Severity: Warning
Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 176
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3122
Function: getPubMedXML
File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 316
Function: require_once
Cardiovascular medicine patients have complex conditions and rapid progress. They will cause a variety of complications during the illness and are difficult to care for. In addition, the above departments have many treatment tools, complex nursing points, and nursing risks. Scientific risk management should be carried out to avoid the occurrence of adverse events. Existing studies incorporating nursing risk management into cardiovascular health care are incomplete. This paper aims to explore the analysis and research methods of nursing cardiovascular medicine applications and effects evaluation based on nursing risk management and deep learning. Through the observation and experiment of grouping 100 cardiovascular medicine patients in a hospital, the total satisfaction degree of the experimental group reached 90%, and the control group was only 48%, which is quite different in comparison. The factors affecting the occurrence of nursing risk have the characteristics of multiplicity, instability, and uncertainty. Therefore, in order to improve the nursing effect and the rescue rate, it is imperative to strengthen the nursing risk management and, at the same time, reduce the patient's physical pain and nursing risk.
Download full-text PDF |
Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9576447 | PMC |
http://dx.doi.org/10.1155/2022/9253868 | DOI Listing |
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