Clinical impact and potential utility of non-enhanced computed tomography performed immediately after transarterial chemoembolization for hepatocellular carcinoma.

Background: Intratumoral lipiodol deposition following transarterial chemoembolization (TACE) is associated with the prognosis of hepatocellular carcinoma (HCC) patients. However, there is insufficient evidence regarding the actual clinical significance of the imaging tests conducted to evaluate the lipiodol uptake after TACE. This study evaluates the clinical impact and potential utility of performing immediate post-TACE non-enhanced computed tomography (NECT) on the treatment of HCC. Methods: This retrospective study at a tertiary referral center included patients undergoing their first session of conventional TACE for initial treatment of HCC from November 2021 to December 2022 with available immediate post-TACE NECT. Patients were categorized based on lipiodol uptake into Cohorts A (incomplete uptake with additional treatment before the first follow-up 1 month after TACE), B incomplete uptake without additional treatment before first follow-up), and C (complete uptake). Survival curves for the time to progression (TTP) were estimated using the Kaplan-Meier method and were compared by using the log-rank test. Results: Out of 189 patients, 58 (29.6%) showed incomplete lipiodol uptake; 2 in Cohort A and 56 in Cohort B. Cohort C included 131 patients (69.3%). Cohort B had the highest rate of residual viable tumor (48.2%) 1 month after TACE, compared to the other cohorts (0% in Cohort A and 32.1% in Cohort C). The median TTP of Cohort B was 7.9 months [95% confidence interval (CI): 4.6-15.7 months], significantly shorter than the 15.4 months (95% CI: 10.9-20.9 months) for Cohort C (P=0.03). During follow-up, no progression occurred in Cohort A. Conclusions: Assessment of lipiodol uptake by performing immediate post-TACE NECT can stratify HCC patients and facilitate early prediction of therapeutic response. Identifying suboptimal lipiodol uptake immediately after TACE can aid future treatment adjustments and potentially improving oncologic outcomes.

2023 Survey on User Experience of Artificial Intelligence Software in Radiology by the Korean Society of Radiology.

OBJECTIVE: In Korea, radiology has been positioned towards the early adoption of artificial intelligence-based software as medical devices (AI-SaMDs); however, little is known about the current usage, implementation, and future needs of AI-SaMDs. We surveyed the current trends and expectations for AI-SaMDs among members of the Korean Society of Radiology (KSR). MATERIALS AND METHODS: An anonymous and voluntary online survey was open to all KSR members between April 17 and May 15, 2023. The survey was focused on the experiences of using AI-SaMDs, patterns of usage, levels of satisfaction, and expectations regarding the use of AI-SaMDs, including the roles of the industry, government, and KSR regarding the clinical use of AI-SaMDs. RESULTS: Among the 370 respondents (response rate: 7.7% [370/4792]; 340 board-certified radiologists; 210 from academic institutions), 60.3% (223/370) had experience using AI-SaMDs. The two most common use-case of AI-SaMDs among the respondents were lesion detection (82.1%, 183/223), lesion diagnosis/classification (55.2%, 123/223), with the target imaging modalities being plain radiography (62.3%, 139/223), CT (42.6%, 95/223), mammography (29.1%, 65/223), and MRI (28.7%, 64/223). Most users were satisfied with AI-SaMDs (67.6% [115/170, for improvement of patient management] to 85.1% [189/222, for performance]). Regarding the expansion of clinical applications, most respondents expressed a preference for AI-SaMDs to assist in detection/diagnosis (77.0%, 285/370) and to perform automated measurement/quantification (63.5%, 235/370). Most respondents indicated that future development of AI-SaMDs should focus on improving practice efficiency (81.9%, 303/370) and quality (71.4%, 264/370). Overall, 91.9% of the respondents (340/370) agreed that there is a need for education or guidelines driven by the KSR regarding the use of AI-SaMDs. CONCLUSION: The penetration rate of AI-SaMDs in clinical practice and the corresponding satisfaction levels were high among members of the KSR. Most AI-SaMDs have been used for lesion detection, diagnosis, and classification. Most respondents requested KSR-driven education or guidelines on the use of AI-SaMDs.

Adequacy of Dialysis and Incidence of Atrial Fibrillation in Patients Undergoing Hemodialysis.

