Analyzing Optimal Wearable Motion Sensor Placement for Accurate Classification of Fall Directions.

Falls represent a significant risk factor, necessitating accurate classification methods. This study aims to identify the optimal placement of wearable sensors-specifically accelerometers, gyroscopes, and magnetometers-for effective fall-direction classification. Although previous research identified optimal sensor locations for distinguishing falls from non-falls, limited attention has been given to the classification of fall direction across different body regions. This study assesses inertial measurement unit (IMU) sensors placed at 12 distinct body locations to determine the most effective positions for capturing fall-related data. The research was conducted in three phases: first, comparing classifiers across all sensor locations to identify the most effective; second, evaluating performance differences between sensors placed on the left and right sides of the body; and third, exploring the efficacy of combining sensors from the upper and lower body regions. Statistical analyses of the results for the most effective classifier model demonstrate that the support vector machine (SVM) is more effective than other classifiers across all sensor locations, with statistically significant differences in performance. At the same time, the comparison between the left and right sensor locations shows no significant performance differences within the same anatomical areas. Regarding optimal sensor placement, the findings indicate that sensors positioned on the pelvis and upper legs in the lower body, as well as on the shoulder and head in the upper body, were the most effective results for accurate fall-direction classification. The study concludes that the optimal sensor configuration for fall-direction classification involves strategically combining sensors placed on the pelvis, upper legs, and lower legs.

Machine learning approaches toward an understanding of acute kidney injury: current trends and future directions.

Acute kidney injury (AKI) is a significant health challenge associated with adverse patient outcomes and substantial economic burdens. Many authors have sought to prevent and predict AKI. Here, we comprehensively review recent advances in the use of artificial intelligence (AI) to predict AKI, and the associated challenges. Although AI may detect AKI early and predict prognosis, integration of AI-based systems into clinical practice remains challenging. It is difficult to identify AKI patients using retrospective data; information preprocessing and the limitations of existing models pose problems. It is essential to embrace standardized labeling criteria and to form international multi-institutional collaborations that foster high-quality data collection. Additionally, existing constraints on the deployment of evolving AI technologies in real-world healthcare settings and enhancement of the reliabilities of AI outputs are crucial. Such efforts will improve the clinical applicability, performance, and reliability of AKI Clinical Support Systems, ultimately enhancing patient prognoses.

The effect of a scenario-based cognitive behavioral therapy mobile app on end-stage kidney disease patients on dialysis.

It has been reported that a scenario-based cognitive behavioral therapy mobile app including Todac Todac was effective in improving depression in the general public. However, no study has been conducted on whether Todac Todac is effective in dialysis patients. Therefore, this study was intended to determine whether the use of this app was effective in improving depression in dialysis patients. Sixty-five end-stage kidney disease patients receiving dialysis at Soonchunhyang University Cheonan Hospital were randomly assigned to the Todac Todac app program (experimental group) or an E-moods daily mood chart app program (control group) for 3 weeks. The degree of depression was measured before and after using the app.After the end of the 3-week program, a small but significant improvement was observed in the Trait anxiety (p < 0.05) and Beck depression index (p < 0.05) in E-moods group and DAS-K scores (p < 0.05) in Todac Todac group. However, no differences were seen in any parameters between the two groups. In addition, Todac Todac was not statistically more effective than the control intervention in the subgroup analysis. The Todac Todac, a scenario-based cognitive behavioral therapy mobile app, seemed to have a limited effect on improving depression in dialysis patients. Therefore, it is necessary to develop new tools to improve depression in dialysis patients.

RIPK3 causes mitochondrial dysfunction and albuminuria in diabetic podocytopathy through PGAM5-Drp1 signaling.

