Systolic blood pressure and chronic kidney disease progression in patients with primary glomerular disease

Kim, Hyung Woo; Park, Sun-Hee; Joo, Young Su; Kang, Shin Chan; Lee, Jee Young; Lee, Sangmi; Chang, Tae Ik; Kang, Ea Wha; Ryu, Dong‐Ryeol; Yoo, Tae‐Hyun; Chin, Ho Jun; Kang, Shin‐Wook; Han, Seung Hyeok

doi:10.1007/s40620-020-00930-x

Cited by 14 publications

(14 citation statements)

References 36 publications

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“…The eGFR formula was also not consistent across studies, 13 studies used the CKD Epidemiology Collaboration (CKD-EPI) equation [ 9 , 41 , 42 , 44 , 46 , 51 , 54 – 56 , 58 , 63 , 65 , 66 ] and 9 studies used the Modification of Diet in Renal Disease (MDRD) equation [ 43 , 45 , 47 , 49 , 53 , 60 , 62 , 64 , 71 ]. Two studies used unique equations customised for their specific cohort [ 48 , 69 ].…”

Section: Resultsmentioning

confidence: 99%

“…The smallest study [ 50 ] had 43 participants and the largest study included over 300,000 patient records [ 54 ]. Included study populations were from the United States [ 45 , 52 – 56 , 60 , 68 , 69 , 72 ], Canada [ 41 , 46 , 58 , 59 ], Taiwan [ 9 , 42 , 70 ], Germany [ 64 , 66 ], Japan [ 48 , 50 , 61 , 67 ], France [ 43 ], Croatia [ 44 ], Korea [ 49 , 51 ], United Kingdom [ 62 ], Iran [ 71 ], Romania [ 65 ], Spain [ 63 ], Netherlands [ 47 ] and China [ 57 ].…”

Section: Resultsmentioning

confidence: 99%

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Prediction models used in the progression of chronic kidney disease: A scoping review

et al. 2022

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Objective To provide a review of prediction models that have been used to measure clinical or pathological progression of chronic kidney disease (CKD). Design Scoping review. Data sources Medline, EMBASE, CINAHL and Scopus from the year 2011 to 17th February 2022. Study selection All English written studies that are published in peer-reviewed journals in any country, that developed at least a statistical or computational model that predicted the risk of CKD progression. Data extraction Eligible studies for full text review were assessed on the methods that were used to predict the progression of CKD. The type of information extracted included: the author(s), title of article, year of publication, study dates, study location, number of participants, study design, predicted outcomes, type of prediction model, prediction variables used, validation assessment, limitations and implications. Results From 516 studies, 33 were included for full-text review. A qualitative analysis of the articles was compared following the extracted information. The study populations across the studies were heterogenous and data acquired by the studies were sourced from different levels and locations of healthcare systems. 31 studies implemented supervised models, and 2 studies included unsupervised models. Regardless of the model used, the predicted outcome included measurement of risk of progression towards end-stage kidney disease (ESKD) of related definitions, over given time intervals. However, there is a lack of reporting consistency on details of the development of their prediction models. Conclusions Researchers are working towards producing an effective model to provide key insights into the progression of CKD. This review found that cox regression modelling was predominantly used among the small number of studies in the review. This made it difficult to perform a comparison between ML algorithms, more so when different validation methods were used in different cohort types. There needs to be increased investment in a more consistent and reproducible approach for future studies looking to develop risk prediction models for CKD progression.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Prediction models used in the progression of chronic kidney disease: A scoping review

et al. 2022

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“…Popularly speaking, CKD is not a sudden attack, but a consequence of long-term neglect of the accumulation of kidney disease by patients. ere are three types of CKD that mainly endanger the health of the population in China: hypertension, glomerulonephritis, and diabetic nephropathy [20,21]. According to Liu Wenhu, director of the Nephrology Department of Beijing Friendship Hospital, "only Compared with that before intervention, P < 0.05; n compared with the control group after 6 months of intervention, P < 0.05.…”

Section: Discussionmentioning

confidence: 99%

Effect of Nursing Intervention on Self-Management and Quality of Life in Patients with Chronic Kidney Disease Evaluated by Renal Diffusion Tensor Imaging Features Using Image Registration Algorithm

