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Antithrombotic agents, including antiplatelet agents and anticoagulants, are widely used in Korea because of the increasing incidence of cardiocerebrovascular disease and the aging population. The management of patients using antithrombotic agents during endoscopic procedures is an important clinical challenge. The clinical practice guidelines for this issue, developed by the Korean Society of Gastrointestinal Endoscopy, were published in 2020. However, new evidence on the use of dual antiplatelet therapy and direct anticoagulant management has emerged, and revised guidelines have been issued in the United States and Europe. Accordingly, the previous guidelines were revised. Cardiologists were part of the group that developed the guideline, and the recommendations went through a consensus-reaching process among international experts. This guideline presents 14 recommendations made based on the Grading of Recommendations, Assessment, Development, and Evaluation methodology and was reviewed by multidisciplinary experts. These guidelines provide useful information that can assist endoscopists in the management of patients receiving antithrombotic agents who require diagnostic and elective therapeutic endoscopy. It will be revised as necessary to cover changes in technology, evidence, or other aspects of clinical practice.

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AIM: Sudden cardiac arrest is a global health issue, with out-of-hospital cardiac arrest (OHCA) posing a major challenge. Bystander cardiopulmonary resuscitation (CPR) and automated external defibrillators (AEDs) improve survival and neurological outcomes. However, their actual usage involves numerous constraints. Therefore, to determine the association between bystander AED use and survival of patients with OHCA, we analyzed South Korea's national OHCA database. METHODS: This retrospective study included cases from the Korea Disease Control and Prevention Agency's Out-of-Hospital Cardiac Arrest Surveillance database from January 2016 to December 2021. Adult OHCA cases treated with bystander intervention were categorized into two groups, CPR with AEDs and without AEDs. Propensity score matching was employed to control for confounders and analyze bystander AED use's impact on survival to discharge and neurological outcomes. RESULTS: Of 182,508 OHCA cases, 35,840 met the inclusion criteria, with 234 (0.7%) receiving bystander CPR with AEDs. The survival rate to discharge in the AED and non-AED group was 46.6% and 23.0%, respectively. However, after adjusting for potential confounders, bystander AED use did not significantly affect survival to discharge (adjusted odds ratio [aOR] 1.01, 95% confidence interval [CI] 0.70-1.44) or favorable neurological outcomes (aOR 1.08, 95% CI 0.99-1.18). CONCLUSION: Survival to discharge or favorable neurological outcomes of patients with OHCA managed using bystander-applied AEDs and those without showed no significant difference. Factors such as AED accessibility and bystander preparedness influence the impact of bystander AED use. Further research should optimize AED deployment and usage strategies to enhance patient survival rate.

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This research introduces a vascular phenotypic and proteomic analysis (VPT) platform designed to perform high-throughput experiments on vascular development. The VPT platform utilizes an open-channel configuration that facilitates angiogenesis by precise alignment of endothelial cells, allowing for a 3D morphological examination and protein analysis. We study the effects of antiangiogenic agents─bevacizumab, ramucirumab, cabozantinib, regorafenib, wortmannin, chloroquine, and paclitaxel─on cytoskeletal integrity and angiogenic sprouting, observing an approximately 50% reduction in sprouting at higher drug concentrations. Precise LC-MS/MS analyses reveal global protein expression changes in response to four of these drugs, providing insights into the signaling pathways related to the cell cycle, cytoskeleton, cellular senescence, and angiogenesis. Our findings emphasize the intricate relationship between cytoskeletal alterations and angiogenic responses, underlining the significance of integrating morphological and proteomic data for a comprehensive understanding of angiogenesis. The VPT platform not only advances our understanding of drug impacts on vascular biology but also offers a versatile tool for analyzing proteome and morphological features across various models beyond blood vessels.

