Reviews
14 December 2021

Safety and Efficiency of Diagnostic Strategies for Ruling Out Pulmonary Embolism in Clinically Relevant Patient Subgroups: A Systematic Review and Individual-Patient Data Meta-analysis

Publication: Annals of Internal Medicine
Volume 175, Number 2

Abstract

Background:

How diagnostic strategies for suspected pulmonary embolism (PE) perform in relevant patient subgroups defined by sex, age, cancer, and previous venous thromboembolism (VTE) is unknown.

Purpose:

To evaluate the safety and efficiency of the Wells and revised Geneva scores combined with fixed and adapted D-dimer thresholds, as well as the YEARS algorithm, for ruling out acute PE in these subgroups.

Data Sources:

MEDLINE from 1 January 1995 until 1 January 2021.

Study Selection:

16 studies assessing at least 1 diagnostic strategy.

Data Extraction:

Individual-patient data from 20 553 patients.

Data Synthesis:

Safety was defined as the diagnostic failure rate (the predicted 3-month VTE incidence after exclusion of PE without imaging at baseline). Efficiency was defined as the proportion of individuals classified by the strategy as “PE considered excluded” without imaging tests. Across all strategies, efficiency was highest in patients younger than 40 years (47% to 68%) and lowest in patients aged 80 years or older (6.0% to 23%) or patients with cancer (9.6% to 26%). However, efficiency improved considerably in these subgroups when pretest probability–dependent D-dimer thresholds were applied. Predicted failure rates were highest for strategies with adapted D-dimer thresholds, with failure rates varying between 2% and 4% in the predefined patient subgroups.

Limitations:

Between-study differences in scoring predictor items and D-dimer assays, as well as the presence of differential verification bias, in particular for classifying fatal events and subsegmental PE cases, all of which may have led to an overestimation of the predicted failure rates of adapted D-dimer thresholds.

Conclusion:

Overall, all strategies showed acceptable safety, with pretest probability–dependent D-dimer thresholds having not only the highest efficiency but also the highest predicted failure rate. From an efficiency perspective, this individual-patient data meta-analysis supports application of adapted D-dimer thresholds.

Primary Funding Source:

Dutch Research Council. (PROSPERO: CRD42018089366)

Get full access to this article

View all available purchase options and get full access to this article.

