Outpatient Renal Function Screening Before Contrast-Enhanced CT Examinations.

Intravascular administration of iodinated contrast media can cause contrast-induced acute kidney injury, especially in patients with an estimated glomerular filtration rate (eGFR) less than 30 mL/min/1.73 m². The American College of Radiology (ACR) and the European Society of Urogenital Radiology (ESUR) guidelines recommend renal function screening based on medical history, but their effectiveness has been under-evaluated. This retrospective study included 2,560 consecutive adult outpatients without eGFR measurements within 180 days before contrast-enhanced computed tomography (CT) at a single tertiary hospital from July through September 2023. On the day of CT, they underwent eGFR tests and 1.1% had an eGFR < 30 mL/min/1.73 m², preferentially with histories of gout and renal disease. According to the ACR and ESUR strategies, 16.9% and 38.8% of all study participants were positive, respectively, identifying 92.6% and 96.3% of patients with renal insufficiency. Both strategies demonstrated high negative predictive values. These results support selective renal function screening before contrast-enhanced examinations.

Urine complement proteins are associated with kidney disease progression of type 2 diabetes in Korean and American cohorts.

Background: Mechanisms of progression of diabetic kidney disease (DKD) are not completely understood. This study uses untargeted and targeted mass spectrometry-based proteomics in two independent cohorts on two continents to decipher the mechanisms of DKD in patients with type 2 diabetes. Methods: We conducted untargeted mass spectrometry on urine samples collected at the time of kidney biopsy from Korean patients with type 2 diabetes and biopsy-proven diabetic nephropathy at Seoul National University Hospital (SNUH-DN cohort; n = 64). These findings were validated using targeted mass spectrometry in urine samples from a Chronic Renal Insufficiency Cohort subgroup with type 2 diabetes and DKD (CRIC-T2D; n = 282). Urinary biomarkers/pathways associated with kidney disease progression (doubling of serum creatinine, ≥50% decrease in estimated glomerular filtration rates, or the development of end-stage kidney disease) were identified. Results: SNUH-DN patients had an estimated glomerular filtration rate (eGFR) of 55 mL/min/1.73 m 2 (interquartile range [IQR], 44-75) and random urine protein-to-creatinine ratio of 3.1 g/g (IQR, 1.7-7.0). Urine proteins clustered into two groups, with cluster 2 having a 4.6-fold greater hazard (95% confidence interval [CI], 1.9-11.5) of disease progression than cluster 1 in multivariable-adjusted, time-to-event analyses. Proteins in cluster 2 mapped to 10 pathways, four of the top five of which were complement or complement-related. A high complement score, constructed from urine complement protein abundance, was strongly correlated to 4 of 5 histopathologic DN features and was associated with a 2.4-fold greater hazard (95% CI, 1.0-5.4) of disease progression than a low complement score. Targeted mass spectrometry of the CRIC-T2D participants, who had an eGFR of 42 mL/min/1.73 m 2 (IQR, 37-49) and 24-hr urine protein of 0.48 g (IQR, 0.10-1.87), showed that the complement score similarly segregated them into rapid and slow DKD progression groups. In both cohorts, the complement score had a linear association with disease progression. Conclusions: Urinary proteomic profiling confirms the association between the complement pathway and rapid DKD progression in two independent cohorts. These results suggest a need to further investigate complement pathway inhibition as a novel treatment for DKD.

Spatial proteomics of human diabetic kidney disease, from health to class III.

