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LDR02193nmm uu200445 4500
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00520240805180516
008181129s2017 |||||||||||||||||c||eng d
020 ▼a 9780438385818
035 ▼a (MiAaPQ)AAI10195464
035 ▼a (MiAaPQ)nursing.yale:10070
040 ▼a MiAaPQ ▼c MiAaPQ ▼d 248032
0820 ▼a 610.73
1001 ▼a Layman, Timothy Richard.
24510 ▼a Early Intervention in Suspected Sepsis Patients.
260 ▼a [S.l.] : ▼b Yale University., ▼c 2017
260 1 ▼a Ann Arbor : ▼b ProQuest Dissertations & Theses, ▼c 2017
300 ▼a 24 p.
500 ▼a Source: Dissertation Abstracts International, Volume: 80-02(E), Section: B.
500 ▼a Adviser: Laura K. Andrews.
5021 ▼a Thesis (D.N.P.)--Yale University, 2017.
520 ▼a Objectives: Inform the development and implementation of an early response algorithm for suspected sepsis patients via a rapid response team.
520 ▼a Background: Recent literature supports the need for early recognition and intervention of suspected sepsis patients, potentially reducing morbidity and mortality.
520 ▼a Methods: A clinically and professionally reviewed algorithm was developed to execute early, sepsis-specific intervention. The algorithm design was carried out in 3 steps: (1) The establishment of recognition criteria based on evidence
520 ▼a Results: Experts rated three of five domains described in the literature (Sepsis/Mortality, Early intervention/treatment, Code SMARRT Algorithm) as having greater than 90% agreement related to relevance and importance.
520 ▼a Conclusions: The implementation of the Code SMARRT algorithm has the potential to reduce unnecessary deaths related to sepsis and septic shock.
590 ▼a School code: 0265.
650 4 ▼a Nursing.
650 4 ▼a Medicine.
690 ▼a 0569
690 ▼a 0564
71020 ▼a Yale University. ▼b Nursing.
7730 ▼t Dissertation Abstracts International ▼g 80-02B(E).
773 ▼t Dissertation Abstract International
790 ▼a 0265
791 ▼a D.N.P.
792 ▼a 2017
793 ▼a English
85640 ▼u http://www.riss.kr/pdu/ddodLink.do?id=T14996534 ▼n KERIS
980 ▼a 201812 ▼f 2019
990 ▼a 관리자