- Email: [email protected]
International Normalized Ratio Variability: A Measure of Anticoagulation Quality or a Powerful Mortality Predictor
International Normalized Ratio Variability: A Measure of Anticoagulation Quality or a Powerful Mortality Predictor Gabriel Vanerio, MD*†
Background: As atrial fibrillation (AF) carries twice the mortality hazard when compared with a similar population without diagnosed AF, the importance of risk stratifying is obvious. Several variables are related to outcome: age, comorbidities, and use of several medications, particularly oral anticoagulants. The CHA2DS2VASc score is an extremely useful tool to predict thromboembolic events and also mortality. The international normalized ratio (INR) variability is a treatment efficacy variable also associated with morbidity in patients receiving warfarin. The objective of the study is to compare the prognostic value of the CHA2DS2VASc versus the INR variability or its combination to predict mortality. Methods: In this observational study, we analyzed 589 patients from our Atrial Fibrillation Cohort, all on warfarin for more than 1 year and had more than 5 INRs performed in the last 2 years. The CHA2DS2VASc, HAS-BLED, and SAMe-TT2R2 scores were calculated as well as the INR variability using the time-in-therapeutic-range (TTR), the percentage of INRs (%INRs) within range, and the standard deviation of the INRs (SDINRs). Kaplan–Meier survival curves were plotted via different cutoff points. Results: The mean TTR was 53 6 23%; 34.6% of the patients had a TTR above 64%. The mean %INRs in range was 50.2 6 20.2; 17.3% of the population had %INRs in range above 70%. The mean SDINRs was .84 6 .54, and 38.4% had SDINRs below .79. Of 598, 139 (22%) discontinued warfarin treatment. Death was responsible for almost 50% of treatment discontinuation. Of 598, 68 patients died during the study period (11.5 %); the most frequent causes of death were heart failure (30%), bleeding (17%), and ischemic stroke (15%). Patient survival had a correlation with TTR, %INRs in range, SDINRs, left ventricular ejection fraction, CHA2DS2VASc, and the combination of CHA2DS2VASc 1 SDINRs (cutoff .1 and ..79, respectively). Conclusions: INR variability is an extremely useful tool to assess anticoagulation quality. Calculation of both CHA2DS2VASc and INR variability appears to be extremely useful to predict mortality in patients with AF receiving warfarin. The SDINRs emerges as a strong mortality predictor compared to the other INR variability indexes. Key Words: Atrial fibrillation— warfarin—anticoagulants—therapeutics—mortality. Ó 2015 by National Stroke Association
From the *CASMU Arrhythmia Service, Montevideo; and †Department of Cardiology, British Hospital, Montevideo, Uruguay. Received March 17, 2015; revision received May 8, 2015; accepted May 17, 2015. The authors have no conflicts of interest to declare. Address correspondence to Gabriel Vanerio, MD, CASMU Arrhythmia Service and the Department of Cardiology, British Hospital, 2420 Av., Italia, Montevideo 11600, Uruguay. E-mail: gabriel. [email protected]. 1052-3057/$ - see front matter Ó 2015 by National Stroke Association http://dx.doi.org/10.1016/j.jstrokecerebrovasdis.2015.05.017
Warfarin is the most common oral anticoagulant (OAC), and approximately 2% of adults in the developed world are receiving warfarin.1 The benefits of OAC in patients with atrial fibrillation (AF) are well known. In the AFFIRM (Atrial Fibrillation Follow-Up Investigation of Rhythm Management) trial, patients on warfarin had a significantly better survival after adjustment for other covariates.2 Despite this key observation, there was no mention of the quality of anticoagulation. Useful measures to evaluate anticoagulation dose management are the time-in-therapeutic range
Journal of Stroke and Cerebrovascular Diseases, Vol. -, No. - (---), 2015: pp 1-6
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(TTR), the fraction of the international normalized ratios (INRs) in range, and other INR variability indexes.3 Long periods with a TTR above 65% or a high percentage of INRs (%INRs) in range are associated with reduction in hemorrhage and thromboembolic events.4-11 Therefore, monitoring INR variability to assess and correct warfarin treatment decreases complications.1 In our country and the rest of South America, there is no sufficient information regarding anticoagulation quality in patients receiving warfarin. There are data available with acenocumarol, a similar compound, but not warfarin.12 In the modern trials with non–vitamin K antagonists, regional data showed wide INR variation that could be explained by patient characteristics or country socioeconomic and health care standards. In Central and South America, the mean TTR on the RE-LY trial was 61%, and in the Rocket-AF trial Latin America, the mean i-TTR was 55.2 6 20%.13,14 As AF carries twice the mortality hazard when compared with a similar population without diagnosed AF, the importance of risk stratifying is obvious. Several variables are associated with outcome: age, comorbidities, use of anticoagulants, and so forth. The CHA2DS2VASc score is an extremely useful tool to predict thromboembolic events and assess treatment efficacy.15,16
Objectives To compare the prognostic value of the CHA2DS2VASc score versus different INR variability methods or its combination to predict mortality in patients receiving warfarin. We hypothesized that the combination of a risk score and a therapeutic evaluation variable has a clinically significant value.
Patients The Montevideo-CASMU Atrial Fibrillation Cohort includes 3196 patients with AF. The registry started on April 1995 and ended in December 2012. In this observational study, we selected patients receiving warfarin with a minimum of 6 international normalized units performed from January 01, 2010, to July 31, 2012; all patients were followed until October 2013. All subjects included were receiving warfarin for more than 12 months before January 2010.
