Abstract
Background
Thrombocytopenia is associated with increased mortality in the general population, but few data exist in patients with atrial fibrillation (AF) taking oral anticoagulants. We investigated factor determinants of thrombocytopenia in a large cohort of patients affected by AF and its association with total mortality.
Methods and Results
Multicenter prospective cohort study, including 5215 patients with AF from the START (Survey on Anticoagulated Patients Register) registry, 3877 (74.3%) and 1338 (25.7%) on vitamin K or non–vitamin K antagonist oral anticoagulants, respectively. Thrombocytopenia was defined by a platelet count <150×109/L. Determinants of thrombocytopenia were investigated, and all‐cause mortality was the primary survival end point of the study. Thrombocytopenia was present in 592 patients (11.4%). At multivariable logistic regression analysis, chronic kidney disease (odds ratio [OR], 1.257; P=0.030), active cancer (OR, 2.065; P=0.001), liver cirrhosis (OR, 7.635; P<0.001), and the use of diuretics (OR, 1.234; P=0.046) were positively associated with thrombocytopenia, whereas female sex (OR, 0.387; P<0.001) and the use of calcium channel blockers (OR, 0.787; P=0.032) were negatively associated. During a median follow‐up of 19.2 months (9942 patient‐years), 391 deaths occurred (rate, 3.93%/year). Mortality rate increased from 3.8%/year to 9.9%/year in patients with normal platelet count and in those with moderate‐severe thrombocytopenia, respectively (log‐rank test, P=0.009). The association between moderate‐severe thrombocytopenia and mortality persisted after adjustment for CHA 2 DS 2 VASc score (hazard ratio, 2.431; 95% CI, 1.254–4.713; P=0.009), but not in the fully adjusted multivariable Cox regression analysis model.
Conclusions
Thrombocytopenia is common in patients with AF. Despite an increased incidence of mortality, thrombocytopenia was not associated with mortality at multivariable analysis. Thrombocytopenia may reflect the presence of comorbidities associated with poor survival in AF.
Keywords: atrial fibrillation, mortality, thrombocytopenia
Subject Categories: Arrhythmias, Atrial Fibrillation
Clinical Perspective
What Is New?
Thrombocytopenia is common in patients experiencing atrial fibrillation and taking oral anticoagulants.
Platelet count was lower in men than women and decreased by aging, and the presence of chronic kidney disease, active cancer, and liver cirrhosis was associated with thrombocytopenia.
We observed a significant association between moderate‐severe thrombocytopenia and mortality, which persisted after adjustment for CHA2DS2 VASc score.
What Are the Clinical Implications?
Thrombocytopenia may identify a subgroup of patients with atrial fibrillation at higher risk of mortality.
When thrombocytopenia is detected, the presence of comorbidities potentially affecting survival should be investigated.
Introduction
The most common causes of thrombocytopenia in adults include acute and chronic infectious diseases, liver cirrhosis, cancer, and use of drugs like heparin, chemotherapies, antibiotics, and antidiabetic medications.1 In addition, platelet count may be reduced in patients with myelofibrosis or hematologic diseases.
Thrombocytopenia is usually defined as a platelet count <150×109/L, and in the general population, it is associated with an increased risk of mortality.2 Furthermore, the presence of a low platelet count was associated with worse short‐ and long‐term outcomes in patients with acute coronary syndrome or cancer.3, 4
The management of patients with thrombocytopenia requiring oral anticoagulation, such as those with venous thromboembolism or atrial fibrillation (AF), is particularly challenging for the potential risk of bleeding.3, 5 Indeed, anticoagulation is generally contraindicated if platelet count is <50×109/L,6 and patients with platelet count <100×109/L were excluded from recent clinical trials with non–vitamin K antagonist (VKA) oral anticoagulants (NOACs).7, 8, 9, 10 Prevalence and determinants of thrombocytopenia in AF patients are still unclear. In 2 recent studies, the prevalence of thrombocytopenia was highly variable, as it ranged from 6% to 24%.4, 5 Furthermore, follow‐up data about the relationship between thrombocytopenia and mortality in patients with AF were not reported.
On the basis of this, the aim of the present study was to assess prevalence and determinants of thrombocytopenia and its relationship with mortality in a large population of the multicenter cohort START (Survey on Anticoagulated Patients Register) registry.