AIMS/HYPOTHESIS: Diabetic kidney disease (DKD) is the leading cause of chronic and end-stage kidney disease in the USA and worldwide. Animal models have taught us much about DKD mechanisms, but translation of this knowledge into treatments for human disease has been slowed by the lag in our molecular understanding of human DKD. METHODS: Using our Spatial TissuE Proteomics (STEP) pipeline (comprising curated human kidney tissues, multiplexed immunofluorescence and powerful analysis tools), we imaged and analysed the expression of 21 proteins in 23 tissue sections from individuals with diabetes and healthy kidneys (n=5), compared to those with DKDIIA, IIA-B and IIB (n=2 each) and DKDIII (n=1). RESULTS: These analyses revealed the existence of 11 cellular clusters (kidney compartments/cell types): podocytes, glomerular endothelial cells, proximal tubules, distal nephron, peritubular capillaries, blood vessels (endothelial cells and vascular smooth muscle cells), macrophages, myeloid cells, other CD45+ inflammatory cells, basement membrane and the interstitium. DKD progression was associated with co-localised increases in inflammatory cells and collagen IV deposition, with concomitant loss of native proteins of each nephron segment. Cell-type frequency and neighbourhood analyses highlighted a significant increase in inflammatory cells and their adjacency to tubular and αSMA+ (α-smooth muscle actin-positive) cells in DKD. Finally, DKD progression showed marked regional variability within single tissue sections, as well as inter-individual variability within each DKD class. CONCLUSIONS/INTERPRETATION: Using the STEP pipeline, we found alterations in protein expression, cellular phenotypic composition and microenvironment structure with DKD progression, demonstrating the power of this pipeline to reveal the pathophysiology of human DKD.

Glomerular crescents are associated with the risk of type 2 diabetic kidney disease progression: a retrospective cohort study.

BACKGROUND: Diabetic kidney disease (DKD) stands as the predominant cause of chronic kidney disease and end-stage kidney disease. Its diverse range of manifestations complicates the treatment approach for patients. Although kidney biopsy is considered the gold standard for diagnosis, it lacks precision in predicting the progression of kidney dysfunction. Herein, we addressed whether the presence of glomerular crescents is linked to the outcomes in patients with biopsy-confirmed type 2 DKD. METHODS: We performed a retrospective evaluation, involving 327 patients diagnosed with biopsy-confirmed DKD in the context of type 2 diabetes, excluding cases with other glomerular diseases, from nine tertiary hospitals. Hazard ratios (HRs) were calculated using a Cox regression model to assess the risk of kidney disease progression, defined as either ≥ 50% decrease in estimated glomerular filtration rates or the development of end-stage kidney disease, based on the presence of glomerular crescents. RESULTS: Out of the 327 patients selected, ten patients had glomerular crescents observed in their biopsied tissues. Over the follow-up period (median of 19 months, with a maximum of 18 years), the crescent group exhibited a higher risk of kidney disease progression than the no crescent group, with an adjusted HR of 2.82 (1.32-6.06) (P = 0.008). The presence of heavy proteinuria was associated with an increased risk of developing glomerular crescents. CONCLUSION: The presence of glomerular crescents is indeed linked to the progression of type 2 DKD. Therefore, it is important to determine whether there is an additional immune-mediated glomerulonephritis requiring immunomodulation, and it may be prudent to monitor the histology and repeat a biopsy.

Risk of mortality and cause of death according to kidney function parameters: a nationwide observational study in Korea.

BACKGROUND: Further study is warranted to determine the association between estimated glomerular filtration rate (eGFR) or albuminuria and the risk of death from diverse causes. METHODS: We screened >10 million general health screening examinees who received health examinations conducted in 2009 using the claims database of Korea. After the exclusion of those previously diagnosed with renal failure and those with missing data, 9,917,838 individuals with available baseline kidney function measurements were included. The primary outcome was mortality and cause-specific death between 2009 and 2019 identified through death certificates based on the diagnostic codes of International Classification of Diseases, 10th revision. Multivariable Cox regression analysis adjusted for various clinicodemographic and social characteristics was used to assess mortality risk. RESULTS: The hazard ratio of death was significantly high in both the eGFR <60 mL/min/1.73 m2 and in the eGFR ≥120 mL/ min/1.73 m2 groups in univariable and multivariable regression analyses when compared to those within the reference range (eGFR of 90-120 mL/min/1.73 m2). The results were similar for death by cardiovascular, cancer, infection, endocrine, respiratory, and digestive causes. We also found that albuminuria was associated with higher risk of death regardless of eGFR range, and those in the higher categories of dipstick albuminuria showed higher risk. CONCLUSION: We reconfirmed the significant association between eGFR, albuminuria, and mortality. Healthcare providers should keep in mind that albuminuria and decreased eGFR as well as kidney hyperfiltration are independent predictors of mortality.