BACKGROUND: Receptor-interacting protein kinase (RIPK)3 is an essential molecule for necroptosis and its role in kidney fibrosis has been investigated using various kidney injury models. However, the relevance and the underlying mechanisms of RIPK3 to podocyte injury in albuminuric diabetic kidney disease (DKD) remain unclear. Here, we investigated the role of RIPK3 in glomerular injury of DKD. METHODS: We analyzed RIPK3 expression levels in the kidneys of patients with biopsy-proven DKD and animal models of DKD. Additionally, to confirm the clinical significance of circulating RIPK3, RIPK3 was measured by ELISA in plasma obtained from a prospective observational cohort of patients with type 2 diabetes, and estimated glomerular filtration rate (eGFR) and urine albumin-to-creatinine ratio (UACR), which are indicators of renal function, were followed up during the observation period. To investigate the role of RIPK3 in glomerular damage in DKD, we induced a DKD model using a high-fat diet in Ripk3 knockout and wild-type mice. To assess whether mitochondrial dysfunction and albuminuria in DKD take a Ripk3-dependent pathway, we used single-cell RNA sequencing of kidney cortex and immortalized podocytes treated with high glucose or overexpressing RIPK3. RESULTS: RIPK3 expression was increased in podocytes of diabetic glomeruli with increased albuminuria and decreased podocyte numbers. Plasma RIPK3 levels were significantly elevated in albuminuric diabetic patients than in non-diabetic controls (p = 0.002) and non-albuminuric diabetic patients (p = 0.046). The participants in the highest tertile of plasma RIPK3 had a higher incidence of renal progression (hazard ratio [HR] 2.29 [1.05-4.98]) and incident chronic kidney disease (HR 4.08 [1.10-15.13]). Ripk3 knockout improved albuminuria, podocyte loss, and renal ultrastructure in DKD mice. Increased mitochondrial fragmentation, upregulated mitochondrial fission-related proteins such as phosphoglycerate mutase family member 5 (PGAM5) and dynamin-related protein 1 (Drp1), and mitochondrial ROS were decreased in podocytes of Ripk3 knockout DKD mice. In cultured podocytes, RIPK3 inhibition attenuated mitochondrial fission and mitochondrial dysfunction by decreasing p-mixed lineage kinase domain-like protein (MLKL), PGAM5, and p-Drp1 S616 and mitochondrial translocation of Drp1. CONCLUSIONS: The study demonstrates that RIPK3 reflects deterioration of renal function of DKD. In addition, RIPK3 induces diabetic podocytopathy by regulating mitochondrial fission via PGAM5-Drp1 signaling through MLKL. Inhibition of RIPK3 might be a promising therapeutic option for treating DKD.

A machine learning-based approach for predicting renal function recovery in general ward patients with acute kidney injury.

BACKGROUND: Acute kidney injury (AKI) is a significant challenge in healthcare. While there are considerable researches dedicated to AKI patients, a crucial factor in their renal function recovery, is often overlooked. Thus, our study aims to address this issue through the development of a machine learning model to predict restoration of kidney function in patients with AKI. METHODS: Our study encompassed data from 350,345 cases, derived from three hospitals. AKI was classified in accordance with the Kidney Disease: Improving Global Outcomes. Criteria for recovery were established as either a 33% decrease in serum creatinine levels at AKI onset, which was initially employed for the diagnosis of AKI. We employed various machine learning models, selecting 43 pertinent features for analysis. RESULTS: Our analysis contained 7,041 and 2,929 patients' data from internal cohort and external cohort respectively. The Categorical Boosting Model demonstrated significant predictive accuracy, as evidenced by an internal area under the receiver operating characteristic (AUROC) of 0.7860, and an external AUROC score of 0.7316, thereby confirming its robustness in predictive performance. SHapley Additive exPlanations (SHAP) values were employed to explain key factors impacting recovery of renal function in AKI patients. CONCLUSION: This study presented a machine learning approach for predicting renal function recovery in patients with AKI. The model performance was assessed across distinct hospital settings, which revealed its efficacy. Although the model exhibited favorable outcomes, the necessity for further enhancements and the incorporation of more diverse datasets is imperative for its application in real- world.

Disruption in glutathione metabolism and altered energy production in the liver and kidney after ischemic acute kidney injury in mice.

Acute kidney injury (AKI) is a systemic disease that affects energy metabolism in various remote organs in murine models of ischemic AKI. However, AKI-mediated effects in the liver have not been comprehensively assessed. After inducing ischemic AKI in 8-10-week-old, male C57BL/6 mice, mass spectrometry metabolomics revealed that the liver had the most distinct phenotype 24 h after AKI versus 4 h and 7 days. Follow up studies with in vivo [13C6]-glucose tracing on liver and kidney 24 h after AKI revealed 4 major findings: (1) increased flux through glycolysis and the tricarboxylic (TCA) cycle in both kidney and liver; (2) depleted hepatic glutathione levels and its intermediates despite unchanged level of reactive oxygen species, suggesting glutathione consumption exceeds production due to systemic oxidative stress after AKI; (3) hepatic ATP depletion despite unchanged rate of mitochondrial respiration, suggesting increased ATP consumption relative to production; (4) increased hepatic and renal urea cycle intermediates suggesting hypercatabolism and upregulation of the urea cycle independent of impaired renal clearance of nitrogenous waste. Taken together, this is the first study to describe the hepatic metabolome after ischemic AKI in a murine model and demonstrates that there is significant liver-kidney crosstalk after AKI.

