Author + information
- Received August 20, 2017
- Revision received November 25, 2017
- Accepted December 18, 2017
- Published online February 26, 2018.
- Seoyoung C. Kim, MD, ScD, MSCEa,b,∗ (, )
- Tuhina Neogi, MD, PhDc,
- Eun Ha Kang, MD, PhD, MPHa,d,
- Jun Liu, MD, MPHa,
- Rishi J. Desai, PhDa,
- MaryAnn Zhang, MDb and
- Daniel H. Solomon, MD, MPHa,b
- aDivision of Pharmacoepidemiology and Pharmacoeconomics, Brigham and Women’s Hospital, Boston, Massachusetts
- bDivision of Rheumatology, Immunology and Allergy, Brigham and Women’s Hospital, Boston, Massachusetts
- cDivision of Rheumatology, Boston University, Boston, Massachusetts
- dDivision of Rheumatology, Department of Internal Medicine, Seoul National University Bundang Hospital, Seongnam, South Korea
- ↵∗Address for correspondence:
Dr. Seoyoung C. Kim, Division of Pharmacoepidemiology and Pharmacoeconomics; Brigham and Women’s Hospital, 1620 Tremont Street, Suite 3030, Boston, Massachusetts 02120.
Background Patients with gout are at an increased risk of cardiovascular (CV) disease including myocardial infarction (MI), stroke, and heart failure (HF).
Objectives The authors conducted a cohort study to examine comparative CV safety of the 2 gout treatments—probenecid and allopurinol—in patients with gout.
Methods Among gout patients ≥65 years of age and enrolled in Medicare (2008 to 2013), those who initiated probenecid or allopurinol were identified. The primary outcome was a composite CV endpoint of hospitalization for MI or stroke. MI, stroke, coronary revascularization, HF, and mortality were assessed separately as secondary outcomes. The authors estimated the incidence rate and hazard ratio of the primary and secondary outcomes in the 1:3 propensity score–matched cohort of probenecid and allopurinol initiators.
Results A total of 9,722 probenecid initiators propensity score–matched to 29,166 allopurinol initiators with mean age of 76 ± 7 years, and 54% males were included. The incidence rate of the primary composite endpoint of MI or stroke per 100 person-years was 2.36 in probenecid and 2.83 in allopurinol initiators with a hazard ratio of 0.80 (95% confidence interval: 0.69 to 0.93). In the secondary analyses, probenecid was associated with a decreased risk of MI, stroke, HF exacerbation, and mortality versus allopurinol. These results were consistent in the subgroup analyses of patients without baseline CV disease or those without baseline chronic kidney disease.
Conclusions In this large cohort of 38,888 elderly gout patients, treatment with probenecid appears to be associated with a modestly decreased risk of CV events including MI, stroke, and HF exacerbation compared with allopurinol.
Gout is the most common inflammatory arthritis with an increasing prevalence in many countries including the United States (1). It is caused by hyperuricemia leading to crystallization of uric acid within the joints and periarticular tissues (2). Urate crystals then activate the NLRP3 inflammasome (i.e., cryopyrin) resulting in the production of interleukin (IL)-1β (3). Overproduction of urate or underexcretion of urate through the kidneys leads to hyperuricemia. Allopurinol, a xanthine oxidase inhibitor, is the mainstay of treatment for gout and can be used in patients who overproduce or underexcrete urate. Probenecid is another treatment option, which has been available for gout for many decades. Probenecid inhibits organic acid reabsorption in the renal proximal tubule, causing the excretion of uric acid through the kidneys; it is not recommended in patients with overproduction of uric acid (2,4,5).