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PURPOSE: This study investigated radiologic features on preoperative MRI to differentiate urothelial carcinoma with squamous differentiation (UCSD) from conventional urothelial carcinoma (UC) in muscle-invasive bladder carcinoma. METHODS: Ninety-nine patients who underwent radical cystectomy and a preoperative bladder MRI scan within three months before surgery were retrospectively enrolled. Various MRI features, including tumor length, location, multiplicity, long-to-short axis ratio, morphology, radiologic stage, and degree of severe necrosis, were analyzed. Univariable and multivariable logistic regression analyses were performed to identify MRI features predictive of UCSD. The diagnostic performance of a significant MRI feature was assessed using 5-fold cross-validation. RESULTS: Among the MRI features, significant radiologic findings associated with UCSD in the univariable analysis included heterogeneous tumor signal intensity in T2-weighted images (odds ratio [OR], 3.365; 95% confidence interval [CI], 1.213-9.986; P = 0.022) and contrast-enhanced T1-weighted images (OR, 4.428; 95% CI, 1.519-12.730; P = 0.007), as well as marked (≥ 50%) severe necrosis (OR, 17.100; 95% CI, 4.699-73.563; P < 0.001). In the multivariable analysis, marked (≥ 50%) severe necrosis (odds ratio [OR], 13.755; 95% confidence interval [CI], 2.796-89.118; P = 0.004) was a significant predictor of UCSD. Marked (≥ 50%) severe necrosis showed a high specificity of 95.0% with a precision of 65.0% for diagnosing UCSD based on 5-fold cross-validation. CONCLUSION: Preoperative bladder MRI revealing marked severe necrosis may be indicative of UCSD and can assist in distinguishing it from conventional UC.

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OBJECTIVE: Previous reports suggest that a high body mass index (BMI) increases the risk of thyroid carcinoma. However, it remains unclear whether a high BMI is associated with the risk of BRAFV600E mutation. We aimed to assess whether a high BMI is associated with an increased risk of BRAFV600E mutation. DESIGN AND METHODS: We screened 6,558 PTC patients who had undergone BRAFV600E mutation testing between January 2009 and December 2017. After exclusion, 6,438 PTC patients were enrolled. We used logistic regression, and restricted cubic spline plots of the adjusted odd ratios (ORs) were illustrated to model the relationship between BMI and BRAFV600E mutation. RESULTS: Among the 6,438 patients, 5,102 (79.2%) had the BRAFV600E mutation, and 4,954 (76.9%) were female. The median BMI was 23.8 (21.6 - 26.2) kg/m2. The primary tumor size was ≤ 1cm in 4,226 patients (65.6 %) and > 1cm in 2,212 patients (34.4 %). The BRAFV600E mutation was significantly associated with high BMI only in patients with primary tumor size > 1cm (OR 1.034; 95% CI 1.003 - 1.065; P = 0.029), whereas no clear association was found in patients with primary tumor size ≤ 1cm (OR 1.007; 95% CI 0.984 - 1.030; P = 0.570). Gender was not a significant factor in either group. CONCLUSIONS: Our study found that a higher BMI was positively associated with BRAFV600E mutation in patients with primary tumor size > 1cm. These results suggest that the association between BMI and BRAFV600E mutation status differs depending on primary tumor size.

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Acanthamoeba keratitis (AK) is a sight-threatening and difficult-to-treat ocular infection. The significant side effects of current AK treatments highlight the urgent need to develop a safe and effective AK medication. In this study, the amoebicidal activity of Iris setosa Pall. ex Link extract (ISE) against Acanthamoeba was examined and its specific amoebicidal mechanism was explored. ISE induced significant morphological changes in Acanthamoeba trophozoites and exhibited amoebicidal activity against A. castellanii and A. polyphaga. ISE was further fractionated into five subfractions by sequential extraction with n-hexane, chloroform, ethyl acetate, n-butanol, and water, and their amoebicidal activities and underlying amoebicidal mechanisms were investigated. The n-butanol subfraction of ISE (ISE-BuOH) displayed selective amoebicidal activity against the Acanthamoeba species with minimal cytotoxicity in human corneal cells (HCE-2). ISE-BuOH triggered apoptosis-like programmed cell death (PCD) in amoebae, characterized by DNA fragmentation, increased ROS production, and caspase-3 activity elevation. ISE-BuOH also demonstrated a partial cysticidal effect against the amoeba species. ISE-BuOH could be a promising candidate in the development of therapeutic drugs for AK.

