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Clinical Science Aspects

Is the Collapsibility Index of the Inferior Vena Cava an Accurate Predictor for the Early Detection of Intravascular Volume Change?

Gui, Jianjun; Yang, Zhengfei†,‡; Ou, Bing; Xu, Anding§; Yang, Fan||; Chen, Qiaozhu||; Jiang, Longyuan; Tang, Wanchun†,‡,¶

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doi: 10.1097/SHK.0000000000000932
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The assessment of fluid responsiveness (FR) is of utmost importance for diagnostic and therapeutic management of critically ill patients, since either hypo- or hypervolemia can contribute to poor clinical outcome (1, 2). The collapsibility index (CI) of the inferior vena cava (IVC), which is evaluated by ultrasonography (US), has been used to predict FR in critical care medicine for many years, because it is noninvasive, lends a rapid diagnosis, and is inexpensive (2, 3). Many critical care units now use IVC-US instead of central venous pressure as a guide for fluid resuscitation. However, there are still many clinically relevant questions regarding the use of CI as a tool to predict FR. One concern is whether or not CI is an accurate predictor for detecting early changes in intravascular volume (IVV). The changes in IVC diameter and/or CI induced by variations in IVV have been found in patients after hemodialysis and in those with acute heart failure after dieresis (4, 5), whereas conflicting findings have been seen in trauma patients and volunteer blood donors (6–9).

The aim of this study was to explore whether or not CI is an accurate indicator for detecting early changes in IVV, as induced by passive leg raise (PLR) in healthy volunteers. Meanwhile, the capacity of CI for the prediction of early IVV change was also investigated.


Study design

This cross-sectional descriptive study was designed according to the Declaration of Helsinki II and was approved by the Medical Ethics Committee of Dongguan Kanghua Hospital.

Study setting and population

From September to December in 2015, we recruited 153 physically active, healthy volunteers over the age of 18 into this study. Participants lived in the local community, and were visiting our hospital for routine comprehensive health check-ups during the study enrollment period. The exclusion criteria included age younger than 18 years, a history of symptomatic cardiovascular or cerebrovascular disease, pregnancy, arrhythmia, cirrhosis, ascites, moderate to severe tricuspid insufficiency, and a body mass index (BMI) above 35 kg/m2. Hypertension was recorded because it has been shown to correlate with IVC diameter, according to our previous study (10). The volunteers received no remuneration for their participation. We excluded eight volunteers from the study since their IVC could not be adequately visualized, either due to obesity or bowel gas.

Study protocol

Participants were notified of the aim and procedures of this study by reading the informed consent before signing. The demographic information was recorded for every participant, including age, gender, and history of hypertension. Each subject wore light clothes without shoes during anthropometric measurements. Waist circumference was measured midway between the lower rib and the iliac crest, while the tape measure was positioned horizontally, parallel to the floor, and the subject stood erect with relaxed abdominal muscles. Blood pressure and heart rate were measured before and 2 min after PLR, using an electronic sphygmomanometer (OMRON HEM-7052) on the right arm. Hypertension was defined as systolic blood pressure ≥140 mm Hg and/or diastolic blood pressure ≥90 mm Hg at the first reading and/or having a history of hypertension. A simple approximation equation was used to estimate the mean arterial pressure, where the mean arterial pressure = diastolic pressure + (1/3) × pulse pressure. The BMI calculation was based on the formula: BMI= weight (kg)/[height (m)]2. With a nonextensible tape measure, the body surface area (BSA) was calculated using the DuBois formula: BSA = (W 0.425 × H 0.725) × 0.007184.

To achieve the same fluid status, participants were asked to fast overnight (at least 8 h) before submitting to the examination. Each volunteer underwent IVC US at baseline and 2 min after PLR during quiet passive respiration in the supine position, using a Toshiba Aplio 500 Ultrasound System (Toshiba Medical Systems Corporation, Tokyo, Japan), equipped with 3.5 MHz convex probe. The transducer was placed just inferior to the xiphoid process along the midline to obtain a long axis image of the IVC. Images were recorded in 15-s B-mode (grayscale) video clips, to ensure that they accounted for respiratory variation and were able to capture the points of maximal and minimal diameters. After the IVC video was obtained, the PLR maneuver was performed (lower limbs were lifted in a straight manner by an assistant to 45°, with the trunk and the bed remaining horizontal). After lower limbs had been lifted for 2 min, the IVC US scan was repeated. Evaluations were performed by one radiologist, Y.F., who had 9 years of experience in cardiovascular US. The measurement of IVC diameter was performed approximately 3 cm from the atrium, where the anterior and posterior walls of the IVC are easily seen and parallel to each other. The maximum and minimum IVC dimensions were detected by measuring the vein lumen at a regular breathing cycle from one interior wall to the opposite interior wall (Fig. 1). CI was calculated with the following equation (11): 

