Introduction
Heart failure (HF) is a prevalent disease in the United States with an estimated 150 000–200 000 cases of advanced HF refractory to medical therapy.1 Cardiogenic shock, whether due to acute myocardial infarction or advanced HF, is also increasingly prevalent.2 The use of temporary and durable mechanical circulatory support (MCS) devices to sustain life in advanced HF and cardiogenic shock patients has skyrocketed, increasing by 30-fold from 2007 to 2012.3,4 Despite its mortality and quality-of-life benefits, MCS therapy continues to be burdened by complications such as stroke, bleeding, and device thrombosis.4 To reduce these complications, appropriate anticoagulation to maintain the delicate balance between bleeding and thrombosis is imperative. However, there is a paucity of high-quality data supporting a specific, evidence-based approach to anticoagulation management in MCS patients. One such evidence gap concerns the optimal method of monitoring anticoagulation with unfractionated heparin in MCS patients.
Unfractionated heparin is a linear polysaccharide with repeating subunits that bind antithrombin. The union of heparin and antithrombin induces a conformational change that rapidly inactivates thrombin and factor Xa as well as other serine proteases in the coagulation cascade, producing heparin's anticoagulant effect.5,6 In hospitalized patients receiving unfractionated heparin, the activated partial thromboplastin time (aPTT) and anti-factor Xa (anti-Xa) activity are the two most common assays used to measure heparin effect.7 The aPTT measures the time it takes plasma to clot when recalcified and exposed to substances that activate the contact-dependent factors. The therapeutic range of aPTT is challenging to standardize and requires re-establishment with each new reagent lot. The aPTT is also affected by various clinical conditions that cause artificial prolongation that does not correlate with bleeding or protection from thrombosis.8,9 These conditions include haemolysis, liver disease, the presence of lupus anticoagulants, and warfarin administration or other vitamin K deficiencies, all of which are frequent in MCS patients.
The anti-Xa assay has gained popularity recently as an alternative method to measure heparin anticoagulation.7 For this assay, plasma is mixed with a known amount of chromogenic factor Xa substrate. If heparin is present, it binds antithrombin and inhibits factor Xa, reducing the amount of colour formed. The quantity of chromophore released is thus inversely proportional to heparin activity. The anti-Xa assay specifically measures the functional activity of heparin and is less influenced by factors that affect the accuracy of the aPTT assay. However, partly due to the chromogenic nature of the test, there may be interference in the setting of hypertriglyceridemia, hyperbilirubinaemia, haemolysis, and recent use of direct factor Xa inhibitor anticoagulants.10 Unlike the aPTT, the anti-Xa assay does not require re-establishment of the therapeutic range with each new lot of reagent.11
Prior studies have attempted to compare the use of aPTT and anti-Xa in the monitoring of unfractionated heparin.8,12–17 The majority of the studies were not in MCS patients and were limited by their retrospective design, small sample size, inability to temporally correlate events with aPTT or anti-Xa values, and inconsistent adjudication of bleeding and thrombosis. Overall, in non-MCS patients the studies showed no significant difference in bleeding, thrombosis, or mortality between the two assays, but that using the anti-Xa assay may lead to a quicker time to and longer duration within the therapeutic range.13,17 Previous studies also showed high rates of discordance between the two assays, ranging between 40% and 75%, with the most common discordant pattern being a high aPTT value relative to anti-Xa.
In this study, we aimed to examine the relationship between aPTT and anti-Xa in monitoring unfractionated heparin specifically in MCS patients and to identify patient factors and types of MCS devices that may influence the concordance pattern between the two measures. We hypothesize that aPTT and anti-Xa are frequently discordant, and patient factors related to inflammation, nutrition, haemolysis, and renal function are associated with discordance. We also hypothesize that different MCS devices are associated with different levels of discordance.
