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Predicting time to asystole following withdrawal of life-sustaining treatment: a systematic review.
Nicolson, C; Burke, A; Gardiner, D; Harvey, D; Munshi, L; Shaw, M; Tsanas, A; Lone, N; Puxty, K.
Affiliation
  • Nicolson C; Department of Critical Care, NHS Greater Glasgow and Clyde, Glasgow Royal Infirmary, Glasgow, UK.
  • Burke A; School of Informatics, University of Edinburgh, Edinburgh, UK.
  • Gardiner D; Edinburgh Medical School, University of Edinburgh, Edinburgh, UK.
  • Harvey D; Critical Care, Nottingham University Hospitals NHS Trust, Nottingham, UK.
  • Munshi L; NHS Blood and Transplant, Watford, UK.
  • Shaw M; Critical Care, Nottingham University Hospitals NHS Trust, Nottingham, UK.
  • Tsanas A; NHS Blood and Transplant, Watford, UK.
  • Lone N; Interdepartmental Division of Critical Care Medicine, University of Toronto, Toronto, ON, Canada.
  • Puxty K; Department of Medicine, Sinai Health System and University Health Network, Toronto, ON, Canada.
Anaesthesia ; 79(6): 638-649, 2024 Jun.
Article in En | MEDLINE | ID: mdl-38301032
ABSTRACT
The planned withdrawal of life-sustaining treatment is a common practice in the intensive care unit for patients where ongoing organ support is recognised to be futile. Predicting the time to asystole following withdrawal of life-sustaining treatment is crucial for setting expectations, resource utilisation and identifying patients suitable for organ donation after circulatory death. This systematic review evaluates the literature for variables associated with, and predictive models for, time to asystole in patients managed on intensive care units. We conducted a comprehensive structured search of the MEDLINE and Embase databases. Studies evaluating patients managed on adult intensive care units undergoing withdrawal of life-sustaining treatment with recorded time to asystole were included. Data extraction and PROBAST quality assessment were performed and a narrative summary of the literature was provided. Twenty-three studies (7387 patients) met the inclusion criteria. Variables associated with imminent asystole (<60 min) included deteriorating oxygenation; absence of corneal reflexes; absence of a cough reflex; blood pressure; use of vasopressors; and use of comfort medications. We identified a total of 20 unique predictive models using a wide range of variables and techniques. Many of these models also underwent secondary validation in further studies or were adapted to develop new models. This review identifies variables associated with time to asystole following withdrawal of life-sustaining treatment and summarises existing predictive models. Although several predictive models have been developed, their generalisability and performance varied. Further research and validation are needed to improve the accuracy and widespread adoption of predictive models for patients managed in intensive care units who may be eligible to donate organs following their diagnosis of death by circulatory criteria.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Withholding Treatment / Heart Arrest Type of study: Prognostic_studies / Risk_factors_studies / Systematic_reviews Limits: Humans Language: En Journal: Anaesthesia Year: 2024 Type: Article Affiliation country: United kingdom

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Withholding Treatment / Heart Arrest Type of study: Prognostic_studies / Risk_factors_studies / Systematic_reviews Limits: Humans Language: En Journal: Anaesthesia Year: 2024 Type: Article Affiliation country: United kingdom