Fig. 1
Fig. 1:
A, Measurement of inferior vena cava collapsibility index (IVC-CI) before passive leg raising.

The difference in CI before and 2 min after PLR (ΔCI) was calculated with the following equation, 

Data analysis

Data are expressed as mean ± standard deviation (SD) and two SD ranges or proportions, when appropriate. The normal distribution of continuous variables was determined by histogram and the one-sample Kolmogorov–Smirnov Test. P > 0.05 was accepted as a normal distribution. The paired t test was used to compare CI, maximum IVC diameter, minimum IVC diameter, heart rate, and mean arterial pressure before and after PLR. Pearson correlation was utilized, to demonstrate potential associations with the ΔCI, and transformations were used in the analysis, as required. Multivariate linear regression (forward selection with likelihood ratio criterion for selection variables: 0.05 to enter, 0.05 to remove) was used to test the independent association of previously correlated variables with the ΔCI. All statistical analyses were performed using Statistical Package for Social Sciences version 19.0 (SPSS Inc, Chicago, Ill). All reported P values were two-tailed, and those < 0.05 were considered to be statistically significant.


Demographic data

The relevant individual characteristics of the 145 volunteers are shown in Table 1. Overall, the mean age was 41.3 ± 15.4 years, mean height was 162.7 ± 8.1 cm, mean weight was 56.7 ± 10.3 kg, and waist circumference was 75.0 ± 8.3 cm, (mean ± SD). The mean BMI and BSA were 22.1 ± 3.2 kg/m2 and 1.6 ± 0.2 m2, respectively (mean ± SD).

Table 1
Table 1:
Demographic characteristics of the study volunteers (n = 145)

Diameters of IVC and CI before and after PLR

The mean maximum IVC, minimum IVC, heart rate (HR), mean arterial pressure (MAP), and CI taken before and 2 min after PLR are shown in Table 2.

Table 2
Table 2:
Correlation between the baseline CI and individual characteristics

The mean maximum IVC, minimum IVC, HR, MAP, and CI taken before and 2 min after PLR were 14.9 ± 3.0 versus 16.6 ± 3.3 mm, 7.9 ± 2.6 versus 10.5 ± 2.8 mm, 75.6 ± 11.9 versus 76.0 ± 11.7 heart beats/min, 82.9 ± 8.0 versus 83.3 ± 7.8 mm Hg, and 47.1 ± 10.5% versus 37.2 ± 10.0%, respectively. Based on the results of the paired sample t test analysis at a 99% confidence level, there was a significant reduction in CI (t = 14.016, P < 0.001) and an increase in the maximum and the minimum IVC values (t = 11.623, P < 0.001; t = 19.321, P < 0.001, respectively). However, no significant differences in HR or MAP were observed before or 2 min after PLR.

There were no obvious correlations between the individual characteristics and the baseline CI (Table 3). However, significantly positive correlations were observed between the ΔCI and age, BMI, minimum IVC, and baseline CI (Table 4). The multiple linear regression analysis indicated that age (year), CI before PLR, and BMI (kg/m2) are independent variables for ΔCI (R2 = 0.320; P < 0.001, P < 0.001, P = 0.017, respectively) (Table 5).

Table 3
Table 3:
Correlation between ΔCI and individual characteristics
Table 4
Table 4:
Sonographic measurement of IVC before and 2 min after PLR
Table 5
Table 5:
Multiple linear regression analysis of the association of ΔCI with candidate individual characteristics


In the present study, we investigated the capacity of IVC to detect early changes in the IVV of healthy Chinese adult volunteers, aged 18 to 84 years (41.3 ± 15.4 years). The percentages of men and women were similar (49.7% vs. 50.3%). We found that CI significantly decreased with the increase of early IVV after 2 min PLR. However, the multivariate linear regression model revealed that its predictive capacity for increased IVV is influenced by age, BMI, and baseline CI. Interestingly, no obvious relationships were observed between the baseline CI and individual characteristics. To our knowledge, this is the first large sample study to investigate the capacity of CI to detect early changes in IVV.