Supplemental Material

Supplement. Patient-Level Data Collected at Baseline

References

1.
Huisman MV, Barco S, Cannegieter SC, et al. Pulmonary embolism. Nat Rev Dis Primers. 2018;4:18028. [PMID: 29770793] doi: 10.1038/nrdp.2018.28
2.
van Es N, van der Hulle T, van Es J, et al. Wells rule and d-dimer testing to rule out pulmonary embolism: a systematic review and individual-patient data meta-analysis. Ann Intern Med. 2016;165:253-61. [PMID: 27182696] doi: 10.7326/M16-0031
3.
Pasha SM, Klok FA, Snoep JD, et al. Safety of excluding acute pulmonary embolism based on an unlikely clinical probability by the Wells rule and normal D-dimer concentration: a meta-analysis. Thromb Res. 2010;125:e123-7. [PMID: 19942258] doi: 10.1016/j.thromres.2009.11.009
4.
Hurwitz LM, Reiman RE, Yoshizumi TT, et al. Radiation dose from contemporary cardiothoracic multidetector CT protocols with an anthropomorphic female phantom: implications for cancer induction. Radiology. 2007;245:742-50. [PMID: 17923509] doi: 10.1148/radiol.2453062046
5.
Kooiman J, Klok FA, Mos IC, et al. Incidence and predictors of contrast-induced nephropathy following CT-angiography for clinically suspected acute pulmonary embolism [Letter]. J Thromb Haemost. 2010;8:409-11. [PMID: 19943871] doi: 10.1111/j.1538-7836.2009.03698.x
6.
van der Pol LM, Dronkers CEA, van der Hulle T, et al. The YEARS algorithm for suspected pulmonary embolism: shorter visit time and reduced costs at the emergency department. J Thromb Haemost. 2018;16:725-733. [PMID: 29431911] doi: 10.1111/jth.13972
7.
Huisman MV, Klok FA. How I diagnose acute pulmonary embolism. Blood. 2013;121:4443-8. [PMID: 23591793] doi: 10.1182/blood-2013-03-453050
8.
Righini M, Van Es J, Den Exter PL, et al. Age-adjusted D-dimer cutoff levels to rule out pulmonary embolism: the ADJUST-PE study. JAMA. 2014;311:1117-24. [PMID: 24643601] doi: 10.1001/jama.2014.2135
9.
Douma RA, le Gal G, Söhne M, et al. Potential of an age adjusted D-dimer cut-off value to improve the exclusion of pulmonary embolism in older patients: a retrospective analysis of three large cohorts. BMJ. 2010;340:c1475. [PMID: 20354012] doi: 10.1136/bmj.c1475
10.
van der Hulle T, Cheung WY, Kooij S, et al; YEARS study group. Simplified diagnostic management of suspected pulmonary embolism (the YEARS study): a prospective, multicentre, cohort study. Lancet. 2017;390:289-297. [PMID: 28549662] doi: 10.1016/S0140-6736(17)30885-1
11.
Kearon C, de Wit K, Parpia S, et al; PEGeD Study Investigators. Diagnosis of pulmonary embolism with d-dimer adjusted to clinical probability. N Engl J Med. 2019;381:2125-2134. [PMID: 31774957] doi: 10.1056/NEJMoa1909159
12.
van Belle A, Büller HR, Huisman MV, et al; Christopher Study Investigators. Effectiveness of managing suspected pulmonary embolism using an algorithm combining clinical probability, D-dimer testing, and computed tomography. JAMA. 2006;295:172-9. [PMID: 16403929] doi: 10.1001/jama.295.2.172
13.
Douma RA, Mos IC, Erkens PM, et al; Prometheus Study Group. Performance of 4 clinical decision rules in the diagnostic management of acute pulmonary embolism: a prospective cohort study. Ann Intern Med. 2011;154:709-18. [PMID: 21646554] doi: 10.7326/0003-4819-154-11-201106070-00002
14.
Mos IC, Douma RA, Erkens PM, et al; Prometheus Study Group. Diagnostic outcome management study in patients with clinically suspected recurrent acute pulmonary embolism with a structured algorithm. Thromb Res. 2014;133:1039-44. [PMID: 24735976] doi: 10.1016/j.thromres.2014.03.050