Methods We utilized 3 methods to estimate INR variability: (1) standard deviation of INRs (SDINRs) for each patient during the observation period, SDINRs; (2) the fraction of INRs in range during the observation period for each patient, expressed in percentage as %INRs; and (3) percentage of TTR estimated by linear interpolation (Rosendaal method, worksheet template available at https:// www.inrpro.com/article.asp?id527)3 Every INR-specific
person-time was calculated by incorporating the frequency of INR measurements and their actual values and assuming that changes between consecutive INR measurements are linear over time. We analyzed 9007 INRs, with a mean of 29 6 5 INRs per patient (range, 6-48). When 3 consecutive INRs were performed with less than 20 days between tests, data were not included. The CHA2DS2VASc, HAS-BLED1, and SAMe-TT₂R₂17 scores were calculated at the time the study started. Target INR was 2-3 for 92% of the patients. All patients were followed, and mortality was the primary end point, when possible; the cause of death was assessed.
AF Type Definitions Paroxysmal AF: self-terminating AF, usually within 48 hours. Persistent AF: when an AF episode either lasts longer than 7 days or requires termination by cardioversion, either with drugs or by direct current cardioversion. Permanent AF: when the presence of the arrhythmia is accepted by the patient (and physician). Hence, rhythm control interventions are, by definition, not pursued in patients with permanent AF.
Outcome Definitions Fatal bleeding that directly causes death with no other explainable cause directly observed (by either clinical specimen [blood, emesis, stool, and so forth] or imaging) or confirmed on autopsy.
Stroke Definition of central nervous system (CNS) infarction: CNS infarction is brain cell death attributable to ischemia, based on pathological, imaging, or other objective evidence of cerebral focal ischemic injury in a defined vascular distribution. CNS infarction includes hemorrhagic infarctions.
Statistical Analysis Categorical data are presented as absolute numbers and percentages, and continuous data as mean values and standard deviations. To compare variables, we utilized the Student t test, chi square and Fisher exact test, and one-way analysis of variance as appropriate. The effect of the presence of one or more mortality predictor was evaluated utilizing Kaplan–Meier survival curves (from January 2010 to October 2013). Factors were compared using the log-rank test, and a P value less than .01 was considered statistically significant. Multivariate Cox regression analysis with time-dependent covariate data was performed and presented as hazard ratios (HRs) with 95% confidence intervals (CI).
DEMOGRAPHICS AND CO-MORBIDITIES
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Results Table 1 summarizes patient’s characteristics and comorbidities. Mean age was 74 6 8 years; 11% of the Table 1. Patient demographics and comorbidities
Gender Age (y)
INRs, mean 6 SD (min-max) Warfarin indication
Chronic renal failure* Hypertension Diabetes BMI .30 CHF COPD CHD Dilated Cardiomyopathy VHD Previous embolic event LVEF ,36% Progression to permanent AF Presence of a permanent PM Type of AF
CHA2DS2VASc
HAS-BLED
Variable
N (%)
Male 19-49 50-69 70-89 .90
321 (54.5) 6 (1.1) 148 (25.1) 429 (72.8) 7 (1.1) 29 6 5 (6-48)
AF alone AF plus VHD (target INR 5 2.5-3.5)
545 (92) 44 (7.4)
INRs, TTR, and SDINRs The mean %INRs in range was 50.2 6 20.2%, and 17.3% of the population had %INRs in range above 70%. By linear interpolation, the mean TTR was 53% 6 23, and 34.6% of the patients had a TTR above 64%. The mean SDINRs was .84 6 .54, and 38.4% had SDINRs below .79. There was no correlation between the CHA2DS2VASc and the quality of anticoagulation; patients at higher risk had similar TTR or %INRs than those at a lower risk (Fig 1). We could not find a correlation between the SAMe-TT₂R₂ and any of the INR variability variables.
Gender 28 (4.7) 432 (73.3) 109 (18.5) 101 (17.1) 57 (9.7) 34 (5.8) 99 (16.8) 62 (10.5) 150 (25.5) 50 (8.5) 51 (10.5) 127 (24.1) 103 (17.5)
Paroxysmal/ persistent/ permanent At the beginning of the study % 0-1 2 3 4 5 .5 0 1 2 3 .3
population had CHA2DS2Vasc score below 2, and a HAS-BLED score below 3 was observed in 60% of the patients. Chronic kidney disease had a low prevalence (4.7%). Mean follow-up was 1.19 6 1 year.
11/38/50
66 (11.2) 77 (13.1) 185 (31.4) 182 (30.9) 59 (10) 20 (3.4) 14 (2.4) 86 (14.6) 254 (43.1) 195 (33.1) 40 (6.9)
Abbreviations: AF, atrial fibrillation; BMI, body mass index; COPD, chronic obstructive pulmonary disease; CHD, coronary heart disease; CHF, congestive heart failure; INR, international normalized ratio; LVEF, left ventricular ejection fraction; max, maximum; min, minimum; PM, pacemaker; SD, standard deviation; VHD; valvular heart disease with mechanical prosthesis. *Creatinine clearance ,60 mL/minute/1.73 m2.
There was a male predominance in the study population, 319 men (54.1%) versus 270 women (45.9%). Women were older, 74 6 9 years, than men, 70 6 9 years; P 5 .01.
