Europe PMC

This website requires cookies, and the limited processing of your personal data in order to function. By using the site you are agreeing to this as outlined in our privacy notice and cookie policy.

Association Between Use of Antithrombotic Medication and Hematuria-Related Complications.

Author information

Affiliations

  • 1. Division of Urology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Ontario, Canada.
      Authors
    • Wallis CJD 1, 3
    • Juvet T 1
    • Matta R 1
    • Herschorn S 1
    • Kodama R 1
    • Satkunasivam R 1
    • Nam RK 1, 3
    (7 authors)
  • 2. Department of Medicine, St Michael's Hospital, University of Toronto, Toronto, Ontario, Canada.
      Authors
    • Lee Y 2
    (1 author)
  • 3. Institute for Health Policy, Management & Evaluation, University of Toronto, Toronto, Ontario, Canada.
      Authors
    • Wallis CJD 1, 3
    • Kulkarni GS 3
    • Nam RK 1, 3
    (3 authors)
  • 4. Department of Medicine, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Ontario, Canada.
      Authors
    • Geerts W 4
    • McLeod A 4
    (2 authors)
  • 5. Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada.
      Authors
    • Narod SA 5
    (1 author)

JAMA, 01 Oct 2017, 318(13):1260-1271
https://doi.org/10.1001/jama.2017.13890 PMID: 28973248 PMCID: PMC5818855

Free full text in Europe PMC

A comment on this article appears in "Re: Association between Use of Antithrombotic Medication and Hematuria-Related Complications." J Urol. 2018 May;199(5):1103.

Abstract 

Importance

Antithrombotic medications are among the most commonly prescribed medications.

Objective

To characterize rates of hematuria-related complications among patients taking antithrombotic medications.

Design, setting, and participants

Population-based, retrospective cohort study including all citizens in Ontario, Canada, aged 66 years and older between 2002 and 2014. The final follow-up date was December 31, 2014.

Exposures

Receipt of an oral anticoagulant or antiplatelet medication.

Main outcomes and measures

Hematuria-related complications, defined as emergency department visit, hospitalization, or a urologic procedure to investigate or manage gross hematuria.

Results

Among 2 518 064 patients, 808 897 (mean [SD] age, 72.1 [6.8] years; 428 531 [53%] women) received at least 1 prescription for an antithrombotic agent over the study period. Over a median follow-up of 7.3 years, the rates of hematuria-related complications were 123.95 events per 1000 person-years among patients actively exposed to antithrombotic agents vs 80.17 events per 1000 person-years among patients not exposed to these drugs (difference, 43.8; 95% CI, 43.0-44.6; P < .001, and incidence rate ratio [IRR], 1.44; 95% CI, 1.42-1.46). The rates of complications among exposed vs unexposed patients (80.17 events/1000 person-years) were 105.78 for urologic procedures (difference, 33.5; 95% CI, 32.8-34.3; P < .001, and IRR, 1.37; 95% CI, 1.36-1.39), 11.12 for hospitalizations (difference, 5.7; 95% CI, 5.5-5.9; P < .001, and IRR, 2.03; 95% CI, 2.00-2.06), and 7.05 for emergency department visits (difference, 4.5; 95% CI, 4.3-4.7; P < .001, and IRR, 2.80; 95% CI, 2.74-2.86). Compared with patients who were unexposed to thrombotic agents, the rates of hematuria-related complications were 191.61 events per 1000 person-years (difference, 117.3; 95% CI, 112.8-121.8) for those exposed to both an anticoagulant and antiplatelet agent (IRR, 10.48; 95% CI, 8.16-13.45), 140.92 (difference, 57.7; 95% CI, 56.9-58.4) for those exposed to anticoagulants (IRR, 1.55; 95% CI, 1.52-1.59), and 110.72 (difference, 26.5; 95% CI, 25.9-27.0) for those exposed to antiplatelet agents (IRR, 1.31; 95% CI, 1.29-1.33). Patients exposed to antithrombotic agents, compared with patients not exposed to these drugs, were more likely to be diagnosed as having bladder cancer within 6 months (0.70% vs 0.38%; odds ratio, 1.85; 95% CI, 1.79-1.92).

