Literature DB >> 28149888

Scoring systems for the characterization of sepsis and associated outcomes.

Natalie McLymont1, Guy W Glover1.   

Abstract

Sepsis is responsible for the utilisation of a significant proportion of healthcare resources and has high mortality rates. Early diagnosis and prompt interventions are associated with better outcomes but is impeded by a lack of diagnostic tools and the heterogeneous and enigmatic nature of sepsis. The recently updated definitions of sepsis have moved away from the centrality of inflammation and the systemic inflammatory response syndrome (SIRS) criteria which have been shown to be non-specific. Sepsis is now defined as a "life-threatening organ dysfunction caused by a dysregulated host response to infection". The Quick (q) Sequential (Sepsis-related) Organ Failure Assessment (SOFA) score is proposed as a surrogate for organ dysfunction and may act as a risk predictor for patients with known or suspected infection, as well as being a prompt for clinicians to consider the diagnosis of sepsis. Early warning scores (EWS) are track and trigger physiological monitoring systems that have become integrated within many healthcare systems for the detection of acutely deteriorating patients. The recent study by Churpek and colleagues sought to compare qSOFA to more established alerting criteria in a population of patients with presumed infection, and compared the ability to predict death or unplanned intensive care unit (ICU) admission. This perspective paper discusses recent advances in the diagnostic criteria for sepsis and how qSOFA may fit into the pre-existing models of acute care and sepsis quality improvement.

Entities:  

Keywords:  Early warning scores (EWS); intensive care unit (ICU); sepsis; the Modified Early Warning Score (MEWS); the National Early Warning Score (NEWS); the Quick (q) Sequential (Sepsis-related) Organ Failure Assessment (qSOFA); the systemic inflammatory response syndrome (SIRS)

Year:  2016        PMID: 28149888      PMCID: PMC5233540          DOI: 10.21037/atm.2016.12.53

Source DB:  PubMed          Journal:  Ann Transl Med        ISSN: 2305-5839


  17 in total

1.  Early goal-directed therapy in the treatment of severe sepsis and septic shock.

Authors:  E Rivers; B Nguyen; S Havstad; J Ressler; A Muzzin; B Knoblich; E Peterson; M Tomlanovich
Journal:  N Engl J Med       Date:  2001-11-08       Impact factor: 91.245

2.  Incidence and Prognostic Value of the Systemic Inflammatory Response Syndrome and Organ Dysfunctions in Ward Patients.

Authors:  Matthew M Churpek; Frank J Zadravecz; Christopher Winslow; Michael D Howell; Dana P Edelson
Journal:  Am J Respir Crit Care Med       Date:  2015-10-15       Impact factor: 21.405

3.  Assessment of Clinical Criteria for Sepsis: For the Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3).

Authors:  Christopher W Seymour; Vincent X Liu; Theodore J Iwashyna; Frank M Brunkhorst; Thomas D Rea; André Scherag; Gordon Rubenfeld; Jeremy M Kahn; Manu Shankar-Hari; Mervyn Singer; Clifford S Deutschman; Gabriel J Escobar; Derek C Angus
Journal:  JAMA       Date:  2016-02-23       Impact factor: 56.272

Review 4.  2001 SCCM/ESICM/ACCP/ATS/SIS International Sepsis Definitions Conference.

Authors:  Mitchell M Levy; Mitchell P Fink; John C Marshall; Edward Abraham; Derek Angus; Deborah Cook; Jonathan Cohen; Steven M Opal; Jean-Louis Vincent; Graham Ramsay
Journal:  Crit Care Med       Date:  2003-04       Impact factor: 7.598

5.  Intensive care unit admitting patterns in the Veterans Affairs health care system.

Authors:  Lena M Chen; Marta Render; Anne Sales; Edward H Kennedy; Wyndy Wiitala; Timothy P Hofer
Journal:  Arch Intern Med       Date:  2012-09-10

6.  Quick Sepsis-related Organ Failure Assessment, Systemic Inflammatory Response Syndrome, and Early Warning Scores for Detecting Clinical Deterioration in Infected Patients outside the Intensive Care Unit.

Authors:  Matthew M Churpek; Ashley Snyder; Xuan Han; Sarah Sokol; Natasha Pettit; Michael D Howell; Dana P Edelson
Journal:  Am J Respir Crit Care Med       Date:  2017-04-01       Impact factor: 21.405

7.  Systemic inflammatory response syndrome criteria in defining severe sepsis.

Authors:  Kirsi-Maija Kaukonen; Michael Bailey; David Pilcher; D Jamie Cooper; Rinaldo Bellomo
Journal:  N Engl J Med       Date:  2015-03-17       Impact factor: 91.245

Review 8.  The Surviving Sepsis Campaign: results of an international guideline-based performance improvement program targeting severe sepsis.

