Literature DB >> 33847904

Prognostic tools for elderly patients with sepsis: in search of new predictive models.

Fernando-Miguel Gamboa-Antiñolo1.   

Abstract

As a tool to support clinical decision-making, Mortality Prediction Models (MPM) can help clinicians stratify and predict patient risk. There are numerous scoring systems for patients with sepsis that predict sepsis-related mortality and the severity of sepsis. But there are currently no MPMs for adults with sepsis who meet the criteria of "good." Clinicians are unlikely to use complex MPMs that require extensive or expensive data collection to impede workflow. Machine learning applied to minimal medical records of patients diagnosed with sepsis can be a useful tool. Progress is needed in the development and validation of clinical decision support tools that can assist in patient risk stratification, prognosis, discussion of patient outcomes, and shared decision making.

Entities:  

Year:  2021        PMID: 33847904     DOI: 10.1007/s11739-021-02729-5

Source DB:  PubMed          Journal:  Intern Emerg Med        ISSN: 1828-0447            Impact factor:   3.397


  25 in total

1.  Identifying infected emergency department patients admitted to the hospital ward at risk of clinical deterioration and intensive care unit transfer.

Authors:  Maura Kennedy; Nina Joyce; Michael D Howell; J Lawrence Mottley; Nathan I Shapiro
Journal:  Acad Emerg Med       Date:  2010-10       Impact factor: 3.451

2.  The Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3).

Authors:  Mervyn Singer; Clifford S Deutschman; Christopher Warren Seymour; Manu Shankar-Hari; Djillali Annane; Michael Bauer; Rinaldo Bellomo; Gordon R Bernard; Jean-Daniel Chiche; Craig M Coopersmith; Richard S Hotchkiss; Mitchell M Levy; John C Marshall; Greg S Martin; Steven M Opal; Gordon D Rubenfeld; Tom van der Poll; Jean-Louis Vincent; Derek C Angus
Journal:  JAMA       Date:  2016-02-23       Impact factor: 56.272

Review 3.  Cardiac dysfunction in sepsis: new theories and clinical implications.

Authors:  R M Grocott-Mason; A M Shah
Journal:  Intensive Care Med       Date:  1998-04       Impact factor: 17.440

Review 4.  Prognostic value of troponins in sepsis: a meta-analysis.

Authors:  Francis Bessière; Safia Khenifer; Julie Dubourg; Isabelle Durieu; Jean-Christophe Lega
Journal:  Intensive Care Med       Date:  2013-04-18       Impact factor: 17.440

5.  Mortality in Emergency Department Sepsis (MEDS) score: a prospectively derived and validated clinical prediction rule.

Authors:  Nathan I Shapiro; Richard E Wolfe; Richard B Moore; Eric Smith; Elizabeth Burdick; David W Bates
Journal:  Crit Care Med       Date:  2003-03       Impact factor: 7.598

6.  The MISSED score, a new scoring system to predict Mortality In Severe Sepsis in the Emergency Department: a derivation and validation study.

Authors:  Narani Sivayoham; Andrew Rhodes; Maurizio Cecconi
Journal:  Eur J Emerg Med       Date:  2014-02       Impact factor: 2.799

Review 7.  Myocardial depression in sepsis: from pathogenesis to clinical manifestations and treatment.

Authors:  Elio Antonucci; Enrico Fiaccadori; Katia Donadello; Fabio Silvio Taccone; Federico Franchi; Sabino Scolletta
Journal:  J Crit Care       Date:  2014-04-05       Impact factor: 3.425

8.  Predisposition, insult/infection, response, and organ dysfunction: A new model for staging severe sepsis.

Authors:  Francesca Rubulotta; John C Marshall; Graham Ramsay; David Nelson; Mitchell Levy; Mark Williams
Journal:  Crit Care Med       Date:  2009-04       Impact factor: 7.598

9.  Sepsis patients in the emergency department: stratification using the Clinical Impression Score, Predisposition, Infection, Response and Organ dysfunction score or quick Sequential Organ Failure Assessment score?

Authors:  Vincent M Quinten; Matijs van Meurs; Anna E Wolffensperger; Jan C Ter Maaten; Jack J M Ligtenberg
Journal:  Eur J Emerg Med       Date:  2018-10       Impact factor: 2.799

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