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New Diagnostic Tools for Pulmonary Embolism Detection Cover

New Diagnostic Tools for Pulmonary Embolism Detection

Open Access
|May 2024

Figures & Tables

Table 1

Unique and unmet challenges associated with pulmonary embolism.

  • Awareness, detection, and diagnosis

  • Rapid notification and mobilization of the institutional PERT

  • Risk stratification (integration of all data to estimate relative risk of morbidity/mortality

  • Determination of optimal therapy

  • Monitoring progress during/after intervention and establishing disposition

  • Ascertaining risk of long-term consequences

  • Expansion of evidence base

Figure 1

Saddle embolism in Viz.ai app.

Table 2

Time to triage. AI: artificial intelligence; PERT: pulmonary embolism response team

COHORTPRE-AI (n = 22)POST-AI (n = 29)POST-AI NON-PERT (n = 20)POST-AI PERT ACTIVATION (n = 9)
Time-to-consult240.45 min
(SD = 320.248)
6.72 min
(SD 2.671)
Time-to-rad30.45 min
(SD = 22.211)
105.34 min
(SD = 109.841)
139.30 min
(SD = 116.9)
29.89 min
(SD = 21.038)
Table 3

Patient and pulmonary embolism characteristics. artificial intelligence; BMI: body mass index; VTE: venous thromboembolism; PE: pulmonary embolism; RV/LV: right ventricular/left ventricular

CHARACTERISTICPRE-AI (n = 22)POST-AI (n = 29)
Sex (% female)45.4% (10/22)55.2% (16/29)
Mean age (years)57.5567.76
Sedentary lifestyle54.5% (12/22)51.7% (15/29)
Recent long-distance travel13.6% (3/22)17.2% (5/29)
History of obesity(BMI > 30)63.6% (14/22)44.8% (13/29)
Prior VTE36.4% (8/22)20.7% (6/29)
Prior cancer diagnosis13.6% (3/22)20.7% (6/29)
Recent surgery22.7% (5/22)17.2% (5/29)
Prior thrombophilia9% (2/22)0% (0/29)
Use of hormone replacement4.5% (1/22)6.9% (2/29)
Centrally located PE86.4% (19/22)72.4% (21/29)
RV/LV ratio ≥ 1.559% (13/22)48.3% (14/29)
Intervention performed100% (22/22)41.4% (12/29)
Figure 2

Specialist communication platform.

Table 4

Patient characteristics. AI: artificial intelligence; BMI: body mass index; VTE: venous thromboembolism; PE: pulmonary embolism; RV/LV: right ventricular/left ventricular

CHARACTERISTICPRE-AI (N = 113)POST-AI (N = 45)
Sex (% female)61 (53.9%)25 (55.5%)
Mean age (years)60.165.3
Sedentary lifestyle48 (42.4%)24 (53.3%)
Recent long distance travel14 (12.3%)9 (20%)
History of obesity(BMI > 30)66 (58.4%)25 (55.5%)
Prior VTE28 (24.7%)8 (17.7%)
Prior cancer diagnosis19 (16.8%)9 (20%)
Recent surgery28 (24.7%)8 (17.7%)
Prior thrombophilia8 (7.1%)0 (0%)
Use of hormone replacement16 (14.1%)4 (8.8%)
Centrally located PE96 (86.7%)35 (77.7%)
RV/LV ratio ≥ 1.573 (64.6%)26 (57.7%)
Table 5

Pre-AI versus post-AI time to assessment. AI: artificial intelligence; PERT: pulmonary embolism response team

PRE-AIPOST-AIP VALUE
Time-to-assessment318.42 min (SD 339.99)5.47 min (SD 2.67)P < .001
In-hospital mortalities10 (8.8%)1 (2.2%)
With PERTWithout PERT
Time-to-anticoagulation83.17 min (SD 61.32)164.96 min (SD 82.88)P = .005
In-hospital mortalities101
DOI: https://doi.org/10.14797/mdcvj.1342 | Journal eISSN: 1947-6108
Language: English
Page range: 5 - 12
Submitted on: Jan 13, 2024
Accepted on: Apr 11, 2024
Published on: May 16, 2024
Published by: Houston Methodist DeBakey Heart & Vascular Center
In partnership with: Paradigm Publishing Services

© 2024 Jacob Shapiro, Adam Reichard, Patrick E. Muck, published by Houston Methodist DeBakey Heart & Vascular Center
This work is licensed under the Creative Commons Attribution-NonCommercial 4.0 License.