WFRF:(Rastgoo S.)
Sökning: WFRF:(Rastgoo S.) > Multiomics, virtual...
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| Fältnamn | Indikatorer | Metadata |
|---|---|---|
| 000 | 03128naa a2200445 4500 | |
| 001 | oai:prod.swepub.kib.ki.se:234008412 | |
| 003 | SwePub | |
| 008 | 240701s2021 | |||||||||||000 ||eng| | |
| 024 | 7 | a http://kipublications.ki.se/Default.aspx?queryparsed=id:2340084122 URI |
| 024 | 7 | a https://doi.org/10.2217/fca-2020-02252 DOI |
| 040 | a (SwePub)ki | |
| 041 | a engb eng | |
| 042 | 9 SwePub | |
| 072 | 7 | a ref2 swepub-contenttype |
| 072 | 7 | a art2 swepub-publicationtype |
| 100 | 1 | a Gladding, PA4 aut |
| 245 | 1 0 | a Multiomics, virtual reality and artificial intelligence in heart failure |
| 264 | 1 | b Future Medicine Ltd,c 2021 |
| 520 | a Aim: Multiomics delivers more biological insight than targeted investigations. We applied multiomics to patients with heart failure (HF) and reduced ejection fraction (HFrEF), with machine learning applied to advanced ECG (AECG) and echocardiography artificial intelligence (Echo AI). Patients & methods: In total, 46 patients with HFrEF and 20 controls underwent metabolomic profiling, including liquid/gas chromatography–mass spectrometry and solid-phase microextraction volatilomics in plasma and urine. HFrEF was defined using left ventricular (LV) global longitudinal strain, EF and N-terminal pro hormone BNP. AECG and Echo AI were performed over 5 min, with a subset of patients undergoing a virtual reality mental stress test. Results: A-ECG had similar diagnostic accuracy as N-terminal pro hormone BNP for HFrEF (area under the curve = 0.95, 95% CI: 0.85–0.99), and correlated with global longitudinal strain (r = -0.77, p < 0.0001), while Echo AI-generated measurements correlated well with manually measured LV end diastolic volume r = 0.77, LV end systolic volume r = 0.8, LVEF r = 0.71, indexed left atrium volume r = 0.71 and indexed LV mass r = 0.6, p < 0.005. AI-LVEF and other HFrEF biomarkers had a similar discrimination for HFrEF (area under the curve AI-LVEF = 0.88; 95% CI: -0.03 to 0.15; p = 0.19). Virtual reality mental stress test elicited arrhythmic biomarkers on AECG and indicated blunted autonomic responsiveness (alpha 2 of RR interval variability, p = 1 × 10-4) in HFrEF. Conclusion: Multiomics-related machine learning shows promise for the assessment of HF. | |
| 700 | 1 | a Loader, S4 aut |
| 700 | 1 | a Smith, K4 aut |
| 700 | 1 | a Zarate, E4 aut |
| 700 | 1 | a Green, S4 aut |
| 700 | 1 | a Villas-Boas, S4 aut |
| 700 | 1 | a Shepherd, P4 aut |
| 700 | 1 | a Kakadiya, P4 aut |
| 700 | 1 | a Hewitt, W4 aut |
| 700 | 1 | a Thorstensen, E4 aut |
| 700 | 1 | a Keven, C4 aut |
| 700 | 1 | a Coe, M4 aut |
| 700 | 1 | a Nakisa, B4 aut |
| 700 | 1 | a Vuong, T4 aut |
| 700 | 1 | a Rastgoo, MN4 aut |
| 700 | 1 | a Jüllig, M4 aut |
| 700 | 1 | a Starc, V4 aut |
| 700 | 1 | a Schlegel, TTu Karolinska Institutet4 aut |
| 710 | 2 | a Karolinska Institutet4 org |
| 773 | 0 | t Future cardiologyd : Future Medicine Ltdg 17:8, s. 1335-1347q 17:8<1335-1347x 1744-8298x 1479-6678 |
| 856 | 4 8 | u http://kipublications.ki.se/Default.aspx?queryparsed=id:234008412 |
| 856 | 4 8 | u https://doi.org/10.2217/fca-2020-0225 |
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- Av författaren/redakt...
- Gladding, PA
- Loader, S
- Smith, K
- Zarate, E
- Green, S
- Villas-Boas, S
- visa fler...
- Shepherd, P
- Kakadiya, P
- Hewitt, W
- Thorstensen, E
- Keven, C
- Coe, M
- Nakisa, B
- Vuong, T
- Rastgoo, MN
- Jüllig, M
- Starc, V
- Schlegel, TT
- visa färre...
- Artiklar i publikationen
- Future cardiolog ...
- Av lärosätet
- Karolinska Institutet
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