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      Diagnosis and Treatment Rules of Chronic Kidney Disease and Nursing Intervention Models of Related Mental Diseases Using Electronic Medical Records and Data Mining

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          Abstract

          Objective

          On the basis of electronic medical records, the data mining technology was adopted to explore the law of chronic kidney disease (CKD) and the intervention mode of mental health of patients.

          Methods

          Based on the electronic medical records, the corresponding data extraction, database establishment, and data cleaning of CKD were performed. After that, the related data analysis, frequency analysis, cluster analysis, and nonparametric analysis were used to explore the laws of CKD diagnosis and treatment and nursing intervention mode of mental illness. The most common causes of CKD were chronic glomerulonephritis (43.76%), aristolochic acid nephritis (16.34%), diabetic nephritis (12.87%), and hypertensive nephritis (11.58%). The major treatment method for end-stage patients was alternative therapies, accounting for 46%. Compared with the depression score before intervention, that of the patients after the mindfulness therapy (50.99 ± 9.77 vs. 47.01 ± 9.33, P=0.024 < 0.5) and target behaviour nursing intervention (52.21 ± 8.12 vs. 48.01 ± 9.33, P=0.032 < 0.05) was obviously decreased.

          Conclusion

          The data mining technology based on electronic records showed a good application prospect in the analysis of the diagnosis and treatment of CKD; and target behaviour nursing and mindfulness intervention were effective psychological intervention models.

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          Most cited references29

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          Adenine-induced chronic kidney disease in rats

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            Interaction of Edge-Cloud Computing Based on SDN and NFV for Next Generation IoT

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              Chronic Kidney Disease and Cardiovascular Disease: Is there Any Relationship?

              Introduction: Chronic Kidney Disease is a growing health burden world wide. Traditional and mutual risk factors between CVD and CKD are age, hypertension, diabetes mellitus, dyslipidem-ia, tobacco use, family history and male gender. In this review, we will focus on whether or not early CKD is an important risk factor for the presence, severity and progression of CVD. Specifically, we will examine both traditional and novel risk factors of both CKD and CVD and how they relate to each other. Conclusion: We will also assess if early treatment of CKD, intensive compared to standard, has an important effect on the halt of the development of CKD as well as CVD. Insights into the pathogene-sis and early recognition of CKD as well as the importance of novel kidney biomarkers will be point-ed out. Also, common pathogenetic mechanisms between CKD and CVD will be discussed
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                Author and article information

                Contributors
                Journal
                J Healthc Eng
                J Healthc Eng
                JHE
                Journal of Healthcare Engineering
                Hindawi
                2040-2295
                2040-2309
                2021
                10 December 2021
                : 2021
                : 5187837
                Affiliations
                1Department of Mental Health, The First Hospital of Hebei Medical University, Shijiazhuang, China
                2Department of Hepatobiliary Surgery, The First Hospital of Hebei Medical University, Shijiazhuang, China
                3Department of Emergency, The First Hospital of Hebei Medical University, Shijiazhuang, China
                4Department of Nephrology, The First Hospital of Hebei Medical University, Shijiazhuang, China
                5Department of Respiratory Medicine, First Hospital of Hebei Medical University, Shijiazhuang, China
                Author notes

                Academic Editor: Osamah Ibrahim Khalaf

                Author information
                https://orcid.org/0000-0003-1663-4393
                https://orcid.org/0000-0002-3018-1522
                Article
                10.1155/2021/5187837
                8683225
                34925735
                03a1e911-9b11-48cd-83e0-f103bffd7c4e
                Copyright © 2021 Yanli Wang et al.

                This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 21 August 2021
                : 20 October 2021
                Funding
                Funded by: Health Commission of Hebei Province
                Award ID: 20210010
                Categories
                Research Article

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