Methods
Anti-Xa protocol
- On June 1, 2016, the University of Washington Medical Center (Seattle, WA) initiated a new protocol of monitoring and dosing intravenous unfractionated heparin based on anti-Xa level in all MCS patients. The protocol prospectively mandated simultaneous paired anti-Xa and aPTT testing on the same blood sample for all heparin monitoring in MCS patients. MCS devices included extracorporeal membrane oxygenation (ECMO), intra-aortic balloon pump (IABP), Impella 2.5/CP/5.0, HeartWare HVAD, HeartMate II (HM2), HeartMate 3 (HM3), total artificial heart (TAH), Centrimag, and TandemHeart. Unfractionated heparin dose was monitored and adjusted via a nurse-driven protocol based on anti-Xa level. Providers could override the anti-Xa protocol based on clinical necessity and manually set the heparin dose. When anti-Xa and aPTT were markedly discordant, providers were encouraged to obtain a ‘discordant panel’ of laboratory tests, which included aPTT, anti-Xa, thrombin time, fibrinogen level, aPTT and PT mixing studies, antithrombin antigen level, factor VIII assay, high sensitivity C-reactive protein level, and pre-albumin.
Study sample
- All paired anti-Xa/aPTT testing results in patients with ECMO, IABP, Impella 2.5/CP/5.0, HVAD, HM2, HM3, and TAH devices up to 31 December 2019 were included in this study. Centrimag and TandemHeart devices were excluded from this analysis due to a very small number of patients (≤10 each). Patient demographics (age, sex, and race), device type, and 14 pre-specified laboratory variables (International Normalized Ratio [INR], haemoglobin, platelet, white blood cell [WBC], estimated glomerular filtration rate [eGFR], AST, ALT, total bilirubin, total protein, albumin, pre-albumin, high sensitivity CRP [CRP], LDH, and haptoglobin) were also collected from the medical centre's electronic clinical data warehouse. For each pair of anti-Xa/aPTT tests, lab values closest in time during the same admission were used for analysis. EGFR was estimated using the MDRD equation. When a patient had both ECMO and another MCS device such as Impella, the patient was counted as an ECMO patient. All discordant panel testing performed during the study period were included as well. The study conformed to the principles outlined in the Declaration of Helsinki and was approved by the University of Washington institutional review board.
Laboratory methods
- The prothrombin time (PT), activated partial thromboplastin time (aPTT) and anti-Xa-based calibrated assay for heparin were conducted on blood collected in 3.2% sodium citrate on a STA Compact Max® or STA R Max® analyser (Diagnostica Stago). The STA®-Neoplastine® CI PLUS assay was used to measure the prothrombin time, STA®-aPTT Automate 5 assay was used to measure the aPTT, and the STA®-Liquid anti-Xa chromogenic assay was used for anti-Xa assessment, according to manufacturer's recommendations for each assay.
Statistical analysis
- Basic descriptive statistics were performed for patient baseline characteristics. Mean and standard deviation were reported for continuous variables with normal distributions. Median and interquartile range (IQR) were reported for non-normal distributions.
- aPTT between 60 and 100 s was defined at the study institution as therapeutic for heparin anticoagulation in MCS patients. Similarly, anti-Xa between 0.3 and 0.7 IU/mL was defined as therapeutic. aPTT and anti-Xa were defined as concordant if they were both therapeutic, both supratherapeutic, or both subtherapeutic. They were discordant in the direction of aPTT > Anti-Xa if aPTT was supratherapeutic and anti-Xa was therapeutic or subtherapeutic or if aPTT was therapeutic and anti-Xa was subtherapeutic. Discordance in the direction of aPTT < Anti-Xa was defined using the same logic.
- To identify patient factors (demographic, device type, and lab covariates) that were associated with concordant versus discordant aPTT/anti-Xa pattern, a random forest model was built using all 18 variables collected. Random forests are a mature and widely used ensemble learning method that constructs a multitude of decision trees (each using a random subset of observations and variables) and outputs results based on majority voting of all the decision trees. A random forest model is particularly suitable here compared to a traditional logistic regression model as it does not assume linearity of independent variables and minimizes overfitting. Missing variable values were imputed by multiple imputation using a previously validated method.18 The most important predictors of concordance versus discordance were identified based on two common measures of variable importance (mean decrease in accuracy and mean decrease in Gini impurity). To maximize the interpretability of the model results, the most important predictors identified by the random forest model were then used in an ordinal logistic regression model to estimate odds ratios and P-values. The ordinal response variable (concordance pattern) was defined in this order: aPTT < Anti-Xa, concordant, aPTT > Anti-Xa.