15.
van der Pol LM, Tromeur C, Bistervels IM, et al; Artemis Study Investigators. Pregnancy-adapted YEARS algorithm for diagnosis of suspected pulmonary embolism. N Engl J Med. 2019;380:1139-1149. [PMID: 30893534] doi: 10.1056/NEJMoa1813865
16.
van der Hulle T, den Exter PL, Mos IC, et al. Optimization of the diagnostic management of clinically suspected pulmonary embolism in hospitalized patients. Br J Haematol. 2014;167:681-6. [PMID: 25146098] doi: 10.1111/bjh.13090
17.
Karami-Djurabi R, Klok FA, Kooiman J, et al. D-dimer testing in patients with suspected pulmonary embolism and impaired renal function. Am J Med. 2009;122:1050-3. [PMID: 19698934] doi: 10.1016/j.amjmed.2009.03.032
18.
Stals MAM, Klok FA, Huisman MV. Diagnostic management of acute pulmonary embolism in special populations. Expert Rev Respir Med. 2020;14:729-736. [PMID: 32268826] doi: 10.1080/17476348.2020.1753505
19.
Geersing GJ, Kraaijpoel N, Büller HR, et al. Ruling out pulmonary embolism across different subgroups of patients and healthcare settings: protocol for a systematic review and individual patient data meta-analysis (IPDMA). Diagn Progn Res. 2018;2:10. [PMID: 31093560] doi: 10.1186/s41512-018-0032-7
20.
Stewart LA, Clarke M, Rovers M, et al; PRISMA-IPD Development Group. Preferred reporting items for systematic review and meta-analyses of individual participant data: the PRISMA-IPD statement. JAMA. 2015;313:1657-65. [PMID: 25919529] doi: 10.1001/jama.2015.3656
21.
McInnes MDF, Moher D, Thombs BD, et al; PRISMA-DTA Group. Preferred reporting items for a systematic review and meta-analysis of diagnostic test accuracy studies: the PRISMA-DTA statement. JAMA. 2018;319:388-396. [PMID: 29362800] doi: 10.1001/jama.2017.19163
22.
Collins GS, Reitsma JB, Altman DG, et al. Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis (TRIPOD): the TRIPOD statement. Ann Intern Med. 2015;162:55-63. [PMID: 25560714] doi: 10.7326/M14-0697
23.
Moons KGM, Wolff RF, Riley RD, et al. PROBAST: a tool to assess risk of bias and applicability of prediction model studies: explanation and elaboration. Ann Intern Med. 2019;170:W1-W33. [PMID: 30596876] doi: 10.7326/M18-1377
24.
Wolff RF, Moons KGM, Riley RD, et al; PROBAST Group. PROBAST: a tool to assess the risk of bias and applicability of prediction model studies. Ann Intern Med. 2019;170:51-58. [PMID: 30596875] doi: 10.7326/M18-1376
25.
Whiting PF, Rutjes AW, Westwood ME, et al; QUADAS-2 Group. QUADAS-2: a revised tool for the quality assessment of diagnostic accuracy studies. Ann Intern Med. 2011;155:529-36. [PMID: 22007046] doi: 10.7326/0003-4819-155-8-201110180-00009
26.
Dronkers CEA, van der Hulle T, Le Gal G, et al; Subcommittee on Predictive and Diagnostic Variables in Thrombotic Disease. Towards a tailored diagnostic standard for future diagnostic studies in pulmonary embolism: communication from the SSC of the ISTH. J Thromb Haemost. 2017;15:1040-1043. [PMID: 28296048] doi: 10.1111/jth.13654
27.
Higgins JP, Thompson SG, Deeks JJ, et al. Measuring inconsistency in meta-analyses. BMJ. 2003;327:557-60. [PMID: 12958120] doi: 10.1136/bmj.327.7414.557
28.
Jolani S, Debray TP, Koffijberg H, et al. Imputation of systematically missing predictors in an individual participant data meta-analysis: a generalized approach using MICE. Stat Med. 2015;34:1841-63. [PMID: 25663182] doi: 10.1002/sim.6451