BACKGROUND: Atrial fibrillation (AF) can lead to stroke, heart failure, and mortality and has a greater prevalence in dialysis patients than in the general population. Several studies have suggested that uremic toxins may contribute to the development of AF. However, the association between dialysis adequacy and incident AF has not been well established. METHODS: In this retrospective nationwide cohort study, we analyzed data from the Korean National Periodic Hemodialysis Quality Assessment from 2013 to 2015 of patients who received outpatient maintenance hemodialysis 3× a week. The main exposure was single pooled Kt/V (spKt/V), which is the dialysis adequacy index, and the primary outcome was the development of AF. For the primary analysis, patients were categorized into quartiles according to baseline spKt/V. The lowest quartile, representing the lowest adequacy, was used as the reference group. Fine-Gray subdistribution hazard models were used, treating all-cause mortality as a competing risk. RESULTS: Of 25 173 patients, the mean age was 60 (51-69) years, and 14 772 (58.7%) were men. During a median follow-up of 5.7 years, incident AF occurred in a total of 3883 (15.4%) patients. Participants with a higher spKt/V tended to have lower AF incidence. In survival analysis, a graded association was observed between the risk of incident AF and spKt/V quartiles: subdistribution hazard ratios and 95% CIs for the second, third, and the highest quartile compared with the lowest quartile were 0.90 (95% CI, 0.82-0.98), 0.84 (95% CI, 0.77-0.93), and 0.79 (95% CI, 0.72-0.88), respectively. CONCLUSIONS: This nationwide cohort study showed that a higher spKt/V is associated with a reduced risk of incident AF. These findings suggests that reducing uremic toxin burden through enhanced dialysis clearance may be associated with a lower risk of AF development in patients undergoing maintenance hemodialysis.

Analysis on efficacy of magnetic resonance lymphangiography using INV-001 in healthy beagle dogs.

We aimed to conduct a proof-of-concept study of INV-001 in visualizing lymphatic vessels and nodes without venous contamination and to determine the optimal dose condition of INV-001 for magnetic resonance lymphangiography (MRL) in healthy beagles. MRL was performed using a 3.0-Tesla (T) whole body clinical magnetic resonance imaging (MRI) scanner. A dose-finding study of INV-001 for MRL in beagles (N = 6) was carried out according to an adaptive optimal dose finding design. For the reproducibility study (N = 6), MRL was conducted at selected INV-001 doses (0.056 and 0.112 mg Fe/kg) with a 15 mM concentration. Additionally, an excretion study (N = 3) of INV-001 was conducted by analyzing T1, T2, and T2* maps of the liver and kidney 48 h post-administration. INV-001 administration at doses of 0.056 and 0.112 mg Fe/kg (concentration: 15 mM) consistently demonstrated the visualization of contrast-enhanced lymphatic vessels and nodes without venous contamination in the beagles. The contrast enhancement effect was highest at 30 min after INV-001 administration, then gradually decreasing. No toxicity-related issues were identified during the study. After 48 h, the T1, T2, and T2* values in the liver and both kidneys were found to be comparable to the pre-administration values, indicating thorough INV-001 excretion. The optimal dosing conditions of INV-001 for MRL for contrast-enhanced visualization of lymphatic vessels and nodes exclusively with no venous contamination in beagles was determined to be 0.056 mg Fe/kg with a 15 mM concentration.

Oligohydramnios affects pulmonary functional/structural abnormalities in school-aged children with bronchopulmonary dysplasia.