Associations of MRI-derived kidney volume, kidney function, body composition and physical performance in ≈38 000 UK Biobank participants: a population-based observational study.

Background: Kidney volume is used as a predictive and therapeutic marker for several clinical conditions. However, there is a lack of large-scale studies examining the relationship between kidney volume and various clinicodemographic factors, including kidney function, body composition and physical performance. Methods: In this observational study, MRI-derived kidney volume measurements from 38 526 UK Biobank participants were analysed. Major kidney volume-related measures included body surface area (BSA)-adjusted total kidney volume (TKV) and the difference in bilateral kidneys. Multivariable-adjusted linear regression and cubic spline analyses were used to explore the association between kidney volume-related measures and clinicodemographic factors. Cox or logistic regression was used to identify the risks of death, non-kidney cancer, myocardial infarction, ischaemic stroke and chronic kidney disease (CKD). Results: The median of BSA-adjusted TKV and the difference in kidney volume were 141.9 ml/m2 [interquartile range (IQR) 128.1-156.9] and 1.08-fold (IQR 1.04-1.15), respectively. Higher BSA-adjusted TKV was significantly associated with higher estimated glomerular filtration rate {eGFR; ß = 0.43 [95% confidence interval (CI) 0.42-0.44]; P < .001}, greater muscle volume [ß = 0.50 (95% CI 0.48-0.51); P < .001] and greater mean handgrip strength [ß = 0.15 (95% CI 0.13-0.16); P < .001] but lower visceral adipose tissue volume [VAT; ß = -0.09 (95% CI -0.11 to -0.07); P < .001] in adjusted models. A greater difference in bilateral kidney volumes was associated with lower eGFR, muscle volume and physical performance but with higher proteinuria and VAT. Higher BSA-adjusted TKV was significantly associated with a reduced risk of CKD [odds ratio (OR) 0.7 (95% CI 0.63-0.77); P < .001], while a greater difference in kidney volume was significantly associated with an increased risk of CKD [OR 1.13 (95% CI 1.07-1.20); P < .001]. Conclusion: Higher BSA-adjusted TKV and lower differences in bilateral kidney volumes are associated with higher kidney function, muscle volume and physical performance and a reduced risk of CKD.

Mortality associated with the neutrophil-lymphocyte ratio in septic acute kidney injury requiring continuous renal replacement therapy.

BACKGROUND: Sepsis is an important cause of acute kidney injury in intensive care unit patients, accounting for 15% to 20% of renal replacement therapy prescriptions. The neutrophil-lymphocyte ratio (NLR), a marker of systemic inflammation and immune response, was previously associated with the mortality rate in multiple conditions. Herein, we aimed to examine how the NLR relates to the mortality rate in septic acute kidney injury patients requiring continuous renal replacement therapy (CRRT). METHODS: The NLRs of 6 and 18 were used for dividing NLRs into three groups and, thus, were set higher than those in previous studies accounting for steroid use in sepsis. Cox proportional hazard models were used to calculate hazard ratios of mortality outcomes before and after matching their propensity scores. RESULTS: A total of 798 septic acute kidney injury patients requiring CRRT were classified into three NLR groups (low, <6 [n = 277]; medium, ≥6 and <18 [n = 115], and high, ≥18 [n = 406], respectively). The in-hospital mortality rates per group were 83.4%, 74.8%, and 70.4%, respectively (p < 0.001). Per the univariable Cox survival analysis after propensity score matching, a high NLR was related to approximately 24% reduced mortality. The survival benefit of the high NLR group compared with the other two groups remained consistent across all subgroups, showing any p for interactions of >0.05. CONCLUSION: A high NLR is associated with better clinical outcomes, such as low mortality, in septic acute kidney injury patients undergoing CRRT.