Kidney biopsy can help to predict renal outcomes of patients with type 2 diabetes mellitus.

Background: In patients with type 2 diabetes mellitus (T2DM), diabetic kidney disease (DKD) is diagnosed based on clinical features. A kidney biopsy is used only in selected cases. This study aimed to reconsider the role of a biopsy in predicting renal outcomes. Methods: Clinical and laboratory parameters and renal biopsy results were obtained from 237 patients with T2DM who underwent renal biopsies at Soonchunhyang University Cheonan Hospital between January 2000 and March 2020 and were analyzed. Results: Of 237 diabetic patients, 29.1% had DKD only, 61.6% had non-DKD (NDKD), and 9.3% had DKD with coexisting NDKD (DKD/NDKD). Of the patients with DKD alone, 43.5% progressed to end-stage kidney disease (ESKD), while 15.8% of NDKD patients and 36.4% of DKD/NDKD patients progressed to ESKD (p < 0.001). In the DKD-alone group, pathologic features like ≥50% global sclerosis (p < 0.001), tubular atrophy (p < 0.001), interstitial fibrosis (p < 0.001), interstitial inflammation (p < 0.001), and the presence of hyalinosis (p = 0.03) were related to worse renal outcomes. The Cox regression model showed a higher risk of progression to ESKD in the DKD/NDKD group compared to the DKD-alone group (hazard ratio [HR], 2.73; p = 0.032), ≥50% global sclerosis (HR, 3.88; p < 0.001), and the degree of mesangial expansion (moderate: HR, 2.45; p = 0.045 and severe: HR, 6.22; p < 0.001). Conclusion: In patients with T2DM, a kidney biopsy can help in identifying patients with NDKD for appropriate treatment, and it has predictive value.

Indoxyl sulfate induces apoptotic cell death by inhibiting glycolysis in human astrocytes.

Background: Neurologic complications, such as cognitive and emotional dysfunction, have frequently been observed in chronic kidney disease (CKD) patients. Previous research shows that uremic toxins play a role in the pathogenesis of CKD-associated cognitive impairment. Since astrocytes contribute to the protection and survival of neurons, astrocyte function and brain metabolism may contribute to the pathogenesis of neurodegeneration. Indoxyl sulfate (IS) is the most popular uremic toxin. However, how IS-induced astrocyte injury brings about neurologic complications in CKD patients has not been elucidated. Methods: The rate of extracellular acidification was measured in astrocytes when IS (0.5-3 mM, 4 or 7 days) treatment was applied. The hexokinase 1 (HK1), pyruvate kinase isozyme M2 (PKM2), pyruvate dehydrogenase (PDH), and phosphofructokinase (PFKP) protein levels were also measured. The activation of the apoptotic pathway was investigated using a confocal microscope, fluorescence-activated cell sorting, and cell three-dimensional imaging was used. Results: In astrocytes, IS affected glycolysis in not only dose-dependently but also time-dependently. Additionally, HK1, PKM2, PDH, and PFKP levels were decreased in IS-treated group when compared to the control. The results were prominent in cases with higher doses and longer exposure duration. The apoptotic features after IS treatment were also observed. Conclusion: Our results showed that the inhibition of glycolysis by IS in astrocytes leads to cell death via apoptosis. Specifically, long-term and higher-dose exposures had more serious effects on astrocytes. Our results suggest that the glycolysis pathway and related targets could provide a novel approach to cognitive dysfunction in CKD patients.

Genome-wide association study and fine-mapping on Korean biobank to discover renal trait-associated variants.