BACKGROUND: The relationship between early life factors and childhood pulmonary function and structure in preterm infants remains unclear. PURPOSE: This study investigated the impact of bronchopulmonary dysplasia (BPD) and perinatal factors on childhood pulmonary function and structure. METHODS: This longitudinal cohort study included preterm participants aged ≥5 years born between 2005 and 2015. The children were grouped by BPD severity according to National Institutes of Health criteria. Pulmonary function tests (PFTs) were performed using spirometry. Chest computed tomography (CT) scans were obtained and scored for hyperaeration or parenchymal lesions. PFT results and chest CT scores were analyzed with perinatal factors. RESULTS: A total 150 children (66 females) aged 7.7 years (6.4-9.9 years) were categorized into non/mild BPD (n=68), moderate BPD (n=39), and severe BPD (n=43) groups. The median z score for forced expiratory volume in 1 second (FEV1), forced vital capacity (FVC), FEV1/FVC ratio, and forced midexpiratory flow (FEF25%-75%) were significantly lower in the severe versus non/mild BPD group (-1.24 vs. -0.18, -0.22 vs. 0.41, -1.80 vs. -1.12, and -1.88 vs. -1.00, respectively; all P<0.05). The median z scores of FEV1, FEV1/ FVC, and FEF25%-75% among asymptomatic patients were also significantly lower in the severe versus non/mild BPD group (-0.82 vs. 0.09, -1.68 vs. -0.87, -1.59 vs. -0.61, respectively; all P<0.05). The severe BPD group had a higher median (range) CT score than the non/mild BPD group (6 [0-12] vs. 1 [0-10], P<0.001). Prenatal oligohydramnios was strongly associated with both low pulmonary function (FEV1/FVC

Pulmonary function characteristics in children with suspected asthma: implications for asthma diagnosis.

BACKGROUND: In children suspected of asthma, diagnosis is confirmed via variable expiratory airflow limitation. However, there is no single gold standard test for diagnosing asthma. OBJECTIVE: This study aimed to evaluate the pulmonary function characteristics in children suspected of asthma without bronchodilator response (BDR) and bronchial hyperresponsiveness (BHR). METHODS: We utilized two separate real-world retrospective observational cohorts of children who underwent both spirometry and bronchial provocation testing for asthma. Spirometry parameters were collected and compared between definite asthma, probable asthma, and non-asthma groups. The original cohort comprised 1199 children who visited the Severance Hospital (Seoul, Korea) between January 2017 and December 2019. The external cohort included 105 children who visited the Gangnam Severance Hospital between January 2019 and December 2019. RESULTS: Probable asthma accounted for 16.8% and 32.4% of the original and external cohorts, respectively. This group showed a significantly higher FeNO level and prevalence of allergic sensitization. Baseline forced expiratory volume in 1 second (FEV1), FEV1/forced vital capacity (FVC), forced expiratory flow at 25-75% of FVC (FEF25-75), and FEF75 showed stepwise decrements from non-asthma, probable asthma, to definite asthma patients (P < 0.001). The probable asthma group showed significantly higher odds of abnormal FEV1/FVC (OR, 2.24 [95%CI, 1.43-3.52])and FEF25-75 (2.05 [1.13-3.73]) than the non-asthma group and lower odds of abnormal FEV1(0.05 [0.01-0.19]),FEV1 /FVC (0.27 [0.18-0.41]), FEF25-75 (0.17 [0.11-0.28]), and FEF75 (0.14 [0.08-0.24]) compared to the definite asthma group. The external cohort was consistent with the original cohort. CONCLUSION: We show evidence of airway dysfunction in children for whom a high clinical suspicion of asthma exists without evidence of BDR and BHR. Repeated pulmonary function tests that closely monitor for subtle lung function impairments and active utilization of additional tests, such as allergic screening and FeNO, should be considered to close the gap in diagnosing asthma.

Comparison of the Pharmacokinetics of Gadolinium-Based and Iron Oxide-Based Contrast Agents inside the Lymphatic Structure using Magnetic Resonance Lymphangiography.

