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Year : 2021  |  Volume : 24  |  Issue : 11  |  Page : 1682-1688

Changes in stroke volume variation and cardiac index during open major bowel surgery

1 Department of Physiology, Melaka Manipal Medical College (Manipal campus), Manipal Academy of Higher Education, Manipal, Karnataka, India
2 Department of Anaesthesiology, Kasturba Medical College, Manipal Academy of Higher Education, Manipal, Karnataka, India

Date of Submission23-Jan-2020
Date of Acceptance16-Apr-2021
Date of Web Publication15-Nov-2021

Correspondence Address:
Dr. A Nileshwar
Department of Anaesthesiology, Kasturba Medical College, Manipal Academy of Higher Education, Manipal, Karnataka
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/njcp.njcp_30_20

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Background: Stroke volume variation (SVV) is a dynamic indicator of preload, which is a determinant of cardiac output. Aims: Aim of this study was to evaluate the relationship between changes in SVV and cardiac index (CI) in patients with normal left ventricular function undergoing major open abdominal surgery. Patients and Methods: Patients undergoing major open abdominal surgery were monitored continuously with FloTrac® to measure SVV and CI along with standard monitoring. Both SVV and CI were noted at baseline and every 10 min thereafter till the end of surgery and were observed for concurrence between the measurements. Results: 1800 pairs of measurement of SVV and CI were obtained from 60 patients. Mean SVV and CI (of all patients) measured at different time points of measurement showed that as SVV increased with time, the CI dropped correspondingly. When individual readings of CI and SVV were plotted against each other, the scatter was found to be wide, reiterating the lack of agreement between the two parameters (R2 = 0.035). SVV >13% suggesting hypovolemia was found at 207 time points. Of these, 175 had a CI >2.5 L/min/m2 and only 32 patients had a CI <2.5 L/min/m2. Conclusion: SVV, a dynamic index of fluid responsiveness can be used to monitor patients expected to have large fluid shifts during major abdominal surgery. It is very specific and has a high negative predictive value. When SVV increases, CI is usually maintained. Since many factors affect SVV and CI, any increase in SVV >13%, must be correlated with other parameters before administration of the fluid challenge.

Keywords: Cardiac index, fluid requirement, major bowel surgery, stroke volume variation

How to cite this article:
Prabhu S P, Nileshwar A, Krishna H M, Prabhu M. Changes in stroke volume variation and cardiac index during open major bowel surgery. Niger J Clin Pract 2021;24:1682-8

How to cite this URL:
Prabhu S P, Nileshwar A, Krishna H M, Prabhu M. Changes in stroke volume variation and cardiac index during open major bowel surgery. Niger J Clin Pract [serial online] 2021 [cited 2023 Jan 26];24:1682-8. Available from:

   Introduction Top

Accurate assessment of fluid status of a patient is required to achieve hemodynamic stability and adequate tissue perfusion to reduce the risk of postoperative complications.[1] Fluid overload is associated with higher rates of morbidity and mortality.[2] Inadequate fluid replacement can lead to prerenal failure.

Clinicians are often challenged with imprecise, nonspecific information to guide fluid therapy. Dynamic indicators of fluid responsiveness such as stroke volume variation (SVV), cardiac index (CI), pulse pressure variation (PPV) are preferred over static indices such as central venous pressure and pulmonary capillary wedge pressure.[3],[4]

The aim of this study was to evaluate the relationship between changes in SVV and CI in patients with normal left ventricular function undergoing major open abdominal surgery.

   Subjects and Methods Top

This prospective study was conducted after obtaining approval from the Institutional Ethics Committee (IEC: 463/2012). The procedures followed were in accordance with the ethical standards of the responsible committee on human experimentation (institutional) and with the Helsinki Declaration of 1975, as revised in 2000. Informed consent was obtained from the research participants. Confidentiality of subjects was also maintained. The trial was registered with the National Clinical Trial Registry of India (CTRI/2018/04/013016). Sixty patients undergoing elective major bowel surgery such as gastrectomy, Whipple's procedure, abdominoperineal resection, anterior resection, sigmoid colectomy, and hemicolectomy were enrolled. Patients aged between 18 and 70 years, of either gender, belonging to ASA I and II physical status requiring invasive arterial pressure monitoring in view of the extensive surgery were enrolled. Patients undergoing laparoscopic surgery were excluded. Laparotomy followed by simple colostomy or jejunostomy was also excluded from the study.

Bowel preparation was done as per surgeon's instructions on the day prior to surgery. All patients were seen by an anesthesia postgraduate a day prior to surgery and they underwent routine preoperative assessment. All patients received Tab Alprazolam 0.25 mg and Tab Pantoprazole 40 mg, the night prior and on the morning of surgery. They were kept fasting as per standard “nil per oral” guidelines.

