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      Efficacy of Stroke Volume Variation, Cardiac Output and Cardiac Index as Predictors of Fluid Responsiveness using Minimally Invasive Vigileo Device in Intracranial Surgeries

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          Functional hemodynamic monitoring using dynamic parameters such as stroke volume variations (SVVs) based on pulse contour analysis is considered more accurate than central venous pressure and mean arterial pressure (MAP) in predicting fluid responsiveness. New device, i.e., Vigileo system, allows automatic and continuous monitoring of cardiac output (CO) based on pulse contour analysis and respiratory stroke volume.


          The study aims to test the above hypothesis using graded volume loading step (VLS) to assess the accuracy of SVV as a predictor of fluid responsiveness in patients undergoing intracranial surgery.

          Materials and Methods:

          After taking ethical committee approval and informed consent, 60 patients aged between 18 and 55 years belonging to the American Society of Anesthesiologists physical status Class I and II, of either sex, scheduled for brain surgery were included in the study. In this study, 5 min after intubation, with stable hemodynamics, patients received volume loading in successive steps (VLS) of 200 ml of lactated Ringer's solution until the stroke volume increased to <10%. Blood pressure (BP), heart rate (HR), stroke volume (SV), and SVV were measured before and after each VLS. Optimal preload augmentation required by each patient was measured by the number of VLS after which an increase in SV was <10%.


          There was a significant decrease in the baseline BP and SV in responsive and nonresponsive groups for the first VLS, but there is no change in HR statistically. There was a significant change in SV after first VLS. Receiver operating characteristic analysis showed a larger area under the curve of 0.758 for SVV compared to other measured variables. The median number of VLS administered were 2 per patient equating to a mean ± SD requirement of 368 ± 176 ml of crystalloid per patient as the optimal preoperative infusion volume.


          SVV is a better predictor of preload responsiveness measured with third-generation Vigileo device when compared to BP and HR.

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          Most cited references 28

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          Does central venous pressure predict fluid responsiveness? A systematic review of the literature and the tale of seven mares.

          Central venous pressure (CVP) is used almost universally to guide fluid therapy in hospitalized patients. Both historical and recent data suggest that this approach may be flawed. A systematic review of the literature to determine the following: (1) the relationship between CVP and blood volume, (2) the ability of CVP to predict fluid responsiveness, and (3) the ability of the change in CVP (DeltaCVP) to predict fluid responsiveness. MEDLINE, Embase, Cochrane Register of Controlled Trials, and citation review of relevant primary and review articles. Reported clinical trials that evaluated either the relationship between CVP and blood volume or reported the associated between CVP/DeltaCVP and the change in stroke volume/cardiac index following a fluid challenge. From 213 articles screened, 24 studies met our inclusion criteria and were included for data extraction. The studies included human adult subjects, healthy control subjects, and ICU and operating room patients. Data were abstracted on study design, study size, study setting, patient population, correlation coefficient between CVP and blood volume, correlation coefficient (or receive operator characteristic [ROC]) between CVP/DeltaCVP and change in stroke index/cardiac index, percentage of patients who responded to a fluid challenge, and baseline CVP of the fluid responders and nonresponders. Metaanalytic techniques were used to pool data. The 24 studies included 803 patients; 5 studies compared CVP with measured circulating blood volume, while 19 studies determined the relationship between CVP/DeltaCVP and change in cardiac performance following a fluid challenge. The pooled correlation coefficient between CVP and measured blood volume was 0.16 (95% confidence interval [CI], 0.03 to 0.28). Overall, 56+/-16% of the patients included in this review responded to a fluid challenge. The pooled correlation coefficient between baseline CVP and change in stroke index/cardiac index was 0.18 (95% CI, 0.08 to 0.28). The pooled area under the ROC curve was 0.56 (95% CI, 0.51 to 0.61). The pooled correlation between DeltaCVP and change in stroke index/cardiac index was 0.11 (95% CI, 0.015 to 0.21). Baseline CVP was 8.7+/-2.32 mm Hg [mean+/-SD] in the responders as compared to 9.7+/-2.2 mm Hg in nonresponders (not significant). This systematic review demonstrated a very poor relationship between CVP and blood volume as well as the inability of CVP/DeltaCVP to predict the hemodynamic response to a fluid challenge. CVP should not be used to make clinical decisions regarding fluid management.
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            Changes in arterial pressure during mechanical ventilation.

            Mechanical ventilation induces cyclic changes in vena cava blood flow, pulmonary artery blood flow, and aortic blood flow. At the bedside, respiratory changes in aortic blood flow are reflected by "swings" in blood pressure whose magnitude is highly dependent on volume status. During the past few years, many studies have demonstrated that arterial pressure variation is neither an indicator of blood volume nor a marker of cardiac preload but a predictor of fluid responsiveness. That is, these studies have demonstrated the value of this physical sign in answering one of the most common clinical questions, Can we use fluid to improve hemodynamics?, while static indicators of cardiac preload (cardiac filling pressures but also cardiac dimensions) are frequently unable to correctly answer this crucial question. The reliable analysis of respiratory changes in arterial pressure is possible in most patients undergoing surgery and in critically ill patients who are sedated and mechanically ventilated with conventional tidal volumes.
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              Pathophysiology and clinical implications of perioperative fluid excess.

               K Holte,  N Sharrock,  H Kehlet (2002)

                Author and article information

                Anesth Essays Res
                Anesth Essays Res
                Anesthesia, Essays and Researches
                Wolters Kluwer - Medknow (India )
                Apr-Jun 2019
                : 13
                : 2
                : 248-253
                Department of Anaesthesiology, Siddhartha Medical College, Vijayawada, Andhra Pradesh, India
                Author notes
                Address for correspondence: Dr. Santhi Sree Mulam, Dr. No. 13-2-2, D1 Apt, Sai Krishna Towers, Latchiraju Street, Opp NGO Home, Suryaraopeta, Kakinada - 533 002, Andhra Pradesh, India. E-mail: santhisreemulam@
                Copyright: © 2019 Anesthesia: Essays and Researches

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