Methods
Study Population
The authors declare that all supporting data are available within the article. Details of the START registry have been previously described.11 Briefly, the START registry is an observational, multicenter, ongoing cohort study that includes patients (aged ≥18 years) who start anticoagulation therapy (ClinicalTrials.gov NCT02219984). The study protocol was accepted by the Institutional Review Board of each participating center, and informed consent was obtained from patients at enrollment. The present analysis is limited to patients with nonvalvular AF starting oral anticoagulants, either VKAs (warfarin or acenocoumarol) or NOACs. Patients treated with low‐molecular‐weight heparin were excluded.
Patients with a life expectancy <6 months, not residents in the participant region, or planning on leaving in the next 6 months were not included in the registry, as well as patients already enrolled in phase 2 or 3 clinical studies. Patients enrolled in other observational or phase 4 studies were considered eligible for the study.
Thrombocytopenia was defined by a platelet count <150×109/L.12 Primary end point of the study was the occurrence of all‐cause mortality. Data on death were obtained from relatives of patients or from general practitioners. CHA2DS2 VASc [congestive heart failure (1 point), hypertension (1 point), age ≥75 years (2 points), diabetes (1 point), prior stroke (2 points), age 65–74 years (1 point), female sex (1 point), and vascular disease (1 point)] and HAS BLED (hypertension i.e. uncontrolled, abnormal renal/liver function, stroke, bleeding history or predisposition, labile international normalized ratio, age >65 years, drugs/alcohol concomitantly) scores were also calculated. In the HAS BLED, the “L” of labile international normalized ratio was scored 0.
Statistical Analysis
Data are expressed as mean and SD or median and interquartile range, depending on variable distribution. Group comparisons were performed by unpaired Student t test. Proportions and categorical variables were tested by the χ2 test.
We divided patients’ cohort according to the presence of thrombocytopenia (ie, platelet count <150×109/L) and performed a descriptive analysis of characteristics of patients with and without low platelet count.
Multivariable logistic regression analysis was used to investigate factors associated with thrombocytopenia and to estimate the adjusted odds ratio (OR) of each variable.
Variables were categorized or dichotomized for the multivariable model, which included the following covariates: persistent/permanent AF (versus paroxysmal AF), female sex, aged ≥75 years, obesity (body mass index ≥30 kg/m2), chronic kidney disease (creatinine clearance <60 mL/min), active cancer, diabetes mellitus, previous cerebrovascular events, previous cardiovascular disease, heart failure, peripheral artery disease, pulmonary disease, liver cirrhosis, smoking, NOACs use (versus VKAs), antiplatelet drugs, lipid‐lowering drugs, antiarrhythmic drugs, angiotensin‐converting enzyme inhibitors, β blockers, calcium channel blockers, diuretics, nitrate, angiotensin receptor blockers, digoxin, proton pump inhibitors, and xanthine oxidase inhibitors.
Survival analysis was performed to investigate the relationship between thrombocytopenia and all‐cause mortality. For this analysis, patients were divided in 3 groups: normal (>150×109/L), mildly reduced (150–100×109/L), and moderately severely reduced (<100×109/L) platelet count.
The cumulative incidence of all‐cause mortality was estimated using a Kaplan‐Meier product‐limit estimator, and survival curves were formally compared using the log‐rank test. Univariate and multivariate stepwise Cox proportional hazards regression analysis was used to calculate the adjusted relative hazard ratios (HRs) of death by each clinical variable. Three models of survival analysis were built: model A, adjusted for age and sex; model B, adjusted for CHA2DS2 VASc score; and model C, fully adjusted.
All tests were 2 tailed, and P<0.05 was considered statistically significant. Analyses were performed using computer software (IBM SPSS 23 Inc).
Results
The cohort was composed of 5236 patients with AF; 4 patients had missing data, and 17 patients taking low‐molecular‐weight heparin were excluded. Thus, the analysis was performed in 5215 patients. Of these patients, 3877 (74.3%) were taking VKAs, and 1338 (25.7%) NOACs: 469 taking dabigatran, 478 taking apixaban, 379 taking rivaroxaban, and 12 taking edoxaban.