PURPOSE: Gadolinium (Gd)-based contrast agents are primarily used for contrast-enhanced magnetic resonance lymphangiography (MRL). However, overcoming venous contamination issues remains challenging. This study aims to assess the MRL efficacy of the newly developed iron-based contrast agent (INV-001) that is specially designed to mitigate venous contamination issues. The study further explores the optimal dosage, including both injection volume and concentration, required to achieve successful visualization of the popliteal lymph nodes and surrounding lymphatic vessels. PROCEDURES: All animals utilized in this study were male Sprague-Dawley (SD) rats weighing between 250 and 300 g. The contrast agents prepared were injected intradermally in the fourth phalanx of both hind limbs using a 30-gauge syringe in SD rats. MRL was performed every 16 min on a coronal 3D time-of-flight sequence with saturation bands using a 9.4-T animal machine. RESULTS: Contrary to Gd-DOTA, which exhibited venous contamination in most animals irrespective of injection dosages and conditions, INV-001 showed no venous contamination. For Gd-DOTA, the popliteal lymph nodes and lymphatic vessels reached peak enhancement 16 min after injection from the injection site and then rapidly washed out. However, with INV-001, they reached peak enhancement between 16 and 32 min after injection, with prolonged visualization of the popliteal lymph node and lymphatic vessels. INV-001 at 0.45 µmol (15 mM, 30 µL) and 0.75 µmol (15 mM, 50 µL) achieved high scores for qualitative image analysis, providing good visualization of the popliteal lymph nodes and lymphatic vessels without issues of venous contamination, interstitial space enhancement, or lymph node enlargement. CONCLUSION: In MRL, INV-001, a novel T1 contrast agent based on iron, enables prolonged enhancement of popliteal lymph nodes and lymphatic vessels without venous contamination.

Whole Process of Standardization of Diffusion-Weighted Imaging: Phantom Validation and Clinical Application According to the QIBA Profile.

Background: To use the apparent diffusion coefficient (ADC) as reliable biomarkers, validation of MRI equipment performance and clinical acquisition protocols should be performed prior to application in patients. This study aims to validate various MRI equipment and clinical brain protocols for diffusion weighted imaging (DWI) using commercial phantom, and confirm the validated protocols in patients' images. Methods: The performance of four different scanners and clinical brain protocols were validated using a Quantitative Imaging Biomarker Alliance (QIBA) diffusion phantom and cloud-based analysis tool. We evaluated the performance metrics regarding accuracy and repeatability of ADC measurement using QIBA profile. The validated clinical brain protocols were applied to 17 patients, and image quality and repeatability of ADC were assessed. Results: The MRI equipment performance of all four MRI scanners demonstrated high accuracy in ADC measurement (ADC bias, -2.3% to -0.4%), excellent linear correlation to the reference ADC value (slope, 0.9 to 1.0; R2, 0.999-1.000), and high short-term repeatability [within-subject-coefficient-of-variation (wCV), 0% to 0.3%]. The clinical protocols were also validated by fulfilling QIBA claims with high accuracy (ADC bias, -3.1% to -0.7%) and robust repeatability (wCV, 0% to 0.1%). Brain DWI acquired using the validated clinical protocols showed ideal image quality (mean score ≥ 2.9) and good repeatability (wCV, 1.8-2.2). Conclusions: The whole process of standardization of DWI demonstrated the robustness of ADC with high accuracy and repeatability across diverse MRI equipment and clinical protocols in accordance with the QIBA claims.

Predicting the Outcome of Pediatric Oral Food Challenges for Determining Tolerance Development.

PURPOSE: Despite the risk of anaphylaxis, oral food challenges (OFCs) are performed clinically for various indications, particularly to confirm tolerance development. This study aimed to assess OFCs by relevant indications and build an outcome prediction model to help determine when to perform OFCs in children who are likely to have developed immune tolerance. METHODS: In total, 432 pediatric OFCs were retrospectively analyzed according to indications. Clinical characteristics, serum total immunoglobulin (Ig) E, blood eosinophils, and specific IgE and IgG4 levels for food allergens were noted and compared. Machine learning was utilized to select the most important variables in determining the passage of the OFCs, and prediction models were constructed using the selected variables. RESULTS: OFCs were most commonly performed to confirm tolerance development (number, %; 267, 61.8%). The most common food allergens tested were egg (191, 44.2%) and milk (135, 31.3%). Children who passed the egg challenges for confirming tolerance acquisition had significantly lower egg white-specific IgE level (P = 0.008). Similarly, those who passed milk challenges had significantly lower cow's milk-specific IgE (P = 0.002) and casein-specific IgE levels (P = 0.005). We developed a nomogram to predict the outcome of OFCs to determine the tolerance acquisition with the selected variables; lower food-specific IgE, higher total IgE, and younger age indicated a higher probability of passage. The area under the curve (95% confidence interval) was 0.623 (0.503-0.743) for egg and 0.734 (0.628-0.840) for milk. CONCLUSIONS: Serum total IgE and food-specific IgE combined with age showed trends toward passing OFCs for confirming tolerance development. The constructed model may be used by clinicians as a practical guide for minimizing the risks of OFCs and a timely reintroduction for children with food allergies.

