| Literature DB >> 28647806 |
Takashi Juri1, Koichi Suehiro2, Sayaka Tsujimoto1, Shigemune Kuwata1, Akira Mukai1, Katsuaki Tanaka1, Tokuhiro Yamada1, Takashi Mori1, Kiyonobu Nishikawa1.
Abstract
This study aimed to assess the reliability of stroke volume variation (SVV) in predicting cardiac output (CO) decrease and hypotension during induction of general anesthesia. Forty-five patients undergoing abdominal surgery under general anesthesia were enrolled. Before induction of anesthesia, patients were required to maintain deep breathing (6-8 times/min), and pre-anesthetic SVV was measured for 1 min by electrical cardiometry. General anesthesia was induced with propofol, remifentanil, rocuronium, and sevoflurane. Study duration was defined from the start of fluid administration till 5 min after tracheal intubation. Blood pressure (BP) was measured every minute. Cardiac output was measured continuously by electrical cardiometry. Receiver operating characteristics (ROC) curves were made regarding the incidence of decreased CO (less than 70% of the baseline) and hypotension (mean BP <65 mmHg). The risk of developing decreased CO and hypotension was evaluated by multivariate logistic regression analysis. The time from the start of the procedure to onset of decreased CO was analyzed by the Kaplan-Meier method. The area under the ROC curve and optimal threshold value of pre-anesthetic SVV for predicting decreased CO and hypotension were 0.857 and 0.693. Patients with lower SVV exhibited a significantly slower onset and lower incidence of decreased CO than those with higher SVV (p = 0.003). Multivariate logistic regression analysis indicated high pre-anesthetic SVV as being an independent risk factor for decreased CO and hypotension (odds ratio, 1.43 and 1.16, respectively). In conclusions, pre-anesthetic SVV can predict incidence of decreased CO and hypotension during induction of general anesthesia.Entities:
Keywords: Anesthesia induction; Cardiac output; Hemodynamic management; Stroke volume variation
Mesh:
Substances:
Year: 2017 PMID: 28647806 DOI: 10.1007/s10877-017-0038-7
Source DB: PubMed Journal: J Clin Monit Comput ISSN: 1387-1307 Impact factor: 2.502