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논문 기본 정보

자료유형
학술저널
저자정보
Sharma Vibhuti (Department of Anaesthesia, Indira Gandhi Medical College Shimla) Sharma Arti (Department of Anaesthesia, Indra Gandhi Medical College, Shimla, India) Sethi Arvind (Department of Anaesthesia, Indira Gandhi Medical College Shimla) Pathania Jyoti (Department of Anaesthesia, Indra Gandhi Medical College, Shimla, India)
저널정보
대한중환자의학회 Acute and Critical Care Acute and Critical Care Vol.39 No.1
발행연도
2024.2
수록면
117 - 126 (10page)
DOI
10.4266/acc.2023.00913

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Background: Point of care ultrasound (POCUS) is being explored for dynamic measurements like inferior vena cava collapsibility index (IVC-CI) and left ventricular outflow tract velocity time integral (LVOT-VTI) to guide anesthesiologists in predicting fluid responsiveness in the preoperative period and in treating post-induction hypotension (PIH) with varying accuracy.Methods: In this prospective, observational study on included 100 adult patients undergoing elective surgery under general anesthesia, the LVOT-VTI and IVC-CI measurements were performed in the preoperative room 15 minutes prior to surgery, and PIH was measured for 20 minutes in the post-induction period.Results: The incidence of PIH was 24%. The area under the curve, sensitivity, specificity, positive predictive value, negative predictive value, and diagnostic accuracy of the two techniques at 95% confidence interval was 0.613, 30.4%, 93.3%, 58.3%, 81.4%, 73.6% for IVC-CI and 0.853, 83.3%, 80.3%, 57.1%, 93.8%, 77.4% for LVOT -VTI, respectively. In multivariate analysis, the cutoff value for IVC-CI was >51.5 and for LVOT-VTI it was ≤17.45 for predicting PIH with odd ratio [OR] of 8.491 (P=0.025) for IVCCI and OR of 17.427 (P<0.001) for LVOT. LVOT-VTI assessment was possible in all the patients, while 10% of patients were having poor window for IVC measurements.Conclusions: We recommend the use of POCUS using LVOT-VTI or IVC-CI to predict PIH, to decrease the morbidity of patients undergoing surgery. Out of these, we recommend LVOT-VTI measurements as it has showed a better diagnostic accuracy (77.4%) with no failure rate.

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