duodenal SEMS placement in patients with malignant duodenal obstruction. Methods: We retrospectively analyzed the data of patients who underwent secondary duodenal stent insertion for duodenal stent dysfunction between January 2016 and December 2021. The primary outcome was stent patency. The secondary outcomes were clinical success, factors associated with dysfunction, patient survival, and adverse events. Results: A total of 109 patients were included. The mean age was 64.4±11.2 years, and 63 patients (57.8%) were male. Ninety-two patients (84.4%) had pancreaticobiliary cancer. Clinical success was achieved in 94 cases (86.2%). Twenty-three patients experienced stent dysfunction with 231 days of median stent patency (95% confidence interval [CI], 169 to not available). After a multivariable Cox hazard analysis of stent patency, the Eastern Cooperative Oncology Group performance status (hazard ratio [HR], 2.13; 95% CI, 1.20 to 3.81; p=0.010) and the first stent patency ≥6 months (HR, 0.33; 95% CI, 0.11 to 0.95; p=0.050) remained significant associated factors. Adverse events occurred in five patients (4.6%). Conclusions: Secondary duodenal stent insertion is a viable option for first duodenal stent obstruction. Further comparative studies involving surgery or EUS-GJ for obstructed duodenal stents are warranted.

Deep conditional generative model for longitudinal single-slice abdominal computed tomography harmonization.

Purpose: Two-dimensional single-slice abdominal computed tomography (CT) provides a detailed tissue map with high resolution allowing quantitative characterization of relationships between health conditions and aging. However, longitudinal analysis of body composition changes using these scans is difficult due to positional variation between slices acquired in different years, which leads to different organs/tissues being captured. Approach: To address this issue, we propose C-SliceGen, which takes an arbitrary axial slice in the abdominal region as a condition and generates a pre-defined vertebral level slice by estimating structural changes in the latent space. Results: Our experiments on 2608 volumetric CT data from two in-house datasets and 50 subjects from the 2015 Multi-Atlas Abdomen Labeling Challenge Beyond the Cranial Vault (BTCV) dataset demonstrate that our model can generate high-quality images that are realistic and similar. We further evaluate our method's capability to harmonize longitudinal positional variation on 1033 subjects from the Baltimore longitudinal study of aging dataset, which contains longitudinal single abdominal slices, and confirmed that our method can harmonize the slice positional variance in terms of visceral fat area. Conclusion: This approach provides a promising direction for mapping slices from different vertebral levels to a target slice and reducing positional variance for single-slice longitudinal analysis. The source code is available at: https://github.com/MASILab/C-SliceGen.