Background: Chronic kidney disease is a significant health burden worldwide, with increasing incidence. Although several genome-wide association studies (GWAS) have investigated single nucleotide polymorphisms (SNP) associated with kidney trait, most studies were focused on European ancestry. Methods: We utilized clinical and genetic information collected from the Korean Genome and Epidemiology Study (KoGES). Results: More than five million SNPs from 58,406 participants were analyzed. After meta-GWAS, 1,360 loci associated with estimated glomerular filtration rate (eGFR) at a genome-wide significant level (p = 5 × 10-8) were identified. Among them, 399 loci were validated with at least one other biomarker (blood urea nitrogen [BUN] or eGFRcysC) and 149 loci were validated using both markers. Among them, 18 SNPs (nine known ones and nine novel ones) with 20 putative genes were found. The aggregated effect of genes estimated by MAGMA gene analysis showed that these significant genes were enriched in kidney-associated pathways, with the kidney and liver being the most enriched tissues. Conclusion: In this study, we conducted GWAS for more than 50,000 Korean individuals and identified several variants associated with kidney traits, including eGFR, BUN, and eGFRcysC. We also investigated functions of relevant genes using computational methods to define putative causal variants.

Loss of Cutibacterium is responsible for chronic kidney disease-associated pruritus in patients on dialysis.

Background: Chronic kidney disease (CKD)-associated pruritus is a severe distressing condition that frequently occurs in patients undergoing dialysis. In this study, the profile of the skin microbiome was analyzed to understand the underlying etiology and potential treatments. Methods: Seventy-six end-stage kidney disease (ESKD) patients (hemodialysis, 40; peritoneal dialysis, 36) and 15 healthy controls were enrolled and swabbed at three sites: back, antecubital fossa, and shin. The pruritus severity of the enrolled subjects was validated by the Worst Itch Numeric Rating Scale (WI-NRS), 5-D itch scale, and Uremic Pruritus in Dialysis Patients (UP-Dial). The 16S gene-based metagenomics method was applied to skin microbiome analysis. Results: In the comparison of bacterial communities of ESKD patients and the control group, there was a significant difference on back. Specifically, the average composition ratio of the Cutibacterium in the back samples was significantly lower in ESKD patients than in healthy controls (p < 0.01). In further analysis of ESKD patients, Cutibacterium was significantly lower in the high pruritus group than in the low pruritus group (p < 0.05), even though other clinical parameters such as age, calcium-phosphorus product, and intact parathyroid hormone showed no significance difference between the groups. Conclusion: In ESKD patients, the skin microbiome of the back was significantly altered, and the severity of itching was related to the reduction of Cutibacterium. This research reveals the relationship between skin microbiota and CKD-associated pruritus in multiple skin sites for the first time. The results of this study suggest a potential data basis for the diagnosis and treatment of CKD-associated pruritus.

Shared decision-making intervention regarding dialysis modality in patients with CKD stage 5.

BACKGROUND: Patients with kidney failure must make complicated decisions about the dialysis modalities used either at home or in-hospital. Different options have varying levels of impact on patients' physical and psychological conditions and their social life. The purpose of this study was to evaluate the implementation of an intervention designed to achieve shared decision making (SDM) in patients' options for dialysis. METHODS: SDM was performed after consent was written for stage 5 chronic kidney disease patients before dialysis, and 435 cases were performed in 408 patients from December 16, 2019 to June 30, 2021. Among these, 101 patients were compared by SDM measurement scale, patient satisfaction, disease recognition scale survey, and dialysis method. RESULTS: The average age of participants was 56 years, with a gender composition of 55 males (54.5%) and 46 females (45.5%). Following SDM, the final dialysis methods decided upon by patients and clinicians were peritoneal dialysis (67 patients, 66.3%), hemodialysis (22 patients, 21.8%), and kidney transplantation (1 patient, 1.0%). CONCLUSIONS: Among participating patients, SDM was effective when used to decide on dialysis treatment, and patients were satisfied with the dialysis method decision process. On the disease awareness scale, those who participated in this project had relatively high positive and low negative perceptions, so it can be concluded that SDM was relatively effective. The implementation of SDM was helpful in selecting patients' best dialysis methods, and SDM scale results were higher in the peritoneal dialysis group than in the hemodialysis group.

Cognitive Sequelae and Hippocampal Dysfunction in Chronic Kidney Disease following 5/6 Nephrectomy.