Characteristics of patients are reported in Table 1. The mean age was 75.0±9.6 years, and 2368 (45.4%) were women. Overall, thrombocytopenia was present in 592 patients (11.4%) (Table 1). Of these patients, 10.4% had mild and 0.96% had moderate‐severe thrombocytopenia. Patients with thrombocytopenia were older; they were more likely to have persistent/permanent AF, active cancer, and liver cirrhosis; and more of them were treated with calcium channel blockers, nitrate, diuretics, and xanthine oxidase inhibitors. A trend for higher use of lipid‐lowering drugs and proton pump inhibitors and diabetes mellitus was also found (Table 1). Among antiarrhythmic drugs, 147 were treated with propafenone, 258 were treated with flecainide, 674 were treated with amiodarone, and 229 were treated with other drugs (dronedarone/unknown).
Table 1.
Characteristics of Patients With AF, According to the Presence of Thrombocytopenia
| Characteristics | All Cohort (n=5215) | Normal Platelet Count (n=4623) | Thrombocytopenia (n=592) | P Value |
|---|---|---|---|---|
| Persistent/permanent AF | 3282 (62.9) | 2883 (62.4) | 399 (67.4) | 0.017 |
| Women | 2368 (45.4) | 2207 (47.7) | 161 (27.2) | <0.001 |
| Age, y | 75.0±9.6 | 74.9±9.7 | 75.6±9.2 | 0.115 |
| Aged ≥75 y | 3051 (58.5) | 2692 (58.2) | 359 (60.6) | 0.268 |
| BMI, kg/m2 | 26.8±4.7 | 26.8±4.7 | 27.0±4.6 | 0.505 |
| Obesity (BMI ≥30 kg/m2) | 1101 (21.1) | 974 (21.1) | 127 (21.5) | 0.831 |
| Creatinine clearance, mL/min | 66.8±28.3 | 66.9±28.2 | 65.9±29.0 | 0.420 |
| CKD (creatinine clearance <60 mL/min) | 2357 (45.2) | 2075 (44.9) | 282 (47.6) | 0.219 |
| Active cancer | 134 (2.6) | 104 (2.2) | 30 (5.1) | <0.001 |
| Hypertension | 4182 (80.2) | 3694 (79.9) | 488 (82.4) | 0.155 |
| Diabetes mellitus | 1048 (20.1) | 911 (19.7) | 137 (23.1) | 0.056 |
| Previous cerebrovascular events | 857 (16.4) | 765 (16.5) | 92 (15.5) | 0.556 |
| Previous cardiovascular disease | 966 (18.5) | 817 (17.7) | 149 (25.2) | <0.001 |
| Heart failure | 808 (15.5) | 706 (15.3) | 102 (17.2) | 0.227 |
| Peripheral artery disease | 332 (6.4) | 289 (6.3) | 43 (7.3) | 0.326 |
| Pulmonary disease | 655 (12.6) | 580 (12.5) | 75 (12.7) | 0.947 |
| Liver cirrhosis | 27 (0.5) | 13 (0.3) | 14 (2.4) | <0.001 |
| Smoking | 688 (13.2) | 609 (13.2) | 79 (13.3) | 0.897 |
| CHA2DS2 VASc score | 3.6±1.5 | 3.6±1.5 | 3.6±1.4 | 0.795 |
| HAS BLED score | 1.27±0.73 | 1.26±0.73 | 1.35±0.73 | 0.010 |
| Anticoagulant drugs | 0.294 | |||
| VKAs | 3877 (74.3) | 3426 (74.1) | 451 (76.2) | |
| NOACs | 1338 (25.7) | 1197 (25.9) | 141 (23.8) | |
| Dabigatran | 469 (9.0) | 416 (9.0) | 53 (9.0) | |
