Pub Date : 2024-06-17eCollection Date: 2024-08-01DOI: 10.1159/000539568
Haifan Xing, Sijie Gu, Ze Li, Xiao-Er Wei, Li He, Qiye Liu, Haoran Feng, Niansong Wang, Hengye Huang, Ying Fan
Introduction: Patients undergoing maintenance hemodialysis are vulnerable to coronavirus disease 2019 (COVID-19), exhibiting a high risk of hospitalization and mortality. Thus, early identification and intervention are important to prevent disease progression in these patients.
Methods: This was a two-center retrospective observational study of patients on hemodialysis diagnosed with COVID-19 at the Lingang and Xuhui campuses of Shanghai Sixth People's Hospital. Patients were randomized into the training (130) and validation cohorts (54), while 59 additional patients served as an independent external validation cohort. Artificial intelligence-based parameters of chest computed tomography (CT) were quantified, and a nomogram for patient outcomes at 14 and 28 days was created by screening quantitative CT measures, clinical data, and laboratory examination items, using univariate and multivariate Cox regression models.
Results: The median dialysis duration was 48 (interquartile range, 24-96) months. Age, diabetes mellitus, serum phosphorus level, lymphocyte count, and chest CT score were identified as independent prognostic indicators and included in the nomogram. The concordance index values were 0.865, 0.914, and 0.885 in the training, internal validation, and external validation cohorts, respectively. Calibration plots showed good agreement between the expected and actual outcomes.
Conclusion: This is the first study in which a reliable nomogram was developed to predict short-term outcomes and survival probabilities in patients with COVID-19 on hemodialysis. This model may be helpful to clinicians in treating COVID-19, managing serum phosphorus, and adjusting the dialysis strategies for these vulnerable patients to prevent disease progression in the context of COVID-19 and continuous emergence of novel viruses.
{"title":"Incorporation of Chest Computed Tomography Quantification to Predict Outcomes for Patients on Hemodialysis with COVID-19.","authors":"Haifan Xing, Sijie Gu, Ze Li, Xiao-Er Wei, Li He, Qiye Liu, Haoran Feng, Niansong Wang, Hengye Huang, Ying Fan","doi":"10.1159/000539568","DOIUrl":"10.1159/000539568","url":null,"abstract":"<p><strong>Introduction: </strong>Patients undergoing maintenance hemodialysis are vulnerable to coronavirus disease 2019 (COVID-19), exhibiting a high risk of hospitalization and mortality. Thus, early identification and intervention are important to prevent disease progression in these patients.</p><p><strong>Methods: </strong>This was a two-center retrospective observational study of patients on hemodialysis diagnosed with COVID-19 at the Lingang and Xuhui campuses of Shanghai Sixth People's Hospital. Patients were randomized into the training (130) and validation cohorts (54), while 59 additional patients served as an independent external validation cohort. Artificial intelligence-based parameters of chest computed tomography (CT) were quantified, and a nomogram for patient outcomes at 14 and 28 days was created by screening quantitative CT measures, clinical data, and laboratory examination items, using univariate and multivariate Cox regression models.</p><p><strong>Results: </strong>The median dialysis duration was 48 (interquartile range, 24-96) months. Age, diabetes mellitus, serum phosphorus level, lymphocyte count, and chest CT score were identified as independent prognostic indicators and included in the nomogram. The concordance index values were 0.865, 0.914, and 0.885 in the training, internal validation, and external validation cohorts, respectively. Calibration plots showed good agreement between the expected and actual outcomes.</p><p><strong>Conclusion: </strong>This is the first study in which a reliable nomogram was developed to predict short-term outcomes and survival probabilities in patients with COVID-19 on hemodialysis. This model may be helpful to clinicians in treating COVID-19, managing serum phosphorus, and adjusting the dialysis strategies for these vulnerable patients to prevent disease progression in the context of COVID-19 and continuous emergence of novel viruses.</p>","PeriodicalId":17830,"journal":{"name":"Kidney Diseases","volume":null,"pages":null},"PeriodicalIF":3.2,"publicationDate":"2024-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11309758/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141917065","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-17eCollection Date: 2024-08-01DOI: 10.1159/000539516
Xingying Zhu, Wai W Cheung, Aihua Zhang, Guixia Ding
Background: Primary hyperoxaluria (PH) is a rare autosomal recessive disorder, mainly due to the increase in endogenous oxalate production, causing a series of clinical features such as kidney stones, nephrocalcinosis, progressive impairment of renal function, and systemic oxalosis. There are three common genetic causes of glycolate metabolism anomalies. Among them, PH type 1 is the most prevalent and severe type, and early end-stage renal failure often occurs.
Summary: This review summarizes PH through pathophysiology, genotype, clinical manifestation, diagnosis, and treatment options. And explore the characteristics of Chinese PH patients.