Evaluation of risk stratification for acute kidney injury: a comparative analysis of EKFC, 2009 and 2021 CKD-EPI glomerular filtration estimating equations.

BACKGROUND: The adoption of the 2021 CKD-EPIcr equation for glomerular filtration rate (GFR) estimation provided a race-free eGFR calculation. However, the discriminative performance for AKI risk has been rarely validated. We aimed to evaluate the differences in acute kidney injury (AKI) prediction or reclassification power according to the three eGFR equations. METHODS: We performed a retrospective observational study within a tertiary hospital from 2011 to 2021. Acute kidney injury was defined according to KDIGO serum creatinine criteria. Glomerular filtration rate estimates were calculated by three GFR estimating equations: 2009 and 2021 CKD-EPIcr, and EKFC. In three equations, AKI prediction performance was evaluated with area under receiver operator curves (AUROC) and reclassification power was evaluated with net reclassification improvement analysis. RESULTS: A total of 187,139 individuals, including 27,447 (14.7%) AKI and 159,692 (85.3%) controls, were enrolled. In the multivariable regression prediction model, the 2009 CKD-EPIcr model (continuous eGFR model 2, 0.7583 [0.755-0.7617]) showed superior performance in AKI prediction to the 2021 CKD-EPIcr (0.7564 [0.7531-0.7597], < 0.001) or EKFC model in AUROC (0.7577 [0.7543-0.761], < 0.001). Moreover, in reclassification of AKI, the 2021 CKD-EPIcr and EKFC models showed a worse classification performance than the 2009 CKD-EPIcr model. (- 7.24 [- 8.21-- 6.21], - 2.38 [- 2.72-- 1.97]). CONCLUSION: Regarding AKI risk stratification, the 2009 CKD-EPIcr equation showed better discriminative performance compared to the 2021 CKD-EPIcr equation in the study population.

Glutamyl-prolyl-tRNA synthetase (EPRS1) drives tubulointerstitial nephritis-induced fibrosis by enhancing T cell proliferation and activity.

Toxin- and drug-induced tubulointerstitial nephritis (TIN), characterized by interstitial infiltration of immune cells, frequently necessitates dialysis for patients due to irreversible fibrosis. However, agents modulating interstitial immune cells are lacking. Here, we addressed whether the housekeeping enzyme glutamyl-prolyl-transfer RNA synthetase 1 (EPRS1), responsible for attaching glutamic acid and proline to transfer RNA, modulates immune cell activity during TIN and whether its pharmacological inhibition abrogates fibrotic transformation. The immunological feature following TIN induction by means of an adenine-mixed diet was infiltration of EPRS1high T cells, particularly proliferating T and γδ T cells. The proliferation capacity of both CD4+ and CD8+ T cells, along with interleukin-17 production of γδ T cells, was higher in the kidneys of TIN-induced Eprs1+/+ mice than in the kidneys of TIN-induced Eprs1+/- mice. This discrepancy contributed to the fibrotic amelioration observed in kidneys of Eprs1+/- mice. TIN-induced fibrosis was also reduced in Rag1-/- mice adoptively transferred with Eprs1+/- T cells compared to the Rag1-/- mice transferred with Eprs1+/+ T cells. The use of an EPRS1-targeting small molecule inhibitor (bersiporocin) under clinical trials to evaluate its therapeutic potential against idiopathic pulmonary fibrosis alleviated immunofibrotic aggravation in TIN. EPRS1 expression was also observed in human kidney tissues and blood-derived T cells, and high expression was associated with worse patient outcomes. Thus, EPRS1 may emerge as a therapeutic target in toxin- and drug-induced TIN, modulating the proliferation and activity of infiltrated T cells.

Intradialytic hypotension and worse outcomes in patients with acute kidney injury requiring intermittent hemodialysis.