| Apixaban | 478 (9.2) | 424 (9.2) | 54 (9.1) | |
| Rivaroxaban | 379 (7.3) | 345 (7.5) | 34 (5.7) | |
| Edoxaban | 12 (0.2) | 12 (0.3) | 0 (0.0) | |
| Antiplatelet drugs | 646 (12.4) | 560 (12.1) | 86 (14.5) | 0.098 |
| Aspirin | 507 (9.7) | 444 (9.6) | 63 (10.6) | 0.418 |
| Others | 205 (3.9) | 175 (3.8) | 30 (5.1) | 0.143 |
| Lipid‐lowering drugs | 1803 (34.6) | 1580 (34.2) | 223 (37.7) | 0.098 |
| Antiarrhythmic drugs | 1308 (25.1) | 1162 (25.1) | 146 (24.7) | 0.840 |
| ACE inhibitors | 1501 (28.8) | 1318 (28.5) | 183 (30.9) | 0.228 |
| β Blockers | 2745 (52.6) | 2421 (52.4) | 324 (54.7) | 0.294 |
| Calcium channel blockers | 1197 (23.0) | 1075 (23.3) | 122 (20.6) | 0.161 |
| Diuretics | 1880 (36.0) | 1634 (35.3) | 246 (41.6) | 0.004 |
| Nitrate | 260 (5.0) | 219 (4.7) | 41 (6.9) | 0.027 |
| Angiotensin receptor blockers | 1191 (22.8) | 1051 (22.7) | 140 (23.6) | 0.640 |
| Digoxin | 480 (9.2) | 427 (9.2) | 53 (9.0) | 0.880 |
| Proton pump inhibitors | 2384 (45.7) | 2093 (45.3) | 291 (49.2) | 0.080 |
| Xanthine oxidase inhibitors (allopurinol and febuxostat) | 386 (7.4) | 329 (7.1) | 57 (9.6) | 0.037 |
Data are given as number (percentage) or mean±SD. ACE indicates angiotensin‐converting enzyme; AF, atrial fibrillation; BMI, body mass index; CKD, chronic kidney disease; NOAC, non‐VKA oral anticoagulant; VKA, vitamin K antagonist.
The CHA2DS2 VASc score was similar between the 2 groups, whereas the HAS BLED score was significantly higher in patients with thrombocytopenia (Table 1).
Women were less likely to have thrombocytopenia compared with men (Table 1). Thus, median platelet count was significantly lower in men than women, independently from aging (Table 2). In particular, in male but not female patients, a significant decrease in platelet count was found according to age group (Table 2).
Table 2.
Median (Interquartile Range) Platelet Count, According to Age and Sex Groups
| Variable | Men | Women | P Value (Between Sex Groups) |
|---|---|---|---|
| Age below median (≤75 y) | 206 (173–246) | 229 (195–276) | <0.001 |
| Age above median (>75 y) | 196 (163–240) | 225 (188–272) | <0.001 |
| P value (between age groups) | <0.001 | 0.201 | … |
Platelet count is given as number×109/L.
At multivariable logistic regression analysis, chronic kidney disease (OR, 1.257; P=0.030), active cancer (OR, 2.065; P=0.001), liver cirrhosis (OR, 7.635; P<0.001), and the use of diuretics (OR, 1.234; P=0.046) were positively associated with thrombocytopenia, whereas female sex (OR, 0.387; P<0.001) and calcium channel blockers (OR, 0.787; P=0.032) were negatively associated (Table 3).
Table 3.