Key messages: Diagnosis of this rare disease is based on clinical symptoms, urinary or blood oxalate concentrations, liver biopsy, and genetic testing. Currently, the main treatment is massive hydration, citrate inhibition of crystallization, dialysis, liver and kidney transplantation, and pyridoxine. Recently, RNA interference drugs have also been used. In addition, technologies such as gene editing and autologous liver cell transplantation are also being developed. C.815_816insGA and c.33_34insC mutation in the AGXT gene could be a common variant in Chinese PH1 population. Mutations at the end of exon 6 account for approximately 50% of all Chinese HOGA1 mutations. Currently, the treatment of PH in China still relies mainly on symptomatic and high-throughput dialysis, with poor prognosis (especially for PH1 patients).
{"title":"Mutation Characteristics of Primary Hyperoxaluria in the Chinese Population and Current International Diagnosis and Treatment Status.","authors":"Xingying Zhu, Wai W Cheung, Aihua Zhang, Guixia Ding","doi":"10.1159/000539516","DOIUrl":"10.1159/000539516","url":null,"abstract":"<p><strong>Background: </strong>Primary hyperoxaluria (PH) is a rare autosomal recessive disorder, mainly due to the increase in endogenous oxalate production, causing a series of clinical features such as kidney stones, nephrocalcinosis, progressive impairment of renal function, and systemic oxalosis. There are three common genetic causes of glycolate metabolism anomalies. Among them, PH type 1 is the most prevalent and severe type, and early end-stage renal failure often occurs.</p><p><strong>Summary: </strong>This review summarizes PH through pathophysiology, genotype, clinical manifestation, diagnosis, and treatment options. And explore the characteristics of Chinese PH patients.</p><p><strong>Key messages: </strong>Diagnosis of this rare disease is based on clinical symptoms, urinary or blood oxalate concentrations, liver biopsy, and genetic testing. Currently, the main treatment is massive hydration, citrate inhibition of crystallization, dialysis, liver and kidney transplantation, and pyridoxine. Recently, RNA interference drugs have also been used. In addition, technologies such as gene editing and autologous liver cell transplantation are also being developed. C.815_816insGA and c.33_34insC mutation in the <i>AGXT</i> gene could be a common variant in Chinese PH1 population. Mutations at the end of exon 6 account for approximately 50% of all Chinese HOGA1 mutations. Currently, the treatment of PH in China still relies mainly on symptomatic and high-throughput dialysis, with poor prognosis (especially for PH1 patients).</p>","PeriodicalId":17830,"journal":{"name":"Kidney Diseases","volume":null,"pages":null},"PeriodicalIF":3.2,"publicationDate":"2024-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11309763/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141917066","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Introduction: Wet contamination was a common problem of peritoneal dialysis (PD) system. We developed a management algorithm for wet contamination of PD system (wet contamination) on the basis of the related research literature and clinical practice experience. The purpose of this study was to observe clinical effect of the management algorithm on the prevention of peritonitis.
Methods: Patients treated wet contamination in a single PD center between October 2017 and September 2022 were included. A management algorithm was established to treat wet contamination. It comprised identification of the contamination type, addressing contaminated or aging catheters, prophylactic antibiotics, and retraining. Demographic data and clinical data about wet contamination were collected and compared.
Results: One hundred and forty-one cases of wet contamination were included in this study. The mean age was 51.7 ± 14.1 years, and 49.6% were female. The proportion of diabetic nephropathy was 9.9%. The median PD duration was 27.0 (1.7-79.7) months. Eighteen episodes (12.8%) of wet contamination-associated peritonitis developed after wet contamination. The main pathogenic bacteria of peritonitis were Gram-positive bacteria (33.3%) and Gram-negative bacteria (27.8%). The incidence of wet contamination-associated peritonitis in the compliance with the management algorithm group was significantly lower than that in the non-compliance with the management algorithm group (0.9 vs. 48.6%; p < 0.001). Non-compliance with management algorithm (OR = 185.861, p < 0.001) together with advance age (OR = 1.116, p < 0.001) and longer distance from home to hospital (OR = 1.007, p < 0.001) were independent risk factors for wet contamination-associated peritonitis.
Conclusion: The management algorithm for wet contamination of PD system could reduce the risk of peritonitis.