Conclusions and relevance

Among older adults in Ontario, Canada, use of antithrombotic medications, compared with nonuse of these medications, was significantly associated with higher rates of hematuria-related complications (including emergency department visits, hospitalizations, and urologic procedures to manage gross hematuria).

Free full text 

Logo of jamasdJAMA NetworkView Article
JAMA
JAMA. 2017 Oct 3; 318(13): 1260–1271.
Published online 2017 Oct 3. https://doi.org/10.1001/jama.2017.13890
PMCID: PMC5818855
PMID: 28973248

Association Between Use of Antithrombotic Medication and Hematuria-Related Complications

Christopher J. D. Wallis, MD, PhD,1,2 Tristan Juvet, MD,1 Yuna Lee, MD, MEd,3 Rano Matta, MD, MSc,1 Sender Herschorn, MD,1 Ronald Kodama, MD,1 Girish S. Kulkarni, MD, PhD,2,4 Raj Satkunasivam, MD, MPH,1 William Geerts, MD,5 Anne McLeod, MD,5 Steven A. Narod, MD,6 and Robert K. Nam, MD, MSccorresponding author1,2
Author information Article notes Copyright and License information Disclaimer

Associated Data

Supplementary Materials

Key Points

Question

Is there an association between the use of oral antithrombotic agents and hematuria-related complications?

Findings

In this cohort study that included 2 518 064 older adults in Ontario, Canada, use of antithrombotic medications, compared with nonuse of these medications, was significantly associated with hematuria-related complications (including emergency department visits, hospitalizations, and urologic procedures).

Meaning

Use of antithrombotic medications was associated with a significant increase in rates of hematuria-related complications.

Abstract

Importance

Antithrombotic medications are among the most commonly prescribed medications.

Objective

To characterize rates of hematuria-related complications among patients taking antithrombotic medications.

Design, Setting, and Participants

Population-based, retrospective cohort study including all citizens in Ontario, Canada, aged 66 years and older between 2002 and 2014. The final follow-up date was December 31, 2014.

Exposures

Receipt of an oral anticoagulant or antiplatelet medication.

Main Outcomes and Measures

Hematuria-related complications, defined as emergency department visit, hospitalization, or a urologic procedure to investigate or manage gross hematuria.

Results

Among 2 518 064 patients, 808 897 (mean [SD] age, 72.1 [6.8] years; 428 531 [53%] women) received at least 1 prescription for an antithrombotic agent over the study period. Over a median follow-up of 7.3 years, the rates of hematuria-related complications were 123.95 events per 1000 person-years among patients actively exposed to antithrombotic agents vs 80.17 events per 1000 person-years among patients not exposed to these drugs (difference, 43.8; 95% CI, 43.0-44.6; P < .001, and incidence rate ratio [IRR], 1.44; 95% CI, 1.42-1.46). The rates of complications among exposed vs unexposed patients (80.17 events/1000 person-years) were 105.78 for urologic procedures (difference, 33.5; 95% CI, 32.8-34.3; P < .001, and IRR, 1.37; 95% CI, 1.36-1.39), 11.12 for hospitalizations (difference, 5.7; 95% CI, 5.5-5.9; P < .001, and IRR, 2.03; 95% CI, 2.00-2.06), and 7.05 for emergency department visits (difference, 4.5; 95% CI, 4.3-4.7; P < .001, and IRR, 2.80; 95% CI, 2.74-2.86). Compared with patients who were unexposed to thrombotic agents, the rates of hematuria-related complications were 191.61 events per 1000 person-years (difference, 117.3; 95% CI, 112.8-121.8) for those exposed to both an anticoagulant and antiplatelet agent (IRR, 10.48; 95% CI, 8.16-13.45), 140.92 (difference, 57.7; 95% CI, 56.9-58.4) for those exposed to anticoagulants (IRR, 1.55; 95% CI, 1.52-1.59), and 110.72 (difference, 26.5; 95% CI, 25.9-27.0) for those exposed to antiplatelet agents (IRR, 1.31; 95% CI, 1.29-1.33). Patients exposed to antithrombotic agents, compared with patients not exposed to these drugs, were more likely to be diagnosed as having bladder cancer within 6 months (0.70% vs 0.38%; odds ratio, 1.85; 95% CI, 1.79-1.92).