Activated Leukocyte Cell Adhesion Molecule Regulates the Expression of Interleukin-33 in RSV Induced Airway Inflammation by Regulating MAPK Signaling Pathways.

PURPOSE: The respiratory syncytial virus (RSV) is a common respiratory virus that causes acute lower respiratory tract infectious diseases, particularly in young children and older individuals. Activated leukocyte cell adhesion molecule (ALCAM) is a membrane glycoprotein expressed in various cell types, including epithelial cells, and is associated with inflammatory responses and various cancers. However, the precise role of ALCAM in RSV-induced airway inflammation remains unclear, and our study aimed to explore this gap in the literature. METHODS: C57BL/6 wild-type, ALCAM knockout mice and airway epithelial cells were infected with RSV and the expression of ALCAM and inflammatory cytokines were measured. We also conducted further experiments using Anti-ALCAM antibody and recombinant ALCAM in airway epithelial cells. RESULTS: The expression levels of ALCAM and inflammatory cytokines increased in both RSV-infected mice and airway epithelial cells. Interestingly, IL-33 expression was significantly reduced in ALCAM-knockdown cells compared to control cells following RSV infection. Anti-ALCAM antibody treatment also reduced IL-33 expression following RSV infection. Furthermore, the phosphorylation of ERK1/2, p38, and JNK was diminished in ALCAM-knockdown cells compared to control cells following RSV infection. Notably, in the control cells, inhibition of these pathways significantly decreased the expression of IL-33. In vivo study also confirmed a reduction in inflammation induced by RSV infection in ALCAM deficient mice compared to wild-type mice. CONCLUSION: These findings demonstrate that ALCAM contributes to RSV-induced airway inflammation at least partly by influencing IL-33 expression through mitogen-activated protein kinase signaling pathways. These results suggest that targeting ALCAM could be a potential therapeutic strategy for alleviating IL-33-associated lung diseases.

Deep learning-based prediction of post-pancreaticoduodenectomy pancreatic fistula.

Postoperative pancreatic fistula is a life-threatening complication with an unmet need for accurate prediction. This study was aimed to develop preoperative artificial intelligence-based prediction models. Patients who underwent pancreaticoduodenectomy were enrolled and stratified into model development and validation sets by surgery between 2016 and 2017 or in 2018, respectively. Machine learning models based on clinical and body composition data, and deep learning models based on computed tomographic data, were developed, combined by ensemble voting, and final models were selected comparison with earlier model. Among the 1333 participants (training, n = 881; test, n = 452), postoperative pancreatic fistula occurred in 421 (47.8%) and 134 (31.8%) and clinically relevant postoperative pancreatic fistula occurred in 59 (6.7%) and 27 (6.0%) participants in the training and test datasets, respectively. In the test dataset, the area under the receiver operating curve [AUC (95% confidence interval)] of the selected preoperative model for predicting all and clinically relevant postoperative pancreatic fistula was 0.75 (0.71-0.80) and 0.68 (0.58-0.78). The ensemble model showed better predictive performance than the individual ML and DL models.

Limitations of the Cough Sound-Based COVID-19 Diagnosis Artificial Intelligence Model and its Future Direction: Longitudinal Observation Study.