{"title":"Effect of a Management Algorithm for Wet Contamination of Peritoneal Dialysis System on the Prevention of Peritonitis: A Prospective Observational Study.","authors":"Chunyan Yi, Wenbo Zhang, Qunying Guo, Jianxiong Lin, Wei Chen, Haiping Mao, Xiao Yang","doi":"10.1159/000539582","DOIUrl":"10.1159/000539582","url":null,"abstract":"<p><strong>Introduction: </strong>Wet contamination was a common problem of peritoneal dialysis (PD) system. We developed a management algorithm for wet contamination of PD system (wet contamination) on the basis of the related research literature and clinical practice experience. The purpose of this study was to observe clinical effect of the management algorithm on the prevention of peritonitis.</p><p><strong>Methods: </strong>Patients treated wet contamination in a single PD center between October 2017 and September 2022 were included. A management algorithm was established to treat wet contamination. It comprised identification of the contamination type, addressing contaminated or aging catheters, prophylactic antibiotics, and retraining. Demographic data and clinical data about wet contamination were collected and compared.</p><p><strong>Results: </strong>One hundred and forty-one cases of wet contamination were included in this study. The mean age was 51.7 ± 14.1 years, and 49.6% were female. The proportion of diabetic nephropathy was 9.9%. The median PD duration was 27.0 (1.7-79.7) months. Eighteen episodes (12.8%) of wet contamination-associated peritonitis developed after wet contamination. The main pathogenic bacteria of peritonitis were Gram-positive bacteria (33.3%) and Gram-negative bacteria (27.8%). The incidence of wet contamination-associated peritonitis in the compliance with the management algorithm group was significantly lower than that in the non-compliance with the management algorithm group (0.9 vs. 48.6%; <i>p</i> < 0.001). Non-compliance with management algorithm (OR = 185.861, <i>p</i> < 0.001) together with advance age (OR = 1.116, <i>p</i> < 0.001) and longer distance from home to hospital (OR = 1.007, <i>p</i> < 0.001) were independent risk factors for wet contamination-associated peritonitis.</p><p><strong>Conclusion: </strong>The management algorithm for wet contamination of PD system could reduce the risk of peritonitis.</p>","PeriodicalId":17830,"journal":{"name":"Kidney Diseases","volume":null,"pages":null},"PeriodicalIF":3.2,"publicationDate":"2024-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11309752/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141917063","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Chi Wang, Qian Xin, Junjuan Li, Jianli Wang, S. Yao, Miao Wang, Maoxiang Zhao, Shuohua Chen, Shouling Wu, Hao Xue
Introduction: The association between the longitudinal patterns of estimated glomerular filtration rate (eGFR) and risk of atrial fibrillation (AF) in populations with normal or mildly impaired renal function is not well-characterized. We sought to explore the eGFR trajectories in populations with normal or mildly impaired renal function and their association with AF. Methods: This prospective cohort study included 62,407 participants who were free of AF, cardiovascular diseases, and moderate to severe renal insufficiency (eGFR <60 mL/min/1.73m2) before 2010. The eGFR trajectories were developed using latent mixture modeling based on examination data in 2006, 2008, and 2010. Incident AF cases were identified in biennial electrocardiogram assessment and a review of medical insurance data and discharge registers. We used Cox regression models to estimate the hazard ratios and 95% confidence intervals (CI) for incident AF. Results: According to survey results for the range and changing pattern of eGFR during 2006 to 2010, four trajectories were identified: high-stable (range, 107.47 to 110.25 mL/min/1.73m2; n=11,719), moderate-increasing (median increase from 83.83 to 100.37 mL/min/1.73m2; n=22,634), high-decreasing (median decrease from 101.72 to 89.10 mL/min/1.73m2; n=7,943), and low-stable (range, 73.48 to 76.78 mL/min/1.73m2; n=20,111). After an average follow-up of 9.63 years, a total of 485 cases of AF were identified. Compared with the high-stable trajectory, the adjusted hazard ratios of AF were 1.70 (95% CI, 1.09–2.66) for the moderate-increasing trajectory, 1.92 (95% CI, 1.18–3.13) for the high-decreasing trajectory, and 2.28 (95% CI, 1.46–3.56) for the low-stable trajectory. The results remained consistent across a number of sensitivity analyses. Conclusions: The trajectories of eGFR were associated with subsequent AF risk in populations with normal or mildly impaired renal function.
{"title":"Association of Estimated Glomerular Filtration Rate Trajectories with Atrial Fibrillation Risk in Populations with Normal or Mildly Impaired Renal Function","authors":"Chi Wang, Qian Xin, Junjuan Li, Jianli Wang, S. Yao, Miao Wang, Maoxiang Zhao, Shuohua Chen, Shouling Wu, Hao Xue","doi":"10.1159/000539289","DOIUrl":"https://doi.org/10.1159/000539289","url":null,"abstract":"Introduction: The association between the longitudinal patterns of estimated glomerular filtration rate (eGFR) and risk of atrial fibrillation (AF) in populations with normal or mildly impaired renal function is not well-characterized. We sought to explore the eGFR trajectories in populations with normal or mildly impaired renal function and their association with AF. \u0000Methods: This prospective cohort study included 62,407 participants who were free of AF, cardiovascular diseases, and moderate to severe renal insufficiency (eGFR <60 mL/min/1.73m2) before 2010. The eGFR trajectories were developed using latent mixture modeling based on examination data in 2006, 2008, and 2010. Incident AF cases were identified in biennial electrocardiogram assessment and a review of medical insurance data and discharge registers. We used Cox regression models to estimate the hazard ratios and 95% confidence intervals (CI) for incident AF. \u0000Results: According to survey results for the range and changing pattern of eGFR during 2006 to 2010, four trajectories were identified: high-stable (range, 107.47 to 110.25 mL/min/1.73m2; n=11,719), moderate-increasing (median increase from 83.83 to 100.37 mL/min/1.73m2; n=22,634), high-decreasing (median decrease from 101.72 to 89.10 mL/min/1.73m2; n=7,943), and low-stable (range, 73.48 to 76.78 mL/min/1.73m2; n=20,111). After an average follow-up of 9.63 years, a total of 485 cases of AF were identified. Compared with the high-stable trajectory, the adjusted hazard ratios of AF were 1.70 (95% CI, 1.09–2.66) for the moderate-increasing trajectory, 1.92 (95% CI, 1.18–3.13) for the high-decreasing trajectory, and 2.28 (95% CI, 1.46–3.56) for the low-stable trajectory. The results remained consistent across a number of sensitivity analyses.\u0000Conclusions: The trajectories of eGFR were associated with subsequent AF risk in populations with normal or mildly impaired renal function.","PeriodicalId":17830,"journal":{"name":"Kidney Diseases","volume":null,"pages":null},"PeriodicalIF":3.7,"publicationDate":"2024-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141118847","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-04-26eCollection Date: 2024-08-01DOI: 10.1159/000539024
Miao Hu, Xiahong Shen, Ling Zhou
Background: Diabetic kidney disease (DKD), a metabolism-related syndrome characterized by abnormal glomerular filtration rate, proteinuria, and renal microangiopathy, is one of the most common forms of chronic kidney disease, whereas extracellular vesicles (EVs) have been recently evidenced as a novel cell communication player in DKD occurrence and progress via releasing various bioactive molecules, including proteins, lipids, and especially RNA, among which noncoding RNAs (including miRNAs, lncRNAs, and circRNAs) are the major regulators. However, the functional relevance of EV-derived ncRNAs in DKD is to be elucidated.