Warfarin Discontinuation Of 598 patients, 139 (22%) discontinued warfarin treatment (defined as no more INRs after October 2011); reasons for discontinuation are displayed in Table 2. The most important cause for discontinuation was death, observed in 49% of this population; in this group, death was attributed to ischemic stroke (10 patients) and hemorrhagic events (hemorrhagic stroke, 6 patients; other hemorrhages, 5 patients; Table 3). The second cause for discontinuation was the use of dabigatran (30%); in this group, only 1 patient died while on this medication. Twenty-seven (4.5%) patients stopped treatment temporarily because of several causes; the most common was their refusal to receive warfarin.
Complications Related to Warfarin Therapy Thirty-seven patients had bleeding complications, 14 patients had severe hemorrhagic complications, 8 had hemorrhagic stroke, and 10 had gastrointestinal bleeding. There was a significant correlation with mortality and hemorrhagic complications. Eighteen patients had an embolic event, and 12 experienced an ischemic stroke.
Mortality Of 589 patients, 68 died during the study period (11.5%), the most frequent causes of death were heart failure (30%), bleeding (17%), and ischemic stroke (15%; Table 3). Patient survival had a significant correlation with TTR, %INRs, and SDINRs. In the Kaplan–Meier analysis,
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Figure 1. Graph bar displaying the TTR (% days in range) and the percentage of INRs in range (y-axis) according to the CHA2DS2VASc category (number of patients in each category, x-axis). The black line represents the SD for each value. We do not observe a correlation as the CHA2DS2VASc increases the TTR or the percentage of INRs in range remains the same or even lower. Comparison showed a significant difference in the means between groups only in the TTR. Abbreviations: INRs, international normalized ratios; SD, standard deviation; TTR, time-in-therapeutic range.
survival curves were significantly different, with cutoff points of TTR above 65%, %INRs above 65%, and SDINRs above .79; log-rank (Mantel–Cox) chi-square, 5.05; P 5 .025; chi-square, 4.49; P 5 .034; and chi-square, 20; P 5 .00001, respectively. Kaplan–Meier survival curves showing mortality differences between CHA2DS2VASc and SDINRs (cutoff .1 and . .79) are shown in Figure 2. In Cox regression with time-varying covariate analysis (Table 4), the association of a low CHA2DS2VASc with SDINRs below .8 was significant with HR of 3.4 (95% CI, 1.5-7.6). Other variables associated with mortality were left ventricular ejection fraction below 35% (HR, 2.5; 95% CI, 1.09-5.77), presence of a permanent pacemaker (HR, 3.4; 95% CI, 1.5-7.6), and obstructive sleep apnea syndrome (HR, 7.5; 95% CI, 1.4-40).
Discussion Hypertension, chronic heart failure, and valvular heart disease are independent risk factors for AF.1 Patients with AF are at high risk of cardiovascular events, and the mortality is twice compared with that in the same population without known AF.1 In our study after multiTable 2. Causes of warfarin therapy discontinuation (n 5 139)
variate analysis, age and gender were not associated with mortality; however, several other recognized risk factors, such as left ventricular ejection fraction less than 35% and chronic obstructive pulmonary disease, were significantly associated with mortality. Monitoring INR variability is recommended to assess anticoagulation quality in patients on warfarin.5-10 The INR variability estimates the deviation of INR from the intended range over time and is based on the hypothesis that patient’s prothrombin time fluctuates all the time, and its value is a risk indicator for thromboembolism and major hemorrhage. In our investigation, the quality of anticoagulation was not satisfactory: only 34% had a TTR above 64%, and 38% SDINRs below .8. We also observed that patients at higher risk had the same anticoagulation quality values that those at a lower risk. Our data demonstrate a real-world scenario: much higher levels were met in other countries with anticoagulation clinics or during an RCT.5,13,14
CHA2DS2VASc and INR Variability Predict Mortality As AF has a higher mortality, detection of variables associated with mortality is obvious. Only anticoagulant therapy has been shown to reduce AF-related deaths.1 Table 3. Cause of death n (%)
n (%) Death Switched to dabigatran (one rivaroxaban) Physician’s (or patient’s) preference Switched to ASA No data available Major bleeding Abbreviation: ASA, acetylsalicylic acid.
68 (49) 40 (30) 14 (10) 7 (5) 6 (4) 4 (2)
Congestive heart failure Ischemic stroke No data Infection Hemorrhagic stroke Other bleeding complications Cancer Other causes
20 (30.8) 10 (15.4) 8 (12.3) 7 (10.8) 6 (9.2) 5 (7.7) 5 (7.7) 4 (6.2)
DEMOGRAPHICS AND CO-MORBIDITIES
Figure 2. Kaplan–Meier survival curves comparing the combination score with a cutoff point of an SD of .8 and a CHA2DS2VASc .1. There is a significant increase in mortality in the group of patients with a high SD and a high CHA2DS2VASc. Abbreviation: SD, standard deviation.