Background: Intradialytic hypotension (IDH) is a critical complication related to worse outcomes in patients undergoing maintenance hemodialysis. Herein, we addressed the impact of IDH on mortality and other outcomes in patients with severe acute kidney injury (AKI) requiring intermittent hemodialysis. Methods: We retrospectively reviewed 1,009 patients who underwent intermittent hemodialysis due to severe AKI. IDH was defined as either dialysis discontinuation due to hemodynamic instability or a decrease in systolic blood pressure (BP) of ≥30 mmHg, with or without a nadir systolic BP of <90 mmHg during the first session. The primary outcome was all-cause mortality, and transfer to the intensive care unit (ICU) due to unstable status was additionally analyzed. Hazard ratios (HRs) of outcomes were calculated using a Cox regression model after adjusting for multiple variables. Risk factors for IDH were evaluated using a logistic regression model. Results: IDH occurred in 449 patients (44.5%) during the first hemodialysis session. Patients with IDH had a higher mortality rate than those without IDH (40% vs. 23%; HR, 1.30; 95% confidence interval [CI], 1.02-1.65). The rate of ICU transfer was higher in patients experiencing IDH than in those without IDH (17% vs. 11%; HR, 1.43; 95% CI, 1.02-2.02). Factors such as old age, high BP and pulse rate, active malignancy, cirrhosis, and hypoalbuminemia were associated with an increased risk of IDH episodes. Conclusion: The occurrence of IDH is associated with worse outcomes in patients with AKI requiring intermittent hemodialysis. Therefore, careful monitoring and early intervention of IDH may be necessary in this patient subset.

Frequency of Fabry disease in chronic kidney disease patients including patients on renal replacement therapy in Korea.

BACKGROUND: Fabry disease (FD) is an X-linked lysosomal storage disorder caused by the deficient activity of α-galactosidase (α-Gal A), affecting multiple organs including kidney. In this study, we aimed to determine the prevalence of FD in patients with chronic kidney disease (CKD) including those on renal replacement therapy in Korea. METHODS: This is a national, multicenter, observational study performed between August 24, 2017 and February 28, 2020. Patients with the presence of proteinuria or treated on dialysis were screened by measuring the α-Gal A enzyme activity using either dried blood spot or whole blood, and plasma globotriaosylsphingosine (lyso-GL3) concentration. A GLA gene analysis was performed in patients with low α-Gal A enzyme activity or increased plasma lyso-GL3 concentration. RESULTS: Of 897 screened patients, 405 (45.2%) were male and 279 (31.1%) were on dialysis. The α-Gal A enzyme activity was measured in 891 patients (99.3%), and plasma lyso-GL3 concentration was measured in all patients. Ten patients were eligible for a GLA gene analysis: eight with low α-Gal A enzyme activity and two with increased plasma lyso-GL3 concentration. The GLA mutations were analyzed in nine patients and one patient was found with a pathogenic mutation. Therefore, one patient was identified with FD, giving a prevalence of 0.1% (1 of 897) in this CKD population. CONCLUSION: Although the prevalence of FD in the CKD population was low (0.1%), screening tests are crucial to detect potential diseases in patients with relatives who can benefit from early treatment.

Primary sclerosing cholangitis causally affects kidney function decline: A Mendelian randomization study.

BACKGROUND AND AIM: The causal linkage between primary sclerosing cholangitis (PSC) and kidney function is unexplored despite their potential for long-term detrimental effects on kidney function. METHODS: Two-sample summary-level Mendelian randomization (MR) study was conducted to identify the association between PSC and kidney function. The genetic variants were extracted from the PSC-specific multi-trait analyzed genome-wide association study (GWAS) of European ancestry. Summary-level data for kidney function traits, including estimated glomerular filtration rate (eGFR), annual eGFR decline, and chronic kidney disease (CKD), were obtained from the CKDGen consortium. Multiplicative random-effects inverse-variance weighted (MR-IVW), and a series of pleiotropy-robust analyses were performed to investigate the causal effects and ascertain their robustness. RESULTS: Significant causal associations between genetically predicted PSC and kidney function traits were identified. Genetically predicted PSC was associated with decreased log-transformed eGFR (MR-IVW; beta = -0.41%; standard error [SE] = 0.02%; P < 0.001), increased rate of annual eGFR decline (MR-IVW; beta = 2.43%; SE = 0.18%; P < 0.001), and higher risk of CKD (MR-IVW; odds ratio = 1.07; 95% confidence interval = 1.06-1.08; P < 0.001). The main findings were supported by pleiotropy-robust analysis, including MR-Egger with bootstrapped error and weighted median. CONCLUSIONS: Our study demonstrates that genetically predicted PSC is causally associated with kidney function impairment. Further studies are warranted to identify the underlying mechanisms.