29.
Sterne JA, White IR, Carlin JB, et al. Multiple imputation for missing data in epidemiological and clinical research: potential and pitfalls. BMJ. 2009;338:b2393. [PMID: 19564179] doi: 10.1136/bmj.b2393
30.
Marshall A, Altman DG, Holder RL, et al. Combining estimates of interest in prognostic modelling studies after multiple imputation: current practice and guidelines. BMC Med Res Methodol. 2009;9:57. [PMID: 19638200] doi: 10.1186/1471-2288-9-57
31.
Sanson BJ, Lijmer JG, Mac Gillavry MR, et al. Comparison of a clinical probability estimate and two clinical models in patients with suspected pulmonary embolism. ANTELOPE-Study Group. Thromb Haemost. 2000;83:199-203. [PMID: 10739372] doi: 10.1055/s-0037-1613785
32.
Geersing GJ, Erkens PM, Lucassen WA, et al. Safe exclusion of pulmonary embolism using the Wells rule and qualitative D-dimer testing in primary care: prospective cohort study. BMJ. 2012;345:e6564. [PMID: 23036917] doi: 10.1136/bmj.e6564
33.
Kearon C, Ginsberg JS, Douketis J, et al; Canadian Pulmonary Embolism Diagnosis Study (CANPEDS) Group. An evaluation of D-dimer in the diagnosis of pulmonary embolism: a randomized trial. Ann Intern Med. 2006;144:812-21. [PMID: 16754923] doi: 10.7326/0003-4819-144-11-200606060-00007
34.
Kline JA, Nelson RD, Jackson RE, et al. Criteria for the safe use of D-dimer testing in emergency department patients with suspected pulmonary embolism: a multicenter US study. Ann Emerg Med. 2002;39:144-52. [PMID: 11823768] doi: 10.1067/mem.2002.121398
35.
Kline JA, Runyon MS, Webb WB, et al. Prospective study of the diagnostic accuracy of the Simplify D-dimer assay for pulmonary embolism in emergency department patients. Chest. 2006;129:1417-23. [PMID: 16778257] doi: 10.1378/chest.129.6.1417
36.
Kline JA, Courtney DM, Kabrhel C, et al. Prospective multicenter evaluation of the pulmonary embolism rule-out criteria. J Thromb Haemost. 2008;6:772-80. [PMID: 18318689] doi: 10.1111/j.1538-7836.2008.02944.x
37.
Runyon MS, Beam DM, King MC, et al. Comparison of the Simplify D-dimer assay performed at the bedside with a laboratory-based quantitative D-dimer assay for the diagnosis of pulmonary embolism in a low prevalence emergency department population. Emerg Med J. 2008;25:70-5. [PMID: 18212136] doi: 10.1136/emj.2007.048918
38.
Kline JA, Hogg MM, Courtney DM, et al. D-dimer threshold increase with pretest probability unlikely for pulmonary embolism to decrease unnecessary computerized tomographic pulmonary angiography. J Thromb Haemost. 2012;10:572-81. [PMID: 22284935] doi: 10.1111/j.1538-7836.2012.04647.x
39.
Penaloza A, Soulié C, Moumneh T, et al. Pulmonary embolism rule-out criteria (PERC) rule in European patients with low implicit clinical probability (PERCEPIC): a multicentre, prospective, observational study. Lancet Haematol. 2017;4:e615-e621. [PMID: 29150390] doi: 10.1016/S2352-3026(17)30210-7
40.
Goekoop RJ, Steeghs N, Niessen RW, et al. Simple and safe exclusion of pulmonary embolism in outpatients using quantitative D-dimer and Wells' simplified decision rule. Thromb Haemost. 2007;97:146-50. [PMID: 17200782] doi: 10.1160/TH06-09-0529
41.
Schouten HJ, Geersing GJ, Oudega R, et al. Accuracy of the Wells clinical prediction rule for pulmonary embolism in older ambulatory adults. J Am Geriatr Soc. 2014;62:2136-41. [PMID: 25366538] doi: 10.1111/jgs.13080