Conclusions and Relevance

Among older adults in Ontario, Canada, use of antithrombotic medications, compared with nonuse of these medications, was significantly associated with higher rates of hematuria-related complications (including emergency department visits, hospitalizations, and urologic procedures to manage gross hematuria).

Introduction

Antithrombotic agents are among the most commonly prescribed medications for older adults in North America. Oral anticoagulants are indicated for primary and secondary prevention of stroke and systemic embolism, as well as treatment of venous thromboembolism. Antiplatelet agents are indicated for primary and secondary prevention of cardiovascular disease. Despite proven benefits, antithrombotic agents are among the medications most commonly associated with adverse events and have contributed to nearly half of all adverse drug events. Further, the rates of these adverse events are increasing. To date, published randomized clinical trials and observational studies of antithrombotic agents have focused on intracranial hemorrhage, gastrointestinal bleeding, and all-cause bleeding as adverse events.

To our knowledge, a complication that has not been examined as the primary outcome in patients treated with antithrombotic agents is hematuria. While hematuria represents a less life-threatening adverse event than intracranial or gastrointestinal bleeding, it is common and involves diagnostic evaluation including abdominal imaging and invasive testing and management. The prevalence, severity, and risk factors for hematuria associated with the use of antithrombotic agents are largely unknown. To better characterize this association, this analysis examined rates of gross hematuria-related complications including hospitalization, emergency department visits, and urologic interventions over a 13-year period among patients who received anticoagulant or antiplatelet therapy from a population-based cohort of adults aged 66 years or older in Ontario, Canada.

Methods

We conducted a population-based, retrospective cohort study of patients aged 66 years or older in Ontario, Canada, between April 2002 and December 2014 using data from the Institute of Clinical Evaluative Sciences (ICES). In Ontario, medical care is reimbursed by a single, government-operated health insurance system (Ontario Health Insurance Plan). The cost of prescription medications is covered for all patients starting at age 65 years through the Ontario Drug Benefit.

This study was designed and conducted according to the Strengthening the Reporting of Observational Studies in Epidemiology guidelines and Reporting of Studies Conducted Using Observational Routinely-Collected Health Data Statement. The Sunnybrook Health Sciences Centre Research Ethics Board approved this study. Individual informed consent was waived owing to the anonymous, aggregated nature of the data.

Study Patients

We identified all residents of Ontario born before 1936, who would be aged 66 years or older during the study interval (2002-2014), based on date of birth using unique identifiers (ICES key number). The index date was defined as each person’s 66th birthday. To include only those patients actively receiving medical care in Ontario during the study interval, we excluded individuals who died and those who emigrated prior to the index date. We further excluded patients diagnosed as having a cancer (other than nonmelanomatous skin cancer) prior to the index date and those with prior endoscopic urologic procedures as these are likely to significantly affect a patient’s likelihood of hematuria-related complications. We also excluded patients older than the age of 105 years.

From linked databases, we collected demographic information including patient age at the time of each prescription, geographic location (local health integration networks), sex, geographically derived socioeconomic status, rurality, and general comorbidity (Johns Hopkins aggregate disease group). The Johns Hopkins aggregate disease group has better discrimination than the Charlson score in comorbidity assessment.

Exposure

The primary exposure was use of any oral antithrombotic agent, including anticoagulant and antiplatelet medications for which the first prescription occurred during the study interval (eTable 1 in the Supplement). We operationalized antithrombotic exposure in an intermittent, time-varying fashion (examples of operationalization of this exposure are in the eFigure in the Supplement). Age 66 years was selected for cohort inclusion to allow for a 1-year look-back to ensure that patients were not exposed to antithrombotic agents prior to study entry.