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This study aimed to establish a deep learning-based predictive model for the prognosis of idiopathic sudden sensorineural hearing loss (SSNHL). Data from 1108 patients with SSNHL between January 2015 and May 2023 were retrospectively analyzed. Patients underwent standardized treatment protocols including high-dose steroid therapy and hearing outcomes were assessed after three months using Siegel's criteria and the American Academy of Otolaryngology-Head and Neck Surgery (AAO-HNS) classification. For predicting patient recovery, a two-layered classification process was implemented. Initially, a set of 22 Multilayer Perceptrons (MLP) networks was employed to categorize the patients. The outcomes from this initial categorization were subsequently relayed to a second-layer meta-classifier for final prognosis determination. The validity of this methodology was ascertained through a K-fold cross-validation procedure executed with 10 distinct splits. The prediction model for complete recovery, based on Siegel's criteria, demonstrated an accuracy of 0.892 and area under the curve (AUC) of 0.922. For the class A prediction, according to AAO-HNS classification, the model showed an accuracy of 0.847 and AUC of 0.918. These results suggest that the model may have the potential to contribute to the establishment of tailored patient management strategies by predicting hearing recovery in patients with SSNHL.

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INTRODUCTION: The widely employed Kidney Donor Profile Index (KDPI) scoring system, designed for assessing deceased donors (DD), plays a pivotal role in predicting graft function post kidney transplantation (KT). Given the dynamic nature of renal function, including serum creatinine (sCr), in managing DDs, it remains uncertain optimal timing to use KDPI for assessing postoperative graft function. METHODS: In this retrospective review, we assessed 246 DDs who were managed within a donor management program from January 2010 to December 2021. We collected sCr values for KDPI scoring at admission, peak, and last measurements before KT. Recipient data included occurrence of slow graft function (SGF), delayed graft function (DGF), and glomerular filtration rate (GFR) at one-year post-transplantation (1 Y). Using Receiver Operating Characteristic (ROC) and Pearson correlation analyses, we explored correlations of KDPI score (admission, peak, last) with graft function (SGF, DGF, GFR 1 Y). RESULTS: The average age of DDs and recipients was 49.78 ± 13.37 and 52.54 ± 10.49 years, respectively, with mean KDPI values at admission, peak, and last measurements of 62.36 ± 25.44, 66.94 ± 24.73, and 63.75 ± 25.80. After transplantation, SGF was observed in 81 recipients (32.9%) and DGF in 32 (13.0%). For SGF, the Area Under the Curve (AUC) from ROC analysis were 0.684 (95% CI, 0.615-0.753; P < .001) at admission, 0.691 (0.623-0.759; P < .001) at peak, and 0.697 (0.630-0.765; P < .001) at the last measurement. In predicting DGF, the corresponding AUC values were 0.746 (0.661-0.831; P < .001) at admission, 0.724 (0.637-0.810; P < .001) at peak, and 0.721 (0.643-0.809; P < .001) at the last. Moreover, KDPI scores at all time points-admission, peak, and last-moderately correlated with GFR 1 Y (R = -0.426, -0.423, -0.417). CONCLUSION: KDPI measurements at all time points, particularly admission, would be more effective in predicting DGF in DDKT.

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Telomerase reverse transcriptase (TERT) promoter mutations are associated with tumor aggressiveness. This study aimed to demonstrate the ultrasonographic (US) features of TERT promoter-mutated follicular thyroid cancer (FTC) and evaluate their predictive performance. A total of 63 patients with surgically confirmed FTC between August 1995 and April 2021 were included. All data were available for analysis of preoperative US findings and TERT promoter mutation results. Genomic DNA was extracted from the archived surgical specimens to identify TERT promoter mutations. Logistic regression analysis was performed to compare US findings between TERT promoter-mutated and wild-type FTCs. Of the 63 patients with FTC, 10 (15.9%) had TERT promoter mutations. TERT promoter-mutated FTCs demonstrated significantly different US suspicion categories compared to wild-type FTCs (Ps = 0.0054 for K-TIRADS and 0.0208 for ACR-TIRADS), with a trend toward an increasing prevalence of the high suspicion category (40.0% for both K-TIRADS and ACR-TIRADS; Ps for trend = 0.0030 for K-TIRADS and 0.0032 for ACR-TIRADS). Microlobulated margins and punctate echogenic foci were independent risk factors associated with TERT promoter mutation in FTC (odds ratio = 9.693, 95% confidence interval = 1.666-56.401, p = 0.0115 for margins; odds ratio = 8.033, 95% confidence interval = 1.424-45.309, p = 0.0182 for punctate echogenic foci). There were no significant differences in the composition and echogenicity of the TERT promoter-mutated and wild-type FTCs. TERT promoter-mutated FTCs were categorized more frequently as high suspicion by the K-TIRADS and ACR-TIRADS. Based on US findings, the independent risk factors for TERT promoter mutations in FTC are microlobulated margins and punctate echogenic foci.