Summary: Studies have reported that EV-derived ncRNAs regulate gene expression via a diverse range of regulatory mechanisms, contributing to diverse phenotypes related to DKD progression. Furthermore, there are already many potential clinical diagnostic and therapeutic studies based on these ncRNAs, which can be expected to have potential applications in clinical practice for EV-derived ncRNAs.
Key messages: In the current review, we summarized the mechanistic role of EVs in DKD according to biological function classifications, including inflammation and oxidative stress, epithelial-mesenchymal transition, cell death, and extracellular matrix deposition. In addition, we comprehensively discussed the potential applications of EV-derived ncRNAs as diagnostic biomarkers and therapeutic targets in DKD.
背景:糖尿病肾病(DKD)是一种以肾小球滤过率异常、蛋白尿和肾脏微血管病变为特征的代谢相关综合征,是最常见的慢性肾病之一、而细胞外囊泡(EVs)通过释放各种生物活性分子,包括蛋白质、脂类,尤其是 RNA,其中非编码 RNAs(包括 miRNAs、lncRNAs 和 circRNAs)是主要的调控因子,最近已被证实是 DKD 发生和发展过程中的一种新型细胞通讯方式。摘要:有研究报告称,EV衍生的ncRNA通过多种调控机制调控基因表达,导致与DKD进展相关的多种表型。此外,目前已有许多基于这些 ncRNAs 的潜在临床诊断和治疗研究,预计 EV 衍生的 ncRNAs 有可能应用于临床实践:在本综述中,我们根据炎症和氧化应激、上皮-间质转化、细胞死亡和细胞外基质沉积等生物功能分类,总结了EVs在DKD中的机理作用。此外,我们还全面讨论了 EV 衍生的 ncRNA 作为 DKD 诊断生物标志物和治疗靶点的潜在应用。
{"title":"Role of Extracellular Vesicle-Derived Noncoding RNAs in Diabetic Kidney Disease.","authors":"Miao Hu, Xiahong Shen, Ling Zhou","doi":"10.1159/000539024","DOIUrl":"10.1159/000539024","url":null,"abstract":"<p><strong>Background: </strong>Diabetic kidney disease (DKD), a metabolism-related syndrome characterized by abnormal glomerular filtration rate, proteinuria, and renal microangiopathy, is one of the most common forms of chronic kidney disease, whereas extracellular vesicles (EVs) have been recently evidenced as a novel cell communication player in DKD occurrence and progress via releasing various bioactive molecules, including proteins, lipids, and especially RNA, among which noncoding RNAs (including miRNAs, lncRNAs, and circRNAs) are the major regulators. However, the functional relevance of EV-derived ncRNAs in DKD is to be elucidated.</p><p><strong>Summary: </strong>Studies have reported that EV-derived ncRNAs regulate gene expression via a diverse range of regulatory mechanisms, contributing to diverse phenotypes related to DKD progression. Furthermore, there are already many potential clinical diagnostic and therapeutic studies based on these ncRNAs, which can be expected to have potential applications in clinical practice for EV-derived ncRNAs.</p><p><strong>Key messages: </strong>In the current review, we summarized the mechanistic role of EVs in DKD according to biological function classifications, including inflammation and oxidative stress, epithelial-mesenchymal transition, cell death, and extracellular matrix deposition. In addition, we comprehensively discussed the potential applications of EV-derived ncRNAs as diagnostic biomarkers and therapeutic targets in DKD.</p>","PeriodicalId":17830,"journal":{"name":"Kidney Diseases","volume":null,"pages":null},"PeriodicalIF":3.2,"publicationDate":"2024-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11309761/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141918608","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-04-16eCollection Date: 2024-08-01DOI: 10.1159/000538929
Joohyung Ha, Jong Cheol Jeong, Jung-Hwa Ryu, Myung-Gyu Kim, Kyu Ha Huh, Kyo Won Lee, Hee-Yeon Jung, Kyung Pyo Kang, Han Ro, Seungyeup Han, Beom Seok Kim, Jaeseok Yang
Introduction: Coronary artery calcification score (CACS) and abdominal aortic calcification score (AACS) are both well-established markers of vascular stiffness, and previous studies have shown that a higher CACS is a risk factor for chronic kidney disease (CKD) progression. However, the impact of pretransplant CACS and AACS on cardiovascular and renal outcomes in kidney transplant patients has not been established.