In the operating room, a patent peripheral intravenous access (18 G or larger) was secured. Preinduction monitoring included pulse oximetry, noninvasive blood pressure and electrocardiogram (Lead II and V5). Postinduction monitoring included capnography, anesthetic agent analyzer (to maintain a minimum alveolar concentration [MAC] of 1–1.3), invasive arterial blood pressure (radial arterial line), urinary catheter, and nasopharyngeal temperature.

All patients received general anesthesia. The decision to use thoracic epidural in addition to general anesthesia was left to the discretion of the consultant anesthetist. After preoxygenation, anesthesia was induced with 2–2.5 mg/kg of propofol and 2 μg/kg of fentanyl followed by neuromuscular blockade with vecuronium 0.1 mg/kg, (succinylcholine 1.5 mg/kg if rapid sequence induction was required). After laryngoscopy and endotracheal intubation, anesthesia was maintained using isoflurane in a mixture of nitrous oxide and oxygen. All patients were ventilated with a tidal volume of 8 mL/kg and at a rate required to maintain normocarbia. Analgesia and titration of anesthetic were done by the anesthetist in charge of the patient.

After induction of anesthesia, a radial arterial line (20 G) was secured for continuous monitoring of arterial blood pressure. The FloTrac sensor was attached to the arterial line and connected to the Vigileo monitor (Edwards Lifesciences, Irvine, California, USA) [Figure 1]. The Vigileo monitor is a very user-friendly device available at our center. The monitor costs about INR 4 lakhs and the transducer INR 10,000. It is used for monitoring dynamic indices in adults with regular cardiac rhythm. Since it is more expensive than a regular arterial pressure transducer, it is used only in patients who undergo major surgical procedures and in hemodynamically unstable patients who need advanced monitoring.
Figure 1: The FloTrac Vigileo monitor

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Once patient data such as age, sex, height, and weight were entered, the system computed stroke volume from the patient's arterial pressure signal and displayed CI and SVV continuously. The baseline readings of SVV and CI were noted. Thereafter, patients were monitored continuously with the FloTrac® (Version 3) in addition to standard monitoring. The readings of SVV and CI were noted every 10 min throughout the surgery.

The baseline fluid therapy was given at a rate of 2 mL/kg/h for maintenance. At the beginning of surgery irrespective of variation of SVV and CI, 200 mL of colloid (6% hydroxyethyl starch) was given over a period of 10 min. Subsequently, additional fluid therapy was guided by SVV as shown by FloTrac®. If the stroke volume variation showed 13% or more, consistently over a period of five minutes, an additional bolus of 200 mL of colloid was given over the next 10 min. The trends were observed and if the stroke volume variation was reducing or if it were less than 13%, no more bolus of fluid was given. If SVV was found to be consistently increasing, the process was repeated until the stroke volume variation was within 13%. Colloid was given as required up to a maximum of 20 mL/kg beyond which fluid boluses were given using Ringer lactate.

Since SVV measured by FloTrac was well-established, these measurements were followed for any decision on fluid therapy. The CI at each of these time points was observed to see whether there was any correlation between the measurements.

Maximum allowable blood loss was calculated as follows:

Where Average hemoglobin (g%) = [(Preoperative Hb + Target Hb)/2]

Allowable blood loss was replaced with colloids (hydroxyethyl starch) up to 20 mL/kg including the fluid boluses given during the procedure. Blood loss exceeding the allowable amount was replaced with packed red cells and fresh frozen plasma when required. Use of inotropes or vasopressors was left at the discretion of the attending anaesthesiologist.

Statistical analysis was performed using the SPSS 16.0 software. Values of continuous data are presented as mean (SD) or median (interquartile range) depending on the skewness of the data; categorical variables are displayed as frequency distributions (n). Mean variation of SVV and CI were plotted. Individual points of SVV and CI were plotted to see the correlation between the two. Sensitivity and specificity of SVV with respect to CI were calculated. Box plots were constructed to compare the trends of SVV and CI in response to volume.

