Ruling out pulmonary embolism across different healthcare settings: A systematic review and individual patient data meta-analysis.


Journal

PLoS medicine
ISSN: 1549-1676
Titre abrégé: PLoS Med
Pays: United States
ID NLM: 101231360

Informations de publication

Date de publication:
01 2022
Historique:
received: 31 08 2021
accepted: 06 01 2022
revised: 08 02 2022
pubmed: 26 1 2022
medline: 1 3 2022
entrez: 25 1 2022
Statut: epublish

Résumé

The challenging clinical dilemma of detecting pulmonary embolism (PE) in suspected patients is encountered in a variety of healthcare settings. We hypothesized that the optimal diagnostic approach to detect these patients in terms of safety and efficiency depends on underlying PE prevalence, case mix, and physician experience, overall reflected by the type of setting where patients are initially assessed. The objective of this study was to assess the capability of ruling out PE by available diagnostic strategies across all possible settings. We performed a literature search (MEDLINE) followed by an individual patient data (IPD) meta-analysis (MA; 23 studies), including patients from self-referral emergency care (n = 12,612), primary healthcare clinics (n = 3,174), referred secondary care (n = 17,052), and hospitalized or nursing home patients (n = 2,410). Multilevel logistic regression was performed to evaluate diagnostic performance of the Wells and revised Geneva rules, both using fixed and adapted D-dimer thresholds to age or pretest probability (PTP), for the YEARS algorithm and for the Pulmonary Embolism Rule-out Criteria (PERC). All strategies were tested separately in each healthcare setting. Following studies done in this field, the primary diagnostic metrices estimated from the models were the "failure rate" of each strategy-i.e., the proportion of missed PE among patients categorized as "PE excluded" and "efficiency"-defined as the proportion of patients categorized as "PE excluded" among all patients. In self-referral emergency care, the PERC algorithm excludes PE in 21% of suspected patients at a failure rate of 1.12% (95% confidence interval [CI] 0.74 to 1.70), whereas this increases to 6.01% (4.09 to 8.75) in referred patients to secondary care at an efficiency of 10%. In patients from primary healthcare and those referred to secondary care, strategies adjusting D-dimer to PTP are the most efficient (range: 43% to 62%) at a failure rate ranging between 0.25% and 3.06%, with higher failure rates observed in patients referred to secondary care. For this latter setting, strategies adjusting D-dimer to age are associated with a lower failure rate ranging between 0.65% and 0.81%, yet are also less efficient (range: 33% and 35%). For all strategies, failure rates are highest in hospitalized or nursing home patients, ranging between 1.68% and 5.13%, at an efficiency ranging between 15% and 30%. The main limitation of the primary analyses was that the diagnostic performance of each strategy was compared in different sets of studies since the availability of items used in each diagnostic strategy differed across included studies; however, sensitivity analyses suggested that the findings were robust. The capability of safely and efficiently ruling out PE of available diagnostic strategies differs for different healthcare settings. The findings of this IPD MA help in determining the optimum diagnostic strategies for ruling out PE per healthcare setting, balancing the trade-off between failure rate and efficiency of each strategy.

Sections du résumé

BACKGROUND
The challenging clinical dilemma of detecting pulmonary embolism (PE) in suspected patients is encountered in a variety of healthcare settings. We hypothesized that the optimal diagnostic approach to detect these patients in terms of safety and efficiency depends on underlying PE prevalence, case mix, and physician experience, overall reflected by the type of setting where patients are initially assessed. The objective of this study was to assess the capability of ruling out PE by available diagnostic strategies across all possible settings.
METHODS AND FINDINGS
We performed a literature search (MEDLINE) followed by an individual patient data (IPD) meta-analysis (MA; 23 studies), including patients from self-referral emergency care (n = 12,612), primary healthcare clinics (n = 3,174), referred secondary care (n = 17,052), and hospitalized or nursing home patients (n = 2,410). Multilevel logistic regression was performed to evaluate diagnostic performance of the Wells and revised Geneva rules, both using fixed and adapted D-dimer thresholds to age or pretest probability (PTP), for the YEARS algorithm and for the Pulmonary Embolism Rule-out Criteria (PERC). All strategies were tested separately in each healthcare setting. Following studies done in this field, the primary diagnostic metrices estimated from the models were the "failure rate" of each strategy-i.e., the proportion of missed PE among patients categorized as "PE excluded" and "efficiency"-defined as the proportion of patients categorized as "PE excluded" among all patients. In self-referral emergency care, the PERC algorithm excludes PE in 21% of suspected patients at a failure rate of 1.12% (95% confidence interval [CI] 0.74 to 1.70), whereas this increases to 6.01% (4.09 to 8.75) in referred patients to secondary care at an efficiency of 10%. In patients from primary healthcare and those referred to secondary care, strategies adjusting D-dimer to PTP are the most efficient (range: 43% to 62%) at a failure rate ranging between 0.25% and 3.06%, with higher failure rates observed in patients referred to secondary care. For this latter setting, strategies adjusting D-dimer to age are associated with a lower failure rate ranging between 0.65% and 0.81%, yet are also less efficient (range: 33% and 35%). For all strategies, failure rates are highest in hospitalized or nursing home patients, ranging between 1.68% and 5.13%, at an efficiency ranging between 15% and 30%. The main limitation of the primary analyses was that the diagnostic performance of each strategy was compared in different sets of studies since the availability of items used in each diagnostic strategy differed across included studies; however, sensitivity analyses suggested that the findings were robust.
CONCLUSIONS
The capability of safely and efficiently ruling out PE of available diagnostic strategies differs for different healthcare settings. The findings of this IPD MA help in determining the optimum diagnostic strategies for ruling out PE per healthcare setting, balancing the trade-off between failure rate and efficiency of each strategy.