Methods: We included 944 kidney transplant recipients from the KoreaN cohort study for Outcome in patients With Kidney Transplantation (KNOW-KT) cohort and categorized them into three groups (low, medium, and high) according to baseline CACS (0, 0 < and ≤100, >100) and AACS (0, 1-4, >4). The low (0), medium (0 < and ≤ 100), and high (>100) CACS groups each consisted of 462, 213, and 225 patients, respectively. Similarly, the low (0), medium (1-4), and high (>4) AACS groups included 638, 159, and 147 patients, respectively. The primary outcome was the occurrence of cardiovascular events. The secondary outcomes were all-cause mortality and composite kidney outcomes, which comprised of >50% decline in the estimated glomerular filtration rate and graft loss. Cox regression analysis was used to investigate the association between baseline CACS/AACS and outcomes.
Results: The high CACS group (N = 462) faced a significantly higher risk for cardiovascular outcomes (adjusted hazard ratio [aHR], 5.97; 95% confidence interval [CI], 2.01-17.7) and all-cause mortality (aHR, 2.74; 95% CI, 1.27-5.92) compared to the low CACS group (N = 225). Similarly, the high AACS group (N = 638) had an elevated risk for cardiovascular outcomes (aHR, 2.38; 95% CI, 1.16-4.88). Furthermore, the addition of CACS to prediction models improved prediction indices for cardiovascular outcomes. However, the risk of renal outcomes did not differ among CACS or AACS groups.
Conclusion: Pretransplant arterial calcification, characterized by high CACS or AACS, is an independent risk factor for cardiovascular outcomes and mortality in kidney transplant patients.
{"title":"Impact of Arterial Calcification on Cardiovascular and Renal Outcomes in Kidney Transplant Patients.","authors":"Joohyung Ha, Jong Cheol Jeong, Jung-Hwa Ryu, Myung-Gyu Kim, Kyu Ha Huh, Kyo Won Lee, Hee-Yeon Jung, Kyung Pyo Kang, Han Ro, Seungyeup Han, Beom Seok Kim, Jaeseok Yang","doi":"10.1159/000538929","DOIUrl":"10.1159/000538929","url":null,"abstract":"<p><strong>Introduction: </strong>Coronary artery calcification score (CACS) and abdominal aortic calcification score (AACS) are both well-established markers of vascular stiffness, and previous studies have shown that a higher CACS is a risk factor for chronic kidney disease (CKD) progression. However, the impact of pretransplant CACS and AACS on cardiovascular and renal outcomes in kidney transplant patients has not been established.</p><p><strong>Methods: </strong>We included 944 kidney transplant recipients from the KoreaN cohort study for Outcome in patients With Kidney Transplantation (KNOW-KT) cohort and categorized them into three groups (low, medium, and high) according to baseline CACS (0, 0 < and ≤100, >100) and AACS (0, 1-4, >4). The low (0), medium (0 < and ≤ 100), and high (>100) CACS groups each consisted of 462, 213, and 225 patients, respectively. Similarly, the low (0), medium (1-4), and high (>4) AACS groups included 638, 159, and 147 patients, respectively. The primary outcome was the occurrence of cardiovascular events. The secondary outcomes were all-cause mortality and composite kidney outcomes, which comprised of >50% decline in the estimated glomerular filtration rate and graft loss. Cox regression analysis was used to investigate the association between baseline CACS/AACS and outcomes.</p><p><strong>Results: </strong>The high CACS group (<i>N</i> = 462) faced a significantly higher risk for cardiovascular outcomes (adjusted hazard ratio [aHR], 5.97; 95% confidence interval [CI], 2.01-17.7) and all-cause mortality (aHR, 2.74; 95% CI, 1.27-5.92) compared to the low CACS group (<i>N</i> = 225). Similarly, the high AACS group (<i>N</i> = 638) had an elevated risk for cardiovascular outcomes (aHR, 2.38; 95% CI, 1.16-4.88). Furthermore, the addition of CACS to prediction models improved prediction indices for cardiovascular outcomes. However, the risk of renal outcomes did not differ among CACS or AACS groups.</p><p><strong>Conclusion: </strong>Pretransplant arterial calcification, characterized by high CACS or AACS, is an independent risk factor for cardiovascular outcomes and mortality in kidney transplant patients.</p>","PeriodicalId":17830,"journal":{"name":"Kidney Diseases","volume":null,"pages":null},"PeriodicalIF":3.2,"publicationDate":"2024-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11309755/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141917064","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Background: The increasing prevalence of kidney diseases has become a significant public health issue, with a global prevalence exceeding 10%. In order to accurately identify biochemical changes and treatment outcomes associated with kidney diseases, novel methods targeting specific genes have been discovered. Among these genes, leucine-rich α-2 glycoprotein 1 (LRG1) has been identified to function as a multifunctional pathogenic signaling molecule in multiple diseases, including kidney diseases. This study aims to provide a comprehensive overview of the current evidence regarding the roles of LRG1 in different types of kidney diseases. Summary: Based on a comprehensive review, it was found that LRG1 was up-regulated in the urine, serum, or renal tissues of patients or experimental animal models with multiple kidney diseases, such as diabetic nephropathy, kidney injury, IgA nephropathy, chronic kidney diseases (CKD), clear cell renal cell carcinoma (ccRCC), end-stage renal disease, canine leishmaniosis-induced kidney disease, kidney fibrosis, and aristolochic acid nephropathy. Mechanistically, the role of LRG1 in kidney diseases is believed to be detrimental, potentially through its regulation of various genes and signaling cascades, i.e. FN1, GPR56, VEGF, VEGFR-2, DR5, GDF15, HIF-1α, SPP1, ALK1-Smad1/5/8, NLRP3-IL-1b, and TGF-β pathway. Key Messages: Further research is needed to fully comprehend the molecular mechanisms by which LRG1 contributes to the pathogenesis and pathophysiology of kidney diseases. It is anticipated that targeted treatments focusing on LRG1 will be utilized in clinical trials and implemented in clinical practice in the future.