Automatic segmentation of atrial fibrillation and flutter in single-lead electrocardiograms by self-supervised learning and Transformer architecture.

OBJECTIVES: Automatic detection of atrial fibrillation and flutter (AF/AFL) is a significant concern in preventing stroke and mitigating hemodynamic instability. Herein, we developed a Transformer-based deep learning model for AF/AFL segmentation in single-lead electrocardiograms (ECGs) by self-supervised learning with masked signal modeling (MSM). MATERIALS AND METHODS: We retrieved data from 11 open-source databases on PhysioNet; 7 of these databases included labeled ECGs, while the other 4 were without labels. Each database contained ECG recordings with durations of ≥30 s. A total of 24 intradialytic ECGs with paroxysmal AF/AFL during 4 h of hemodialysis sessions at Seoul National University Hospital were used for external validation. The model was pretrained by predicting masked areas of ECG signals and fine-tuned by predicting AF/AFL areas. Cross-database validation was used for evaluation, and the intersection over union (IOU) was used as a main performance metric in external database validation. RESULTS: In the 7 labeled databases, the areas marked as AF/AFL constituted 41.1% of the total ECG signals, ranging from 0.19% to 51.31%. In the evaluation per ECG segment, the model achieved IOU values of 0.9254 and 0.9477 for AF/AFL segmentation and other segmentation tasks, respectively. When applied to intradialytic ECGs with paroxysmal AF/AFL, the IOUs for the segmentation of AF/AFL and non-AF/AFL were 0.9896 and 0.9650, respectively. Model performance by different training procedure indicated that pretraining with MSM and the application of an appropriate masking ratio both contributed to the model performance. It also showed higher IOUs of AF/AFL labels than in previous studies when training and test databases were matched. CONCLUSION: The present model with self-supervised learning by MSM performs robustly in segmenting AF/AFL.

Soluble suppression of tumorigenicity 2 is a potential predictor of post-liver transplant renal outcomes.

Acute kidney injury is considered an independent prognostic factor for mortality in patients with liver cirrhosis. Non-treated acute kidney injury can progress to hepatorenal syndrome with a poor prognosis. As suppression of tumorigenicity 2 (ST2) is a member of the interleukin-1 receptor family that aggravates inflammation and fibrotic changes in multiple organs, we measured soluble ST2 (sST2) level in the serum and urine of liver-transplant recipients at the time of transplantation. The serum sST2 level significantly increased in liver-transplant recipients with suppressed kidney function compared with that in recipients with normal function. In recipients with severely decreased liver function (model for end-stage liver disease score ≥ 30), the serum sST2 level was higher than that in recipients with preserved liver function (model for end-stage liver disease score ≤ 20, P = 0.028). The serum sST2 level in recipients with hepatorenal syndrome was higher than that in liver-transplant recipients without hepatorenal syndrome (P = 0.003). The serum sST2 level in patients with hepatorenal syndrome was higher than that in recipients without a history of acute kidney injury (P = 0.004). Recipients with hepatorenal syndrome and recovered kidney function showed higher sST2 levels than those who did not recover (P = 0.034). Collectively, an increase in the serum sST2 level reflects a decrease in both kidney and liver functions. Thus, measuring sST2 level at the time of liver transplantation can help predict renal outcomes.