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Aging manifests as many phenotypes, among which age-related changes in brain vessels are important, but underexplored. Thus, in the present study, we constructed a model to predict age using cerebrovascular morphological features, further assessing their clinical relevance using a novel pipeline. Age prediction models were first developed using data from a normal cohort (n = 1181), after which their relevance was tested in two stroke cohorts (n = 564 and n = 455). Our novel pipeline adapted an existing framework to compute generic vessel features for brain vessels, resulting in 126 morphological features. We further built various machine learning models to predict age using only clinical factors, only brain vessel features, and a combination of both. We further assessed deviation from healthy aging using the age gap and explored its clinical relevance by correlating the predicted age and age gap with various risk factors. The models constructed using only brain vessel features and those combining clinical factors with vessel features were better predictors of age than the clinical factor-only model (r = 0.37, 0.48, and 0.26, respectively). Predicted age was associated with many known clinical factors, and the associations were stronger for the age gap in the normal cohort. The age gap was also associated with important factors in the pooled cohort atherosclerotic cardiovascular disease risk score and white matter hyperintensity measurements. Cerebrovascular age, computed using the morphological features of brain vessels, could serve as a potential individualized marker for the early detection of various cerebrovascular diseases.

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Hypertension is among the most important risk factors for cardiovascular disease, chronic kidney disease, and dementia. The artificial intelligence (AI) field is advancing quickly, and there has been little discussion on how AI could be leveraged for improving the diagnosis and management of hypertension. AI technologies, including machine learning tools, could alter the way we diagnose and manage hypertension, with potential impacts for improving individual and population health. The development of successful AI tools in public health and health care systems requires diverse types of expertise with collaborative relationships between clinicians, engineers, and data scientists. Unbiased data sources, management, and analyses remain a foundational challenge. From a diagnostic standpoint, machine learning tools may improve the measurement of blood pressure and be useful in the prediction of incident hypertension. To advance the management of hypertension, machine learning tools may be useful to find personalized treatments for patients using analytics to predict response to antihypertension medications and the risk for hypertension-related complications. However, there are real-world implementation challenges to using AI tools in hypertension. Herein, we summarize key findings from a diverse group of stakeholders who participated in a workshop held by the National Heart, Lung, and Blood Institute in March 2023. Workshop participants presented information on communication gaps between clinical medicine, data science, and engineering in health care; novel approaches to estimating BP, hypertension risk, and BP control; and real-world implementation challenges and issues.

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The accessibility of the retina with the use of non-invasive and relatively low-cost ophthalmic imaging techniques and analytics provides a unique opportunity to improve the detection, diagnosis and monitoring of systemic diseases. The National Heart, Lung, and Blood Institute conducted a workshop in October 2022 to examine this concept. On the basis of the discussions at that workshop, this Roadmap describes current knowledge gaps and new research opportunities to evaluate the relationships between the eye (in particular, retinal biomarkers) and the risk of cardiovascular diseases, including coronary artery disease, heart failure, stroke, hypertension and vascular dementia. Identified gaps include the need to simplify and standardize the capture of high-quality images of the eye by non-ophthalmic health workers and to conduct longitudinal studies using multidisciplinary networks of diverse at-risk populations with improved implementation and methods to protect participant and dataset privacy. Other gaps include improving the measurement of structural and functional retinal biomarkers, determining the relationship between microvascular and macrovascular risk factors, improving multimodal imaging 'pipelines', and integrating advanced imaging with 'omics', lifestyle factors, primary care data and radiological reports, by using artificial intelligence technology to improve the identification of individual-level risk. Future research on retinal microvascular disease and retinal biomarkers might additionally provide insights into the temporal development of microvascular disease across other systemic vascular beds.