Authors:  Mitchell M Levy; R Phillip Dellinger; Sean R Townsend; Walter T Linde-Zwirble; John C Marshall; Julian Bion; Christa Schorr; Antonio Artigas; Graham Ramsay; Richard Beale; Margaret M Parker; Herwig Gerlach; Konrad Reinhart; Eliezer Silva; Maurene Harvey; Susan Regan; Derek C Angus
Journal:  Intensive Care Med       Date:  2010-01-13       Impact factor: 17.440

9.  The epidemiology of severe sepsis in England, Wales and Northern Ireland, 1996 to 2004: secondary analysis of a high quality clinical database, the ICNARC Case Mix Programme Database.

Authors:  David A Harrison; Catherine A Welch; Jane M Eddleston
Journal:  Crit Care       Date:  2006       Impact factor: 9.097

10.  qSOFA does not replace SIRS in the definition of sepsis.

Authors:  Jean-Louis Vincent; Greg S Martin; Mitchell M Levy
Journal:  Crit Care       Date:  2016-07-17       Impact factor: 9.097

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  17 in total

1.  Respiratory adjusted shock index for identifying occult shock and level of Care in Sepsis Patients.

Authors:  Lynn Jiang; Nicholas D Caputo; Bernard P Chang
Journal:  Am J Emerg Med       Date:  2019-01-15       Impact factor: 2.469

2.  The authors reply.

Authors:  Majid Afshar; Talar Markossian; Cara Joyce
Journal:  Crit Care Med       Date:  2020-02       Impact factor: 7.598

3.  A comparison of machine learning models versus clinical evaluation for mortality prediction in patients with sepsis.

Authors:  William P T M van Doorn; Patricia M Stassen; Hella F Borggreve; Maaike J Schalkwijk; Judith Stoffers; Otto Bekers; Steven J R Meex
Journal:  PLoS One       Date:  2021-01-19       Impact factor: 3.240

4.  Effect of a machine learning-based severe sepsis prediction algorithm on patient survival and hospital length of stay: a randomised clinical trial.

Authors:  David W Shimabukuro; Christopher W Barton; Mitchell D Feldman; Samson J Mataraso; Ritankar Das
Journal:  BMJ Open Respir Res       Date:  2017-11-09

5.  Effect of a sepsis prediction algorithm on patient mortality, length of stay and readmission: a prospective multicentre clinical outcomes evaluation of real-world patient data from US hospitals.

Authors:  Hoyt Burdick; Eduardo Pino; Denise Gabel-Comeau; Andrea McCoy; Carol Gu; Jonathan Roberts; Sidney Le; Joseph Slote; Emily Pellegrini; Abigail Green-Saxena; Jana Hoffman; Ritankar Das
Journal:  BMJ Health Care Inform       Date:  2020-04

6.  Reply to Maitra and Bhattacharjee: Adherence to the Prevailing Sepsis Definition Is Quintessential to Subphenotype Identification.

Authors:  Sivasubramanium V Bhavani; Philip A Verhoef; Matthew M Churpek
Journal:  Am J Respir Crit Care Med       Date:  2020-01-15       Impact factor: 21.405

7.  Digital Alerting and Outcomes in Patients With Sepsis: Systematic Review and Meta-Analysis.

Authors:  Meera Joshi; Hutan Ashrafian; Sonal Arora; Sadia Khan; Graham Cooke; Ara Darzi
Journal:  J Med Internet Res       Date:  2019-12-20       Impact factor: 5.428

8.  Validation of a machine learning algorithm for early severe sepsis prediction: a retrospective study predicting severe sepsis up to 48 h in advance using a diverse dataset from 461 US hospitals.

Authors:  Hoyt Burdick; Eduardo Pino; Denise Gabel-Comeau; Carol Gu; Jonathan Roberts; Sidney Le; Joseph Slote; Nicholas Saber; Emily Pellegrini; Abigail Green-Saxena; Jana Hoffman; Ritankar Das
Journal:  BMC Med Inform Decis Mak       Date:  2020-10-27       Impact factor: 2.796

9.  Survival prediction of patients with sepsis from age, sex, and septic episode number alone.

Authors:  Davide Chicco; Giuseppe Jurman
Journal:  Sci Rep       Date:  2020-10-13       Impact factor: 4.379

10.  Selective transperineal prostate biopsy for fluoroquinolone-resistance patients reduces sepsis and cost.

Authors:  Abdullah Al-Mitwalli; Grigorios Kyriazis; Omar El-Taji; Elizabeth Chandra; Wearmouth Deborah; Phillipa Burns; Youssef Fady; Matthew Simms; Smith Nicholas
Journal:  Curr Urol       Date:  2021-04-26
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