Nephrology in China

Wang, Angela Yee-Moon; An, Yu; Cai, Guangyan; Chen, Jianghua; Chen, Wei; Chen, Xiangmei; Cui, Zhao; Hao, Chuan‐Ming; Hou, Fanfan; Liu, Bi‐Cheng; Liu, Zhihong; Niu, Qingyu; Sun, Qiannan; Wang, Ren-Ding; Xu, Dianqing; Yang, Chao; Yang, Li; Zhang, Luxia; Zhao, Ming‐Hui; Zuo, Li; Yu, Xueqing

doi:10.1007/978-3-030-56890-0_20

Cited by 6 publications

(9 citation statements)

References 176 publications

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“…However, in Chinese hospitals, access to advanced specialized training is often limited. 55 To overcome these challenges, healthcare institution managers should prioritize specialized training for medical personnel. Thus, the study highlights the need for an integrated approach that considers the unique perspectives and contributions of both doctors and nurses in the realm of DKD management, aiming to bridge the gap in clinical practice for optimized patient outcomes.…”

Section: Discussionmentioning

confidence: 99%

Chinese Healthcare Workers’ Knowledge, Attitudes, and Practices in Diabetic Kidney Management: A Multi-Centered Cross-Sectional Study

Duan,

Wen,

Yan

et al. 2024

RMHP

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Background Given the importance of diabetic kidney disease (DKD) management, this study aims to explore the knowledge, attitudes, and practices in disease management demonstrated by healthcare workers from the nephrology department. Materials and Methods This study is a multi-centered cross-sectional study, and adopts snowball sampling, with 530 healthcare workers being recruited to complete a questionnaire covering areas such as demographic characteristics, knowledge, attitude, and practices (KAP) of DKD management. This data was analyzed using descriptive statistics and binary logistics analysis. Results In this study, 530 healthcare workers were studied, including 94 doctors and 436 nurses. The participants were mainly from general tertiary hospitals in 14 provinces. For Chinese nurse, the results indicate that both poor knowledge level (Odds Ratio (OR) =0.63, 95% Confidence Interval (CI): 0.42–0.94) and having experience in further medical training in nephrology (OR=1.92, 95% CI: 1.20–3.08) are associated with the practice levels. For Chinese doctors, having not experience in further medical training in nephrology (OR=0.36, 95% CI: 0.15–0.83) are associated with their practice levels. Conclusion In summary, Chinese doctors and nurses in this study showed positive attitudes towards DKD management, but their knowledge and practical skills were lacking. This underscores a notable gap in achieving optimal DKD care. Notably, nurses’ knowledge influenced their management practices, and additional nephrology training correlated with better engagement. To improve patient care, enhancing nephrology healthcare professional training and addressing knowledge-practice disparities are recommended.

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Section: Discussionmentioning

confidence: 99%

Chinese Healthcare Workers’ Knowledge, Attitudes, and Practices in Diabetic Kidney Management: A Multi-Centered Cross-Sectional Study

Duan,

Wen,

Yan

et al. 2024

RMHP

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“…Donor grafts were allocated by the Organ Procurement Organization through the China Organ Transplant Response System, which is an encrypted national network run electronically to ensure fairness and transparency in the organ allocation process. 28,29 Except for the general organ allocation principles, the following priorities were adopted for pediatric recipients: (1) kidneys from donors aged <2 y were allocated preferentially to <5-y-old recipients; (2) kidneys from ≥2- and <7-y-old donors were allocated preferentially to <14-y-old recipients; (3) kidneys from ≥7- and <18-y-old donors were allocated preferentially to <18-y-old recipients. 30 Pediatric kidneys for transplantation were treated as national rather than only local or regional resources for pediatric recipients.…”

