title: Prognostic models in acute pulmonary embolism: a systematic review and meta-analysis.
abstract: OBJECTIVE
  To review the evidence for existing prognostic models in acute pulmonary embolism (PE) and determine how valid and useful they are for predicting patient outcomes.
  
  
  METHODS
  Systematic review and meta-analysis.
  
  
  METHODS
  OVID MEDLINE and EMBASE, and The Cochrane Library from inception to July 2014, and sources of grey literature.
  
  
  METHODS
  Studies aiming at constructing, validating, updating or studying the impact of prognostic models to predict all-cause death, PE-related death or venous thromboembolic events up to a 3-month follow-up in patients with an acute symptomatic PE.
  
  
  METHODS
  Study characteristics and study quality using prognostic criteria. Studies were selected and data extracted by 2 reviewers.
  
  
  METHODS
  Summary estimates (95% CI) for proportion of risk groups and event rates within risk groups, and accuracy.
  
  
  RESULTS
  We included 71 studies (44,298 patients). Among them, 17 were model construction studies specific to PE prognosis. The most validated models were the PE Severity Index (PESI) and its simplified version (sPESI). The overall 30-day mortality rate was 2.3% (1.7% to 2.9%) in the low-risk group and 11.4% (9.9% to 13.1%) in the high-risk group for PESI (9 studies), and 1.5% (0.9% to 2.5%) in the low-risk group and 10.7% (8.8% to12.9%) in the high-risk group for sPESI (11 studies). PESI has proved clinically useful in an impact study. Shifting the cut-off or using novel and updated models specifically developed for normotensive PE improves the ability for identifying patients at lower risk for early death or adverse outcome (0.5-1%) and those at higher risk (up to 20-29% of event rate).
  
  
  CONCLUSIONS
  We provide evidence-based information about the validity and utility of the existing prognostic models in acute PE that may be helpful for identifying patients at low risk. Novel models seem attractive for the high-risk normotensive PE but need to be externally validated then be assessed in impact studies.
authors.affiliation: Department of Vascular Medicine, Sainte Musse Hospital, Toulon La Seyne Hospital Centre, Toulon, France DPhil Programme in Evidence-Based Healthcare, University of Oxford, Oxford, UK.
authors.forename: Antoine
authors.initials: A
authors.lastname: Elias
authors.affiliation: Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.
authors.forename: Susan
authors.initials: S
authors.lastname: Mallett
authors.affiliation: Department of Vascular Medicine, Sainte Musse Hospital, Toulon La Seyne Hospital Centre, Toulon, France.
authors.forename: Marie
authors.initials: M
authors.lastname: Daoud-Elias
authors.affiliation: Department of Vascular Medicine, Sainte Musse Hospital, Toulon La Seyne Hospital Centre, Toulon, France.
authors.forename: Jean-Noël
authors.initials: JN
authors.lastname: Poggi
authors.affiliation: Northern Ireland Network for Trials Methodology Research, Queen's University Belfast, Belfast, UK.
authors.forename: Mike
authors.initials: M
authors.lastname: Clarke
mesh_terms: D000208:Acute Disease; D006305:Health Status Indicators; D006801:Humans; D008962:Models, Theoretical; D011237:Predictive Value of Tests; D011379:Prognosis; D011655:Pulmonary Embolism / Q000175:diagnosis* / Q000401:mortality; D018570:Risk Assessment / Q000379:methods*; D012720:Severity of Illness Index; D054556:Venous Thromboembolism
keywords: prediction rules; prognostic models; pulmonary embolism; risk stratification; systematic review