Zhou

2022

Concepts in Magnetic Resonance Part A

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The aim of this research was to explore the effect of nursing intervention on self-management and quality of life in patients with chronic kidney disease (CKD) by using the renal diffusion tensor imaging (DTI) feature of image registration algorithm. A total of 100 patients with CKD were randomly divided into experimental group (nursing maintenance guidance intervention) and control group (routine nursing), with 50 cases in each group. The image effect before and after registration, self-management behavior after 6 months, quality of life, DTI-related parameters, and renal function indicators were collected and analyzed. The results showed that the images were clearer than those before registration, the self-management ability in the control group (92.81 ± 19.32) was smaller than that in the experimental group (107.12 ± 18.78), the quality of life in the experimental group (121.47 ± 11.21) was greater than that in the control group (104.89 ± 12.11), and the corresponding magnetic resonance apparent diffusion coefficient (ADC) (2.54 ± 0.28) and fractional anisotropy (FA) (0.28 ± 0.07) in the cortex were greater than those in the control group (2.35 ± 0.21, 0.23 ± 0.04). The differences were statistically significant ( P < 0.05 ). The corresponding ADC value (2.32 ± 0.22) and FA value (0.59 ± 0.02) of medulla were greater than those of the control group (2.12 ± 0.24 and 0.41 ± 0.17). The levels of serum creatinine (Scr) (μmol/L) (421.38 ± 42.78) and 24 h urinary protein (24 h-Upro) (mg/d) (1,836.7 ± 545.98) were lower than those of the control group, and the differences had statistical significance ( P < 0.05 ). In summary, the registration algorithm can enhance the effect of image presentation and nursing intervention has positive significance for the self-management and quality of life of patients with CKD.

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“…Previous surveys have identified multiple factors associated with CKD, including diabetes, homocysteine ( Yang et al, 2022 ), hypertension ( Kim et al, 2021 ) and tea intake ( Zhang et al, 2022 ). Among those factors, the role of adiponectin in the onset and progression of CKD has attracted researchers’ attention.…”

Section: Introductionmentioning

confidence: 99%

Genetically predicted adiponectin causally reduces the risk of chronic kidney disease, a bilateral and multivariable mendelian randomization study

Luo

et al. 2022

Front. Genet.

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Background: It is not clarified whether the elevation of adiponectin is the results of kidney damage, or the cause of kidney function injury. To explore the causal association of adiponectin on estimated glomerular filtration rate (eGFR) and chronic kidney disease (CKD), this study was performed.Materials and methods: The genetic association of adiponectin were retrieved from one genome-wide association studies with 39,883 participants. The summary-level statistics regarding the eGFR (133,413 participants) and CKD (12,385 CKD cases and 104,780 controls) were retrieved from the CKDGen consortium in the European ancestry. Single-variable Mendelian randomization (MR), bilateral and multivariable MR analyses were used to verify the causal association between adiponectin, eGFR, and CKD.Results: Genetically predicted adiponectin reduces the risk of CKD (OR = 0.71, 95% CI = 0.57–0.89, p = 0.002) and increases the eGFR (β = 0.014, 95% CI = 0.001–0.026, p = 0.034) by the inverse variance weighting (IVW) estimator. These findings remain consistent in the sensitivity analyses. No heterogeneity and pleiotropy were detected in this study (P for MR-Egger 0.617, P for global test > 0.05, and P for Cochran’s Q statistics = 0.617). The bilateral MR identified no causal association of CKD on adiponectin (OR = 1.01, 95% CI = 0.96–1.07, p = 0.658), nor did it support the association of eGFR on adiponectin (OR = 0.86, 95% CI = 0.68–1.09, p = 0.207) by the IVW estimator. All the sensitivity analyses reported similar findings (p > 0.05). Additionally, after adjusting for cigarette consumption, alcohol consumption, body mass index, low density lipoprotein, and total cholesterol, the ORs for CKD are 0.70 (95% CI = 0.55–0.90, p = 0.005), 0.75 (95% CI = 0.58–0.97, p = 0.027), 0.82 (95% CI = 0.68–0.99, p = 0.039), 0.74 (95% CI = 0.59–0.93, p = 0.011), and 0.79 (95% CI = 0.61–0.95, p = 0.018), respectively.Conclusion: Using genetic data, this study provides novel causal evidence that adiponectin can protect the kidney function and further reduce the risk of CKD.

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Systolic blood pressure and chronic kidney disease progression in patients with primary glomerular disease

Cited by 14 publications

References 36 publications

Prediction models used in the progression of chronic kidney disease: A scoping review

Prediction models used in the progression of chronic kidney disease: A scoping review

Effect of Nursing Intervention on Self-Management and Quality of Life in Patients with Chronic Kidney Disease Evaluated by Renal Diffusion Tensor Imaging Features Using Image Registration Algorithm

Genetically predicted adiponectin causally reduces the risk of chronic kidney disease, a bilateral and multivariable mendelian randomization study

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