It is well known that patients with gout are at an increased risk of cardiovascular (CV) disease (CVD) including myocardial infarction (MI), stroke, and heart failure (HF) (6–8). Although controversies still exist whether uric acid plays a causal role in the development of CVD, beneficial effects of allopurinol on lowering blood pressure and improving endothelial function and metabolic profile have been reported (9–11). A randomized controlled trial in high-risk HF patients, the EXACT-HF (Xanthine Oxidase Inhibition for Hyperuricemic Heart Failure Patients) study, allopurinol did not, however, improve the composite clinical endpoint related to HF (12). Observational cohort studies have shown conflicting results with regard to effect of xanthine oxidase inhibitors, mainly allopurinol, on reducing the risk of future CVD (13–15). However, no data exist with regard to the effect of probenecid on CVD among gout patients. Probenecid is not only a competitive inhibitor of the organic anion transporter (5,16), but also an inhibitor of pannexin 1 channels—an ATP release channel—involved in the activation of the inflammasome which releases IL-1β (17). Therefore, probenecid may exhibit beneficial effects in gout by lowering serum uric acid levels and reducing systemic inflammation through the inhibition of pannexin 1 channels and reduced production of IL-1β (17). IL-1β is also known to play a pivotal role in the pathogenesis of atherosclerosis (18). Furthermore, probenecid may have an effect on CV risk as a potent and selective agonist of transient receptor potential vanilloid 2 (TRPV2) channels (19,20). TRPV2 is expressed in cardiomyocytes, and several experimental studies found an inotropic effect of probenecid (19,21–23). Therefore, it is plausible to hypothesize that probenecid may have cardioprotective effects in gout patients.
The primary objective of this study was, therefore, to compare the risk of CV events including MI or stroke in patients with gout initiating probenecid versus allopurinol in a population representative cohort. We also assessed the risk of other CV endpoints including coronary revascularization and HF, and all-cause mortality in patients with gout initiating probenecid versus allopurinol.
We used claims data from Medicare Parts A, B, and D for the period from 2008 through 2013. Medicare is a federally funded program and provides health care coverage for nearly all legal residents of the United States ≥65 years of age and selected disabled populations <65 years of age. Medicare Part A generally covers inpatient care, Part B is for outpatient medical services including some drugs given in a physician’s office or clinic, and Part D provides outpatient prescription drug coverage (24). Because the Medicare database does not contain laboratory results, we used Medicare data linked with the Brigham and Women’s Hospital’s electronic medical record (EMR) database (2007 to 2013) to select a subgroup of gout patients enrolled in Medicare who had laboratory test results such as serum uric acid and creatinine levels. The study protocol was approved by the Institutional Review Board of the Brigham and Women’s Hospital, which granted a waiver of informed consent.
We identified adults age 65 years or older who had ≥1 International Classification of Diseases-9th Revision (ICD-9) code for gout (274.x). Use of probenecid or allopurinol was identified through national drug codes. Patients who were continuously enrolled in the Medicare Parts A, B, and D for ≥1 year before the first dispensing date (i.e., index date) of probenecid or allopurinol were selected as probenecid or allopurinol initiators (Figure 1). Probenecid initiators were required to be naive to probenecid for the 1-year baseline period before the index date. Similarly, allopurinol initiators were required to be naive to allopurinol for the same baseline period. Patients who started both drugs at the same date were excluded. To assess patients’ baseline characteristics adequately, we excluded patients with no active claim in 1 year before the index date. We further excluded patients who used pegloticase or rasburicase, 2 drugs used in severe refractory gout, or had a diagnosis of end-stage renal disease or dialysis at baseline to minimize confounding by the severity of gout and renal function at baseline. For the subgroup in the linked Medicare-EMR database, we applied the same inclusion and exclusion criteria as in the preceding text, and additionally required them to have ≥1 measurement for serum uric acid and serum creatinine level before the index date.
For the primary as-treated analysis, study subjects were followed up from the day after the index date until the earliest event of the following: 1) death; 2) outcome occurrence; 3) end of study database period; 4) insurance disenrollment; 5) nursing home admission; or 6) 30 days (grace period) after the last drug available date due to drug discontinuation or switching to the other drug. Last drug available date was defined as the last drug dispensing date plus days of supply of the exposure drug.
For the secondary intention-to-treat (ITT) analysis, patients were followed up from the day after the index date to the earliest occurrence of the following: 1) death; 2) outcome occurrence; 3) end of study database period; 4) insurance disenrollment; 5) nursing home admission; or 6) 366th day after the index date.
The primary outcome of interest was a composite CV endpoint of hospitalization for MI or stroke for any length of stay. Secondary outcomes included MI, stroke, coronary revascularization, new-onset HF, and HF exacerbation all based on hospital discharge diagnosis codes, and all-cause deaths. Coronary revascularization was identified using ICD-9 procedure codes, Current Procedural Terminology codes, or diagnosis-related group codes. These claims-based algorithms for these CV outcomes had positive predictive values of ≥90% (25–27).