42.
Wicki J, Perneger TV, Junod AF, et al. Assessing clinical probability of pulmonary embolism in the emergency ward: a simple score. Arch Intern Med. 2001;161:92-7. [PMID: 11146703] doi: 10.1001/archinte.161.1.92
43.
Perrier A, Roy PM, Aujesky D, et al. Diagnosing pulmonary embolism in outpatients with clinical assessment, D-dimer measurement, venous ultrasound, and helical computed tomography: a multicenter management study. Am J Med. 2004;116:291-9. [PMID: 14984813] doi: 10.1016/j.amjmed.2003.09.041
44.
Perrier A, Roy PM, Sanchez O, et al. Multidetector-row computed tomography in suspected pulmonary embolism. N Engl J Med. 2005;352:1760-8. [PMID: 15858185] doi: 10.1056/NEJMoa042905
45.
Righini M, Le Gal G, Aujesky D, et al. Diagnosis of pulmonary embolism by multidetector CT alone or combined with venous ultrasonography of the leg: a randomised non-inferiority trial. Lancet. 2008;371:1343-52. [PMID: 18424324] doi: 10.1016/S0140-6736(08)60594-2
46.
Galipienzo J, Garcia de Tena J, Flores J, et al. Effectiveness of a diagnostic algorithm combining clinical probability, D-dimer testing, and computed tomography in patients with suspected pulmonary embolism in an emergency department. Rom J Intern Med. 2012 Jul-Sep;50:195-202. [PMID: 23330286]
47.
Ghanima W, Almaas V, Aballi S, et al. Management of suspected pulmonary embolism (PE) by D-dimer and multi-slice computed tomography in outpatients: an outcome study. J Thromb Haemost. 2005;3:1926-32. [PMID: 16102097] doi: 10.1111/j.1538-7836.2005.01544.x
48.
van der Hulle T, van Es N, den Exter PL, et al. Is a normal computed tomography pulmonary angiography safe to rule out acute pulmonary embolism in patients with a likely clinical probability? A patient-level meta-analysis. Thromb Haemost. 2017;117:1622-9. [PMID: 28569924] doi: 10.1160/TH17-02-0076
49.
Carrier M, Klok FA. Symptomatic subsegmental pulmonary embolism: to treat or not to treat. Hematology Am Soc Hematol Educ Program. 2017;2017:237-241. [PMID: 29222261] doi: 10.1182/asheducation-2017.1.237
50.
den Exter PL, Kroft LJM, Gonsalves C, et al. Establishing diagnostic criteria and treatment of subsegmental pulmonary embolism: a Delphi analysis of experts. Res Pract Thromb Haemost. 2020;4:1251-1261. [PMID: 33313465] doi: 10.1002/rth2.12422
51.
van der Pol LM, Bistervels IM, van Mens TE, et al. Lower prevalence of subsegmental pulmonary embolism after application of the YEARS diagnostic algorithm. Br J Haematol. 2018;183:629-635. [PMID: 30198551] doi: 10.1111/bjh.15556
52.
Girard P, Penaloza A, Parent F, et al. Reproducibility of clinical events adjudications in a trial of venous thromboembolism prevention. J Thromb Haemost. 2017;15:662-669. [PMID: 28092428] doi: 10.1111/jth.13626
53.
Tritschler T, Kraaijpoel N, Girard P, et al; Subcommittee on Predictive and Diagnostic Variables in Thrombotic Disease. Definition of pulmonary embolism-related death and classification of the cause of death in venous thromboembolism studies: communication from the SSC of the ISTH. J Thromb Haemost. 2020;18:1495-1500. [PMID: 32496023] doi: 10.1111/jth.14769
54.
Wang J, Bossuyt P, Geskus R, et al; IMPORT Study Group. Using individual patient data to adjust for indirectness did not successfully remove the bias in this case of comparative test accuracy. J Clin Epidemiol. 2015;68:290-8. [PMID: 25475365] doi: 10.1016/j.jclinepi.2014.10.005