   Results Top

The demographic data are shown in [Table 1]. The surgical procedures and their duration are given in [Table 2]. A total of 1800 pairs of measurements were obtained from sixty patients. [Figure 2] shows the mean SVV and CI (of all patients) measured at different time points of measurement (0 min, 10 min, 20 min, and so on) against time. It can be seen from the graph that changes in SVV were actually mirrored by changes in CI. Also, SVV increased with time and the CI dropped correspondingly. At the beginning and at the end of the surgery, SVV was lower and CI was higher.
Table 1: Demographic data of patients

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Table 2: Duration of surgery and surgical procedures

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Figure 2: Comparison of mean variation as measured by stroke volume variation (SVV) and Cardiac index (CI) with respect to time

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When individual readings of CI and SVV were plotted against each other, however, the scatter was found to be wide, reiterating lack of agreement between the two parameters (R2 = 0.035) [Figure 3]. Two (dotted) lines were drawn on the graph, one parallel to Y-axis, corresponding to an SVV of 13%, and the other, parallel to X-axis, corresponding to a CI of 2.5 L/min/m2, indicating clinically acceptable values. These lines divide the observations into four boxes [Figure 3]. The boxes are labeled Box 1, Box 2, Box 3, and Box 4. Box 1, labeled “normal,” corresponded to those patients whose SVV was <13% and CI was >2.5 L/min/m2. Out of the 1800 points, 1524 were in Box 1 (normal). Box 2, indicating reduced contractility had 69 observations where SVV was <13% but CI was also <2.5 L/min/m2. SVV >13% suggesting hypovolemia was found at 207 observations. Of these, 175 had a CI of >2.5 L/min/m2 (Box 3—Compensated) and only 32 points had a CI of <2.5 L/min/m2 (Box 4—Uncompensated).
Figure 3: Correlation between individual points of SVV and CI

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ROC curve was generated for CI and SVV [Figure 4]. The area under the ROC (AUROC) curve was 0.66. The two parameters do not have sufficient correlation between them. The sensitivity and specificity of SVV >13% as a surrogate index of the reduced CI was 32% and 89%, respectively [Table 3]. The positive predictive value was 15% whereas the negative predictive value was 95%.
Figure 4: Receiver operating characteristic curve for SVV and CI

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Table 3: Sensitivity and Specificity between SVV and CI

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[Figure 5] shows Box plot to compare the trends of SVV and CI in response to volume. Although SVV decreased and CI increased within 10 min after fluid challenge, 15–20 min elapsed before the parameters returned to normal.
Figure 5: Box plot to compare the trends of SVV and CI in response to volume

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   Discussion Top

Assessment of the adequacy of the intravascular volume is of prime importance to avoid hypovolemia and tissue hypoperfusion.[1] Most of the dynamic variables assessing fluid responsiveness are invasive, technically challenging, or require additional catheters. Several studies demonstrated the value of FloTrac-derived SVV in predicting fluid responsiveness in various clinical settings.[5],[6],[7] Many studies have shown that such an approach is associated with better intraoperative hemodynamic stability, reduced length of hospital stay, ICU admission, and costs, faster return of bowel movement and fewer complications.[8],[9],[10],[11],[12],[13],[14] Also, goal-directed fluid therapy was shown to be safe and significantly reduced the volume of intraoperative resuscitation in patients undergoing liver resection and orthopedic surgery.[15],[16] Current clinical investigations indicated positive effects of stroke volume optimization.[17],[18] There is evidence that SVV and pulse pressure variation are good indicators of fluid responsiveness in mechanically ventilated patients without cardiac arrhythmias.[19]

This study evaluated the effectiveness of SVV and CI using FloTrac® which applies a minimally invasive technique to study the relationship between changes in SVV and CI in patients with normal left ventricular function (as shown by the preoperative transthoracic echocardiogram) undergoing major open abdominal surgery.

ROC analysis of SVV in different studies showed largely a good prediction of fluid responsiveness, and SVV threshold values ranged from 10% to 13%.[20] A meta-analysis that included 22 studies and 807 patients reported a pooled sensitivity for predicting fluid responsiveness of 88% with a specificity of 89%. The median threshold of the PPV was 12% (interquartile range = 10–13%).[21]

Therefore, in our study, SVV was targeted to predict fluid requirement with the threshold of 13%. Also, in most studies with respect to SVV and CI, boluses of fluid were given and the responses were measured.[22],[23] In our study, measurements were followed by fluid boluses, if there was a suggestion of hypovolemia.

Stroke volume variation is a measure of change in stroke volume that occurs with a change in intrathoracic pressure during respiration. With controlled mechanical ventilation, the stroke volume increases with inspiration and decreases during expiration. The percentage change during the most recent 20 s is measured and displayed as SVV. It is calculated using the following formula

SVV = (SV max – SV min)/SV mean × 100.

These cyclic variations in SV are physiologically observed in all patients, but are much wider in hypovolemic states, as their amplitude is predictive of fluid responsiveness. During hypovolemia, the variations of SVV/PPV are more distinct and the variation drops if the intravascular volume is restored, and it has been shown to reliably predict changes in CO.

