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Wiki Education Foundation-supported course assignment

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This article is or was the subject of a Wiki Education Foundation-supported course assignment. Further details are available on the course page. Student editor(s): Bangabullet90. Peer reviewers: Pavikavarma.

Above undated message substituted from Template:Dashboard.wikiedu.org assignment by PrimeBOT (talk) 07:29, 17 January 2022 (UTC)[reply]

Ultrasound-assisted thrombolysis

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doi:10.1016/j.amjcard.2019.07.040 JFW | T@lk 08:02, 12 September 2019 (UTC)[reply]

European guidelines (ESC/ERS)

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https://www.ers-education.org/Media/Media.aspx?idMedia=418654 JFW | T@lk 13:55, 18 September 2019 (UTC)[reply]

I was going to put the same source here, and here's a couple another ways to get there. It is free if you go to the doi link also. Konstantinides SV, Meyer G, Becattini C, Bueno H, Geersing GJ, Harjola VP, Huisman MV, Humbert M, Jennings CS, Jiménez D, Kucher N, Lang IM, Lankeit M, Lorusso R, Mazzolai L, Meneveau N, Ní Áinle F, Prandoni P, Pruszczyk P, Righini M, Torbicki A, Van Belle E, Zamorano JL (August 2019). "2019 ESC Guidelines for the diagnosis and management of acute pulmonary embolism developed in collaboration with the European Respiratory Society (ERS)". European Heart Journal. doi:10.1093/eurheartj/ehz405. PMID 31504429. PDF Thanks. Biosthmors (talk) 20:44, 6 January 2020 (UTC)[reply]

@Biosthmors: It's a chunky document but there are some important changes to previous recommendations. For instance, CTPA is considered appropriate as a first line investigation in pregnancy, where previously VQ had the edge because of radiation dose to breasts. JFW | T@lk 22:45, 6 January 2020 (UTC)[reply]

NICE NG158

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Guideline updated here. Need to review references to CG144 and replace. JFW | T@lk 09:57, 5 May 2020 (UTC)[reply]

Added

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This was added:

Machine learning model (PERFORM)[1] have been developed to generate a patient-specific risk score for PE by analyzing longitudinal clinical data as clinical decision support for patients referred for CT imaging for PE in order to reduce the rate of CTPA imaging. The model was tested on holdout patient EMR data from 2 large, academic medical practices. A total of 3397 annotated CT imaging examinations for PE from 3214 unique patients seen at Stanford University hospitals and clinics were used for training and validation. The models were externally validated on 240 unique patients seen at Duke University Medical Center. The comparison with clinical scoring systems was done on randomly selected 100 outpatient samples from Stanford University hospitals and clinics and 101 outpatient samples from Duke University Medical Center. The model achieved an AUROC performance of predicting a positive PE study of 0.90 (95% CI, 0.87-0.91) on intrainstitutional holdout data with an AUROC of 0.71 (95% CI, 0.69-0.72) on an external data set from Duke University Medical Center; superior AUROC performance and cross-institutional generalization of the model of 0.81 (95% CI, 0.77-0.87) and 0.81 (95% CI, 0.73-0.82), respectively, were noted on holdout outpatient populations from both intrainstitutional and extrainstitutional data

Not ready for prime time in the article. Needs a WP:MEDRS source at least. JFW | T@lk 20:51, 9 December 2020 (UTC)[reply]

References

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Participate in the deletion discussion at the nomination page. —Community Tech bot (talk) 09:39, 30 June 2021 (UTC)[reply]