{"title":"LRG1 contributes to the pathogenesis of multiple kidney diseases: a comprehensive review","authors":"Chunyan Chen, Jingwei Zhang, Tao Yu, Haiya Feng, Jian Liao, Yifei Jia","doi":"10.1159/000538443","DOIUrl":"https://doi.org/10.1159/000538443","url":null,"abstract":"Background: The increasing prevalence of kidney diseases has become a significant public health issue, with a global prevalence exceeding 10%. In order to accurately identify biochemical changes and treatment outcomes associated with kidney diseases, novel methods targeting specific genes have been discovered. Among these genes, leucine-rich α-2 glycoprotein 1 (LRG1) has been identified to function as a multifunctional pathogenic signaling molecule in multiple diseases, including kidney diseases. This study aims to provide a comprehensive overview of the current evidence regarding the roles of LRG1 in different types of kidney diseases. \u0000Summary: Based on a comprehensive review, it was found that LRG1 was up-regulated in the urine, serum, or renal tissues of patients or experimental animal models with multiple kidney diseases, such as diabetic nephropathy, kidney injury, IgA nephropathy, chronic kidney diseases (CKD), clear cell renal cell carcinoma (ccRCC), end-stage renal disease, canine leishmaniosis-induced kidney disease, kidney fibrosis, and aristolochic acid nephropathy. Mechanistically, the role of LRG1 in kidney diseases is believed to be detrimental, potentially through its regulation of various genes and signaling cascades, i.e. FN1, GPR56, VEGF, VEGFR-2, DR5, GDF15, HIF-1α, SPP1, ALK1-Smad1/5/8, NLRP3-IL-1b, and TGF-β pathway. \u0000Key Messages: Further research is needed to fully comprehend the molecular mechanisms by which LRG1 contributes to the pathogenesis and pathophysiology of kidney diseases. It is anticipated that targeted treatments focusing on LRG1 will be utilized in clinical trials and implemented in clinical practice in the future.","PeriodicalId":17830,"journal":{"name":"Kidney Diseases","volume":null,"pages":null},"PeriodicalIF":3.7,"publicationDate":"2024-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140750939","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Background: This study aimed to develop and validate a machine learning (ML) model based on serum Klotho for predicting end-stage kidney disease (ESKD) and cardiovascular disease (CVD) in patients with chronic kidney disease (CKD). Methods: Five different ML models were trained to predict the risk of ESKD and CVD at three different time points (3, 5, and 8-year) using a cohort of 400 non-dialysis CKD patients. The dataset was divided into a training set (70%) and an internal validation set (30%). These models were informed by data comprising 47 clinical features, including serum Klotho. The best-performing model was selected and used to identify risk factors for each outcome. Model performance was assessed using various metrics. Results: The findings showed that the Lasso regression model had the highest accuracy (C-index=0.71) in predicting ESKD. The features mainly included in this model were estimated glomerular filtration rate (eGFR), 24-hour urinary microalbumin, serum albumin, phosphate, parathyroid hormone, and serum Klotho, which achieved the highest area under the curve (AUC) of 0.930 (95% CI: 0.897-0.962). In addition, for the CVD risk prediction, the Random Survival Forest (RSF) model with the highest accuracy (C-index=0.66) was selected and achieved the highest AUC of 0.782 (95% CI: 0.633-0.930). The features mainly included in this model were age, history of primary hypertension, calcium, tumor necrosis factor-alpha, and serum Klotho. Conclusion: We successfully developed and validated Klotho-based ML risk prediction models for CVD and ESKD in CKD patients with good performance, indicating their high clinical utility.