Multivariable Logistic Regression Analysis of Factors Associated With Thrombocytopenia (Platelet Count <150×109/L)
| Variable | Odds Ratio | 95% CI | P Value | |
|---|---|---|---|---|
| Lower | Upper | |||
| Persistent/permanent AF (vs paroxysmal) | 1.156 | 0.956 | 1.398 | 0.135 |
| Female sex | 0.387 | 0.316 | 0.475 | <0.001 |
| Aged ≥75 y | 1.077 | 0.879 | 1.319 | 0.476 |
| Obesity (BMI ≥30 kg/m2) | 1.090 | 0.869 | 1.368 | 0.456 |
| CKD (creatinine clearance <60 mL/min) | 1.257 | 1.022 | 1.547 | 0.030 |
| Active cancer | 2.065 | 1.341 | 3.177 | 0.001 |
| Diabetes mellitus | 1.080 | 0.868 | 1.344 | 0.492 |
| Previous cerebrovascular events | 0.930 | 0.728 | 1.187 | 0.559 |
| Previous cardiovascular disease | 1.235 | 0.965 | 1.580 | 0.093 |
| Heart failure | 0.924 | 0.714 | 1.196 | 0.550 |
| Peripheral artery disease | 0.994 | 0.703 | 1.407 | 0.975 |
| Pulmonary disease | 0.864 | 0.658 | 1.136 | 0.295 |
| Liver cirrhosis | 7.635 | 3.458 | 16.854 | <0.001 |
| Smoking | 0.829 | 0.638 | 1.078 | 0.162 |
| NOAC use (vs VKAs) | 0.897 | 0.728 | 1.106 | 0.309 |
| Antiplatelet drugs | 0.934 | 0.710 | 1.229 | 0.626 |
| Lipid‐lowering drugs | 1.014 | 0.825 | 1.248 | 0.892 |
| Antiarrhythmic drugs | 1.035 | 0.840 | 1.275 | 0.747 |
| ACE inhibitors | 1.056 | 0.860 | 1.298 | 0.601 |
| β Blockers | 1.023 | 0.850 | 1.231 | 0.808 |
| Calcium channel blockers | 0.787 | 0.632 | 0.979 | 0.032 |
| Diuretics | 1.234 | 1.004 | 1.517 | 0.046 |
| Nitrate | 1.191 | 0.819 | 1.732 | 0.359 |
| Angiotensin receptor blockers | 1.090 | 0.873 | 1.361 | 0.446 |
| Digoxin | 1.022 | 0.745 | 1.403 | 0.893 |
| Proton pump inhibitors | 1.057 | 0.877 | 1.274 | 0.562 |
| Xanthine oxidase inhibitors | 1.076 | 0.788 | 1.468 | 0.645 |
ACE indicates angiotensin‐converting enzyme; AF, atrial fibrillation; BMI, body mass index; CKD, chronic kidney disease; NOAC, non‐VKA oral anticoagulant; VKA, vitamin K antagonist.
Survival Analysis
Median follow‐up was 19.2 (interquartile range, 8.8–35.4) months, yielding 9942 patient‐years of observation; 391 deaths were registered with an annual incidence rate of 3.93% (95% CI, 3.6%–4.3%). Incidence of mortality increased from 3.8%/year in patients with normal platelet count to 9.9%/year in those with moderate‐severe thrombocytopenia (Table 4).
Table 4.
Annual Incidence Rates of Mortality and Univariate HR, According to Thrombocytopenia Groups
| Variable | No. of Deaths/No. of Patients | Annual Incidence Rate (95% CI) | P Value | Univariate HR (95% CI) | P Value |
|---|---|---|---|---|---|
| Normal platelet count (>150×109/L) | 334/4623 | 3.8 (3.4–4.2) | Reference | Reference | Reference |
| Mild thrombocytopenia (150–100×109/L) | 48/542 | 4.6 (3.4–6.1) | 0.230 | 1.201 (0.888–1.626) | 0.235 |
| Moderate‐severe thrombocytopenia (<100×109/L) | 9/50 | 9.9 (4.5–18.8) |
0.003a
0.029b |
2.558 (1.320–4.961) | 0.005 |
HR indicates hazard ratio.
vs normal platelet count.
vs mild thrombocytopenia.
Kaplan‐Meier curves showed a significant decrease of survival across the 3 groups of thrombocytopenia (log‐rank test, P=0.009; Figure). Univariate Cox regression analysis showed that moderate‐severe, but not mild, thrombocytopenia was associated with mortality (Table 4). Among antiarrhythmic drugs, we found that propafenone (univariate HR, 0.339; 95% CI, 0.126–0.908; P=0.031) and flecainide (n=258; univariate HR, 0.370; 95% CI, 0.183–0.747; P=0.006), but not amiodarone (n=674; univariate HR, 0.865; 95% CI, 0.640–1.169; P=0.344) or other antiarrhythmic drugs (n=229 dronedarone/unknown; univariate HR, 0.692; 95% CI, 0.412–1.162; P=0.164), were associated with mortality. However, given the low number of deaths in each group (4 in the propafenone group, 8 in the flecainide group, 49 in the amiodarone group, and 15 in the other group), antiarrhythmic drugs were grouped for multivariable analysis.
Figure 1.
Kaplan‐Meier curves for risk of mortality, according to the presence of thrombocytopenia.