Neurological disorders are prevalent in patients with chronic kidney disease (CKD). Vascular factors and uremic toxins are involved with cognitive impairment in CKD. In addition, vascular dementia-induced alterations in the structure and function of the hippocampus can lead to deficits in hippocampal synaptic plasticity and cognitive function. However, regardless of this clinical evidence, the pathophysiology of cognitive impairment in patients with CKD is not fully understood. We used male Sprague Dawley rats and performed 5/6 nephrectomy to observe the changes in behavior, field excitatory postsynaptic potential, and immunostaining of the hippocampus following CKD progression. We measured the hippocampus volume on magnetic resonance imaging scans in the controls (n = 34) and end-stage renal disease (ESRD) hemodialysis patients (n = 42). In four cognition-related behavior assays, including novel object recognition, Y-maze, Barnes maze, and classical contextual fear conditioning, we identified deficits in spatial working memory, learning and memory, and contextual memory, as well as the ability to distinguish familiar and new objects, in the rats with CKD. Immunohistochemical staining of Na+/H+ exchanger1 was increased in the hippocampus of the CKD rat models. We performed double immunofluorescent staining for aquaporin-4 and glial fibrillary acidic protein and then verified the high coexpression in the hippocampus of the CKD rat model. Furthermore, results from recoding of the field excitatory postsynaptic potential (fEPSP) in the hippocampus showed the reduced amplitude and slope of fEPSP in the CKD rats. ESRD patients with cognitive impairment showed a significant decrease in the hippocampus volume compared with ESRD patients without cognitive impairment or the controls. Our findings suggest that uremia resulting from decreased kidney function may cause the destruction of the blood-brain barrier and hippocampus-related cognitive impairment in CKD.

Transiently Observed Trace Albuminuria on Urine Dipstick Test Is Associated With All-Cause Death, Cardiovascular Death, and Incident Chronic Kidney Disease: A National Health Insurance Service-National Sample Cohort in Korea.

Introduction: Albuminuria is a well-known risk factor for end-stage kidney disease, all-cause mortality, and cardiovascular mortality, even when the albumin-to-creatinine ratio is <30 mg/g. However, the association between transiently observed trace albuminuria and these major adverse outcomes has not yet been reported. This study aimed to examine the effect of transient albuminuria on these major adverse outcomes using the National Health Insurance Service data in Korea. Methods and Results: The National Health Insurance Service-National Sample Cohort from Korea, followed from 2002 to 2015, consisted of 1,025,340 individuals, accounting for 2.2% of the total Korean population. We analyzed the effect of transient albuminuria on all-cause death, cardiovascular death, and incident chronic kidney disease (CKD) and compared it with the group without albuminuria. Among 1,025,340 individuals, 121,876 and 2,815 had transient albuminuria and no albuminuria, respectively. Adjusted hazard ratios of the transient albuminuria group for cardiovascular death and incident CKD were 1.76 (1.01-3.08) and 1.28 (1.15-1.43), respectively. There were significant differences in all-cause death, cardiovascular death, and incident CKD between the two groups after propensity score matching (p = 0.0037, p = 0.015, and p < 0.0001, respectively). Propensity score matching with bootstrapping showed that the hazard ratios of the transient albuminuria group for all-cause death and cardiovascular death were 1.39 (1.01-1.92) and 2.18 (1.08-5.98), respectively. Conclusions: In this nationwide, large-scale, retrospective cohort study, transient albuminuria was associated with all-cause death, cardiovascular death, and incident CKD, suggesting that transient albuminuria could be a risk marker for adverse outcomes in the future, and that its own subclinical phenotype could play an important role during the course of CKD.

Clinical Safety of Expanded Hemodialysis Compared with Hemodialysis Using High-Flux Dialyzer during a Three-Year Cohort.

Expanded hemodialysis (HD) equipped with a medium cut-off (MCO) membrane provides superior removal of larger middle molecules. However, there is still little research on the long-term benefits of expanded HD. Over a three-year period, this observational study evaluated the efficacy and safety profile of expanded HD for inflammatory cytokines, including IL-6. We conducted a prospective cohort study to investigate the inflammatory cytokine changes and a retrospective observational cohort study to investigate long-term clinical efficacy and safety over a three-year period. We categorized the patients according to dialyzer used: MCO and high-flux (HF) dialyzer. The inflammatory cytokines, including IFN-γ, IL-1ß, IL-6, and TNF-α, were measured annually. The concentrations and changes of the four cytokines over time did not differ between the HF group (n = 15) and MCO group (n = 27). In both prospective and retrospective (HF group, n = 38; MCO group, n = 76) cohorts, there were no significant differences in either death, cardiovascular events, infections, or hospitalizations. Furthermore, the temporal changes in laboratory values, including serum albumin and erythropoietin prescriptions, did not differ significantly between the two groups in either the prospective or retrospective cohorts. In conclusion, clinical efficacy and safety outcomes, as well as inflammatory cytokines, did not differ with expanded HD compared with HF dialysis during a three-year treatment course, although the level of inflammatory cytokine was stable.