On the date of filling their first prescription during the study interval, patients were considered “exposed” and remained exposed until 14 days following the prescription end date (washout period). Fifteen days following the prescription end date, patients were considered to be “unexposed.” When the washout period coincided with prescription renewal, patients had continuous, ongoing exposure. When patients discontinued antithrombotic therapy and then restarted after discontinuation, a new exposure period commenced. Similarly, when patients switched medications, exposure and outcome time was allocated to each medication during the prescription period plus the 14-day washout period.

Outcomes

We measured counts of total hematuria-related complications, which was the sum of the counts of 3 specific end points including the occurrence of emergency department visits for gross hematuria, hospital admissions with a primary diagnosis of gross hematuria, or urologic procedures to manage gross hematuria. No other adverse events were included in this total. Specific diagnostic and procedural codes are provided in eTable 2 in the Supplement.

Data Sources

We linked the following validated data sets using patients’ unique ICES key numbers: the Ontario Drug Benefit database, which provides information on all outpatient prescription pharmaceuticals; the Canadian Institute for Health Information Discharge Abstract Database, which contains records for all hospitalizations; the Canadian Institute for Health Information National Ambulatory Care Reporting System, which contains records for emergency department visits; the Ontario Health Insurance Plan database, which tracks claims paid for physician billings, laboratories, and out-of-province providers (physicians, allied health, and hospitals); the Ontario Cancer Registry, a population-based registry estimated to be 95% or more complete; and the Registered Persons database for demographic information (validation details in eTable 3 in the Supplement).

Statistical Analysis

We measured the total number of complications each individual experienced rather than the first presentation of a complication. Patients contributed data until the date of death or until the last date of follow-up. Patients with missing data were excluded from the multivariate analysis. We calculated incidence density rates of each complication using the total count of the complication as the numerator and number of person-years exposed as the denominator, stratified by exposure to antithrombotic agents. Multivariable negative binomial regression was used to study the association between exposure to antithrombotic agents (operationalized in the time-varying manner described above) and complications due to the skewed nature of health services data. We expressed this as the incidence rate ratio (IRR), the ratio of incidence density rate during antithrombotic agent exposure to the rate during unexposed periods. Each rate ratio was adjusted for the association of patient age, sex, comorbidity, income quintile, region of residence, and rurality with tests for interaction. We tested for interaction between exposure variables using separate interaction terms in the models (ie, exposure A × exposure B). Where there was statistical significance, we included the interaction term in the final model and expressed the results using the interaction. This only occurred for the interaction between antithrombotic exposure and age at prescription. As a result, we expressed the IRR for antithrombotic exposure in a stratified fashion according to the patient’s age at the time of prescription.

We compared differences in the IRR of hematuria-related complications between medications using pairwise tests for heterogeneity between aspirin and other antiplatelet agents and between each of the 4 anticoagulants. Many patients received more than 1 agent during the study interval, and some received them concurrently. While assessing the association of each medication, concurrent exposures were handled using each medication as an independent exposure variable within the multivariable models such that an effect estimate could be derived for each medication. As concurrent antiplatelet and anticoagulant exposure may have a synergistic effect, the association of combination therapy was also assessed.

Subgroup Analyses

We conducted several preplanned subgroup analyses to understand modifying risks, given the known association between hematuria and benign prostatic hypertrophy (BPH) and medical kidney disease. As a surrogate for BPH, we examined patients’ prescriptions for BPH-related medications. We assessed the association of receipt of BPH-related medications in the year prior to antithrombotic exposure on rates of hematuria-related complications among men (eTable 4 in the Supplement). Then, among all patients, we assessed for the association of medical kidney disease by including consultation with a nephrologist.

We identified patients diagnosed as having bladder cancer within 6 months after an episode of hematuria using the Ontario Cancer Registry. We calculated the standardized incidence ratio (SIR) of bladder cancer among patients receiving antithrombotic agents by identifying the age- and sex-stratified expected number of bladder cancer cases based on the Ontario population. We then calculated the SIR as the ratio of the observed number of bladder cancer cases divided by the expected number of cases. Logistic regression analysis was also performed to calculate the odds ratio for being diagnosed as having cancer between the exposed and unexposed group, as patients are only diagnosed as having cancer once.