Automated Reference Kidney Histomorphometry using a Panoptic Segmentation Neural Network Correlates to Patient Demographics and Creatinine.

Reference histomorphometric data of healthy human kidneys are lacking due to laborious quantitation requirements. We leveraged deep learning to investigate the relationship of histomorphometry with patient age, sex, and serum creatinine in a multinational set of reference kidney tissue sections. A panoptic segmentation neural network was developed and used to segment viable and sclerotic glomeruli, cortical and medullary interstitia, tubules, and arteries/arterioles in digitized images of 79 periodic acid-Schiff (PAS)-stained human nephrectomy sections showing minimal pathologic changes. Simple morphometrics (e.g., area, radius, density) were measured from the segmented classes. Regression analysis was used to determine the relationship of histomorphometric parameters with age, sex, and serum creatinine. The model achieved high segmentation performance for all test compartments. We found that the size and density of nephrons, arteries/arterioles, and the baseline level of interstitium vary significantly among healthy humans, with potentially large differences between subjects from different geographic locations. Nephron size in any region of the kidney was significantly dependent on patient creatinine. Slight differences in renal vasculature and interstitium were observed between sexes. Finally, glomerulosclerosis percentage increased and cortical density of arteries/arterioles decreased as a function of age. We show that precise measurements of kidney histomorphometric parameters can be automated. Even in reference kidney tissue sections with minimal pathologic changes, several histomorphometric parameters demonstrated significant correlation to patient demographics and serum creatinine. These robust tools support the feasibility of deep learning to increase efficiency and rigor in histomorphometric analysis and pave the way for future large-scale studies.

Spatially Aware Transformer Networks for Contextual Prediction of Diabetic Nephropathy Progression from Whole Slide Images.

Diabetic nephropathy (DN) in the context of type 2 diabetes is the leading cause of end-stage renal disease (ESRD) in the United States. DN is graded based on glomerular morphology and has a spatially heterogeneous presentation in kidney biopsies that complicates pathologists' predictions of disease progression. Artificial intelligence and deep learning methods for pathology have shown promise for quantitative pathological evaluation and clinical trajectory estimation; but, they often fail to capture large-scale spatial anatomy and relationships found in whole slide images (WSIs). In this study, we present a transformer-based, multi-stage ESRD prediction framework built upon nonlinear dimensionality reduction, relative Euclidean pixel distance embeddings between every pair of observable glomeruli, and a corresponding spatial self-attention mechanism for a robust contextual representation. We developed a deep transformer network for encoding WSI and predicting future ESRD using a dataset of 56 kidney biopsy WSIs from DN patients at Seoul National University Hospital. Using a leave-one-out cross-validation scheme, our modified transformer framework outperformed RNNs, XGBoost, and logistic regression baseline models, and resulted in an area under the receiver operating characteristic curve (AUC) of 0.97 (95% CI: 0.90-1.00) for predicting two-year ESRD, compared with an AUC of 0.86 (95% CI: 0.66-0.99) without our relative distance embedding, and an AUC of 0.76 (95% CI: 0.59-0.92) without a denoising autoencoder module. While the variability and generalizability induced by smaller sample sizes are challenging, our distance-based embedding approach and overfitting mitigation techniques yielded results that suggest opportunities for future spatially aware WSI research using limited pathology datasets.

Real-time dual prediction of intradialytic hypotension and hypertension using an explainable deep learning model.