During the 1-year baseline period before initiation of probenecid or allopurinol (i.e., index date), we assessed more than 65 variables potentially associated with severity of gout and CV risk. These variables were demographics, the index year, regions, CVD, chronic kidney disease (CKD), and other comorbidities, gout-related medications such as glucocorticoids, colchicine, or nonsteroidal anti-inflammatory drugs (NSAIDs) including both nonselective NSAIDs and selective cyclooxygenase-2 inhibitors, other medications, physician orders of outpatient laboratory tests, and markers of health care utilization intensity (list of covariates in Table 1). History of any CVD and recent (within 60 days before the index date) CVD were defined as having an inpatient or outpatient diagnosis of MI, coronary artery disease, coronary revascularization, or stroke, or transient ischemic attack before the index date. To further assess patients’ comorbidity burden, we calculated the combined Comorbidity Score that included 47 conditions in the Charlson and Elixhauser measures (28). We also collected data on the starting daily dose of probenecid or allopurinol in the study population. For the subgroup in the linked Medicare-EMR database, we additionally assessed their baseline serum uric acid and creatinine levels.
We assessed patients’ baseline characteristics by cross-tabulation. To control for over 65 potential baseline confounders simultaneously, we used propensity score (PS) matching (29). We defined the PS as the predicted probability of a patient starting probenecid versus allopurinol given patient characteristics at baseline. The PS was estimated using multivariable logistic regression that included all the covariates listed in Table 1 and the index year (C-statistic = 0.7). Probenecid and allopurinol initiators were matched with a fixed ratio of 1:3 implementing the nearest neighbor matching with a matching caliper of 0.05 on the PS scale (30,31). The variables with the standardized differences <10% between the 2 groups were considered well-balanced after PS matching (31,32).
For the primary as-treated analysis, we calculated the incidence rates (IRs) with 95% confidence intervals (CIs) for the primary and secondary outcomes in the PS-matched cohort. For the HF exacerbation outcome, only patients with a history of HF at baseline were analyzed. For the new-onset HF outcome, patients with no baseline HF were examined. Cumulative incidence plots between treatment groups were compared. Cox proportional hazards regression models estimated the hazard ratio (HR) with 95% CI for the primary and secondary outcomes in the probenecid group versus the allopurinol group.
We evaluated whether the initial daily dose of probenecid or allopurinol was titrated up during the follow-up time as recommended by the American College of Rheumatology guidelines for management of gout (4). The daily dose for a given prescription was calculated as the number of pills or tablets prescribed multiplied by the strengths of the pills or tablets divided by the days’ supply. To estimate patients’ adherence to treatment with probenecid or allopurinol, we calculated a proportion of days covered as the number of days covered by dispensed prescriptions × 100 divided by the total number of days of follow-up for each patient. For the secondary ITT analysis, IR and HR were calculated for the primary outcome.
Pre-specified subgroup analyses stratified by the baseline CVD status were performed. In addition, because CKD is considered one of the most important confounders by indication between the 2 drugs, we conducted a subgroup analysis in the 1:3 PS-matched cohort of patients with no diagnosis of CKD at baseline.
To minimize potential bias due to differences in the follow-up time between the PS-matched groups, we also conducted a sensitivity analysis where Cox proportional hazards models stratified on PS-matching sets (i.e., 1 probenecid initiators matched with 3 allopurinol initiators) estimated the HR of the primary or secondary outcome associated with initiation of probenecid or allopurinol (33,34). In addition, we performed a sensitivity analysis after excluding probenecid initiators who had prior use of allopurinol, and allopurinol initiators who had prior use of probenecid to make all the study patients naive to both drugs on the index date.
Proportional hazards assumption was tested by including the interaction term between exposure and follow-up time, and was not violated in any of the models for primary analysis (35). All analyses were conducted in SAS 9.4 software (SAS Institute, Cary, North Carolina).
We identified >2.8 million patients with ≥1 diagnosis of gout enrolled in Medicare Parts A, B, and D during the study period. After applying inclusion and exclusion criteria (Figure 2), we identified 339,870 patients ≥65 years of age with ≥1 diagnosis of gout who initiated a urate-lowering drug (i.e., allopurinol, febuxostat, or probenecid). Of those, 9,722 initiated probenecid and 303,936 started allopurinol. After PS matching with a 1:3 fixed ratio, 100% of probenecid initiators and 9.6% of all allopurinol initiators were included for the study cohort.