Comments

0 Comments
Sign In to Submit A Comment

Information & Authors

Information

Published In

cover image Annals of Internal Medicine
Annals of Internal Medicine
Volume 175Number 2February 2022
Pages: 244 - 255

History

Published online: 14 December 2021
Published in issue: February 2022

Keywords

Authors

Affiliations

Department of Thrombosis and Hemostasis, Leiden University Medical Center, Leiden, the Netherlands (M.A.M.S., M.V.H., F.A.K.)
Toshihiko Takada, MD, PhD https://orcid.org/0000-0002-8032-6224
Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands, and Department of General Medicine, Shirakawa Satellite for Teaching and Research (STAR), Fukushima Medical University, Fukushima, Japan (T.T.)
Noémie Kraaijpoel, MD, PhD https://orcid.org/0000-0002-1124-695X
Department of Vascular Medicine, Amsterdam University Medical Center, location AMC, Amsterdam Cardiovascular Sciences, Amsterdam, the Netherlands (N.K., N.v.E., H.R.B.)
Department of Vascular Medicine, Amsterdam University Medical Center, location AMC, Amsterdam Cardiovascular Sciences, Amsterdam, the Netherlands (N.K., N.v.E., H.R.B.)
Harry R. Büller, MD, PhD
Department of Vascular Medicine, Amsterdam University Medical Center, location AMC, Amsterdam Cardiovascular Sciences, Amsterdam, the Netherlands (N.K., N.v.E., H.R.B.)
D. Mark Courtney, MD, PhD
Department of Emergency Medicine, The University of Texas Southwestern Medical Center, Dallas, Texas (D.M.C.)
Yonathan Freund, MD, PhD
Department of Emergency Medicine, Pitié-Salpêtrière University Hospital, Assistance Publique–Hôpitaux de Paris, Paris, France (Y.F.)
Javier Galipienzo, MD
Service of Anesthesiology, Hospital MD Anderson Cancer Center, Madrid, Spain (J.G.)
Grégoire Le Gal, MD, PhD
Department of Medicine, University of Ottawa, Ottawa Hospital Research Institute, Thrombosis Research Group, Ottawa, Ontario, Canada (G.L.G., P.S.W.)
Department of Medicine, Østfold Hospital Trust and Institute of Clinical Medicine, University of Oslo, Oslo, Norway (W.G.)
Menno V. Huisman, MD, PhD https://orcid.org/0000-0003-1423-5348
Department of Thrombosis and Hemostasis, Leiden University Medical Center, Leiden, the Netherlands (M.A.M.S., M.V.H., F.A.K.)
Department of Emergency Medicine, Indiana University School of Medicine, Indianapolis, Indiana (J.A.K.)
Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands (K.G.M.M., M.v.S., G.J.G.)
Sameer Parpia, PhD
Department of Oncology, McMaster University, Hamilton, Ontario, Canada (S.P.)
Division of Angiology and Hemostasis, Department of Medical Specialties, Geneva University Hospital and Faculty of Medicine, Geneva, Switzerland (A.P., M.R., H.R.E.)
Division of Angiology and Hemostasis, Department of Medical Specialties, Geneva University Hospital and Faculty of Medicine, Geneva, Switzerland (A.P., M.R., H.R.E.)
Division of Angiology and Hemostasis, Department of Medical Specialties, Geneva University Hospital and Faculty of Medicine, Geneva, Switzerland (A.P., M.R., H.R.E.)
Pierre-Marie Roy, MD, PhD https://orcid.org/0000-0003-4811-6793
Department of Emergency Medicine, University of Angers, Angers, France (P.M.R.)
Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands (K.G.M.M., M.v.S., G.J.G.)
Department of Medicine, University of Ottawa, Ottawa Hospital Research Institute, Thrombosis Research Group, Ottawa, Ontario, Canada (G.L.G., P.S.W.)
Department of Emergency Medicine, Queen's University, Kingston, and Departments of Medicine and Health Research Methods, Evidence, and Impact (HEI), McMaster University, Hamilton, Ontario, Canada (K.d.W.).
Geert-Jan Geersing, MD, PhD
Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands (K.G.M.M., M.v.S., G.J.G.)
Frederikus A. Klok, MD, PhD https://orcid.org/0000-0001-9961-0754
Department of Thrombosis and Hemostasis, Leiden University Medical Center, Leiden, the Netherlands (M.A.M.S., M.V.H., F.A.K.)
Grant Support: By grant 91616030 from the Dutch Research Council.
Reproducible Research Statement: Study protocol: The study protocol was published previously (19). This project was also preregistered at the PROSPERO database for systematic reviews (CRD42018089366). Statistical code and data set: Not available.
Corresponding Author: Frederikus A. Klok, MD, PhD, Department of Medicine–Thrombosis and Hemostasis, Leiden University Medical Center, Albinusdreef 2, Leiden, the Netherlands; e-mail, [email protected].
Author Contributions: Conception and design: G.J. Geersing, F.A. Klok, N. Kraaijpoel, N. van Es, G. Le Gal, M.V. Huisman, K.G.M. Moons, M. Righini, M. van Smeden.
Analysis and interpretation of the data: M.A.M. Stals, T. Takada, N. Kraaijpoel, N. van Es, H.R. Büller, G. Le Gal, M.V. Huisman, K.G.M. Moons, M. Righini, M. van Smeden, P.S. Wells, K. de Wit, G.J. Geersing, F.A. Klok.
Drafting of the article: M.A.M. Stals, T. Takada, N. Kraaijpoel, N. van Es, M. van Smeden, G.J. Geersing, F.A. Klok.
Critical revision of the article for important intellectual content: M.A.M. Stals, T. Takada, N. Kraaijpoel, N. van Es, H.R. Büller, D.M. Courtney, Y. Freund, J. Galipienzo, G. Le Gal, W. Ghanima, M.V. Huisman, J.A. Kline, K.G.M. Moons, S. Parpia, A. Perrier, M. Righini, H. Robert-Ebadi, P.M. Roy, M. van Smeden, P.S. Wells, K. de Wit, G.J. Geersing, F.A. Klok.
Final approval of the article: M.A.M. Stals, T. Takada, N. Kraaijpoel, N. van Es, H.R. Büller, D.M. Courtney, Y. Freund, J. Galipienzo, G. Le Gal, W. Ghanima, M.V. Huisman, J.A. Kline, K.G.M. Moons, S. Parpia, A. Perrier, M. Righini, H. Robert-Ebadi, P.M. Roy, M. van Smeden, P.S. Wells, K. de Wit, G.J. Geersing, F.A. Klok.
Provision of study materials or patients: Y. Freund, G. Le Gal, W. Ghanima, S. Parpia, M. Righini, P.M. Roy, P.S. Wells, G.J. Geersing.
Statistical expertise: T. Takada, K.G.M. Moons, M. van Smeden, G.J. Geersing.
Obtaining of funding: M. Righini, G.J. Geersing.
Administrative, technical, or logistic support: G. Le Gal, J.A. Kline, M. Righini, G.J. Geersing, F.A. Klok.
Collection and assembly of data: M.A.M. Stals, T. Takada, N. Kraaijpoel, N. van Es, Y. Freund, J. Galipienzo, G. Le Gal, W. Ghanima, M.V. Huisman, J.A. Kline, A. Perrier, M. Righini, K. de Wit, G.J. Geersing, F.A. Klok.
This article was published at Annals.org on 14 December 2021.