Both intradialytic hypotension (IDH) and hypertension (IDHTN) are associated with poor outcomes in hemodialysis patients, but a model predicting dual outcomes in real-time has never been developed. Herein, we developed an explainable deep learning model with a sequence-to-sequence-based attention network to predict both of these events simultaneously. We retrieved 302,774 hemodialysis sessions from the electronic health records of 11,110 patients, and these sessions were split into training (70%), validation (10%), and test (20%) datasets through patient randomization. The outcomes were defined when nadir systolic blood pressure (BP) < 90 mmHg (termed IDH-1), a decrease in systolic BP ≥ 20 mmHg and/or a decrease in mean arterial pressure ≥ 10 mmHg (termed IDH-2), or an increase in systolic BP ≥ 10 mmHg (i.e., IDHTN) occurred within 1 h. We developed a temporal fusion transformer (TFT)-based model and compared its performance in the test dataset, including receiver operating characteristic curve (AUROC) and area under the precision-recall curves (AUPRC), with those of other machine learning models, such as recurrent neural network, light gradient boosting machine, random forest, and logistic regression. Among all models, the TFT-based model achieved the highest AUROCs of 0.953 (0.952-0.954), 0.892 (0.891-0.893), and 0.889 (0.888-0.890) in predicting IDH-1, IDH-2, and IDHTN, respectively. The AUPRCs in the TFT-based model for these outcomes were higher than the other models. The factors that contributed the most to the prediction were age and previous session, which were time-invariant variables, as well as systolic BP and elapsed time, which were time-varying variables. The present TFT-based model predicts both IDH and IDHTN in real time and offers explainable variable importance.

Causal Effect of Chondroitin, Glucosamine, Vitamin, and Mineral Intake on Kidney Function: A Mendelian Randomization Study.

The causal effects of chondroitin, glucosamine, and vitamin/mineral supplement intake on kidney function remain unknown, despite being commonly used. We conducted a two-sample summary-level Mendelian randomization (MR) analysis to test for causal associations between regular dietary supplement intake and kidney function. Genetic instruments for chondroitin, glucosamine, and vitamin/mineral supplement intake were obtained from a genome-wide association study of European ancestry. Summary statistics for the log-transformed estimated glomerular filtration rate (log-eGFR) were provided by the CKDGen consortium. The multiplicative random-effects inverse-variance weighted method showed that genetically predicted chondroitin and glucosamine intake was causally associated with a lower eGFR (chondroitin, eGFR change beta = -0.113%, standard error (SE) = 0.03%, p-value = 2 × 10-4; glucosamine, eGFR change beta = -0.240%, SE = 0.035%, p-value = 6 × 10-12). However, a genetically predicted vitamin/mineral supplement intake was associated with a higher eGFR (eGFR change beta = 1.426%, SE = 0.136%, p-value = 1 × 10-25). Validation analyses and pleiotropy-robust MR results for chondroitin and vitamin/mineral supplement intake supported the main results. Our MR study suggests a potential causal effect of chondroitin and glucosamine intake on kidney function. Therefore, clinicians should carefully monitor their long-term effects.

Discovery of Biomarkers Related to Interstitial Fibrosis and Tubular Atrophy among Kidney Transplant Recipients by mRNA-Sequencing.

Interstitial fibrosis and tubular atrophy (IF/TA) after kidney transplantation causes a chronic deterioration of graft function. IF/TA can be diagnosed by means of a graft biopsy, which is a necessity as non-invasive diagnostic methods are unavailable. In this study, we identified IF/TA-related differentially expressed genes (DEGs) through next-generation sequencing using peripheral blood mononuclear cells. Blood samples from kidney transplant recipients undergoing standard immunosuppressive therapy (tacrolimus/mycophenolate mofetil or mycophenolate sodium/steroid) and diagnosed as IF/TA (n = 41) or normal (controls; n = 41) at their one-year protocol biopsy were recruited between January of 2020 and August of 2020. DEGs were derived through mRNA sequencing and validated by means of a quantitative real-time polymerase chain reaction. We identified 34 DEGs related to IF/TA. ADAMTS2, PLIN5, CLDN9, and KCNJ15 demonstrated a log2(fold change) of >1.5 and an area under the receiver operating characteristic curve (AUC) value of >0.6, with ADAMTS2 showing the largest AUC value and expression levels, which were 3.5-fold higher in the IF/TA group relative to that observed in the control group. We identified and validated DEGs related to IF/TA progression at one-year post-transplantation. Specifically, we identified ADAMTS2 as a potential IF/TA biomarker.