Before PS matching, probenecid initiators were less likely to have CKD (28.4% vs. 39.0%) and recent HF (3.2% vs. 5.6%), and have their serum uric acid level tested (64.5% vs. 74.8%) compared with allopurinol initiators (Online Table 1).
Table 1 shows baseline characteristics of the 2 groups matched on PS. The mean age of the PS-matched groups was 76 ± 7 years; 54% were male, and 79% were white. At baseline, 28% in both groups had CVD, 27% HF, 28% CKD, and 46% diabetes. Use of gout-related medications including colchicine (71%), oral steroids (35%), NSAIDs (44%), and opioids (48%) was common in both groups. All the baseline covariates were well-balanced between the PS-matched groups with a standardized difference <10% (31). Before the index date, 1% of the allopurinol group used probenecid, and 14% of the probenecid group took allopurinol. The majority of colchicine use was noted at the time of treatment initiation with probenecid or allopurinol because 63.9% of probenecid initiators and 42.1% of allopurinol initiators had a dispensing for colchicine at the index date.
Patterns of probenecid or allopurinol treatment
In the PS-matched cohort, the median (interquartile range [IQR]) initial daily dose was 1,000 mg (500 to 1,000 mg) for the probenecid group and 176 mg (100 to 300 mg) for the allopurinol group; 44.0% of probenecid initiators were started on a daily dose <1,000 mg, and 62.6% of allopurinol initiators were started on a daily dose <300 mg. During the follow-up, 9.2% of probenecid initiators and 22.3% of allopurinol initiators had the daily dose increased. There was a large difference in the adherence between the 2 groups. The median (IQR) proportion of days covered for 180 days was 39.8% (17.1% to 88.4%) with probenecid and 87.3% (50.3% to 100%) with allopurinol. The median (IQR) proportion of days covered for 365 days was 26.1% (8.5% to 80.9%) with probenecid and 82.2% (34.1% to 99.5%) with allopurinol. Nearly one-third of patients who discontinued probenecid were switched to allopurinol or febuxostat after their follow-up time ended.
The median (IQR) follow-up time for the primary as-treated analysis was 118 days (61 to 469 days) among probenecid initiators and 358 days (103 to 854 days) among allopurinol initiators. However, given the large size of the study cohort, 2,890 (29.7%) probenecid and 14,468 (49.6%) allopurinol initiators had a follow-up time over 1 year, and 1,534 (15.8%) probenecid and 8,817 (30.2%) allopurinol initiators were followed up for >2 years.
Risk of CV events
During a total of 50,427 person-years of follow-up in the PS-matched cohort for the as-treated analysis, 1,385 patients—203 probenecid and 1,182 allopurinol initiators—developed the primary composite endpoint of hospitalization for MI or stroke (Table 2). The IR of the composite endpoint of MI or stroke per 100 person-years was 2.36 (95% CI: 2.05 to 2.71) among probenecid initiators and 2.83 (95% CI: 2.67 to 2.99) among allopurinol initiators. The HR of the primary outcome was 0.80 (95% CI: 0.69 to 0.93) in the probenecid group compared with the allopurinol group. Cumulative incidence plots showed consistent results with the log-rank test p value of 0.003 (Central Illustration).
In the as-treated analysis, the IRs of the secondary outcomes were also lower in the probenecid group versus the allopurinol group with a HR of 0.81 for MI (95% CI: 0.67 to 0.99) and a HR of 0.72 (95% CI: 0.57 to 0.90) for stroke (Table 2). There was no difference in the IR of coronary revascularization between the 2 groups (HR: 0.94; 95% CI: 0.81 to 1.09). Among the patients with no baseline HF (Table 3), the IR of hospitalization for new-onset HF was similar between the 2 groups (HR: 0.95; 95% CI: 0.84 to 1.08). However, the IR of hospitalization for HF exacerbation in patients with baseline HF was lower in the probenecid group than the allopurinol group (HR: 0.91; 95% CI: 0.83 to 0.997). The rate of all-cause deaths (Table 2) was also lower among the probenecid group versus the allopurinol group with the HR of 0.87 (95% CI: 0.76 to 0.997).