Emotional and cognitive changes in chronic kidney disease.

Chronic kidney disease (CKD) leads to cognitive impairment and emotional changes. However, the precise mechanism underlying the crosstalk between the kidneys and the nervous system is not fully understood. Inflammation and cerebrovascular disease can influence the development of depression in CKD. CKD is one of the strongest risk factors for cognitive impairment. Moreover, cognitive impairment occurs in CKD as patients experience the dysregulation of several brain functional domains due to damage caused to multiple cortical regions and to subcortical modulatory neurons. The differences in structural brain changes between CKD and non-CKD dementia may be attributable to the different mechanisms that occur in CKD. The kidney and brain have similar anatomical vascular systems, which may be susceptible to traditional risk factors. Vascular factors are assumed to be involved in the development of cognitive impairment in patients with CKD. Vascular injury induces white matter lesions, silent infarction, and microbleeds. Uremic toxins may also be directly related to cognitive impairment in CKD. Many uremic toxins, such as indoxyl sulfate, are likely to have an impact on the central nervous system. Further studies are required to identify therapeutic targets to prevent changes in the brain in patients with CKD.

Prediction Model of Acute Respiratory Failure in Patients with Acute Pesticide Poisoning by Intentional Ingestion: Prediction of Respiratory Failure in Pesticide Intoxication (PREP) Scores in Cohort Study.

Acute respiratory failure is the primary cause of mortality in patients with acute pesticide poisoning. The aim of the present study was to develop a new and efficient score system for predicting acute respiratory failure in patients with acute pesticide poisoning. This study was a retrospective observational cohort study comprised of 679 patients with acute pesticide poisoning by intentional poisoning. We divided this population into a ratio of 3:1; training set (n = 509) and test set (n = 170) for model development and validation. Multivariable logistic regression models were used in developing a score-based prediction model. The Prediction of Respiratory failure in Pesticide intoxication (PREP) scoring system included a summation of the integer scores of the following five variables; age, pesticide category, amount of ingestion, Glasgow Coma Scale, and arterial pH. The PREP scoring system developed accurately predicted respiratory failure (AUC 0.911 [0.849-0.974], positive predictive value 0.773, accuracy 0.873 in test set). We came up with four risk categories (A, B, C and D) using PREP scores 20, 40 and 60 as the cut-off for mechanical ventilation requirement risk. The PREP scoring system developed in the present study could predict respiratory failure in patients with pesticide poisoning, which can be easily implemented in clinical situations. Further prospective studies are needed to validate the PREP scoring system.

Arrhythmia and Heart Rate Variability during Long Interdialytic Periods in Patients on Maintenance Hemodialysis: Prospective Observational Cohort Study.

Sudden cardiac death among hemodialysis patients is related to the hemodialysis schedule. Mortality is highest within 12 h before and after the first hemodialysis sessions of a week. We investigated the association of arrhythmia occurrence and heart rate variability (HRV) using an electrocardiogram (ECG) monitoring patch during the long interdialytic interval in hemodialysis patients. This was a prospective observational study with 55 participants on maintenance hemodialysis for at least six months. A patch-type ECG monitoring device was applied to record arrhythmia events and HRV during 72 h of a long interdialytic period. Forty-nine participants with sufficient ECG data out of 55 participants were suitable for the analysis. The incidence of supraventricular tachycardia and ventricular tachycardia did not significantly change over time. The square root of the mean squared differences of successive NN intervals (RMSSD), the proportion of adjacent NN intervals differing by >50 ms (pNN50), and high-frequency (HF) increased during the long interdialytic interval. The gap in RMSSD, pNN50, HF, and the low-frequency/high-frequency (LF/HF) ratio between patients with and without significant arrhythmias increased significantly over time during the long interdialytic interval. The daily changes in RMSSD, pNN50, HF, and the LF/HF ratio were more prominent in patients without significant arrhythmias than in those with significant arrhythmias. The electrolyte fluctuation between post-hemodialysis and subsequent pre-hemodialysis was not considered in this study. The study results suggest that the decreased autonomic response during interdialytic periods in dialysis patients is associated with poor cardiac arrhythmia events.