The association between moderate‐severe thrombocytopenia and mortality persisted after adjustment for age and sex (Table 5, model A) and CHA2DS2 VASc score (Table 5, model B). However, it was no longer significant at fully adjusted multivariable Cox regression analysis (Table 5, model C): HR, 1.147 (95% CI, 0.840–1.566; P=0.390) for platelet count 150 to 100×109/L; and HR, 1.712 (95% CI, 0.873–3.3354; P=0.117) for platelet count <100×109/L versus normal platelet count. All significant predictors of mortality are reported in Table 5.
Table 5.
Cox Proportional Hazards Regression Analysis of Factors Associated With All‐Cause Mortality
| Variable | HR | 95% Confidence Interval | P Value | |
|---|---|---|---|---|
| Lower | Upper | |||
| Model A (adjusted for age and sex) | ||||
| Mild thrombocytopenia | 1.169 | 0.859 | 1.591 | 0.320 |
| Moderate‐severe thrombocytopenia | 2.232 | 1.147 | 4.342 | 0.018 |
| Sex | 0.841 | 0.686 | 1.032 | 0.097 |
| Age | 1.134 | 1.116 | 1.152 | <0.001 |
| Model B (adjusted for CHA2DS2 VASc score) | ||||
| Mild thrombocytopenia | 1.259 | 0.930 | 1.704 | 0.136 |
| Moderate‐severe thrombocytopenia | 2.431 | 1.254 | 4.713 | 0.009 |
| CHA2DS2 VASc score | 1.342 | 1.257 | 1.433 | <0.001 |
| Model C (stepwise fully adjusted) | ||||
| Aged ≥75 y | 2.339 | 1.730 | 3.163 | <0.001 |
| Chronic kidney disease (Cr Cl <60 mL/min) | 2.372 | 1.854 | 3.035 | <0.001 |
| Active cancer | 2.855 | 1.869 | 4.360 | <0.001 |
| Diabetes mellitus | 1.315 | 1.035 | 1.671 | 0.025 |
| Heart failure | 1.382 | 1.072 | 1.781 | 0.013 |
| Pulmonary disease | 1.513 | 1.180 | 1.941 | 0.001 |
| Previous cardiovascular disease | 1.351 | 1.047 | 1.744 | 0.021 |
| Peripheral artery disease | 1.845 | 1.345 | 2.531 | <0.001 |
| Antiarrhythmic drugs | 0.764 | 0.593 | 0.984 | 0.037 |
| Lipid‐lowering drugs | 0.608 | 0.477 | 0.774 | <0.001 |
| Diuretics | 1.521 | 1.222 | 1.894 | <0.001 |
| Angiotensin receptor blockers | 0.769 | 0.598 | 0.989 | 0.041 |
Cr Cl indicates creatinine clearance.
Thrombocytopenia and Bleeding
During follow‐up, 133 major bleeding events were reported. Univariate Cox regression analysis found that moderate‐severe thrombocytopenia resulted in a significant association with major bleeding (HR, 3.699; 95% CI, 1.170–11.692; P=0.026). This association was not evident for mild thrombocytopenia (HR, 1.218; 95% CI, 0.700–2.118; P=0.486).
Discussion
The study shows a relatively high prevalence of thrombocytopenia in AF patients on treatment with oral anticoagulants. The incidence of mortality increased with the severity of thrombocytopenia and persisted after adjustment for CHA2DS2 VASc score.
The present study reports a prevalence of thrombocytopenia of 11.4%, which is in between the prevalence reported in previous studies.4, 5 For the study that reported a prevalence of 5.7% of white patients, it is possible that the difference in age of the population could account for the different results; thus, the mean age of the cohort of Yadav et al. was lower than that of our study (mean, 65 versus 75 years, respectively).4 Conversely, a significantly higher prevalence of thrombocytopenia of 24.2% has been reported in the Korean population,5 despite a significantly lower prevalence of comorbidities, such as hypertension, chronic kidney disease, and previous cerebrovascular events, compared with the present cohort. Another large nationwide study, including 8478 middle‐aged participants without cardiovascular risk factors, reported a prevalence of thrombocytopenia of 16.5%.13
We found that chronic kidney disease, active cancer, and liver cirrhosis, which are frequent features of patients with AF,14 were significantly associated with thrombocytopenia; this is in accordance with previous reports in different clinical settings.15 In addition, we found a sex‐based difference in platelet count, with women having mean higher platelet count than men. This difference was evident both in younger (aged ≤75 years) and elderly (aged >75 years) patients. This finding is in keeping with a previous study on a large sample of the Italian general population,16 showing higher platelet count in women than men. In the same study, a decrease in platelet count by aging was present both in men and women, whereas we found a decrease of platelet count according to age in men but not in women.