{"title":"A Klotho-based Machine Learning Model for Prediction of both Kidney and Cardiovascular Outcomes in Chronic Kidney Disease","authors":"Yating Wang, Yu Shi, Tangli Xiao, Xianjin Bi, Qingyu Huo, Shaobo Wang, Jiachuan Xiong, Jinghong Zhao","doi":"10.1159/000538510","DOIUrl":"https://doi.org/10.1159/000538510","url":null,"abstract":"Background: This study aimed to develop and validate a machine learning (ML) model based on serum Klotho for predicting end-stage kidney disease (ESKD) and cardiovascular disease (CVD) in patients with chronic kidney disease (CKD).\u0000Methods: Five different ML models were trained to predict the risk of ESKD and CVD at three different time points (3, 5, and 8-year) using a cohort of 400 non-dialysis CKD patients. The dataset was divided into a training set (70%) and an internal validation set (30%). These models were informed by data comprising 47 clinical features, including serum Klotho. The best-performing model was selected and used to identify risk factors for each outcome. Model performance was assessed using various metrics.\u0000Results: The findings showed that the Lasso regression model had the highest accuracy (C-index=0.71) in predicting ESKD. The features mainly included in this model were estimated glomerular filtration rate (eGFR), 24-hour urinary microalbumin, serum albumin, phosphate, parathyroid hormone, and serum Klotho, which achieved the highest area under the curve (AUC) of 0.930 (95% CI: 0.897-0.962). In addition, for the CVD risk prediction, the Random Survival Forest (RSF) model with the highest accuracy (C-index=0.66) was selected and achieved the highest AUC of 0.782 (95% CI: 0.633-0.930). The features mainly included in this model were age, history of primary hypertension, calcium, tumor necrosis factor-alpha, and serum Klotho.\u0000Conclusion: We successfully developed and validated Klotho-based ML risk prediction models for CVD and ESKD in CKD patients with good performance, indicating their high clinical utility.","PeriodicalId":17830,"journal":{"name":"Kidney Diseases","volume":null,"pages":null},"PeriodicalIF":3.7,"publicationDate":"2024-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140384432","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-03-18eCollection Date: 2024-06-01DOI: 10.1159/000538372
Yan Tu, Zuo-Lin Li, Hong Liu, Ri-Ning Tang, Gui-Hua Wang, Lin-Li Lv, Bin Wang, Bi-Cheng Liu
Introduction: Roxadustat, the first-in-class drug for the treatment of renal anemia, has demonstrated efficacy in renal anemia with microinflammation. Additional data are needed regarding the efficacy of roxadustat on renal anemia with systemic macroinflammation.
Methods: Three cohorts of renal anemia based on the basic level of high-sensitivity CRP were included. Patients with hsCRP ≤2 mg/L were selected as non-inflammation (NI) group; 2< hsCRP ≤10 mg/L as microinflammation (MI) group; hsCRP≥10 mg/L as macroinflammation (MA) group. Patients received oral roxadustat three times per week for 52 weeks. The primary end point was the hemoglobin level over weeks 12-52. The second end point was the cumulative proportion of patients achieving hemoglobin response by the end of week 12.
Results: A total of 107 patients with chronic kidney diseases (CKDs) were enrolled. Overall, the baseline hemoglobin level of patients was 79.99 ± 11.20 g/L. Roxadustat could significantly increase the hemoglobin level in all of the three groups and did not show any significant difference (p > 0.05, respectively). Meanwhile, compared with that of the NI group, there was no significant difference in hemoglobin response rate in the MA group both at week 12 (p = 0.06; 95% confidence interval [CI], 0.9531-13.75) and week 52 (p = 0.37; 95% CI, 0.5080-7.937). Moreover, the hemoglobin response was independent of baseline hsCRP level (p = 0.72, 95% CI, -0.1139 to 0.0794). More importantly, roxadustat significantly reduced ferritin and serum iron levels and increased total iron-binding capacity in the three groups, which showed no significant differences among the three groups (p > 0.05, respectively).
Conclusion: Roxadustat significantly improves anemia in CKD patients with systemic macroinflammation.