Metrics & Citations

Metrics

Citations

If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. For an editable text file, please select Medlars format which will download as a .txt file. Simply select your manager software from the list below and click Download.

For more information or tips please see 'Downloading to a citation manager' in the Help menu.

Format





Download article citation data for:
Milou A.M. Stals, Toshihiko Takada, Noémie Kraaijpoel, et al. Safety and Efficiency of Diagnostic Strategies for Ruling Out Pulmonary Embolism in Clinically Relevant Patient Subgroups: A Systematic Review and Individual-Patient Data Meta-analysis. Ann Intern Med.2022;175:244-255. [Epub 14 December 2021]. doi:10.7326/M21-2625

View More

Login Options:
Purchase

You will be redirected to acponline.org to sign-in to Annals to complete your purchase.

Access to EPUBs and PDFs for FREE Annals content requires users to be registered and logged in. A subscription is not required. You can create a free account below or from the following link. You will be redirected to acponline.org to create an account that will provide access to Annals. If you are accessing the Free Annals content via your institution's access, registration is not required.

Create your Free Account

You will be redirected to acponline.org to create an account that will provide access to Annals.

View options

PDF/EPUB

View PDF/EPUB

Related in ACP Journals

Full Text

View Full Text

Media

Figures

Other

Tables

Share

Share

Copy the content Link

Share on social media