A mortality rate of 3.93%/year was registered in the present study, which is substantially in line with previous studies reporting an incidence of mortality ranging from 2.19%17 to 5.15%.18, 19, 20 At survival analysis, we found a progressive increase of mortality rate from 3.8%/year in patients with normal platelet count to 4.6% and 9.9% in patients with mild and moderate‐severe thrombocytopenia, respectively. This association persisted after adjustment for CHA2DS2 VASc score but was lost at fully adjusted multivariable hazard Cox regression analysis. This suggests that some risk factors not currently used for thromboembolic risk stratification, such as chronic liver and kidney disease or active cancer, may be associated with thrombocytopenia. These factors should be evaluated in patients presenting with thrombocytopenia.
Thrombocytopenia has also been proposed as a risk factor for mortality in other clinical cardiovascular settings, such as patients experiencing an acute ischemic stroke,21 a myocardial infarction,22 or undergoing percutaneous coronary intervention.23 However, mechanisms underlying this association have not been explored. Beyond platelet count, an important factor to be considered is platelet function, which may be increased by aging and cardiovascular risk factors.24 Thus, in a previous study, patients with AF presenting with an increased urinary excretion of thromboxane B2, a marker of systemic platelet activation, experienced a higher rate of cardiovascular events, independently from platelet count.25
Another interesting finding of the study is the inverse association between antiarrhythmic drugs and mortality. In particular, univariate analysis showed that propafenone and flecainide, but not amiodarone, were associated with a lower mortality rate. However, the low number of deaths in each group of antiarrhythmic users did not allow us to explore the association between mortality and single drugs. The association between antiarrhythmic drugs and relevant clinical outcomes, such as thromboembolism, heart failure, ischemic heart disease, and cardiovascular mortality, needs further research, mostly considering the potential adverse effects related to the use of these drugs.26, 27
The studys has implications and limitations. The presence of thrombocytopenia in AF should be regarded as a marker of coexistence of comorbidities associated with poor survival. The reasons for men having less platelet count with a decline according to age should be further investigated. Another limitation of the study is the lack of information on the quality of anticoagulation in patients treated with VKAs. Finally, data reflect a cohort representative of the Italian population and cannot be transferred to another population. Furthermore, to better understand the role of thrombocytopenia in patients with AF taking oral anticoagulants, the association between thrombocytopenia and other end points, such as cardiovascular events and bleeding, should be further explored.
In conclusion, thrombocytopenia is frequent in patients with AF receiving treatment with oral anticoagulants. Despite an increased risk of mortality, thrombocytopenia may not represent per se a risk factor for mortality but may rather mirror the presence of comorbidities associated with poor survival.