- For discordant panel analysis, a multivariate linear regression model was used with aPTT as the response variable and anti-Xa and other co-variables as the explanatory variables including antithrombin antigen, factor VIII, fibrinogen, prothrombin time (PT), pre-albumin, and CRP. The relationship between antithrombin antigen level and heparin infusion rate adjusted for anti-Xa level was also examined using linear regression.
Results
Sample size and patient baseline characteristics
- From 1 June 2016 to 31 December 2019, a total of 23 001 pairs of simultaneously measured anti-Xa and aPTT labs were performed. These paired labs originated from 699 unique patients and 862 patient-device pairs as some patients had more than one device (e.g., changing to Impella after failing IABP). Baseline characteristics are included in Table 1.
Table 1 Baseline characteristics
| Characteristics | Observations ( |
| Age (years) | 54.3 ± 15.6 |
| Sex (% female) | 25.4% |
| Race (% white) | 74.6% |
| Device | |
| IABP (233 patients) | 11.5% |
| Impella (226 patients) | 16.7% |
| TAH (15 patients) | 6.5% |
| ECMO (148 patients) | 11.3% |
| HM2 (68 patients) | 15.0% |
| HM3 (53 patients) | 9.1% |
| HW (119 patients) | 29.9% |
| Albumin (g/dL) | 3.1 ± 0.6 |
| ALT (units/L) | 25 [15–49] |
| AST (units/L) | 35 [22–64] |
| CRP (mg/L) | 82 [22–143] |
| eGFR (mL/min/1.73 m2) | 65 [40, >90] |
| Haptoglobin (mg/dL) | 67 [<30, 145] |
| Haemoglobin (g/dL) | 8.8 ± 1.8 |
| INR | 1.6 ± 0.5 |
| LDH (units/L) | 346 [236–595] |
| Platelet (thousand/mL) | 199 ± 107 |
| Pre-albumin (mg/dL) | 14.9 ± 6.4 |
| Total bilirubin (mg/dL) | 0.8 [0.5–1.4] |
| Total protein (g/dL) | 6.0 ± 1.0 |
| WBC (thousand/mL) | 12.2 ± 6.5 |
Concordance and discordance pattern
- Overall, aPTT and anti-Xa were concordant (both supra-, sub-, or therapeutic) 35.5% of the time. They were discordant in the direction of aPTT > Anti-Xa 61.5% of the time and in the direction of aPTT < Anti-Xa 3.0% of the time. A more detailed representation of the concordance/discordance pattern is depicted in Figure 1.
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Predictors of concordance versus discordance
- A random forest model was fitted using patient demographic, device type, and lab variables to predict concordance pattern. The model achieved an accuracy of 78.0% using all the collected variables compared to an accuracy of 65.7% using an INR-only model. For reference, a null model guessing the majority outcome every time had an accuracy of 61.5% as the most common pattern (aPTT > Anti-Xa) occurred in 61.5% of the observations. INR was the most important factor affecting concordance, followed by eGFR, platelet, haemoglobin, pre-albumin and WBC. Race and sex were the least important factors (Figure 2). High INR, eGFR, and total bilirubin, as well as low platelet, haemoglobin, pre-albumin, WBC, and haptoglobin were all associated with a high aPTT compared to anti-Xa (Table 2).
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Table 2 Estimated odds ratios and
| Variable | Odds ratioa (95% CI) | |
| INR | 5.81 (5.31 to 6.36) | <0.001 |
| eGFR (10 mL/min/1.73m2) | 1.02 (1.01 to 1.04) | <0.001 |
| Platelet (100 000/mL) | 0.83 (0.80 to 0.85) | <0.001 |
| Haemoglobin (g/dL) | 0.84 (0.82 to 0.85) | <0.001 |
| Pre-albumin (mg/dL) | 0.95 (0.94 to 0.95) | <0.001 |
| WBC (thousand/mL) | 0.97 (0.96 to 0.97) | <0.001 |
| Total bilirubin (mg/dL) | 1.04 (1.03 to 1.06) | <0.001 |
| Haptoglobin (10 mg/dL) | 0.98 (0.97 to 0.98) | <0.001 |
| Device - ECMO | 1.00 | Ref |
| IABP | 1.56 (1.38 to 1.76) | <0.001 |
| Impella | 1.35 (1.22 to 1.50) | <0.001 |
| TAH | 2.76 (2.35 to 3.24) | <0.001 |
| HM2 | 3.22 (2.84 to 3.64) | <0.001 |
| HM3 | 2.79 (2.43 to 3.21) | <0.001 |
| HW | 3.42 (3.05 to 3.83) | <0.001 |
Concordance pattern by mechanical circulatory support device type
- Using ECMO as the reference, IABP and Impella were slightly more likely (OR 1.56 and 1.35, respectively) to be associated with a relatively high aPTT compared to anti-Xa, whereas TAH, HM2, HM3, and HW were much more likely (OR range 2.76–3.42) (Figure 3). There was no statistically significant difference among the three durable VADs in terms of their propensity for high aPTT compared to anti-Xa.