Statistical significance was set at P < .05 based on a 2-tailed comparison. All analyses were performed using SAS Enterprise Guide 6.1 (SAS Institute Inc).

Results

We identified 4 184 141 residents of Ontario born before 1936, who would be aged 66 years or older during the study interval (2002-2014). Following exclusion of individuals who died (n = 915 892) and emigrated (n = 317 141) prior to the index date, those diagnosed as having a cancer (other than nonmelanomatous skin cancer) prior to the index date (n = 348 302), those with prior endoscopic urologic procedures (n = 84 674), and those older than the age of 105 years (n = 68), the final cohort comprised 2 518 064 individuals aged 66 years and older. Of these, 607 323 died after the index date, and 208 159 were lost to follow-up: 111 845 had a date of last contact of more than 2 years before the end of the study period, and 96 314 had loss of continuous health insurance coverage.

Of these participants, 808 897 filled at least 1 prescription for an antithrombotic agent, while 1 709 167 were not exposed during the study interval. Patients who filled a prescription for an antithrombotic agent were older (median age, 70 years vs 66 years; P < .001), more likely to be male (47.0% vs 41.9%; P < .001), had a lower level of income (20.8% vs 17.9%; P < .001), and had higher levels of comorbidity (30.6% vs 18.4%; P < .001) (Table 1). Patients exposed to antithrombotic agents were significantly more likely to have been diagnosed as having a relevant medical condition in the 5 years preceding the index date than those who were not exposed (Table 1).

Table 1.

Demographics of Study Cohort, Stratified by Exposure to Antithrombotic Agents (Study Interval Between 2002-2014)
CharacteristicNo. (%)P Value
TotalUnexposed During Study IntervalaEver Exposed During Study Intervala
Sample size2 518 0641 709 167808 897
Age, y
Mean (SD)70.16 (6.41)69.23 (6.00)72.12 (6.79)<.001
Median (IQR)66 (66-73)66 (66-70)70 (66-77)<.001
Age, categorical
66-69 y1 642 981 (65.2)1 254 546 (73.4)388 435 (48.0)<.001
70-74 y339 136 (13.5)180 692 (10.6)158 444 (19.6)
75-79 y257 889 (10.3)127 262 (7.4)130 623 (16.1)
80-84 y157 432 (6.3)77 235 (4.5)80 197 (9.9)
≥85 y120 626 (4.8)69 432 (4.1)51 194 (6.3)
Sex
Female1 421 828 (56.5)993 297 (58.1)428 531 (53.0)<.001
Male1 096 236 (43.5)715 870 (41.9)380 366 (47.0)
Income quintile
1: Lowest474 591 (18.8)306 713 (17.9)167 878 (20.8)<.001
2516 527 (20.5)342 915 (20.1)173 612 (21.5)
3497 811 (19.8)336 594 (19.7)161 217 (19.9)
4490 999 (19.5)340 295 (19.9)150 704 (18.6)
5: Highest514 187 (20.4)363 335 (21.3)150 852 (18.6)
Missing23 949 (1.0)19 315 (1.1)4634 (0.6)
Comorbidity (ADG category)b
0-2483 388 (19.2)386 160 (22.6)97 228 (12.0)<.001
3-5764 884 (30.4)549 985 (32.2)214 899 (26.6)
6-8707 808 (28.1)458 864 (26.8)248 944 (30.8)
≥9561 984 (22.3)314 158 (18.4)247 826 (30.6)
Select relevant medical diagnoses in the 5 y prior to index date
Atrial fibrillation81 963 (3.3)18 375 (1.1)63 588 (7.9)<.001
Ischemic stroke19 101 (0.8)5536 (0.3)13 565 (1.7)<.001
TIA97 545 (3.9)37 614 (2.2)59 931 (7.4)<.001
DVT or PE11 834 (0.5)4191 (0.2)7643 (0.9)<.001
Valvular heart disease30 796 (1.2)10 822 (0.6)19 974 (2.5)<.001
Myocardial infarction98 242 (3.9)35 205 (2.1)63 037 (7.8)<.001
Angina384 786 (15.3)164 120 (9.6)220 666 (27.3)<.001
PAD85 831 (3.4)37 421 (2.2)48 410 (6.0)<.001
Contact with urologist prior to age 66 y
No1 901 967 (75.5)1 355 229 (79.3)546 738 (67.6)<.001
Yes616 097 (24.5)353 938 (20.7)262 159 (32.4)
Geographic region (local health integration network)
Erie St Clair135 385 (5.4)87 891 (5.1)47 494 (5.9)<.001
South West199 549 (7.9)136 629 (8.0)62 920 (7.8)
Waterloo Wellington122 346 (4.9)85 880 (5.0)36 466 (4.5)
Hamilton Niagara Haldimand Brant298 521 (11.9)200 685 (11.7)97 836 (12.1)
Central West120 468 (4.8)83 785 (4.9)36 683 (4.5)
Mississauga Halton178 018 (7.1)123 852 (7.2)54 166 (6.7)
Toronto Central217 274 (8.6)147 169 (8.6)70 105 (8.7)
Central296 960 (11.8)204 867 (12.0)92 093 (11.4)
Central East296 284 (11.8)200 062 (11.7)96 222 (11.9)
South East120 322 (4.8)81 968 (4.8)38 354 (4.7)
Champlain239 674 (9.5)164 629 (9.6)75 045 (9.3)
North Simcoe Muskoka92 450 (3.7)61 119 (3.6)31 331 (3.9)
North East134 038 (5.3)83 881 (4.9)50 157 (6.2)
North West49 366 (2.0)31 827 (1.9)17 539 (2.2)
Missing17 409 (0.7)14 923 (0.9)2486 (0.3)
Rural area
Yes370 167 (14.7)245 095 (14.3)125 072 (15.5)<.001
No2 130 309 (84.6)1 449 063 (84.8)681 246 (84.2)
Missing17 588 (0.7)15 009 (0.9)2579 (0.3)