During mechanical ventilation, variations in stroke volumes have been used as predictors of fluid responsiveness. Mechanical ventilation induces cyclic variations in cardiac preload, which is reflected in the cyclic changes in arterial pulse pressure, systolic arterial pressure, and left ventricular stroke volume.[24] While cyclical changes associated with ventilation do not produce changes in cardiac output in adequately filled patients, it can cause significant changes with hypovolemia.[24] Essentially, patients with wide variations in the stroke volume will be on the steep portion of Frank Starling's curve that plots the effects of preload on the stroke volume.

Cardiac output is a product of stroke volume and heart rate. The stroke volume is determined by preload, contractility, and afterload. We had enrolled only patients with normal left ventricular function undergoing prolonged open bowel surgery. Of the 1800 time points of simultaneous measurement of SVV and CI, there were 1524 points (88.5% of all time points) where SVV was <13% and CI >2.5 L/min/m2. At these points, the physiology of the patients could be considered normal and did not need intervention. Only 2% (69 time points) was seen to have a CI <2.5 L/min/m2. The anesthetic used in these patients was not expected to depress the myocardial contractility significantly. Isoflurane produces more vasodilatation than myocardial depression. These 69 time points were seen in 18 patients. Their baseline cardiac function was normal. Intraoperatively, the heart rate and blood pressure were within normal limits. The CI ranged between 1.4 and 2.4 L/min/m2 at these time points. Even in these patients, the CI was low only transiently and improved to normal by the end of surgery.

At the 207 time points where SVV was >13% signifying hypovolemia, at 175 time points, the CI was normal or high. In patients with normal left ventricular function, a rise in SVV is expected to reflect as a drop in CI. This could be explained by the compensation that occurs in response to a decrease in preload with sympathetic activation. Moreover, the stress response of surgery contributing to changes in cardiac output must also be considered. Interestingly, in most of the patients, heart rate and blood pressure were stable. The compensation must have been more in the form of increased systemic vascular resistance or increased contractility. Hence, at 45 time points from this group, the fluid challenge was given even though CI was >2.5 mL/min/m. 2 These patients were undergoing major surgery such as Whipple's procedure (14 patients), abdominoperineal resection (4 patients), hemicolectomy (3 patients), and the blood loss was between 1200 and 3000 mL. Colloids were given up to a maximum of 20 mL/kg as required beyond which blood loss was replaced with packed cell or fresh frozen plasma.

There were only 32 time points (in 12 patients) out of a total of 207 where the SVV was >13%, that the CI <2.5 L/min/m2 suggesting uncompensated hypovolemia. Thus, 85% of the time, the patients maintained their cardiac output even though there was hypovolemia.

Krisztián Tánczos et al.[25] in their very elegant animal experiments showed how SVV must be used to decide on volume requirement rather than CI. Significant hypovolemia can be masked by an increase in CI. However, fluid responsiveness alone does not indicate whether fluids are needed. Patients should not receive fluids only because of a high SVV value. This concept has been stressed in a review by Bennett and Cecconi.[26]

The slope of the Frank-Starling curve increases or decreases depending on cardiac contractility.[27] Therefore, physicians would need a reliable measure to distinguish those two types of patient populations to avoid any consequence of fluid excess. Shah et al.[28] compared cardiac output monitoring using Vigileo™ and a new smartphone-based application Capstesia™. They concluded that Capstesia™ is a reliable and feasible alternative to Vigileo monitor for intraoperative cardiac output monitoring in oncosurgical patients. Toyama et al.[29] opined that goal-directed fluid therapy with SVV has no greater effect when compared to liberal fluid therapy. However, goal-directed therapy using SVV along with other parameters could benefit the postoperative outcomes.

Maintenance of global indices of perfusion may not reflect perfusion in the peripheral tissues. Future research could be targeted at the evaluation of monitors of microcirculation during prolonged surgery and large fluid shifts.

   Conclusion Top

Changes in SVV and CI although seem largely reciprocal, the relationship between them is very varied. An increase in SVV is usually associated with normal or increased CI probably due to compensatory mechanisms. A decreased CI is more often associated with low SVV, suggesting impaired contractility rather than hypovolaemia. The response to volume infusion can be much more varied with SVV as compared to CI. SVV is very specific and has a high negative predictive value. Since many factors affect SVV and CI, any increase in SVV >13%, must also be correlated with other clinical and monitoring parameters before administration of the fluid challenge.


We would like to thank Dr. Asha Kamath, Professor, and Head, Department of Data Science and Associate Director, PSPH, MAHE. Manipal for the statistical guidance.

Financial support and sponsorship


Conflicts of interest

There are no conflicts of interest.

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  [Figure 1], [Figure 2], [Figure 3], [Figure 4], [Figure 5]

  [Table 1], [Table 2], [Table 3]

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