Subgroup and sensitivity analyses
For the subgroup in the linked Medicare-EMR database, we identified 5,973 patients ≥65 years of age with ≥1 diagnosis of gout who initiated a urate-lowering drug. Of those, 1,969 (33%) had ≥1 measurement for serum uric acid and creatinine level before the index date. After applying other exclusion criteria, there were only 34 probenecid and 1,847 allopurinol initiators. In this subgroup, the mean serum uric acid level was 7.2 ± 2.1 mg/dl in the probenecid and 7.8 ± 2.3 mg/dl in the allopurinol group. The mean ± SD serum creatinine level was 1.2 ± 0.5 mg/dl in the probenecid and 1.3 ± 0.5 mg/dl in the allopurinol group. Due to the small number of probenecid initiators, none developed MI or stroke during follow-up.
In the analysis stratified by the baseline CVD status (Table 4), the HR for the composite endpoint of MI or stroke was 0.82 (95% CI: 0.67 to 0.99) among probenecid initiators with baseline CVD (n = 2,758) versus allopurinol initiators with baseline CVD (n = 8,274) matched on PS. Among patients with no baseline CVD, the HR for the composite endpoint of MI or stroke was 0.77 (95% CI: 0.61 to 0.98) associated with probenecid (n = 6,964) versus allopurinol (n = 20,892). In the subgroup of patients with no baseline CKD (Table 4), the HR for the composite endpoint of MI or stroke was 0.84 (95% CI: 0.70 to 1.01) associated with probenecid (n = 6,962) versus allopurinol (n = 20,886).
In the sensitivity analysis where we used Cox proportional hazards models stratified on PS-matching sets, the HR of the primary outcome was similar to the main result with a slightly wider confidence interval (0.81; 95% CI: 0.68 to 0.97) in the probenecid group compared with the allopurinol group. The sensitivity analyses for the secondary outcomes also showed consistent results (data not shown). In addition, we found similar results from the sensitivity analysis where patients were required to be naive to both probenecid and allopurinol at baseline with the HR of 0.78 (95% CI: 0.67 to 0.92) for the primary outcome in the probenecid group (n = 8,351) versus the allopurinol group (n = 25,053).
This large observational study including Medicare-enrolled elderly patients with gout found an association between probenecid use and a lower risk of CV events compared with allopurinol. Although both probenecid and allopurinol have been available for a long time for the management of gout, to the best of our knowledge, this is the first study that has evaluated the CV effect of probenecid directly compared with allopurinol in a population-representative cohort of gout patients. Inflammation plays a critical role in the pathogenesis of both gout and CVD. IL-1β, a proinflammatory cytokine primarily produced by monocytes and macrophages, is the main cytokine involved in gout (3). Monocytes and macrophages are also important cells in the development of atherosclerotic plaque, and accumulating data support the role of IL-1β in atherothrombosis (18,36). Probenecid lowers serum uric acid by blocking reuptake of uric acid in the kidneys and may exhibit an anti-inflammatory effect through its inhibition of pannexin 1 channels, thereby reducing IL-1β. Prior studies have hypothesized potential beneficial effects of IL-1β inhibition on CVD (37), and canakinumab, an IL-1β inhibitor, reduced the risk of major adverse CV events in patients with prior heart attack and inflammatory atherosclerosis in the CANTOS (Canakinumab Anti-Inflammatory Thrombosis Outcomes Study). Nevertheless, further investigation on the pathophysiological mechanisms by which probenecid may modulate the risk of CV events is needed. Probenecid is also a potent and selective agonist of TRPV2 channel (19,20); several studies support its inotropic effect (19,21–23). In our study, probenecid was associated with a 20% lower risk of hospitalization for MI or stroke compared with allopurinol, whereas the magnitude of the association between probenecid and hospitalization for HF exacerbation was smaller (9%). We also did not observe any link between probenecid and new-onset HF. Probenecid is known to increase the concentration of some drugs such as antibiotics and NSAIDs when used concomitantly, but drug interactions between probenecid and statins or other CV drugs are not reported.