Abbreviations: ADG, aggregate disease groups; DVT, deep vein thrombosis; IQR, interquartile range; PAD, peripheral arterial disease; PE, pulmonary embolism; TIA, transient ischemic attack.

aDifferences between participants who were exposed and unexposed were compared using the χ2 test for categorical data and the Wilcoxon rank sum test for continuous data.
bAggregate disease groups are score-based comorbidity assessments based on resource use of health care (range, 0-34). Higher scores indicate higher levels of comorbidity.

Over a median follow-up of 7.3 years, gross hematuria-related complication rates were higher during active exposure to any antithrombotic agent (123.95 events/1000 person-years) than during unexposed periods (80.17 events/1000 person-years; difference, 43.8; 95% CI, 43.0-44.6; P < .001; Table 2). Of the hematuria-related complications, urologic procedures were the most common (105.78 events/1000 person-years; difference, 33.5; 95% CI, 32.8-34.3; P < .001), followed by hospitalizations (11.12 events/1000 person-years; difference, 5.7; 95% CI, 5.5-5.9; P < .001) and emergency department visits (7.05 events/1000 person-years; difference, 4.5; 95% CI, 4.3-4.7; P < .001; Table 2). The crude rate ratio for the development of hematuria-related complications was 1.44 (95% CI, 1.42-1.46) for exposure to antithrombotic agents compared with unexposed periods. Despite the fact that urologic procedures were the most common complication, the association between antithrombotic agent use and complications, when compared with unexposed periods, was highest for emergency department visits (crude rate ratio, 2.80; 95% CI, 2.74-2.86), followed by hospitalizations (crude rate ratio, 2.03; 95% CI, 2.00-2.06) and urologic procedures (crude rate ratio, 1.37; 95% CI, 1.36-1.39). These associations persisted on multivariable analysis with increasing age, male sex, and increasing comorbidity being significantly associated with rates of hematuria-related complications (Table 3). The highest rate was for emergency visits among adults aged 85 years and older (adjusted rate ratio, 4.74; 95% CI, 4.51-4.99; Table 3).

Table 2.