{"title":"Roxadustat on Renal Anemia with Macroinflammation: A Retrospective Cohort Study.","authors":"Yan Tu, Zuo-Lin Li, Hong Liu, Ri-Ning Tang, Gui-Hua Wang, Lin-Li Lv, Bin Wang, Bi-Cheng Liu","doi":"10.1159/000538372","DOIUrl":"10.1159/000538372","url":null,"abstract":"<p><strong>Introduction: </strong>Roxadustat, the first-in-class drug for the treatment of renal anemia, has demonstrated efficacy in renal anemia with microinflammation. Additional data are needed regarding the efficacy of roxadustat on renal anemia with systemic macroinflammation.</p><p><strong>Methods: </strong>Three cohorts of renal anemia based on the basic level of high-sensitivity CRP were included. Patients with hsCRP ≤2 mg/L were selected as non-inflammation (NI) group; 2< hsCRP ≤10 mg/L as microinflammation (MI) group; hsCRP≥10 mg/L as macroinflammation (MA) group. Patients received oral roxadustat three times per week for 52 weeks. The primary end point was the hemoglobin level over weeks 12-52. The second end point was the cumulative proportion of patients achieving hemoglobin response by the end of week 12.</p><p><strong>Results: </strong>A total of 107 patients with chronic kidney diseases (CKDs) were enrolled. Overall, the baseline hemoglobin level of patients was 79.99 ± 11.20 g/L. Roxadustat could significantly increase the hemoglobin level in all of the three groups and did not show any significant difference (<i>p</i> > 0.05, respectively). Meanwhile, compared with that of the NI group, there was no significant difference in hemoglobin response rate in the MA group both at week 12 (<i>p</i> = 0.06; 95% confidence interval [CI], 0.9531-13.75) and week 52 (<i>p</i> = 0.37; 95% CI, 0.5080-7.937). Moreover, the hemoglobin response was independent of baseline hsCRP level (<i>p</i> = 0.72, 95% CI, -0.1139 to 0.0794). More importantly, roxadustat significantly reduced ferritin and serum iron levels and increased total iron-binding capacity in the three groups, which showed no significant differences among the three groups (<i>p</i> > 0.05, respectively).</p><p><strong>Conclusion: </strong>Roxadustat significantly improves anemia in CKD patients with systemic macroinflammation.</p>","PeriodicalId":17830,"journal":{"name":"Kidney Diseases","volume":null,"pages":null},"PeriodicalIF":3.7,"publicationDate":"2024-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11149990/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141248061","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Background: Ferroptosis, a newly recognized form of programmed cell death, is distinguished by its reliance on reactive oxygen species and iron-mediated lipid peroxidation, setting it apart from established types like apoptosis, cell necrosis, and autophagy. Recent studies suggest its role in exacerbating or mitigating diseases by influencing metabolic and signaling pathways in conditions such as tumors and ischemic organ damage. Evidence also links ferroptosis to various kidney diseases, prompting a review of its research status and potential breakthroughs in understanding and treating these conditions.
Summary: In acute kidney disease (AKI), ferroptosis has been confirmed in animal kidneys after being induced by various factors such as renal ischemia-reperfusion and cisplatin, and glutathione peroxidase 4 (GPX4) is linked with AKI. Ferroptosis is associated with renal fibrosis in chronic kidney disease (CKD), TGF-β1 being crucial in this regard. In diabetic nephropathy (DN), high SLC7A11 and low nuclear receptor coactivator 4 (NCOA4) expressions are linked to disease progression. For polycystic kidney disease (PKD), ferroptosis promotes the disease by regulating ferroptosis in kidney tissue. Renal cell carcinoma (RCC) and lupus nephritis (LN) also have links to ferroptosis, with mtDNA and iron accumulation causing RCC and oxidative stress causing LN.
Key messages: Ferroptosis is a newly identified form of programmed cell death that is associated with various diseases. It targets metabolic and signaling pathways and has been linked to kidney diseases such as AKI, CKD, PKD, DN, LN, and clear cell RCC. Understanding its role in these diseases could lead to breakthroughs in their pathogenesis, etiology, and treatment.
{"title":"A Deep Insight into Ferroptosis in Renal Disease: Facts and Perspectives.","authors":"Zhongyu Han, Yuanke Luo, Haoran Chen, Guochen Zhang, Luling You, Meiqi Zhang, Yumeng Lin, Lan Yuan, Shiyi Zhou","doi":"10.1159/000538106","DOIUrl":"10.1159/000538106","url":null,"abstract":"<p><strong>Background: </strong>Ferroptosis, a newly recognized form of programmed cell death, is distinguished by its reliance on reactive oxygen species and iron-mediated lipid peroxidation, setting it apart from established types like apoptosis, cell necrosis, and autophagy. Recent studies suggest its role in exacerbating or mitigating diseases by influencing metabolic and signaling pathways in conditions such as tumors and ischemic organ damage. Evidence also links ferroptosis to various kidney diseases, prompting a review of its research status and potential breakthroughs in understanding and treating these conditions.</p><p><strong>Summary: </strong>In acute kidney disease (AKI), ferroptosis has been confirmed in animal kidneys after being induced by various factors such as renal ischemia-reperfusion and cisplatin, and glutathione peroxidase 4 (GPX4) is linked with AKI. Ferroptosis is associated with renal fibrosis in chronic kidney disease (CKD), TGF-β1 being crucial in this regard. In diabetic nephropathy (DN), high SLC7A11 and low nuclear receptor coactivator 4 (NCOA4) expressions are linked to disease progression. For polycystic kidney disease (PKD), ferroptosis promotes the disease by regulating ferroptosis in kidney tissue. Renal cell carcinoma (RCC) and lupus nephritis (LN) also have links to ferroptosis, with mtDNA and iron accumulation causing RCC and oxidative stress causing LN.</p><p><strong>Key messages: </strong>Ferroptosis is a newly identified form of programmed cell death that is associated with various diseases. It targets metabolic and signaling pathways and has been linked to kidney diseases such as AKI, CKD, PKD, DN, LN, and clear cell RCC. Understanding its role in these diseases could lead to breakthroughs in their pathogenesis, etiology, and treatment.</p>","PeriodicalId":17830,"journal":{"name":"Kidney Diseases","volume":null,"pages":null},"PeriodicalIF":3.7,"publicationDate":"2024-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11149998/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141248057","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}