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OBJECTIVE: Endovascular aortic aneurysm repair (EVAR) is the primary treatment for abdominal aortic aneurysms, constituting 70%-80% of interventions. Despite initial benefits, long-term studies show increased mortality. Using nationwide data, this study assesses outcomes of EVAR, open aortic repair (OAR), and EVAR explantation (EE) in Korea, while exploring characteristics of late open conversion, including the rising EE incidence. METHODS: Employing the National Health Insurance Service database, covering health-related data for nearly 50 million Koreans, the study spanned from 2002 to 2020. Patients with AAA diagnoses (I71.3 or I71.4) were categorized into OAR, EVAR, and EE groups based on procedural codes. Statistical analyses, including t-tests, Fisher's exact tests, Cox proportional hazard models, and multivariate Cox regression, assessed baseline characteristics, mortality risks, and factors within the EE group. RESULTS: The analysis encompassed 26,195 patients, with 66.19% in the EVAR group, 31.87% in the OAR group, and 1.94% in the EE group. EVAR cases steadily increased from 2002 to 2018. Survival rates favored EVAR, followed by OAR and EE. 30-day survival was lower in EE than EVAR. Multivariate analysis for EE revealed no risk factors for 30-days survival but identified age, chronic kidney disease, high Charlson Comorbidity Index scores, and less than 6 months since EVAR as risk factors for overall mortality. CONCLUSION: Rising EE trends with increased EVAR adoption, particularly evident in the Korean dataset, underscore inferior outcomes. This highlights the critical need for strategic initial treatment decisions and timely interventions to enhance overall results and mitigate the unfavorable EE incidence.

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BACKGROUND: Sex differences in stroke outcomes are notable, with women experiencing higher incidence rates, greater disability-adjusted life years, and poorer recovery compared to men, even after adjusting for age and comorbidities. Despite the disproportionate burden in women, studies have reported that women are less likely to receive appropriate stroke treatment than men. AIM: This study investigated temporal trends of sex differences in acute reperfusion therapy and early outcomes in patients with acute ischemic stroke over 10 years in South Korea. METHODS: A retrospective analysis of Korean Stroke Registry included patients with acute ischemic stroke from 2012 to 2021. The study outcomes were the temporal trends of acute reperfusion therapy and early outcomes over 10 years in men and women, respectively. In addition, this study analyzed the temporal trends of sex differences in these parameters during the same period. Early outcomes include the proportions of favorable functional outcomes at discharge, discharge patterns, and in-hospital mortality. RESULTS: A total of 93,692 patients (68.4 years, 40.1% women) with acute ischemic stroke were finally enrolled. Women had a higher age at stroke onset, a higher prevalence of atrial fibrillation, and more severe strokes than men. Women had lower proportion of favorable functional outcomes at discharge and higher proportion of in-hospital mortality compared to men each year. The proportion of patients who received intravenous thrombolysis was lower or similar in women compared to men in most years, and the proportion of patients who received endovascular thrombectomy did not significantly differ between sexes annually. Sex differences in acute reperfusion therapy remained unchanged over 10 years. CONCLUSION: Women have received acute reperfusion therapy at similar or lower rates than men and experienced poorer outcomes, despite having more stroke risk factors and often more severe strokes.

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Antithrombotic agents, including antiplatelet agent and anticoagulants are widely used in Korea due to increasing incidence of cardio-cerebrovascular disease and aging population. The management of patients using antithrombotic agents during endoscopic procedures is an important clinical challenge. Clinical practice guideline regarding this issue which was developed by the Korean Society of Gastrointestinal Endoscopy was published in 2020. However, since then, new evidence has emerged for the use of dual antiplatelet therapy and direct anticoagulant management, and revised guidelines were issued in the US and Europe. Accordingly, the previous guidelines were revised, cardiologists also participated in the development group, and the recommendations went through a consensus process among international experts. This guideline presents 14 recommendations made according to the Grading of Recommendations, Assessment, Development, and Evaluation methodology, and was reviewed by multidisciplinary experts. This guideline provides useful information that can assist endoscopists in the management of patients on antithrombotic agents who require diagnostic and elective therapeutic endoscopy. It will be revised as necessary to cover changes in technology, evidence, or other aspects of clinical practice.