Incidence Density Rates of Hematuria-Related Complications for Each Antithrombotic Agent Exposure (Study Interval Between 2002-2014)
VariableSample SizeExposure Time (Person-Years)Any Hematuria-Related ComplicationEmergency Department VisitsHospitalizationsUrologic Procedures
No. of EventsIncidence Density RateaNo. of EventsIncidence Density RateaNo. of EventsIncidence Density RateaNo. of EventsIncidence Density Ratea
No antithrombotic1 709 16715 864 7081 271 90180.1739 8462.5185 9415.421 146 07772.24
Any antithromboticb808 8972 600 520322 322123.9518 3227.0528 90511.12275 076105.78
Difference from no antithrombotic (95% CI)43.8
(43.0-44.6)		4.5
(4.3-4.7)		5.7
(5.5-5.9)		33.5
(32.8-34.3)
Aspirin315 639795 68675 03394.331804.0053536.7366 49883.57
Difference from no aspirin (95% CI)c8.3
(7.7-9.0)		0.9
(0.7-1.0)		0.5
(0.3-0.7)		8.9
(8.3-9.5)
Other antiplatelet275 887706 98891 927130.0346216.54782311.0779 477112.42
Difference from no other antiplatelet (95% CI)c45.4
(44.6-4.2)		3.5
(3.3-3.7)		5.0
(4.8-5.3)		36.8
(36.1-37.6)
Apixiban15 10266121085164.097611.5013219.96877132.64
Difference from no apixiban (95% CI)c77.8
(68.9-86.7)		8.3
(5.8-10.9)		13.7
(10.4-17.1)		55.7
(47.5-63.9)
Dabigatran43 45157 6758319144.2462610.8593216.166760117.21
Difference from no dabigatran (95% CI)c58.1
(55.2-61.0)		7.7
(6.9-8.6)		10.0
(8.9-11.0)		40.4
(37.7-43.0)
Rivaroxaban87 91240 6687672188.6576618.8492222.675984147.14
Difference from no rivaroxaban (95% CI)c102.5
(98.7-106.3)		15.7
(14.4-17.0)		16.5
(15.0-17.9)		70.3
(66.9-73.8)
Warfarin320 347887 691123 100138.6788049.9212 46814.05101 816114.70
Difference from no warfarin (95% CI)c55.0
(54.2-55.7)		7.1
(6.9-7.3)		8.2
(7.9-8.4)		39.6
(39.0-40.3)
aIncidence density rates are expressed as the number of events per 1000 person-years.
bTotals in the “any antithrombotic” category may not equal the total of the component exposures owing to concurrent exposure.
cEach drug has different nonexposure time; difference in incidence density rate for each drug is not based on “No antithrombotic” row.

Table 3.

Multivariable Negative Binomial Regression Models Assessing the Association Between Exposure to Antithrombotic Agents (Primary Exposure) and Hematuria-Related Complications
VariableAssociation of Antithrombotic Medication Exposure, Stratified by Age at Prescription
Patients 66-69 yPatients 70-74 yPatients 75-79 yPatients 80-84 yPatients ≥85 y
UnexposedExposedUnexposedExposedUnexposedExposedUnexposedExposedUnexposedExposed
Sample size1 254 546388 435180 692158 444127 262130 62377 23580 19769 43251 194
Exposure time (person-years)9 166 367563 1892 966 576605 3322 008 765607 3661 082 624473 134640 373351 500
Any Hematuria-Related Complication
No. of events663 54759 870274 00077 477189 02583 64596 96062 88848 36938 442
Incidence density ratea72.39106.3192.36127.9994.1137.7289.56132.9275.53109.37
Adjusted rate ratio (95% CI)b1.18 (1.15-1.20)1.56 (1.53-1.60)1.78 (1.74-1.81)1.82 (1.77-1.86)1.65 (1.60-1.69)
P Value<.001<.001<.001<.001<.001
Emergency Department Visits
No. of events18 098315984093929652146434087372927312862
Incidence density ratea1.975.612.846.493.257.643.787.884.278.14
Adjusted rate ratio (95% CI)b2.17 (2.07-2.28)2.75 (2.63-2.88)3.55 (3.40-3.70)3.97 (3.79-4.15)4.74 (4.51-4.99)
P Value<.001<.001<.001<.001<.001
Hospitalizations
No. of events45 542546817 178663612 17971556937569741053949
Incidence density ratea4.979.715.7910.966.0611.786.4112.046.4111.24
Adjusted rate ratio (95% CI)b1.51 (1.46-1.56)1.83 (1.78-1.89)2.09 (2.03-2.16)2.29 (2.22-2.37)2.35 (2.26-2.45)
P Value<.001<.001<.001<.001<.001
Urologic Procedures
No. of events599 89651 238248 40066 909170 31671 84485 93253 45541 53331 630
Incidence density ratea65.4590.9883.73110.5384.79118.2979.37112.9864.8689.99
Adjusted rate ratio
(95% CI)b		1.11 (1.08-1.13)1.48 (1.45-1.52)1.67 (1.64-1.71)1.69 (1.64-1.73)1.47 (1.42-1.51)
P Value<.001<.001<.001<.001<.001
aIncidence density rates are expressed as the number of events per 1000 person-years.
bModels adjusted for association of participant sex, comorbidity, rurality, income quintile, and geographic region of residence. Among all these variables, a significant interaction was found between age and antithrombotic use (type 3 P < .001). Test for trend using Cochran-Armitage test for age group, P < .001. Rate ratios comparing antithrombotic exposed and unexposed periods, with stratification by patient age owing to a significant interaction between these 2 variables.