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Discordant panel analysis
- A total of 253 discordant lab panels were performed in 184 unique patients. Less than 3% of data were missing from the analysed variables and were imputed as described above. Lower antithrombin antigen level was associated with higher aPTT for any given anti-Xa level and the association was statistically significant (Table 3). Lower antithrombin antigen level also had a statistically significant association with higher heparin dose to achieve any given anti-Xa level (an increase of 0.61 units/kg/hour per 10% decrease in antithrombin antigen, P = 0.006).
Table 3 Multivariate linear regression analysis of aPTT/anti-Xa relationship based on discordant panel variables
| Response variable: aPTT | ||
| Explanatory variables | Coefficient (95% CI) | |
| Anti-Xa | 29.89 (25.99 to 33.78) | <0.001 |
| Antithrombin antigen | −11.41 (−17.24 to −5.59) | <0.001 |
| Factor VIII | −4.43 (−9.12 to 0.26) | 0.066 |
| Fibrinogen | 0.73 (−5.07 to 6.53) | 0.805 |
| PT | 10.17 (6.19–14.16) | <0.001 |
| Pre-albumin | −0.93 (−6.33 to 4.47) | 0.735 |
| CRP | −2.77 (−8.48 to 2.94) | 0.343 |
Discussion
In this study, we aimed to examine the relationship between aPTT and anti-Xa in monitoring IV heparin in MCS patients and to identify patient factors and types of MCS devices that may influence the concordance pattern between the two measures. Out of 23 001 paired values of aPTT and anti-Xa, we found that aPTT and anti-Xa were concordant only 35.5% of the time and for most discordant pairs, the aPTT suggested a greater heparin effect than did the anti-Xa level. The discordant pattern of aPTT > anti-Xa was associated with high INR, eGFR, and total bilirubin, as well as low platelets, haemoglobin, pre-albumin, white blood cell count, and haptoglobin. Durable MCS devices (TAH, HM2, HM3, and HW) were much more likely to be associated with aPTT > anti-Xa compared to the temporary support devices (ECMO, IABP, and Impella).
To our knowledge, our study is the first large, prospective study to evaluate the relationship between aPTT and anti-Xa for heparin monitoring in MCS patients. There have been a small number of publications on this topic in ECMO or continuous flow VAD patients; however, their sample sizes have all been very small (<40 patients), limiting their analytical power.10,14,15,19 Our results are consistent with the finding from prior studies that, for discordant values, the pattern of aPTT > anti-Xa is much more common than aPTT < anti-Xa. Several published studies have also studied this topic in hospitalized patients in general and found similar discordance patterns.12,13,16
Prior studies have also suggested that haemoglobin, bilirubin, and baseline INR/warfarin administration may artificially elevate aPTT levels in MCS patients, but due to small sample sizes these relationships could not be adequately elucidated.10,15,19 Our study's large sample size enabled us to examine 18 demographic and laboratory variables' effect on the aPTT/anti-Xa discordance pattern. We were able to show that INR, renal function, nutrition, platelet count, and haemolysis were all associated with aPTT > anti-Xa. Given how common these clinical factors are disturbed in MCS patients, it is not surprising that the aPTT/anti-Xa discordance rate is high and quite variable in this patient population. Incorporating these patient factors into a random forest model improved the accuracy of model prediction for concordance versus discordance from a baseline of 61.5% to 78%, suggesting that while the studied variables are significant factors there are still many unknown variables that contribute to aPTT-anti-Xa discordance. Realistically, it is impractical to consider all confounding variables in determining which patient may have an inaccurate aPTT or anti-Xa. Thus, given that the anti-Xa assay is less affected by exogenous factors, it is worth further investigating whether using the anti-Xa assay to monitor heparin in MCS patients leads to better clinical outcomes.