In our study, a CHA2DS2VASc score of 2 or more and INR variability indexes such as a TTR below 65%, the % INRs in range below 70%, and the SDINRs below .8 were Table 4. Cox proportional hazard regression of patient survival with time-varying covariates in our population
Hypertension Diabetes CHF COPD CHD Dilated cardiomyopathy VHD LVEF ,35% Obstructive sleep apnea Chronic kidney disease Progression permanent AF Presence of Permanent PM CHA2DS2VASc 1 SDINRs (cutoff .1 and ..79) HAS-BLED $ 3 TTR ,65% INRs in range ,65% SAMe-TT₂R₂ .2
Hazard ratio
95% Confidence interval
1.4 .6 2.5 1.1 .8 .9 1.2 2.5* 7.5* 1.5 1.0 3.4* 3.5*
(.6-3.3) (.2-1.5) (.9-6.9) (.4-2.7) (.3-1.8) (.3-2.6) (.6-2.5) (1.1-5.7) (1.4-40.2) (.3-6.5) (.5-2.3) (1.5-7.6) (1.7-7.2)
.7 .4 1.5 .9
(.4-1.5) (.1-1.1) (.7-8.6) (.5-1.5)
Abbreviations: AF, atrial fibrillation; COPD, chronic obstructive pulmonary disease; CHD, coronary heart disease; CHF, congestive heart failure; INR, international normalized ratio; LVEF, left ventricular ejection fraction; PM, pacemaker; SD, standard deviation; TTR, time-in-therapeutic range. *Indicates that a significant difference was found.
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associated with higher mortality. Only the SDINRs remained significant after Cox analysis. The ability of the CHA2DS2VASc score to predict cardiovascular events in stable anticoagulated patients with AF has been previously described.1,16 According to a meta-analysis by Hart et al,18 the use of OAC not only reduces stroke compared with placebo or control but also significantly reduces cardiovascular events and mortality.19 The importance of measuring anticoagulation quality to monitor patients on warfarin is well established. The present study confirms the importance to assess INR variability and reveals that the CHA2DS2VASc and the SDINRs alone or in combination are powerful predictors of mortality. Previous observations correlated TTR and INR variability with mortality. Patients who spent at least 70% of time within the therapeutic range had a 79% reduced risk of stroke compared to patients who spent 30% of time or less within range. Mortality rates were also significantly lower with at least 70% of time spent within therapeutic range.1,7,9 In another work, the SDINRs was a better predictor of mortality, stroke, bleeding, and hospitalization than the TTR in patients with AF receiving warfarin therapy.20 Other similar techniques to evaluate INR variability had shown similar results.21 We recommend utilizing the SDINRs because it is easy to calculate and has a powerful prognostic value. To our knowledge, this is the first time that a combination of a thromboembolic risk score and a time-dependent therapeutic variable is used to evaluate mortality, which adds intrinsic value to the equation. However, the usefulness of the INR variability is limited because we will be able to predict complications or even mortality only after several months on warfarin. It appears very reasonable that patients with an increased INR variability should receive non–antivitamin K agents. We could not find a significant relation between the SAMe-TT₂R₂ score and INR variability because we believe that other variables are also involved, particularly related to the patient characteristics and the health team involved.
Limitations A selection bias could be present because we only analyzed selected patients on warfarin and therefore unstable patients from our registry were already selfexcluded before we started the study.
Conclusions INR variability is an extremely useful tool to assess anticoagulation quality, but the SDINRs emerge as a very strong mortality predictor compared with other INR variability indexes. Furthermore, calculation of
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CHA2DS2VASc plus INR variability appears to be extremely useful to predict mortality in patients with AF receiving warfarin. Acknowledgment: G.V. contributed to the concept and design, analysis, and interpretation of data; critical writing and revising of the intellectual content; and also the final approval of the version to be published.
References 1. Camm AJ, Lip GY, De Caterina R, et al, ESC Committee for Practice Guidelines (CPG). 2012 focused update of the ESC Guidelines for the management of atrial fibrillation: an update of the 2010 ESC Guidelines for the management of atrial fibrillation. Developed with the special contribution of the European Heart Rhythm Association. Eur Heart J 2012;33:2719. 2. Wyse DG, Waldo AL, DiMarco JP, et al, Atrial Fibrillation Follow-up Investigation of Rhythm Management (AFFIRM) Investigators. A comparison of rate control and rhythm control in patients with atrial fibrillation. N Engl J Med 2002;347:1825. 3. Rosendaal FR, Cannegieter SC, van der Meer FJ, et al. A method to determine the optimal intensity of oral anticoagulant therapy. Thromb Haemost 1993;69:236. 4. Garcıa AD, Lopes RD, Hylek EM. New-onset atrial fibrillation and warfarin initiation: high risk periods and implications for new antithrombotic drugs. Thromb Haemost 2010;104:1099. 5. Clark NP. Frequency of monitoring, non-adherence, and other topics dear to an anticoagulation clinic provider. J Thromb Thrombolysis 2013;35:320. 6. Lader E, Martin N, Cohen G, et al. Warfarin therapeutic monitoring: is 70% time in the therapeutic range the best we can do? J Clin Pharm Ther 2012;37:375. 7. Nelson WW, Choi JC, Vanderpoel J, et al. Impact of comorbidities and patient characteristics on international normalized ratio control over time in patients with nonvalvular atrial fibrillation. Am J Cardiol 2013;112:509. 8. Rose AJ, Berlowitz DR, Miller DR, et al. INR targets and site-level anticoagulation control: results from the Veterans AffaiRs Study to Improve Anticoagulation (VARIA). J Thromb Haemost 2012;10:590. 9. Han SY, Palmeri ST, Broderick SH, et al. Quality of anticoagulation with warfarin in patients with nonvalvular atrial fibrillation in the community setting. J Electrocardiol 2013;46:45. 10. Olesen JB, Lip GY, Lindhardsen J, et al. Risks of thromboembolism and bleeding with thromboprophylaxis in