Identifiants

pubmed: 35077453
doi: 10.1371/journal.pmed.1003905
pii: PMEDICINE-D-21-03745
pmc: PMC8824365
doi:

Types de publication

Journal Article Meta-Analysis Research Support, Non-U.S. Gov't Systematic Review

Langues

eng

Sous-ensembles de citation

IM

Pagination

e1003905

Déclaration de conflit d'intérêts

I have read the journal’s policy and the following authors of this manuscript have the following competing interests: FAK reports research grants from Bayer, Bristol-Myers Squibb, Boehringer-Ingelheim, MSD, Daiichi-Sankyo, Actelion, the Dutch thrombosis association, The Netherlands Organisation for Health Research and Development and the Dutch Heart foundation. GLG holds the Chair on Diagnosis of Venous Thromboembolism from the Department of Medicine, University of Ottawa and a Clinician Scientist award from the Heart and Stroke Foundation of Canada. WG reports advisory board participation from Amgen, Novartis, Pfizer, Principia Biopharma Inc, a Sanofi Company, and Sanofi, SOBI, Griffols, UCB; lecture honoraria from Amgen, Novartis, and Pfizer; and grants from Bayer, Bristol Myers Squibb, SOBI, Griffols and Pfizer. No other disclosures were reported.

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Auteurs

Geert-Jan Geersing (GJ)

Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands.

Toshihiko Takada (T)

Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands.
Department of General Medicine, Shirakawa Satellite for Teaching And Research (STAR), Fukushima Medical University, Fukushima, Japan.

Frederikus A Klok (FA)

Department of Medicine, Thrombosis and Haemostasis, Dutch Thrombosis Network, Leiden University Medical Center, Leiden, the Netherlands.

Harry R Büller (HR)

Department of Medicine, Amsterdam University Medical Center, Amsterdam Cardiovascular Sciences, Amsterdam, the Netherlands.

D Mark Courtney (DM)

Department of Emergency Medicine, University of Texas Southwestern Medical Center, Dallas, Texas, United States of America.

Yonathan Freund (Y)

Sorbonne University, Emergency Department, Hôpital Pitié-Salpêtrière, Assistance Publique-Hôpitaux de Paris, Paris, France.

Javier Galipienzo (J)

Service of Anesthesiology, MD Anderson Cancer Center Madrid, Madrid, Spain.

Gregoire Le Gal (G)

Department of Medicine, University of Ottawa, Ottawa Hospital Research Institute, Ottawa, Canada.

Waleed Ghanima (W)

Department of Medicine, Østfold Hospital Trust, Norway and Institute of Clinical Medicine, University of Oslo, Oslo, Norway.

Jeffrey A Kline (JA)

Department of Emergency Medicine, Wayne State School of Medicine, Detroit, Michigan, United States of America.

Menno V Huisman (MV)

Department of Medicine, Thrombosis and Haemostasis, Dutch Thrombosis Network, Leiden University Medical Center, Leiden, the Netherlands.

Karel G M Moons (KGM)

Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands.
Cochrane Netherlands, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands.

Arnaud Perrier (A)

Division of Angiology and Hemostasis, Geneva University Hospitals and Faculty of Medicine, Geneva, Switzerland.

Sameer Parpia (S)

Department of Oncology, McMaster University, Hamilton, Canada.
Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Canada.

Helia Robert-Ebadi (H)

Division of Angiology and Hemostasis, Geneva University Hospitals and Faculty of Medicine, Geneva, Switzerland.

Marc Righini (M)

Division of Angiology and Hemostasis, Geneva University Hospitals and Faculty of Medicine, Geneva, Switzerland.

Pierre-Marie Roy (PM)

UNIV Angers, UMR (CNRS 6015-INSERM 1083) and CHU Angers, Department of Emergency Medicine, F-CRIN InnoVTE, Angers, France.

Maarten van Smeden (M)

Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands.

Milou A M Stals (MAM)

Department of Medicine, Thrombosis and Haemostasis, Dutch Thrombosis Network, Leiden University Medical Center, Leiden, the Netherlands.

Philip S Wells (PS)

Department of Medicine, University of Ottawa, Ottawa Hospital Research Institute, Ottawa, Canada.

Kerstin de Wit (K)

Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Canada.
Department of Emergency Medicine, Queen's University, Kingston, Canada.

Noémie Kraaijpoel (N)

Department of Medicine, Amsterdam University Medical Center, Amsterdam Cardiovascular Sciences, Amsterdam, the Netherlands.

Nick van Es (N)

Department of Medicine, Amsterdam University Medical Center, Amsterdam Cardiovascular Sciences, Amsterdam, the Netherlands.

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