BACKGROUND: The outbreak of SARS-CoV-2 in 2019 has necessitated the rapid and accurate detection of COVID-19 to manage patients effectively and implement public health measures. Artificial intelligence (AI) models analyzing cough sounds have emerged as promising tools for large-scale screening and early identification of potential cases. OBJECTIVE: This study aimed to investigate the efficacy of using cough sounds as a diagnostic tool for COVID-19, considering the unique acoustic features that differentiate positive and negative cases. We investigated whether an AI model trained on cough sound recordings from specific periods, especially the early stages of the COVID-19 pandemic, were applicable to the ongoing situation with persistent variants. METHODS: We used cough sound recordings from 3 data sets (Cambridge, Coswara, and Virufy) representing different stages of the pandemic and variants. Our AI model was trained using the Cambridge data set with subsequent evaluation against all data sets. The performance was analyzed based on the area under the receiver operating curve (AUC) across different data measurement periods and COVID-19 variants. RESULTS: The AI model demonstrated a high AUC when tested with the Cambridge data set, indicative of its initial effectiveness. However, the performance varied significantly with other data sets, particularly in detecting later variants such as Delta and Omicron, with a marked decline in AUC observed for the latter. These results highlight the challenges in maintaining the efficacy of AI models against the backdrop of an evolving virus. CONCLUSIONS: While AI models analyzing cough sounds offer a promising noninvasive and rapid screening method for COVID-19, their effectiveness is challenged by the emergence of new virus variants. Ongoing research and adaptations in AI methodologies are crucial to address these limitations. The adaptability of AI models to evolve with the virus underscores their potential as a foundational technology for not only the current pandemic but also future outbreaks, contributing to a more agile and resilient global health infrastructure.

Mapping Changes in Glutamate with Glutamate-Weighted MRI in Forced Swim Test Model of Depression in Rats.

Chemical exchange saturation transfer with glutamate (GluCEST) imaging is a novel technique for the non-invasive detection and quantification of cerebral Glu levels in neuromolecular processes. Here we used GluCEST imaging and 1H magnetic resonance spectroscopy (1H MRS) to assess in vivo changes in Glu signals within the hippocampus in a rat model of depression induced by a forced swim test. The forced swimming test (FST) group exhibited markedly reduced GluCEST-weighted levels and Glu concentrations when examined using 1H MRS in the hippocampal region compared to the control group (GluCEST-weighted levels: 3.67 ± 0.81% vs. 5.02 ± 0.44%, p < 0.001; and Glu concentrations: 6.560 ± 0.292 µmol/g vs. 7.133 ± 0.397 µmol/g, p = 0.001). Our results indicate that GluCEST imaging is a distinctive approach to detecting and monitoring Glu levels in a rat model of depression. Furthermore, the application of GluCEST imaging may provide a deeper insight into the neurochemical involvement of glutamate in various psychiatric disorders.

Prognostic value of CT-based radiomics in grade 1-2 pancreatic neuroendocrine tumors.

BACKGROUND: Surgically resected grade 1-2 (G1-2) pancreatic neuroendocrine tumors (PanNETs) exhibit diverse clinical outcomes, highlighting the need for reliable prognostic biomarkers. Our study aimed to develop and validate CT-based radiomics model for predicting postsurgical outcome in patients with G1-2 PanNETs, and to compare its performance with the current clinical staging system. METHODS: This multicenter retrospective study included patients who underwent dynamic CT and subsequent curative resection for G1-2 PanNETs. A radiomics-based model (R-score) for predicting recurrence-free survival (RFS) was developed from a development set (441 patients from one institution) using least absolute shrinkage and selection operator-Cox regression analysis. A clinical model (C-model) consisting of age and tumor stage according to the 8th American Joint Committee on Cancer staging system was built, and an integrative model combining the C-model and the R-score (CR-model) was developed using multivariable Cox regression analysis. Using an external test set (159 patients from another institution), the models' performance for predicting RFS and overall survival (OS) was evaluated using Harrell's C-index. The incremental value of adding the R-score to the C-model was evaluated using net reclassification improvement (NRI) and integrated discrimination improvement (IDI). RESULTS: The median follow-up periods were 68.3 and 59.7 months in the development and test sets, respectively. In the development set, 58 patients (13.2%) experienced recurrence and 35 (7.9%) died. In the test set, tumors recurred in 14 patients (8.8%) and 12 (7.5%) died. In the test set, the R-score had a C-index of 0.716 for RFS and 0.674 for OS. Compared with the C-model, the CR-model showed higher C-index (RFS, 0.734 vs. 0.662, p = 0.012; OS, 0.781 vs. 0.675, p = 0.043). CR-model also showed improved classification (NRI, 0.330, p < 0.001) and discrimination (IDI, 0.071, p < 0.001) for prediction of 3-year RFS. CONCLUSIONS: Our CR-model outperformed the current clinical staging system in prediction of the prognosis for G1-2 PanNETs and added incremental value for predicting postoperative recurrence. The CR-model enables precise identification of high-risk patients, guiding personalized treatment planning to improve outcomes in surgically resected grade 1-2 PanNETs.