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BACKGROUND AND PURPOSE: Infarct volume and other imaging markers are increasingly used as surrogate measures for clinical outcome in acute ischemic stroke research, but how improvements in these imaging surrogates translate into better clinical outcomes is currently unclear. We investigated how changes in infarct volume at 24 hours alter the probability of achieving good clinical outcome (modified Rankin Scale [mRS] 0-2). METHODS: Data are from endovascular thrombectomy patients from the randomized controlled ESCAPE-NA1 (Efficacy and Safety of Nerinetide for the Treatment of Acute Ischaemic Stroke) trial. Infarct volume at 24 hours was manually segmented on non-contrast computed tomography or diffusion-weighted magnetic resonance imaging. Probabilities of achieving good outcome based on infarct volume were obtained from a multivariable logistic regression model. The probability of good outcome was plotted against infarct volume using linear spline regression. RESULTS: A total of 1,099 patients were included in the analysis (median final infarct volume 24.9 mL [interquartile range: 6.6-92.2]). The relationship between total infarct volume and good outcome probability was nearly linear for infarct volumes between 0 mL and 250 mL. In this range, a 10% increase in the probability of achieving mRS 0-2 required a decrease in infarct volume of approximately 34.0 mL (95% confidence interval: -32.5 to -35.6). At infarct volumes above 250 mL, the probability of achieving mRS 0-2 probability was near zero. The relationships of tissue-specific infarct volumes and parenchymal hemorrhage volume generally showed similar patterns, although variability was high. CONCLUSION: There seems to be a near-linear association between total infarct volume and probability of achieving good outcome for infarcts up to 250 mL, whereas patients with infarct volumes greater than 250 mL are highly unlikely to have a favorable outcome.

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BACKGROUND AND PURPOSE: Accurate classification of ischemic stroke subtype is important for effective secondary prevention of stroke. We used diffusion-weighted image (DWI) and atrial fibrillation (AF) data to train a deep learning algorithm to classify stroke subtype. METHODS: Model development was done in 2,988 patients with ischemic stroke from three centers by using U-net for infarct segmentation and EfficientNetV2 for subtype classification. Experienced neurologists (n=5) determined subtypes for external test datasets, while establishing a consensus for clinical trial datasets. Automatically segmented infarcts were fed into the model (DWI-only algorithm). Subsequently, another model was trained, with AF included as a categorical variable (DWI+AF algorithm). These models were tested: (1) internally against the opinion of the labeling experts, (2) against fresh external DWI data, and (3) against clinical trial dataset. RESULTS: In the training-and-validation datasets, the mean (±standard deviation) age was 68.0±12.5 (61.1% male). In internal testing, compared with the experts, the DWI-only and the DWI+AF algorithms respectively achieved moderate (65.3%) and near-strong (79.1%) agreement. In external testing, both algorithms again showed good agreements (59.3%-60.7% and 73.7%-74.0%, respectively). In the clinical trial dataset, compared with the expert consensus, percentage agreements and Cohen's kappa were respectively 58.1% and 0.34 for the DWI-only vs. 72.9% and 0.57 for the DWI+AF algorithms. The corresponding values between experts were comparable (76.0% and 0.61) to the DWI+AF algorithm. CONCLUSION: Our model trained on a large dataset of DWI (both with or without AF information) was able to classify ischemic stroke subtypes comparable to a consensus of stroke experts.