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patients with atrial fibrillation: a net clinical benefit analysis using a ‘real world’ nationwide cohort study. Thromb Haemost 2011;106:739. Schmitt L, Speckman J, Ansell J. Quality assessment of anticoagulation dose management: comparative evaluation of measures of time-in-therapeutic range. J Thromb Thrombolysis 2003;15:213. Casais P, S anchez Luceros A, Meschengieser S, et al. INR variability in anticoagulation with acenocoumarol: is it useful for identifying patients at risk of bleeding and thrombosis? Haematologica 1999;84:753. Van Spall HG, Wallentin L, Yusuf S, et al. Variation in warfarin dose adjustment practice is responsible for differences in the quality of anticoagulation control between centers and countries: an analysis of patients receiving warfarin in the randomized evaluation of long-term anticoagulation therapy (RE-LY) trial. Circulation 2012;126: 2309. Singer DE, Hellkamp AS, Piccini JP, et al, ROCKET AF Investigators. Impact of global geographic region on time in therapeutic range on warfarin anticoagulant therapy: data from the ROCKET AF clinical trial. J Am Heart Assoc 2013;3:e000521. Larsen TB, Lip GY, Skjøth F, et al. Added predictive ability of the CHA2DS2VASc risk score for stroke and death in patients with atrial fibrillation: the prospective Danish Diet, Cancer, and Health cohort study. Circ Cardiovasc Qual Outcomes 2012;5:335. Jover E, Rold an V, Gallego P, et al. Predictive value of the CHA2DS2-VASc score in atrial fibrillation patients at high risk for stroke despite oral anticoagulation. Rev Esp Cardiol (Engl Ed) 2012;65:627. Lip GY, Haguenoer K, Saint-Etienne C, et al. Relationship of the SAMe-TT₂R₂ score to poor-quality anticoagulation, stroke, clinically relevant bleeding, and mortality in patients with atrial fibrillation. Chest 2014;146:719. Hart RG, Pearce LA, Aguilar MI. Meta-analysis: antithrombotic therapy to prevent stroke in patients who have non-valvular atrial fibrillation. Ann Intern Med 2007;146:857. Gallagher AM, Setakis E, Plumb JM, et al. Risks of stroke and mortality associated with suboptimal anticoagulation in atrial fibrillation patients. Thromb Haemost 2011;106:968. Lind M, Fahlen M, Kosiborod M, et al. Variability of INR and its relationship with mortality, stroke, bleeding and hospitalizations in patients with atrial fibrillation. Thromb Res 2012;129:32. Van Den Ham HA, Klungel OH, Leufkens HG, et al. The patterns of anticoagulation control and the risk of stroke, bleeding and mortality in patients with non-valvular atrial fibrillation. J Thromb Haemost 2013;11:107.
Background: As atrial fibrillation (AF) carries twice the mortality hazard when compared with a similar population without diagnosed AF, the importance of risk stratifying is obvious. Several variables are related to outcome: age, comorbidities, and use of several medications, particularly oral anticoagulants. The CHA2DS2VASc score is an extremely useful tool to predict thromboembolic events and also mortality. The international normalized ratio (INR) variability is a treatment efficacy variable also associated with morbidity in patients receiving warfarin. The objective of the study is to compare the prognostic value of the CHA2DS2VASc versus the INR variability or its combination to predict mortality. Methods: In this observational study, we analyzed 589 patients from our Atrial Fibrillation Cohort, all on warfarin for more than 1 year and had more than 5 INRs performed in the last 2 years. The CHA2DS2VASc, HAS-BLED, and SAMe-TT2R2 scores were calculated as well as the INR variability using the time-in-therapeutic-range (TTR), the percentage of INRs (%INRs) within range, and the standard deviation of the INRs (SDINRs). Kaplan–Meier survival curves were plotted via different cutoff points. Results: The mean TTR was 53 6 23%; 34.6% of the patients had a TTR above 64%. The mean %INRs in range was 50.2 6 20.2; 17.3% of the population had %INRs in range above 70%. The mean SDINRs was .84 6 .54, and 38.4% had SDINRs below .79. Of 598, 139 (22%) discontinued warfarin treatment. Death was responsible for almost 50% of treatment discontinuation. Of 598, 68 patients died during the study period (11.5 %); the most frequent causes of death were heart failure (30%), bleeding (17%), and ischemic stroke (15%). Patient survival had a correlation with TTR, %INRs in range, SDINRs, left ventricular ejection fraction, CHA2DS2VASc, and the combination of CHA2DS2VASc 1 SDINRs (cutoff .1 and ..79, respectively). Conclusions: INR variability is an extremely useful tool to assess anticoagulation quality. Calculation of both CHA2DS2VASc and INR variability appears to be extremely useful to predict mortality in patients with AF receiving warfarin. The SDINRs emerges as a strong mortality predictor compared to the other INR variability indexes. Key Words: Atrial fibrillation— warfarin—anticoagulants—therapeutics—mortality. Ó 2015 by National Stroke Association
From the *CASMU Arrhythmia Service, Montevideo; and †Department of Cardiology, British Hospital, Montevideo, Uruguay. Received March 17, 2015; revision received May 8, 2015; accepted May 17, 2015. The authors have no conflicts of interest to declare. Address correspondence to Gabriel Vanerio, MD, CASMU Arrhythmia Service and the Department of Cardiology, British Hospital, 2420 Av., Italia, Montevideo 11600, Uruguay. E-mail: gabriel. [email protected]. 1052-3057/$ - see front matter Ó 2015 by National Stroke Association http://dx.doi.org/10.1016/j.jstrokecerebrovasdis.2015.05.017