Identification of acute myocardial infarction and stroke events using the National Health Insurance Service database in Korea.

OBJECTIVES: The escalating burden of cardiovascular disease (CVD) is a critical public health issue worldwide. CVD, especially acute myocardial infarction (AMI) and stroke, is the leading contributor to morbidity and mortality in Korea. We aimed to develop algorithms for identifying AMI and stroke events from the National Health Insurance Service (NHIS) database and validate these algorithms through medical record review. METHODS: We first established a concept and definition of "hospitalization episode," taking into account the unique features of health claims-based NHIS database. We then developed first and recurrent event identification algorithms, separately for AMI and stroke, to determine whether each hospitalization episode represents a true incident case of AMI or stroke. Finally, we assessed our algorithms' accuracy by calculating their positive predictive values (PPVs) based on medical records of algorithm- identified events. RESULTS: We developed identification algorithms for both AMI and stroke. To validate them, we conducted retrospective review of medical records for 3,140 algorithm-identified events (1,399 AMI and 1,741 stroke events) across 24 hospitals throughout Korea. The overall PPVs for the first and recurrent AMI events were around 92% and 78%, respectively, while those for the first and recurrent stroke events were around 88% and 81%, respectively. CONCLUSIONS: We successfully developed algorithms for identifying AMI and stroke events. The algorithms demonstrated high accuracy, with PPVs of approximately 90% for first events and 80% for recurrent events. These findings indicate that our algorithms hold promise as an instrumental tool for the consistent and reliable production of national CVD statistics in Korea.

Allergic rhinitis phenotypes with distinct transcriptome profiles in children: A birth cohort.

BACKGROUND: Allergic rhinitis (AR) phenotypes in childhood are unclear. OBJECTIVES: This study sought to determine AR phenotypes and investigate their natural course and clinical and transcriptomic characteristics. METHODS: Latent class trajectory analysis was used for phenotyping AR in 1050 children from birth through 12 years using a birth cohort study. Blood transcriptome analyses were performed to define the underlying mechanisms of each phenotype. RESULTS: Five AR phenotypes were identified: early onset (n = 88, 8.4%), intermediate transient (n = 110, 10.5%), late onset (n = 209, 19.9%), very late onset (n=187, 17.8%), and never/infrequent (n = 456, 43.4%). Children with early-onset AR were associated with higher AR severity and sensitizations to foods at age 1 year and inhalants at age 3 years and asthma symptoms, but not with bronchial hyperresponsiveness (BHR). Children with late-onset AR phenotype associated with sensitizations to various foods at age 1 year but not from age 3 years, and to inhalants from age 7 years and with asthma with BHR. Children with very late-onset AR phenotype associated with sensitizations to foods throughout preschool age and to inhalants at ages 7 and 9 years and with asthma with BHR. Transcriptome analysis showed that early-onset AR was associated with viral/bacterial infection-related defense response, whereas late-onset AR was associated with T cell-related immune response. CONCLUSIONS: Early-onset AR phenotype was associated with sensitization to foods and inhalants at an early age and asthma symptoms, but not with BHR, whereas very late- and late-onset AR phenotypes were positively associated with sensitization to inhalants and asthma with BHR. Transcriptomic analyses indicated that early- and late-onset AR phenotypes had distinct underlying mechanisms related to AR as well.

Clinicoradiological Factors Predicting Lymph Node Metastasis in Patients with Nonfunctioning Pancreatic Neuroendocrine Neoplasms: A Systematic Review and Meta-Analysis.

