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Causal inference in perioperative medicine observational research: part 2, advanced methods.
Krishnamoorthy, Vijay; McLean, Duncan; Ohnuma, Tetsu; Harris, Steve K; Wong, Danny J N; Wilson, Matt; Moonesinghe, Ramani; Raghunathan, Karthik.
Afiliação
  • Krishnamoorthy V; Critical Care and Perioperative Epidemiologic Research (CAPER) Unit, Department of Anesthesiology, Duke University Hospital, Durham, NC, USA. Electronic address: vijay.krishnamoorthy@duke.edu.
  • McLean D; Department of Anesthesiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
  • Ohnuma T; Critical Care and Perioperative Epidemiologic Research (CAPER) Unit, Department of Anesthesiology, Duke University Hospital, Durham, NC, USA.
  • Harris SK; Critical Care, University College London Hospitals NHS Foundation Trust, London, UK.
  • Wong DJN; Department of Anaesthesia, Guy's and Saint Thomas' NHS Foundation Trust, London, UK.
  • Wilson M; Critical Care, University College London Hospitals NHS Foundation Trust, London, UK.
  • Moonesinghe R; Critical Care, University College London Hospitals NHS Foundation Trust, London, UK.
  • Raghunathan K; Critical Care and Perioperative Epidemiologic Research (CAPER) Unit, Department of Anesthesiology, Duke University Hospital, Durham, NC, USA.
Br J Anaesth ; 125(3): 398-405, 2020 09.
Article em En | MEDLINE | ID: mdl-32527658
ABSTRACT
Although RCTs represent the gold standard in clinical research, most clinical questions cannot be answered using this technique, because of ethical considerations, time, and cost. The goal of observational research in clinical medicine is to gain insight into the relationship between a clinical exposure and patient outcome, in the absence of evidence from RCTs. Observational research offers additional benefit when compared with data from RCTs the conclusions are often more generalisable to a heterogenous population, which may be of greater value to everyday clinical practice. In Part 2 of this methods series, we will introduce the reader to several advanced methods for supporting the case for causality between an exposure and outcome, including mediation analysis, natural experiments, and joint effects methods.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Pesquisa Biomédica / Estudos Observacionais como Assunto / Medicina Perioperatória Tipo de estudo: Observational_studies Limite: Humans Idioma: En Revista: Br J Anaesth Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Pesquisa Biomédica / Estudos Observacionais como Assunto / Medicina Perioperatória Tipo de estudo: Observational_studies Limite: Humans Idioma: En Revista: Br J Anaesth Ano de publicação: 2020 Tipo de documento: Article