Estimation of shunt fraction by transesophageal echocardiography during one-lung ventilation

Verfasser / Beitragende:
[Miao Wang, Quan Gong, Wei Wei]
Ort, Verlag, Jahr:
2015
Enthalten in:
Journal of Clinical Monitoring and Computing, 29/2(2015-04-01), 307-311
Format:
Artikel (online)
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024 7 0 |a 10.1007/s10877-014-9606-2  |2 doi 
035 |a (NATIONALLICENCE)springer-10.1007/s10877-014-9606-2 
245 0 0 |a Estimation of shunt fraction by transesophageal echocardiography during one-lung ventilation  |h [Elektronische Daten]  |c [Miao Wang, Quan Gong, Wei Wei] 
520 3 |a As the blood flow volume in non-dependent lung composed the primary part of the intrapulmonary shunt during one-lung ventilation (OLV), the shunt fraction (SF) during OLV can be represented by the ratio of blood flow volume in non-dependent lung to the bilateral lung. The purpose of this study is to estimate the shunt in non-dependent lung by transesophageal echocardiography (TEE). Fifteen adult patients requiring OLV for thoracic surgery were enrolled in the study. The upper pulmonary venous flow pattern in bilateral lung and main pulmonary artery flow pattern were acquired respectively by TEE for their velocity time integral (VTI) measurements in following time intervals: before OLV (T0), 30min after OLV (T30) and 60min after OLV (T60). Simultaneously the arterial blood was sampled for gas analysis. SF was calculated by VTI of bilateral upper pulmonary veins, and percentage change of blood flow (BFP) was the ratio of upper pulmonary venous VTI between in OLV period and before OLV in non-dependent lung. There was significant decrease in PaO2 and increase in cardiac output after OLV. The pulmonary blood flow in non-dependent lung decreased significantly compared with T0, and SF was 37.1±8.3 and 35.2±7.2% respectively at T30 and T60. There was significant liner correlation between SF and PaO2 (r=0.717), and between BFP and PaO2 (r=0.593). It is feasible to estimate intrapulmonary shunt by TEE in anesthetized patients undergoing OLV. SF measured by TEE has significant correlation with PaO2, and it wouldexpected to be used to predict hypoxemia during OLV. 
540 |a Springer Science+Business Media New York, 2014 
690 7 |a Transesophageal echocardiography  |2 nationallicence 
690 7 |a Shunt fraction  |2 nationallicence 
690 7 |a Pulmonary blood flow  |2 nationallicence 
690 7 |a One-lung ventilation  |2 nationallicence 
700 1 |a Wang  |D Miao  |u Department of Anesthesiology, West China Hospital, Sichuan University, No 37, Guo-xue-xiang Street, 610041, Chengdu, Sichuan, China  |4 aut 
700 1 |a Gong  |D Quan  |u Department of Orthopedics, West China Hospital, Sichuan University, 610041, Chengdu, Sichuan, China  |4 aut 
700 1 |a Wei  |D Wei  |u Department of Anesthesiology, West China Hospital, Sichuan University, No 37, Guo-xue-xiang Street, 610041, Chengdu, Sichuan, China  |4 aut 
773 0 |t Journal of Clinical Monitoring and Computing  |d Springer Netherlands  |g 29/2(2015-04-01), 307-311  |x 1387-1307  |q 29:2<307  |1 2015  |2 29  |o 10877 
856 4 0 |u https://doi.org/10.1007/s10877-014-9606-2  |q text/html  |z Onlinezugriff via DOI 
898 |a BK010053  |b XK010053  |c XK010000 
900 7 |a Metadata rights reserved  |b Springer special CC-BY-NC licence  |2 nationallicence 
908 |D 1  |a research-article  |2 jats 
949 |B NATIONALLICENCE  |F NATIONALLICENCE  |b NL-springer 
950 |B NATIONALLICENCE  |P 856  |E 40  |u https://doi.org/10.1007/s10877-014-9606-2  |q text/html  |z Onlinezugriff via DOI 
950 |B NATIONALLICENCE  |P 700  |E 1-  |a Wang  |D Miao  |u Department of Anesthesiology, West China Hospital, Sichuan University, No 37, Guo-xue-xiang Street, 610041, Chengdu, Sichuan, China  |4 aut 
950 |B NATIONALLICENCE  |P 700  |E 1-  |a Gong  |D Quan  |u Department of Orthopedics, West China Hospital, Sichuan University, 610041, Chengdu, Sichuan, China  |4 aut 
950 |B NATIONALLICENCE  |P 700  |E 1-  |a Wei  |D Wei  |u Department of Anesthesiology, West China Hospital, Sichuan University, No 37, Guo-xue-xiang Street, 610041, Chengdu, Sichuan, China  |4 aut 
950 |B NATIONALLICENCE  |P 773  |E 0-  |t Journal of Clinical Monitoring and Computing  |d Springer Netherlands  |g 29/2(2015-04-01), 307-311  |x 1387-1307  |q 29:2<307  |1 2015  |2 29  |o 10877