2020
DOI: 10.15537/smj.2020.11.25450
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Long-stay patients in pediatric intensive care units

Abstract: Objectives: To explore the changing patterns of long-stay patients (LSP) to improve the utilization of pediatric intensive care units (PICUs) resources. Methods: This is a 2-points cross-sectional study (5 years apart; 2014-2019) conducted among PICUs and SCICUs in Riyadh, Saudi Arabia. Children who have stayed in PICU for more than 21 days were included. Results: Out of the 11 units approached, 10 (90%) agreed to participate. The prevalence … Show more

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Cited by 4 publications
(5 citation statements)
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“…As reported in our previous publication, between 2014 and 2019, the LSP’s overall percentage in all surveyed hospitals dropped by 7.5%, from 31% to 23.5%. 9 At the hospital level, each unit varied in its improvement, from between a 5% to a 33% drop in their LSP percentage (see Figure 2 ). One outlier unit had entirely resolved its LSP issue (0 cases in 2019, from two cases and a percentage of 28.6% in 2014).…”
Section: Resultsmentioning
confidence: 99%
See 3 more Smart Citations
“…As reported in our previous publication, between 2014 and 2019, the LSP’s overall percentage in all surveyed hospitals dropped by 7.5%, from 31% to 23.5%. 9 At the hospital level, each unit varied in its improvement, from between a 5% to a 33% drop in their LSP percentage (see Figure 2 ). One outlier unit had entirely resolved its LSP issue (0 cases in 2019, from two cases and a percentage of 28.6% in 2014).…”
Section: Resultsmentioning
confidence: 99%
“…This paper is a continuum to previous research by the authors, 9 which explains data source, data collection tool, recruitment, and data collection process. The same seven PICUs and three pediatric SCICUs in Riyadh, Saudi Arabia, were included in the current study.…”
Section: Methodsmentioning
confidence: 99%
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“…Following the panel and conference attendees' discussions, the use of ChatGPT-4 helped to summarize the extensive human-human discussions, rapidly and reliably, with the AI generating a structured summarization in these complex medical situations that contribute to prolonged hospitalization and resource utilization [19][20][21]. We hereby demonstrated for the first time in the medical literature integrating ChatGPT-4 in re-generating more interactive and challenging scenarios [22][23][24], then using the same AI chatbot to analyze and summarize the panel discussion transcripts to provide a meaningful summary of key themes, insights, and expert consensus recommendations, to be shared with the medical literature.…”
Section: Discussionmentioning
confidence: 99%