Interestingly, lower antithrombin antigen levels were associated with a higher aPTT for any given anti-Xa level as well as higher heparin doses at any given anti-Xa level. This observation is compatible with the antithrombin-dependent mechanism of heparin and suggests that the anti-Xa assay may be especially useful in patients with reduced antithrombin activity. However, further investigation is required to determine if higher heparin doses in patients with reduced antithrombin levels may have any clinically significant effect on outcomes.
The finding that the aPTT/anti-Xa discordance pattern is similar among the three durable VADs (HM2, HM3, and HW) is reassuring as it suggests that we do not need a different heparin monitoring protocol for each VAD platform. It also suggests that changes in VAD engineering such as moving from axial to centrifugal flow and having a magnetically levitated rotor have not altered the performance of the heparin assays. Additionally, it is notable that all durable MCS devices including VADs and TAH have significantly more aPTT/anti-Xa discordance than the temporary MCS devices, which to our knowledge has never been reported in the literature. The underlying cause of this observation deserves further research.
Despite our large sample size (23 001 pairs of simultaneously measured anti-Xa and aPTT from 862 patient-device pairs), our data were collected from a single center with potential limitations on the generalizability of our results. Secondly, we showed that aPTT and anti-Xa were often discordant, which is theoretically due to aPTT being more easily confounded by other patient factors. However, we have not proven in practice that using an anti-Xa based monitoring protocol leads to improved clinical outcomes compared to an aPTT-based protocol. This question is a focus of ongoing research at our centre and others, and will be the subject of our upcoming manuscripts.
Conflict of interest
The authors have no relevant conflict of interest to disclose.
Funding
This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.
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Abstract
Aims
It is unclear whether activated partial thromboplastin time (aPTT) or anti‐Xa is more accurate for monitoring heparin anticoagulation in mechanical circulatory support (MCS) patients. This study investigates the relationship between aPTT and anti‐Xa in MCS patients and identifies predictors of discordance.
Methods and results
aPTT and anti‐Xa were simultaneously measured in a prospective cohort of MCS patients receiving unfractionated heparin at a tertiary academic medical centre. Therapeutic aPTT and anti‐Xa levels were 60–100 s and 0.3–0.7 IU/mL, respectively, and concordance was defined as both levels being subtherapeutic, therapeutic, or supratherapeutic. To identify predictors of discordance, both a machine learning random forest model and a multivariate regression model were applied to patient demographics, device type, and 14 laboratory variables; 23 001 pairs of simultaneously measured aPTT/anti‐Xa were collected from 699 MCS patients. aPTT and anti‐Xa were concordant in 35.5% of paired observations and discordant in 64.5% (aPTT > antiXa 61.5%; aPTT < antiXa 3.0%). Discordance with a high aPTT relative to anti‐Xa (aPTT > antiXa) was associated with high INR, eGFR, and total bilirubin, as well as low platelets, haemoglobin, pre‐albumin, white blood cell count, and haptoglobin. Total artificial heart and durable ventricular assist devices were more likely to be associated with aPTT > anti‐Xa than temporary MCS devices.
Conclusions
aPTT and anti‐Xa were frequently discordant in MCS patients receiving heparin anticoagulation. Clinical conditions common in MCS patients such as concurrent warfarin use, malnutrition, haemolysis, and thrombocytopenia, as well as durable type of MCS devices were associated with a high aPTT relative to anti‐Xa.
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Details
; Li, Ang 2 ; Beckman, Jennifer A. 3 ; Kim, Christopher 3 ; Granich, Marian A. 3 ; Mondin, John 1 ; Sabath, Daniel E. 3 ; Garcia, David A. 3 ; Mahr, Claudius 1 1 Medical City Healthcare, Dallas, TX, USA
2 Division of Hematology & Oncology, Baylor College of Medicine, Houston, TX, USA
3 University of Washington, Seattle, WA, USA