A Novel Device for the Evaluation of Hemostatic Function in Critical Care Settings

Abstract

Major surgical procedures often result in significant intra- and postoperative bleeding. The ability to identify the cause of the bleeding has the potential to reduce the transfusion of blood products and improve patient care. We present a novel device, the Quantra Hemostasis Analyzer, which has been designed for automated, rapid, near-patient monitoring of hemostasis. The Quantra is based on Sonic Estimation of Elasticity via Resonance Sonorheometry, a proprietary technology that uses ultrasound to measure clot time and clot stiffness from changes in viscoelastic properties of whole blood during coagulation. We present results of internal validation and analytical performance testing of the technology and demonstrate the ability to characterize the key functional components of hemostasis.

Conflict of interest statement

Conflicts of Interest: Elisa A. Ferrante is an employee of HemoSonics LLC.

Kiev R. Blasier is an employee of HemoSonics LLC.

Thomas B. Givens is an employee of HemoSonics LLC.

Cynthia A. Lloyd is an employee of HemoSonics LLC.

Timothy J. Fischer is an employee and shareholder of HemoSonics LLC.

Francesco Viola is an employee and shareholder of HemoSonics LLC.

Figures

Figure 1

(Left) Research Use Only (RUO) development version of the Quantra Hemostasis Analyzer. The Quantra is a fully automated instrument that requires no sample handling steps from the user. The dimensions of the instrument are comparable to those of a blood gas analyzer. (Right) RUO cartridge used with the Quantra. The cartridge uses four independent channels that are optimized to measure clot time or clot stiffness.

Figure 2

(Top panel) Typical SEER Sonorheometry shear modulus curves obtained with the Quantra Surgical Cartridge. Measurements were performed with a whole blood sample from a healthy donor spiked with 6 IU of unfractionated heparin. (Bottom panel) SEER Sonorheometry shear modulus curves obtained in the presence of low fibrinongen levels (Clauss fibrinogen of 95 mg/dl). Estimates of clot time and clot stiffness are generated from all of these curves within 15 minutes of test initiation.

Figure 3

Schematic representation of SEER Sonorheometry. The technology is composed of three fundamental steps, as represented by the three panels in this figure. First, an ultrasound pulse is transmitted in the blood sample to generate a shear wave, causing the sample to resonate (left panel). A series of ultrasound “tracking” pulses is then sent within the sample and the returning echoes are used to estimate the sample motion (middle panel). The shape of the estimated displacement curve is directly related to the shear modulus of the sample. The time-displacement curve can be compared to theoretical models to determine the actual shear modulus for that specific point in time. This process is repeated every 4 seconds to form a signature curve that shows shear modulus vs time (right panel).

Figure 4

Quantra Clot Time variation as a function of low molecular weight heparin (LMWH) concentration (n = 5 for each test condition). Error bars show one standard deviation.

Figure 5

Scatter plot of Quantra Clot Time vs TEG Reaction (R) time using whole blood samples with varying functionality of the coagulation factors. Paired measurements were obtained by running the same sample and reagents on both systems. The r-value of the best line fit is 0.95 (n = 34, 99% CI [0.88 – 0.98]).

Figure 6

(Top Panel) Dose Response Curve for abciximab (ReoPro) concentration on the Quantra analyzer (n=5 for each test condition) and (Bottom Panel) SEER Sonorheometry Clot Stiffness vs TEG shear elastic modulus strength (G) parameter across a broad range of clot stiffness values. In each plot, error bars indicate one standard deviation.

Figure 6

(Top Panel) Dose Response Curve for abciximab (ReoPro) concentration on the Quantra analyzer (n=5 for each test condition) and (Bottom Panel) SEER Sonorheometry Clot Stiffness vs TEG shear elastic modulus strength (G) parameter across a broad range of clot stiffness values. In each plot, error bars indicate one standard deviation.

Figure 7

(Top Panel) Quantra Fibrinogen Contribution as a function of target fibrinogen concentration. Whole blood samples from 5 healthy volunteers were mixed with fibrinogen depleted plasma to yield concentrations of 75, 100, 150, 200, 250 and 286 mg/dl (n = 4 for each test condition). For each subject, data show high linearity across the fibrinogen range tested with an average correlation (r-value) with the best line fit of 0.99. (Bottom Panel) Scatter plot of the Quantra Fibrinogen Contribution vs the fibrinogen concentration determined by the Clauss assay as implemented in the Stago STart4 analyzer. The r-value of the best line fit is 0.94 (n = 29, 99% CI [0.87 – 0.98]).

Figure 7

(Top Panel) Quantra Fibrinogen Contribution as a function of target fibrinogen concentration. Whole blood samples from 5 healthy volunteers were mixed with fibrinogen depleted plasma to yield concentrations of 75, 100, 150, 200, 250 and 286 mg/dl (n = 4 for each test condition). For each subject, data show high linearity across the fibrinogen range tested with an average correlation (r-value) with the best line fit of 0.99. (Bottom Panel) Scatter plot of the Quantra Fibrinogen Contribution vs the fibrinogen concentration determined by the Clauss assay as implemented in the Stago STart4 analyzer. The r-value of the best line fit is 0.94 (n = 29, 99% CI [0.87 – 0.98]).