The ability of CI to detect early changes in IVV has been controversial in previous studies (7, 12). Lyon et al. (7) found that both the mean maximum and minimum IVC diameters decreased by about 5 mm after a 450 mL blood donation in 31 volunteers. Although the CI has not been calculated in this study, we can deduce that it would have increased by donation, according to the CI equation. However, Resnick et al. (12) reported that there was no significant change in CI after a 500 mL blood donation in 39 volunteers. Nevertheless, different methods were applied in these two and the present studies (B-mode vs. M-mode). It is important to point out that M-mode CI measurements could potentially lead to inaccurate results, since the natural movement of the diaphragm during respiration results in the caudal displacement of the IVC; therefore, two different locations of IVC are measured during inspiration and expiration (13). In addition, volunteers involved in the former study were older than those in the latter (mean age: 49.5 years vs. 32 years). Moreover, the results of both studies were obtained by univariate analysis, while individual characteristics including age, weight, and height were not taken into account.

The results of our study indicate that age is an independent variable for ΔCI. Although age was not shown to be closely related to CI in our previous study, aging was positively correlated with the maximum and the minimum IVC diameters in adult volunteers (10). Increased age was accompanied by an increase in the resting values of the right atrium pressure (RAP) that was detected by a right heart catheterization (14). In theory, increased RAP might decrease blood return from the IVC to the right atrium. In the present study, IVV in the IVC increased after 2 min of PLR and the return of blood from the IVC to the atrium in subjects with increased age might decrease, which in turn would reduce the CI value. Kircher et al. and Ommen et al. also indicated that lower IVC-CI was correlated with higher RAP (15, 16). Therefore, these speculations could explain our results that decreasing CI after PLR is related to age.

Our present study also showed that baseline CI and BMI were independent variables for ΔCI. It is simple to understand the relationship between BMI and ΔCI, because a high BMI is associated with increased return of blood from the legs to the IVC while performing PLR (17). However, the exact mechanism of the relationship between baseline CI and ΔCI is not yet clear, although previous studies have shown that early fluid challenges in IVC-CI were associated with the lower baseline IVC-CI (18). Further study is necessary to elucidate the relationship between volume status, baseline CI, and ΔCI.

Our result that ΔCI is an indicator to detect early IVV changes is in agreement with previous studies conducted in healthy blood donors in 2013 and in 2015 (8, 19). Previous studies and our present results combine to show that IVC diameters and/or IVC-CI can detect changes in IVV (19–22). However, the influences of individual traits on the capacity to detect early IVV changes have not been taken into account in any of these other studies. Our results show that individual characteristics are closely related to the ability of CI to detect early changes in IVV. These findings suggest that we should take into account the effects of individual characteristics, especially baseline IVC-CI and age, when using US to measure IVC parameters and/or CI to monitor the volume changes in critically ill patients.

The mean value of IVC-CI was significantly reduced by PLC, suggesting that IVC-CI could reflect an early change of IVV. Nevertheless, only 121 of the volunteers (83.4%) saw a reduction in IVC-CI and only 73 (50.3%) experienced a reduction greater than 10%. We therefore inferred that IVC-CI has poor sensitivity, making it inadequate for clinical application.

There are several limitations in our study. First, the volunteers who enrolled in our study were physically active, healthy, and were visiting the Department of US for routine comprehensive health checkups. This may have led to some selection bias. Second, although the participants who suffered from moderate to severe tricuspid insufficiency were excluded from our study, mild tricuspid insufficiency was neither recorded nor analyzed.


The IVC-CI measured by ultrasound is useful for the detection of early IVV change induced by 2 min PLR. However, its ability to detect this increase in IVV is influenced by age, BMI, and baseline CI. Moreover, as a tool for detecting intravascular volume change, IVC-CI is of little value for clinical applications, due to its poor sensitivity.


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Collapsibility index; inferior vena cava; intravascular volume; passive leg raise

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