Appendix
START2 Registry Investigators
Sophie Testa, Oriana Paoletti, UO Laboratorio Analisi, Centro Emostasi e Trombosi A O Istituti Ospitalieri di Cremona, Cremona; Benilde Cosmi, Giuliana Guazzaloca, Ludovica Migliaccio, UO di Angiologia e Malattie Coagulazione, AOU S Orsola‐Malpighi, Bologna, Bologna; Daniela Poli, Rossella Marcucci, Niccolò Maggini, SOD Malattie Aterotrombotiche, Azienda Ospedaliero Universitaria‐Careggi, Firenze; Vittorio Pengo, Dipartimento di Scienze Cardio‐Toraco‐Vascolari, Centro Trombosi, AOU Padova, Padova; Anna Falanga, Teresa Lerede, USC SIMT, Centro Emostasi e Trombosi, Ospedale Papa Giovanni XXIII, Bergamo; Lucia Ruocco, UO Analisi Chimico‐Cliniche, Azienda Ospedaliero Universitaria Pisana, Pisa; Giuliana Martini, Centro Emostasi, Spedali Civili Di Brescia, Brescia; Simona Pedrini, Federica Bertola, Servizio di Laboratorio, Istituto Ospedaliero Fondazione Poliambulanza Brescia; Lucilla Masciocco, Pasquale Saracino, Angelo Benvenuto, UOC Medicina Interna, Centro Controllo Coagulazione, Presidio Ospedaliero Lastaria, Lucera (Foggia); Claudio Vasselli, Laboratorio Patologia Clinica, Policlinico Casilino, Roma; Francesco Violi, Pasquale Pignatelli, Daniele Pastori, Centro Trombosi, Clinica Medica Policlinico Umberto I, Università la Sapienza Roma; Elvira Grandone, Donatella Colaizzo, Centro Trombosi Casa del Sollievo e della Sofferenza, S Giovanni Rotondo (Foggia); Marco Marzolo, UOC Medicina Interna, Ospedale di Rovigo; Mauro Pinelli, Daniela Mastroiacovo, UOSD Angiologia e Diagnostica Vascolare, Ospedale SS Filippo e Nicola, Avezzano (L'Aquila); Walter Ageno, Giovanna Colombo, UO Medicina I, Ospedale di Circolo, Varese; Eugenio Bucherini, SS Medicina Vascolare‐Angiologia, Ambulatorio Anticoagulanti, Ospedale Civile di Faenza, Faenza (Ravenna); Domizio Serra, Centro Trombosi, Ospedale Evangelico Internazionale, Genova; Andrea Toma, Pietro Barbera, UOC di Patologia Clinica, Ambulatorio Terapia Anticoagulante Orale, OC “L.Cazzavillan” Arzignano, (Vicenza); Carmelo Paparo, Patologia Clinica, Ospedale Maggiore Chieri (Torino); Antonio Insana, SC Patologia Clinica, Ospedale Santa Croce Moncalieri, Moncalieri (Torino); Serena Rupoli, Clinica Ematologica, AOU‐Ospedali Riuniti Ancona, Ancona; Giuseppe Malcangi, Centro Emofilia e Trombosi, Policlinico di Bari, Bari; Maddalena Loredana Zighetti, SIMT‐AO San Paolo, Milano; Catello Mangione, Sezione Trasfusionale Ospedale di Galatina, Galatina (Lecce); Domenico Lione, UOC Patologia Clinica, Ospedale Perrino, Brindisi; Paola Casasco, Servizio Medicina Trasfusionale Tortona (Alessandria); Giovanni Nante, UOS Geriatria ULSS 16 Padova, Padova; Alberto Tosetto, Divisione di Ematologia, Ospedale San Bortolo, Vicenza; Vincenzo Oriana, Centro Emofilia, Presidio Ospedaliero Morelli‐Reggio Calabria; Nicola Lucio Liberato, UO Medicina Interna Ospedale di Casorate Primo, Pavia.
Disclosures
None.
(J Am Heart Assoc. 2019;8:e012596 DOI: 10.1161/JAHA.119.012596.)
Contributor Information
Francesco Violi, Email: francesco.violi@uniroma1.it.
the START2 Registry Investigators:
Sophie Testa, Oriana Paoletti, Benilde Cosmi, Giuliana Guazzaloca, Ludovica Migliaccio, Daniela Poli, Rossella Marcucci, Niccolò Maggini, Vittorio Pengo, Anna Falanga, Teresa Lerede, Lucia Ruocco, Giuliana Martini, Simona Pedrini, Federica Bertola, Lucilla Masciocco, Pasquale Saracino, Angelo Benvenuto, Claudio Vasselli, Francesco Violi, Pasquale Pignatelli, Daniele Pastori, Elvira Grandone, Donatella Colaizzo, Marco Marzolo, Mauro Pinelli, Walter Ageno, Giovanna Colombo, Eugenio Bucherini, Domizio Serra, Andrea Toma, Pietro Barbera, Carmelo Paparo, Antonio Insana, Serena Rupoli, Giuseppe Malcangi, Maddalena Loredana Zighetti, Catello Mangione, Domenico Lione, Paola Casasco, Giovanni Nante, Alberto Tosetto, Vincenzo Oriana, and Nicola Lucio Liberato
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