Section: Methodsmentioning

confidence: 99%

The Outcome of Transplanting Kidneys From Very Small Pediatric Deceased Donors

Zhang

Liu

et al. 2023

Transplantation

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Background. Kidneys from very small pediatric donors (VSPDs, aged <2 y) are underutilized. Concerns regarding potentially inferior outcomes hinder the use in pediatric recipients. Methods. All pediatric kidney-only transplants from <18-year-old donors between January 2012 and May 2021 in our center were included in this study. Outcomes were compared between VSPD and normal pediatric donor (NPD, aged 2–18 y) groups, and 3-y death-censored graft survival was assessed by the multivariable Cox proportional hazard model. Results. Of all 252 enrolled patients, 149 (59.1%) received kidneys from NPDs and 103 (40.9%) from VSPDs. The 3-y graft survival rates of the NPD and VSPD groups were 91.2% and 88.6%, respectively (P = 0.385). The adjusted hazard ratio of 3-y graft loss was 1.2 (95% confidence interval, 0.6-2.5; P = 0.659) for the VSPD group compared with the NPD group. There was no significant difference in estimated glomerular filtration rate at 3 y posttransplant observed between NPD and VSPD groups (86.9 ± 26.8 versus 87 ± 27.9 mL/min/1.73 m2; P = 0.991). Patients (n = 12, 4.8%) who received kidneys from donors <5 kg contributed 5 (5/39, 12.8%) with delayed graft function and the sole primary nonfunction in our cohort. Conclusions. Although attention to preventing complications is necessary, especially for kidneys from donors <5 kg, kidneys from VSPDs did not appear to impart added risk for 3-y graft loss and renal function.

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“…A model-based IR approach, where docids are embedded into the model, was first introduced in (Metzler et al, 2021;Tay et al, 2022). Since then, several other models (Wang et al, 2022;Zhuang et al, 2022;Zhou et al, 2022b) incorporating a query augmentation module have been developed to enhance the performance. Moreover, the model-based IR framework has been extended to knowledge-intensive language tasks, leading to notable improvements in performance (Chen et al, 2022a;Bevilacqua et al, 2022;Chen et al, 2022b).…”

Section: Related Workmentioning

confidence: 99%

“…Building upon DSI, SEAL (Bevilacqua et al, 2022) uses n-grams within passages as potential identifiers. DSI-QG (Zhuang et al, 2022), NCI (Wang et al, 2022), and Ultron (Zhou et al, 2022b) incorporate query generation modules for data augmentation.…”

Section: Baselinesmentioning

confidence: 99%

Enhancing Generative Retrieval with Reinforcement Learning from Relevance Feedback

Zhou,

Dou,

Wen

2023

Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing

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The recent advent of end-to-end generative retrieval marks a significant shift in document retrieval methods, leveraging differentiable search indexes to directly produce relevant document identifiers (docids) in response to a specific query. Nevertheless, this approach faces two fundamental challenges: (i) a discrepancy between the token-level probabilistic optimization and the broader document-level relevance estimation; (ii) an overemphasis on top-1 results at the expense of overall ranking quality. To tackle these challenges, we propose a generative retrieval model with reinforcement learning from relevance feedback, which aims to align token-level docid generation with document-level relevance estimation. The training process incorporates three stages: supervised fine-tuning, relevance reward model training, and reinforced learning-to-rank from relevance feedback. To train a high-quality reward model, we define "relevance" under three progressive scenarios, which collectively offer a comprehensive evaluation of the document relevance. Experiments conducted on two benchmark datasets demonstrate the effectiveness of our proposed approach.

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Nephrology in China

Cited by 6 publications

References 176 publications

Chinese Healthcare Workers’ Knowledge, Attitudes, and Practices in Diabetic Kidney Management: A Multi-Centered Cross-Sectional Study

Chinese Healthcare Workers’ Knowledge, Attitudes, and Practices in Diabetic Kidney Management: A Multi-Centered Cross-Sectional Study

The Outcome of Transplanting Kidneys From Very Small Pediatric Deceased Donors

Enhancing Generative Retrieval with Reinforcement Learning from Relevance Feedback

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