Abstract
Introduction Chronic thromboembolic pulmonary hypertension (CTEPH) is often diagnosed late in acute pulmonary embolism survivors: more efficient testing to expedite diagnosis may considerably improve patient outcomes. The InShape II algorithm safely rules out CTEPH (failure rate 0.29%) while requiring echocardiography in only 19% of patients but may be improved by adding detailed reading of the computed tomography pulmonary angiography diagnosing the index pulmonary embolism. Methods We evaluated 12 new algorithms, incorporating the CTEPH prediction score, ECG reading, N‑terminal pro-brain natriuretic peptide levels and dedicated computed tomography pulmonary angiography reading, in the international InShape II cohort (n=341) and part of the German FOCUS cohort (n=171). Evaluation criteria included failure rate, defined as the incidence of confirmed CTEPH in pulmonary embolism patients in whom echocardiography was deemed unnecessary by the algorithm, and the overall net reclassification index compared to the InShape II algorithm. Results The algorithm starting with computed tomography pulmonary angiography reading of the index pulmonary embolism for six signs of CTEPH, followed by ECG/N-terminal pro-brain natriuretic peptide level assessment and echocardiography resulted in the most beneficial change compared to InShape II, with a need for echocardiography in 20% (+5%), a failure rate of 0% and a net reclassification index of +3.5%, reflecting improved performance over the InShape II algorithm. In the FOCUS cohort, this approach lowered echocardiography need to 24% (−6%) and missed no CTEPH cases, with a net reclassification index of +6.0%. Conclusion Dedicated computed tomography pulmonary angiography reading of the index pulmonary embolism improved the performance of the InShape II algorithm and may improve the selection of pulmonary embolism survivors who require echocardiography to rule out CTEPH.
| Original language | English |
|---|---|
| Article number | 2400544 |
| Journal | European respiratory journal |
| Volume | 64 |
| Issue number | 4 |
| DOIs | |
| Publication status | Published - 1 Oct 2024 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
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