Warfarin is the most common oral anticoagulant (OAC), and approximately 2% of adults in the developed world are receiving warfarin.1 The benefits of OAC in patients with atrial fibrillation (AF) are well known. In the AFFIRM (Atrial Fibrillation Follow-Up Investigation of Rhythm Management) trial, patients on warfarin had a significantly better survival after adjustment for other covariates.2 Despite this key observation, there was no mention of the quality of anticoagulation. Useful measures to evaluate anticoagulation dose management are the time-in-therapeutic range
Journal of Stroke and Cerebrovascular Diseases, Vol. -, No. - (---), 2015: pp 1-6
1
G. VANERIO
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(TTR), the fraction of the international normalized ratios (INRs) in range, and other INR variability indexes.3 Long periods with a TTR above 65% or a high percentage of INRs (%INRs) in range are associated with reduction in hemorrhage and thromboembolic events.4-11 Therefore, monitoring INR variability to assess and correct warfarin treatment decreases complications.1 In our country and the rest of South America, there is no sufficient information regarding anticoagulation quality in patients receiving warfarin. There are data available with acenocumarol, a similar compound, but not warfarin.12 In the modern trials with non–vitamin K antagonists, regional data showed wide INR variation that could be explained by patient characteristics or country socioeconomic and health care standards. In Central and South America, the mean TTR on the RE-LY trial was 61%, and in the Rocket-AF trial Latin America, the mean i-TTR was 55.2 6 20%.13,14 As AF carries twice the mortality hazard when compared with a similar population without diagnosed AF, the importance of risk stratifying is obvious. Several variables are associated with outcome: age, comorbidities, use of anticoagulants, and so forth. The CHA2DS2VASc score is an extremely useful tool to predict thromboembolic events and assess treatment efficacy.15,16
Objectives To compare the prognostic value of the CHA2DS2VASc score versus different INR variability methods or its combination to predict mortality in patients receiving warfarin. We hypothesized that the combination of a risk score and a therapeutic evaluation variable has a clinically significant value.
Patients The Montevideo-CASMU Atrial Fibrillation Cohort includes 3196 patients with AF. The registry started on April 1995 and ended in December 2012. In this observational study, we selected patients receiving warfarin with a minimum of 6 international normalized units performed from January 01, 2010, to July 31, 2012; all patients were followed until October 2013. All subjects included were receiving warfarin for more than 12 months before January 2010.
Methods We utilized 3 methods to estimate INR variability: (1) standard deviation of INRs (SDINRs) for each patient during the observation period, SDINRs; (2) the fraction of INRs in range during the observation period for each patient, expressed in percentage as %INRs; and (3) percentage of TTR estimated by linear interpolation (Rosendaal method, worksheet template available at https:// www.inrpro.com/article.asp?id527)3 Every INR-specific
person-time was calculated by incorporating the frequency of INR measurements and their actual values and assuming that changes between consecutive INR measurements are linear over time. We analyzed 9007 INRs, with a mean of 29 6 5 INRs per patient (range, 6-48). When 3 consecutive INRs were performed with less than 20 days between tests, data were not included. The CHA2DS2VASc, HAS-BLED1, and SAMe-TT₂R₂17 scores were calculated at the time the study started. Target INR was 2-3 for 92% of the patients. All patients were followed, and mortality was the primary end point, when possible; the cause of death was assessed.
AF Type Definitions Paroxysmal AF: self-terminating AF, usually within 48 hours. Persistent AF: when an AF episode either lasts longer than 7 days or requires termination by cardioversion, either with drugs or by direct current cardioversion. Permanent AF: when the presence of the arrhythmia is accepted by the patient (and physician). Hence, rhythm control interventions are, by definition, not pursued in patients with permanent AF.
Outcome Definitions Fatal bleeding that directly causes death with no other explainable cause directly observed (by either clinical specimen [blood, emesis, stool, and so forth] or imaging) or confirmed on autopsy.
Stroke Definition of central nervous system (CNS) infarction: CNS infarction is brain cell death attributable to ischemia, based on pathological, imaging, or other objective evidence of cerebral focal ischemic injury in a defined vascular distribution. CNS infarction includes hemorrhagic infarctions.
Statistical Analysis Categorical data are presented as absolute numbers and percentages, and continuous data as mean values and standard deviations. To compare variables, we utilized the Student t test, chi square and Fisher exact test, and one-way analysis of variance as appropriate. The effect of the presence of one or more mortality predictor was evaluated utilizing Kaplan–Meier survival curves (from January 2010 to October 2013). Factors were compared using the log-rank test, and a P value less than .01 was considered statistically significant. Multivariate Cox regression analysis with time-dependent covariate data was performed and presented as hazard ratios (HRs) with 95% confidence intervals (CI).