Pericoronary fat attenuation index in computed tomography angiography is associated with mortality in end-stage renal disease.

BACKGROUND: An increased pericoronary fat attenuation index (FAI) on computed tomography angiography (CTA) is associated with increased all-cause and cardiac mortality in the general population. However, the ability of pericoronary FAI to predict long-term outcomes in chronic kidney disease (CKD) patients is unknown. METHODS: In this single-center retrospective longitudinal cohort study, we assessed the utility of CTA-based pericoronary FAI measurement to predict mortality of CKD patients, including those with end-stage renal disease (ESRD). Mapping and analysis of pericoronary FAI involved three major proximal coronary arteries. The prognostic value of pericoronary FAI for long-term mortality was assessed with multivariable Cox regression models. RESULTS: Among 268 CKD participants who underwent coronary CTA, 209 participants with left anterior descending artery (LAD) FAI measurements were included. The pericoronary FAI measured at the LAD was not significantly associated with adjusted risk of allcause mortality (hazard ratio [HR], 2.08; 95% confidence interval [CI], 0.94-3.51) in any CKD group. However, ESRD patients with elevated pericoronary FAI values had a greater adjusted risk of all-cause mortality compared with the low-FAI group (HR, 2.26; 95% CI, 1.11-4.61). CONCLUSION: The pericoronary FAI measured at the LAD predicted long-term mortality in patients with ESRD, which could provide an opportunity for early primary intervention in ESRD patients.

Psychological distress of patients with end-stage kidney disease undergoing dialysis during the 2019 coronavirus disease pandemic: A cross-sectional study in a University Hospital.

INTRODUCTION: Previous studies have revealed that the COVID-19 pandemic can cause psychological distress such as depression and anxiety. Patients with chronic kidney disease (CKD) might be more vulnerable to psychological distress due to the COVID-19 pandemic. Its impact could be different according to dialysis modality. The aim of this study was to investigate COVID-19-related psychological stress experienced by end-stage kidney disease (ESKD) patients and identify differences in concerns about COVID-19 between hemodialysis (HD) and peritoneal dialysis (PD) patients. METHODS: This cross-sectional study included 148 dialysis patients at Soonchunhyang University Cheonan Hospital from August 2020 to September 2020. These patients responded to a questionnaire covering mental health status and COVID-19 related concerns. Symptoms of depression, anxiety, stress, and insomnia were measured using a 9-item Patient Health Questionnaire (PHQ-9), a 7-item Generalized Anxiety Disorder (GAD-7) scale, a 22-item Impact of Event Scale-Revised (IES-R), and a 7-item Insomnia severity Index (ISI), respectively. Outcomes of HD and PD patients were compared by propensity score matching analysis. RESULTS: Dialysis patients reported psychological distress including symptoms of depression, anxiety, stress, and insomnia. HD patients showed higher scores for depression (p = 0.018), anxiety(p = 0.005), stress(p<0.001), and insomnia(p = 0.006) than the PD patients. After propensity score matching, HD was associated with depression(p = 0.0131), anxiety(p = 0.0143), and stress(p = 0.000415). CONCLUSION: Dialysis patients showed psychological distress during the COVID-19 pandemic period, with HD patients having more severe symptoms than PD patients.

Deep-Learning-Based Coronary Artery Calcium Detection from CT Image.

One of the most common methods for diagnosing coronary artery disease is the use of the coronary artery calcium score CT. However, the current diagnostic method using the coronary artery calcium score CT requires a considerable time, because the radiologist must manually check the CT images one-by-one, and check the exact range. In this paper, three CNN models are applied for 1200 normal cardiovascular CT images, and 1200 CT images in which calcium is present in the cardiovascular system. We conduct the experimental test by classifying the CT image data into the original coronary artery calcium score CT images containing the entire rib cage, the cardiac segmented images that cut out only the heart region, and cardiac cropped images that are created by using the cardiac images that are segmented into nine sub-parts and enlarged. As a result of the experimental test to determine the presence of calcium in a given CT image using Inception Resnet v2, VGG, and Resnet 50 models, the highest accuracy of 98.52% was obtained when cardiac cropped image data was applied using the Resnet 50 model. Therefore, in this paper, it is expected that through further research, both the simple presence of calcium and the automation of the calcium analysis score for each coronary artery calcium score CT will become possible.