Severity: Warning
Message: file_get_contents(https://...@gmail.com&api_key=61f08fa0b96a73de8c900d749fcb997acc09&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 197
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 197
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 271
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3165
Function: getPubMedXML
File: /var/www/html/application/controllers/Detail.php
Line: 597
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 511
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 317
Function: require_once
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Background: Patients admitted from the emergency department to the wards, who progress to a critically unwell state, may require expeditious admission to the intensive care unit. It can be argued that earlier recognition of such patients, to facilitate prompt transfer to intensive care, could be linked to more favourable clinical outcomes. Nevertheless, this can be clinically challenging, and there are currently no established evidence-based methods for predicting the need for intensive care in the future.
Objectives: We aimed to analyse the emergency department data to describe the characteristics of patients who required an intensive care admission within 48 h of presentation. Secondly, we planned to test the feasibility of using this data to identify the associated risk factors for developing a predictive model.
Methods: We designed a retrospective case-control study. Cases were patients admitted to intensive care within 48 h of their emergency department presentation. Controls were patients who did not need an intensive care admission. Groups were matched based on age, gender, admission calendar month, and diagnosis. To identify the associated variables, we used a conditional logistic regression model.
Results: Compared to controls, cases were more likely to be obese, and smokers and had a higher prevalence of cardiovascular (39 [35.1%] vs 20 [18%], p = 0.004) and respiratory diagnoses (45 [40.5%] vs 25 [22.5%], p = 0.004). They received more medical emergency team reviews (53 [47.8%] vs 24 [21.6%], p < 0.001), and more patients had an acute resuscitation plan (31 [27.9%] vs 15 [13.5%], p = 0.008). The predictive model showed that having acute resuscitation plans, cardiovascular and respiratory diagnoses, and receiving medical emergency team reviews were strongly associated with having an intensive care admission within 48 h of presentation.
Conclusions: Our study used emergency department data to provide a detailed description of patients who had an intensive care unit admission within 48 h of their presentation. It demonstrated the feasibility of using such data to identify the associated risk factors to develop a predictive model.
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http://dx.doi.org/10.1016/j.aucc.2024.01.012 | DOI Listing |