Although our study generated important and interesting findings, our results should be interpreted with caution. First, as noted in any nonrandomized observational studies, this study is subject to residual or unmeasured confounding and cannot prove the causality. In other words, probenecid initiators might be different from allopurinol initiators with regard to severity of gout or CKD, serum uric acid levels, body mass index, smoking, or severity of underlying comorbidities such as CVD, hypertension, diabetes, or HF, because such clinical or laboratory data were not available in the Medicare data. However, we included several proxies of gout severity such as use of baseline steroids, NSAIDs, and colchicine, as well as proxies of CVD severity such as use of diuretics, nitrates, and statins, and physician orders of electrocardiogram, echocardiogram, and cardiac stress tests in the PS model. We also conducted subgroup analyses by CKD and CVD at baseline and found similar results. Although the number of probenecid initiators was small in the subgroup of patients in the linked Medicare-EMR database, we confirmed that there was no substantial difference in the mean serum creatinine level between probenecid (1.2 mg/dl) and allopurinol (1.3 mg/dl) initiators. Nonetheless, in order to completely avoid confounding, we would need a randomized controlled trial to determine the potential benefit of probenecid. Second, potential misclassification of outcomes is possible because we mainly relied on billing diagnosis and procedure codes. Furthermore, because we defined new-onset HF as well as HF exacerbation on the basis of hospital discharge diagnosis, this study did not capture patients who were managed in an outpatient setting for mild HF in the secondary outcome analysis. Third, this study may not be able to answer the long-term CV effect of probenecid or allopurinol because the median duration of active treatment with either drug was <1 year. However, >10,000 patients remained in the study for >2 years. Fourth, although our study likely reflects current clinical practice for management of gout in the elderly, the doses for probenecid and allopurinol were generally lower, with the starting daily dose for allopurinol in >60% of allopurinol initiators <300 mg. Furthermore, <25% of allopurinol initiators had the daily dose increased during follow-up. Fifth, there was a difference in the adherence to probenecid versus allopurinol. Although it is possible that the observed difference in the medication adherence between the 2 groups may lead to a biased estimate, we found consistent results in the ITT analysis up to 365 days of follow-up, as well as the sensitivity analysis with Cox regression stratifying on PS-matching sets. This analysis specifically compared each probenecid initiator to the 3 PS-matched allopurinol initiators for the same duration of follow-up (33,34).
Given the limitations of observational studies of drugs including confounding and suboptimal adherence to treatment, future studies are needed to further determine the effect of probenecid on CV risk. Prospective interventional studies that evaluate the effect of probenecid on intermediate endpoints of CVD may be helpful to delineate the potential mechanism by which probenecid modulate CV risks. In our study cohort with the mean age of 76 years, the IR of hospitalization for MI or stroke was >2 per 100 person-years in both drug groups, and the rate difference in the PS-matched cohort was 0.47 per 100 person-years. On the basis of the absolute risk difference that we observed, the number of gout patients needed to treat with probenecid versus allopurinol to prevent 1 additional hospitalization for MI or stroke would be 213. If a similar magnitude of the effect noted in our study is confirmed in a trial, the needed to treat will not be very large, given the high prevalence of CV risk factors in the typical older gout population.
In this large cohort study of 38,888 elderly gout patients enrolled in Medicare, use of probenecid appears to be associated with a modestly decreased risk of CV events including MI, stroke, and HF exacerbation compared with allopurinol. Given the high CV morbidity and mortality in gout patients, potential positive effects of probenecid should be further examined.
COMPETENCY IN PATIENT CARE: In patients with gout, the urate-lowering drug probenecid is associated with a modestly lower risk of cardiovascular events, including MI, stroke, and HF exacerbation, than allopurinol.
TRANSLATIONAL OUTLOOK: Future studies should address the pathophysiological mechanisms by which probenecid and allopurinol modulate cardiovascular risk.
Dr. Kim is partially supported by National Institutes of Health (NIH) grant R21 AR069271. Dr. Neogi’s effort was supported by NIH grant K24 AR070892. Dr. Solomon’s effort was supported by NIH grant K24 AR055989. Dr. Kim has received research grants to the Brigham and Women’s Hospital from Roche/Genentech, Pfizer, Bristol-Myers Squibb, Merck, and AstraZeneca for unrelated studies. Dr. Desai has received research grants to the Brigham and Women’s Hospital from Merck. Dr. Solomon has received research grants to the Brigham and Women’s Hospital from Lilly, Pfizer, AstraZeneca, Genentech, Amgen, and CORRONA; and serves in an unpaid role on a trial sponsored by Pfizer unrelated to the current study. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose.
- Abbreviations and Acronyms
- confidence interval
- chronic kidney disease
- cardiovascular disease
- electronic medical record
- heart failure
- hazard ratio
- interquartile range
- incidence rate
- myocardial infarction
- nonsteroidal anti-inflammatory drug
- propensity score
- transient receptor potential vanilloid 2
- Received August 20, 2017.
- Revision received November 25, 2017.
- Accepted December 18, 2017.
- 2018 American College of Cardiology Foundation
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