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Ruling out pulmonary embolism across different healthcare settings : A systematic review and individual patient data meta-analysis. / Geersing, Geert-Jan; Takada, Toshihiko; Klok, Frederikus A. et al.

In: PLoS medicine, Vol. 19, No. 1, e1003905, 01.01.2022.

Research output: Contribution to journalArticleAcademicpeer-review

Harvard

Geersing, G-J, Takada, T, Klok, FA, Büller, HR, Courtney, DM, Freund, Y, Galipienzo, J, le Gal, G, Ghanima, W, Kline, JA, Huisman, MV, Moons, KGM, Perrier, A, Parpia, S, Robert-Ebadi, H, Righini, M, Roy, P-M, van Smeden, M, Stals, MAM, Wells, PS, de Wit, K, Kraaijpoel, N & van Es, N 2022, 'Ruling out pulmonary embolism across different healthcare settings: A systematic review and individual patient data meta-analysis', PLoS medicine, vol. 19, no. 1, e1003905. https://doi.org/10.1371/journal.pmed.1003905

APA

Geersing, G-J., Takada, T., Klok, F. A., Büller, H. R., Courtney, D. M., Freund, Y., Galipienzo, J., le Gal, G., Ghanima, W., Kline, J. A., Huisman, M. V., Moons, K. G. M., Perrier, A., Parpia, S., Robert-Ebadi, H., Righini, M., Roy, P-M., van Smeden, M., Stals, M. A. M., ... van Es, N. (2022). Ruling out pulmonary embolism across different healthcare settings: A systematic review and individual patient data meta-analysis. PLoS medicine, 19(1), [e1003905]. https://doi.org/10.1371/journal.pmed.1003905

Vancouver

Geersing G-J, Takada T, Klok FA, Büller HR, Courtney DM, Freund Y et al. Ruling out pulmonary embolism across different healthcare settings: A systematic review and individual patient data meta-analysis. PLoS medicine. 2022 Jan 1;19(1):e1003905. doi: 10.1371/journal.pmed.1003905

Author

Geersing, Geert-Jan ; Takada, Toshihiko ; Klok, Frederikus A. et al. / Ruling out pulmonary embolism across different healthcare settings : A systematic review and individual patient data meta-analysis. In: PLoS medicine. 2022 ; Vol. 19, No. 1.

BibTeX

@article{335f3f0ee687438286366746135a177c,
title = "Ruling out pulmonary embolism across different healthcare settings: A systematic review and individual patient data meta-analysis",
abstract = "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.",
author = "Geert-Jan Geersing and Toshihiko Takada and Klok, {Frederikus A.} and B{\"u}ller, {Harry R.} and Courtney, {D. Mark} and Yonathan Freund and Javier Galipienzo and {le Gal}, Gregoire and Waleed Ghanima and Kline, {Jeffrey A.} and Huisman, {Menno V.} and Moons, {Karel G. M.} and Arnaud Perrier and Sameer Parpia and Helia Robert-Ebadi and Marc Righini and Pierre-Marie Roy and {van Smeden}, Maarten and Stals, {Milou A. M.} and Wells, {Philip S.} and {de Wit}, Kerstin and No{\'e}mie Kraaijpoel and {van Es}, Nick",
note = "Funding Information: GJG is supported by a personal Vidi grant from the Dutch Research Council (grant number 91719304). URL: https://www.nwo.nl/en/calls/nwo-talent-programme The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Publisher Copyright: Copyright: {\textcopyright} 2022 Geersing et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.",
year = "2022",
month = jan,
day = "1",
doi = "10.1371/journal.pmed.1003905",
language = "English",
volume = "19",
journal = "PLoS medicine",
issn = "1549-1277",
publisher = "Public Library of Science",
number = "1",

}

RIS

TY - JOUR

T1 - Ruling out pulmonary embolism across different healthcare settings

T2 - A systematic review and individual patient data meta-analysis

AU - Geersing, Geert-Jan

AU - Takada, Toshihiko

AU - Klok, Frederikus A.

AU - Büller, Harry R.

AU - Courtney, D. Mark

AU - Freund, Yonathan

AU - Galipienzo, Javier

AU - le Gal, Gregoire

AU - Ghanima, Waleed

AU - Kline, Jeffrey A.

AU - Huisman, Menno V.

AU - Moons, Karel G. M.

AU - Perrier, Arnaud

AU - Parpia, Sameer

AU - Robert-Ebadi, Helia

AU - Righini, Marc

AU - Roy, Pierre-Marie

AU - van Smeden, Maarten

AU - Stals, Milou A. M.

AU - Wells, Philip S.

AU - de Wit, Kerstin

AU - Kraaijpoel, Noémie

AU - van Es, Nick

N1 - Funding Information: GJG is supported by a personal Vidi grant from the Dutch Research Council (grant number 91719304). URL: https://www.nwo.nl/en/calls/nwo-talent-programme The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Publisher Copyright: Copyright: © 2022 Geersing et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

PY - 2022/1/1

Y1 - 2022/1/1

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=85123841103&partnerID=8YFLogxK

U2 - 10.1371/journal.pmed.1003905

DO - 10.1371/journal.pmed.1003905

M3 - Article

C2 - 35077453

VL - 19

JO - PLoS medicine

JF - PLoS medicine

SN - 1549-1277

IS - 1

M1 - e1003905

ER -

ID: 21578433