INTRODUCTION: Lymph node metastasis of nonfunctioning pancreatic neuroendocrine neoplasms (pNENs) potentially leads to poor survival. Given the contradictory results in the literature regarding factors associated with lymph node metastasis of nonfunctioning pNENs, we conducted a systematic review and meta-analysis to determine the preoperative predictors of lymph node metastasis. METHODS: Original studies reporting factors associated with lymph node metastasis in patients with nonfunctioning pNENs were identified in PubMed, EMBASE, and Cochrane Library databases, and data from eligible studies were analyzed using random-effects meta-analysis to obtain pooled estimates of odds ratios (ORs) and their 95% confidence intervals (CIs). RESULTS: Eleven studies were included. Tumor size (>2 cm or >2.5 cm; OR, 5.80 [95% CI, 4.07-8.25]) and pancreatic head location (OR, 1.75 [95% CI, 1.05-2.94]) were significant preoperative predictors of lymph node metastasis. Old age (OR, 1.07 [95% CI, 0.68-1.68]) and male sex (OR, 1.12 [95% CI, 0.74-1.70]) were not significantly associated with lymph node metastasis. CONCLUSIONS: A large tumor size and pancreatic head location can be useful for planning optimal treatment in patients with nonfunctioning pNENs.

Insights from the COCOA birth cohort: The origins of childhood allergic diseases and future perspectives.

The ongoing COhort for Childhood Origin of Asthma and allergic diseases (COCOA) study is a prospective birth cohort investigating the origin and natural courses of childhood allergic diseases, including atopic dermatitis, food allergy, allergic rhinitis and asthma, with long-term prognosis. Initiated under the premise that allergic diseases result from a complex interplay of immune development alterations, environmental exposures, and host susceptibility, the COCOA study explores these dynamic interactions during prenatal and postnatal periods, framed within the hygiene and microbial hypotheses alongside the developmental origins of health and disease (DOHaD) hypothesis. The scope of the COCOA study extends to genetic predispositions, indoor and outdoor environmental variables affecting mothers and their offsprings such as outdoor and indoor air pollution, psychological factors, diets, and the microbiomes of skin, gut, and airway. We have embarked on in-depth investigations of diverse risk factors and the pathophysiological underpinnings of allergic diseases. By employing multi-omics approaches-proteomics, transcriptomics, and metabolomics-we gain deeper insights into the distinct pathophysiological processes across various endotypes of childhood allergic diseases, incorporating the exposome using extensive resources within the COCOA study. Integration with large-scale datasets, such as national health insurance records, enhances robustness and mitigates potential limitations inherent to birth cohort studies. As part of global networks focused on childhood allergic diseases, the COCOA study fosters collaborative research across multiple cohorts. The findings from the COCOA study are instrumental in informing precision medicine strategies for childhood allergic diseases, underpinning the establishment of disease trajectories.

Nanoplastics exacerbate Parkinson's disease symptoms in C. elegans and human cells.

The increasing prevalence of nanoplastics in our environment due to the widespread use of plastics poses potential health risks that are not yet fully understood. This study examines the physiological and neurotoxic effects of these minuscule nanoplastic particles on the nematode Caenorhabditis elegans as well as on human cells. Here, we find that 25 nm polystyrene nanoplastic particles can inhibit animal growth and movement at very low concentrations, with varying effects on their surface groups. Furthermore, these nanoplastic particles not only accumulate in the digestive tract but also penetrate further into extraintestinal tissues. Such nanoplastics significantly compromise the integrity of the intestinal barrier, leading to "leaky gut" conditions and cause mitochondrial fragmentation in muscles, which possibly explains the observed movement impairments. A striking discovery was that these nanoplastics exacerbate symptoms similar to those of Parkinson's disease (PD), including dopaminergic neuronal degeneration, locomotor dysfunction, and accumulation of α-Synuclein aggregates. Importantly, our study demonstrates that the detrimental effects of nanoplastics on the aggregation of α-Synuclein extend to both C. elegans and human cell models of PD. In conclusion, our research highlights the potential health hazards linked to the physicochemical properties of nanoplastics, underlining the urgency of understanding their interactions with biological systems. ENVIRONMENTAL IMPLICATION: The escalating prevalence of nanoplastics in the environment due to widespread plastic usage raises potential health risks. Studies conducted on C. elegans indicate that even low concentrations of 25 nm polystyrene nanoplastics can impair growth and movement. These particles accumulate in the digestive system, compromising the intestinal barrier, causing "leaky gut", as well as inducing Parkinson's-like symptoms. Importantly, in both C. elegans and human cell models of Parkinson's disease, such nanoplastics penetrate tissues or cells and increase α-Synuclein aggregates. This underscores the urgent need to understand the interactions of nanoplastics with biological systems and highlights potential environmental and health consequences.