DEMOGRAPHICS AND CO-MORBIDITIES
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Results Table 1 summarizes patient’s characteristics and comorbidities. Mean age was 74 6 8 years; 11% of the Table 1. Patient demographics and comorbidities
Gender Age (y)
INRs, mean 6 SD (min-max) Warfarin indication
Chronic renal failure* Hypertension Diabetes BMI .30 CHF COPD CHD Dilated Cardiomyopathy VHD Previous embolic event LVEF ,36% Progression to permanent AF Presence of a permanent PM Type of AF
CHA2DS2VASc
HAS-BLED
Variable
N (%)
Male 19-49 50-69 70-89 .90
321 (54.5) 6 (1.1) 148 (25.1) 429 (72.8) 7 (1.1) 29 6 5 (6-48)
AF alone AF plus VHD (target INR 5 2.5-3.5)
545 (92) 44 (7.4)
INRs, TTR, and SDINRs The mean %INRs in range was 50.2 6 20.2%, and 17.3% of the population had %INRs in range above 70%. By linear interpolation, the mean TTR was 53% 6 23, and 34.6% of the patients had a TTR above 64%. The mean SDINRs was .84 6 .54, and 38.4% had SDINRs below .79. There was no correlation between the CHA2DS2VASc and the quality of anticoagulation; patients at higher risk had similar TTR or %INRs than those at a lower risk (Fig 1). We could not find a correlation between the SAMe-TT₂R₂ and any of the INR variability variables.
Gender 28 (4.7) 432 (73.3) 109 (18.5) 101 (17.1) 57 (9.7) 34 (5.8) 99 (16.8) 62 (10.5) 150 (25.5) 50 (8.5) 51 (10.5) 127 (24.1) 103 (17.5)
Paroxysmal/ persistent/ permanent At the beginning of the study % 0-1 2 3 4 5 .5 0 1 2 3 .3
population had CHA2DS2Vasc score below 2, and a HAS-BLED score below 3 was observed in 60% of the patients. Chronic kidney disease had a low prevalence (4.7%). Mean follow-up was 1.19 6 1 year.
11/38/50
66 (11.2) 77 (13.1) 185 (31.4) 182 (30.9) 59 (10) 20 (3.4) 14 (2.4) 86 (14.6) 254 (43.1) 195 (33.1) 40 (6.9)
Abbreviations: AF, atrial fibrillation; BMI, body mass index; COPD, chronic obstructive pulmonary disease; CHD, coronary heart disease; CHF, congestive heart failure; INR, international normalized ratio; LVEF, left ventricular ejection fraction; max, maximum; min, minimum; PM, pacemaker; SD, standard deviation; VHD; valvular heart disease with mechanical prosthesis. *Creatinine clearance ,60 mL/minute/1.73 m2.
There was a male predominance in the study population, 319 men (54.1%) versus 270 women (45.9%). Women were older, 74 6 9 years, than men, 70 6 9 years; P 5 .01.
Warfarin Discontinuation Of 598 patients, 139 (22%) discontinued warfarin treatment (defined as no more INRs after October 2011); reasons for discontinuation are displayed in Table 2. The most important cause for discontinuation was death, observed in 49% of this population; in this group, death was attributed to ischemic stroke (10 patients) and hemorrhagic events (hemorrhagic stroke, 6 patients; other hemorrhages, 5 patients; Table 3). The second cause for discontinuation was the use of dabigatran (30%); in this group, only 1 patient died while on this medication. Twenty-seven (4.5%) patients stopped treatment temporarily because of several causes; the most common was their refusal to receive warfarin.
Complications Related to Warfarin Therapy Thirty-seven patients had bleeding complications, 14 patients had severe hemorrhagic complications, 8 had hemorrhagic stroke, and 10 had gastrointestinal bleeding. There was a significant correlation with mortality and hemorrhagic complications. Eighteen patients had an embolic event, and 12 experienced an ischemic stroke.
Mortality Of 589 patients, 68 died during the study period (11.5%), the most frequent causes of death were heart failure (30%), bleeding (17%), and ischemic stroke (15%; Table 3). Patient survival had a significant correlation with TTR, %INRs, and SDINRs. In the Kaplan–Meier analysis,
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Figure 1. Graph bar displaying the TTR (% days in range) and the percentage of INRs in range (y-axis) according to the CHA2DS2VASc category (number of patients in each category, x-axis). The black line represents the SD for each value. We do not observe a correlation as the CHA2DS2VASc increases the TTR or the percentage of INRs in range remains the same or even lower. Comparison showed a significant difference in the means between groups only in the TTR. Abbreviations: INRs, international normalized ratios; SD, standard deviation; TTR, time-in-therapeutic range.
survival curves were significantly different, with cutoff points of TTR above 65%, %INRs above 65%, and SDINRs above .79; log-rank (Mantel–Cox) chi-square, 5.05; P 5 .025; chi-square, 4.49; P 5 .034; and chi-square, 20; P 5 .00001, respectively. Kaplan–Meier survival curves showing mortality differences between CHA2DS2VASc and SDINRs (cutoff .1 and . .79) are shown in Figure 2. In Cox regression with time-varying covariate analysis (Table 4), the association of a low CHA2DS2VASc with SDINRs below .8 was significant with HR of 3.4 (95% CI, 1.5-7.6). Other variables associated with mortality were left ventricular ejection fraction below 35% (HR, 2.5; 95% CI, 1.09-5.77), presence of a permanent pacemaker (HR, 3.4; 95% CI, 1.5-7.6), and obstructive sleep apnea syndrome (HR, 7.5; 95% CI, 1.4-40).