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Ischemic stroke is a major cause of mortality worldwide. Proper etiological subtyping of ischemic stroke is crucial for tailoring treatment strategies. This study explored the utility of circulating microRNAs encapsulated in extracellular vesicles (EV-miRNAs) to distinguish the following ischemic stroke subtypes: large artery atherosclerosis (LAA), cardioembolic stroke (CES), and small artery occlusion (SAO). Using next-generation sequencing (NGS) and machine-learning techniques, we identified differentially expressed miRNAs (DEMs) associated with each subtype. Through patient selection and diagnostic evaluation, a cohort of 70 patients with acute ischemic stroke was classified: 24 in the LAA group, 24 in the SAO group, and 22 in the CES group. Our findings revealed distinct EV-miRNA profiles among the groups, suggesting their potential as diagnostic markers. Machine-learning models, particularly logistic regression models, exhibited a high diagnostic accuracy of 92% for subtype discrimination. The collective influence of multiple miRNAs was more crucial than that of individual miRNAs. Additionally, bioinformatics analyses have elucidated the functional implications of DEMs in stroke pathophysiology, offering insights into the underlying mechanisms. Despite limitations like sample size constraints and retrospective design, our study underscores the promise of EV-miRNAs coupled with machine learning for ischemic stroke subtype classification. Further investigations are warranted to validate the clinical utility of the identified EV-miRNA biomarkers in stroke patients.

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BACKGROUND: The need and values of patient- and family-centred care (PFCC) have been globally increasing in the health care landscape. However, the concept of PFCC and the components in adult intensive care units (ICUs) remain wide-ranging. AIM: To elucidate the core concepts of PFCC interventions and evaluate the effects of the interventions in adult ICUs. STUDY DESIGN: We searched electronic databases (PubMed, Cochrane Central, CINAHL, EMBASE, PsycINFO, RISS, KMbase and KoreaMed) from inception to 20 June 2022, for all studies on PFCC interventions. Three authors independently conducted data screening and extraction. The core concepts and the effects of PFCC interventions in adult ICUs were examined. The effects of patient- and family-centred care interventions in adult ICUs were examined. The quality of the included studies was evaluated using the Mixed Methods Appraisal Tool. RESULTS: Overall, 3507 records were identified, and 14 full-text articles were assessed. Participants in the included studies were patients and/or their family members in adult ICUs. The main concepts of the studies were participation and information-sharing. Only two studies used collaboration as the main concept of intervention. PFCC interventions have shown positive outcomes for patients, including increased satisfaction, improvement of patient health status and reduced incidence of complications. They have also been beneficial for families, leading to higher satisfaction levels and decreased anxiety. Additionally, these interventions have positively impacted health care providers by enhancing satisfaction and improving rounding efficiency. Moreover, they have influenced health care utilization by decreasing hospital costs and length of stay. CONCLUSIONS: This review highlights the advantages of PFCC interventions for patients, families and health care providers in adult ICUs. Future research should focus on developing strategies to incorporate collaboration more comprehensively as a core concept in the implementation of PFCC interventions. RELEVANCE TO CLINICAL PRACTICE: Future research endeavours must prioritize collaborative efforts involving health care providers, patients and their families by deploying an array of strategies within the intensive care unit setting.

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We investigate the structures of 24-crown-8/H+/l-tryptophan (CR/TrpH+) and 24-crown-8/H+/l-serine (CR/SerH+) noncovalent host-guest complex both in the gas phase and in an aqueous solution by quantum chemical methods. The Gibbs free energies of the complex in the two phases are calculated to determine the thermodynamically most favorable conformer in each phase. Our predictions indicate that both the carboxyl and the ammonium in CR/TrpH+ and the ammonium in the CR/SerH+ complexes in the lowest Gibbs free energy configurations form hydrogen bonds (H-bonds) with the CR host in the gas phase, while the conformer with the "naked" (devoid of H-bond with the CR host) -CO2H (and/or -OH) is much less favorable (Gibbs free energy higher by >3.6 kcal/mol). In the solution phase, however, a "thermodynamic reversal" occurs, making the higher Gibbs free energy gas-phase CR/TrpH+ and CR/SerH+ conformers thermodynamically more favorable under the influence of solvent molecules. Consequently, the global minimum Gibbs free energy structure in solution is structurally correlated with the thermodynamically much less gas-phase conformer. Discussions are provided concerning the possibility of elucidating host-guest-solvent interactions in solution from the gas-phase host-guest configurations in molecular detail.