Discussion Hypertension, chronic heart failure, and valvular heart disease are independent risk factors for AF.1 Patients with AF are at high risk of cardiovascular events, and the mortality is twice compared with that in the same population without known AF.1 In our study after multiTable 2. Causes of warfarin therapy discontinuation (n 5 139)
variate analysis, age and gender were not associated with mortality; however, several other recognized risk factors, such as left ventricular ejection fraction less than 35% and chronic obstructive pulmonary disease, were significantly associated with mortality. Monitoring INR variability is recommended to assess anticoagulation quality in patients on warfarin.5-10 The INR variability estimates the deviation of INR from the intended range over time and is based on the hypothesis that patient’s prothrombin time fluctuates all the time, and its value is a risk indicator for thromboembolism and major hemorrhage. In our investigation, the quality of anticoagulation was not satisfactory: only 34% had a TTR above 64%, and 38% SDINRs below .8. We also observed that patients at higher risk had the same anticoagulation quality values that those at a lower risk. Our data demonstrate a real-world scenario: much higher levels were met in other countries with anticoagulation clinics or during an RCT.5,13,14
CHA2DS2VASc and INR Variability Predict Mortality As AF has a higher mortality, detection of variables associated with mortality is obvious. Only anticoagulant therapy has been shown to reduce AF-related deaths.1 Table 3. Cause of death n (%)
n (%) Death Switched to dabigatran (one rivaroxaban) Physician’s (or patient’s) preference Switched to ASA No data available Major bleeding Abbreviation: ASA, acetylsalicylic acid.
68 (49) 40 (30) 14 (10) 7 (5) 6 (4) 4 (2)
Congestive heart failure Ischemic stroke No data Infection Hemorrhagic stroke Other bleeding complications Cancer Other causes
20 (30.8) 10 (15.4) 8 (12.3) 7 (10.8) 6 (9.2) 5 (7.7) 5 (7.7) 4 (6.2)
DEMOGRAPHICS AND CO-MORBIDITIES
Figure 2. Kaplan–Meier survival curves comparing the combination score with a cutoff point of an SD of .8 and a CHA2DS2VASc .1. There is a significant increase in mortality in the group of patients with a high SD and a high CHA2DS2VASc. Abbreviation: SD, standard deviation.
In our study, a CHA2DS2VASc score of 2 or more and INR variability indexes such as a TTR below 65%, the % INRs in range below 70%, and the SDINRs below .8 were Table 4. Cox proportional hazard regression of patient survival with time-varying covariates in our population
Hypertension Diabetes CHF COPD CHD Dilated cardiomyopathy VHD LVEF ,35% Obstructive sleep apnea Chronic kidney disease Progression permanent AF Presence of Permanent PM CHA2DS2VASc 1 SDINRs (cutoff .1 and ..79) HAS-BLED $ 3 TTR ,65% INRs in range ,65% SAMe-TT₂R₂ .2
Hazard ratio
95% Confidence interval
1.4 .6 2.5 1.1 .8 .9 1.2 2.5* 7.5* 1.5 1.0 3.4* 3.5*
(.6-3.3) (.2-1.5) (.9-6.9) (.4-2.7) (.3-1.8) (.3-2.6) (.6-2.5) (1.1-5.7) (1.4-40.2) (.3-6.5) (.5-2.3) (1.5-7.6) (1.7-7.2)
.7 .4 1.5 .9
(.4-1.5) (.1-1.1) (.7-8.6) (.5-1.5)
Abbreviations: AF, atrial fibrillation; COPD, chronic obstructive pulmonary disease; CHD, coronary heart disease; CHF, congestive heart failure; INR, international normalized ratio; LVEF, left ventricular ejection fraction; PM, pacemaker; SD, standard deviation; TTR, time-in-therapeutic range. *Indicates that a significant difference was found.
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associated with higher mortality. Only the SDINRs remained significant after Cox analysis. The ability of the CHA2DS2VASc score to predict cardiovascular events in stable anticoagulated patients with AF has been previously described.1,16 According to a meta-analysis by Hart et al,18 the use of OAC not only reduces stroke compared with placebo or control but also significantly reduces cardiovascular events and mortality.19 The importance of measuring anticoagulation quality to monitor patients on warfarin is well established. The present study confirms the importance to assess INR variability and reveals that the CHA2DS2VASc and the SDINRs alone or in combination are powerful predictors of mortality. Previous observations correlated TTR and INR variability with mortality. Patients who spent at least 70% of time within the therapeutic range had a 79% reduced risk of stroke compared to patients who spent 30% of time or less within range. Mortality rates were also significantly lower with at least 70% of time spent within therapeutic range.1,7,9 In another work, the SDINRs was a better predictor of mortality, stroke, bleeding, and hospitalization than the TTR in patients with AF receiving warfarin therapy.20 Other similar techniques to evaluate INR variability had shown similar results.21 We recommend utilizing the SDINRs because it is easy to calculate and has a powerful prognostic value. To our knowledge, this is the first time that a combination of a thromboembolic risk score and a time-dependent therapeutic variable is used to evaluate mortality, which adds intrinsic value to the equation. However, the usefulness of the INR variability is limited because we will be able to predict complications or even mortality only after several months on warfarin. It appears very reasonable that patients with an increased INR variability should receive non–antivitamin K agents. We could not find a significant relation between the SAMe-TT₂R₂ score and INR variability because we believe that other variables are also involved, particularly related to the patient characteristics and the health team involved.
Limitations A selection bias could be present because we only analyzed selected patients on warfarin and therefore unstable patients from our registry were already selfexcluded before we started the study.
Conclusions INR variability is an extremely useful tool to assess anticoagulation quality, but the SDINRs emerge as a very strong mortality predictor compared with other INR variability indexes. Furthermore, calculation of
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CHA2DS2VASc plus INR variability appears to be extremely useful to predict mortality in patients with AF receiving warfarin. Acknowledgment: G.V. contributed to the concept and design, analysis, and interpretation of data; critical writing and revising of the intellectual content; and also the final approval of the version to be published.
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