We then examined each antithrombotic medication individually: 315 639 individuals filled prescriptions for aspirin (dose ≥82 mg), 275 887 for other antiplatelet agents, 15 102 for apixaban, 43 451 for dabigatran, 87 912 for rivaroxaban, and 320 347 for warfarin. Hematuria-related complications were more common during exposure to anticoagulants than antiplatelet agents, and patients experienced the lowest rates of complications during exposure to older medications (aspirin and warfarin; Table 2). Among anticoagulants, in multivariable models, exposure to dabigatran (and not warfarin) was associated with the lowest rate of complications, while rivaroxaban had the highest rate for each age group (Table 4). Other antiplatelet agents, including clopidogrel, prasugrel, tricagrelor, ticlopidine, and dipyridamole, were associated with higher rates of hematuria-related complications than acetylsalicylic acid (≥82-mg dosage; Table 4).

Table 4.

Multivariable Negative Binomial Regression Models Assessing the Association Between Exposure to Specific Antithrombotic Agents (Primary Exposure) and Any Hematuria-Related Complication
VariableAssociation of Antithrombotic Medication Exposure, Stratified by Age at Prescription
Patients 66-69 yPatients 70-74 yPatients 75-79 yPatients 80-84 yPatients ≥85 y
UnexposedExposedUnexposedExposedUnexposedExposedUnexposedExposedUnexposedExposed
Aspirin (n = 315 639)
Exposure time (person-years)10 160 989160 7913 348 981204 0222 291 823195 0571 210 425140 412657 32495 404
No. of events801 23312 811334 91220 065227 89020 062108 22813 84246 9278253
Incidence density rate78.8579.68100.0098.3599.44102.8589.4198.5871.3986.51
Adjusted rate ratio (95% CI)a0.90 (0.87-0.94)1.16 (1.13-1.20)1.28 (1.23-1.32)1.26 (1.21-1.32)1.18 (1.12-1.25)
P value<.001<.001<.001<.001<.001
Other Antiplatelet Agents (n = 275 887)
Exposure time (person-years)10 280 093135 3023 387 590156 7732 290 944161 7511 174 989135 987624 623117 175
No. of events799 87314 457332 88620 759221 92423 889103 14619 32744 46713 495
Incidence density ratea77.81106.8598.27132.4196.87147.6987.79142.1271.19115.17
Adjusted rate ratio (95% CI)a1.15 (1.11-1.19)1.53 (1.48-1.58)1.75 (1.69-1.81)1.79 (1.72-1.86)1.59 (1.52-1.67)
P value<.001<.001<.001<.001<.001
Apixiban (n = 15 102)
Exposure time (person-years)10 779 9519223 521 6711 4202 368 67616511 187 2431334601 0751284
No. of events868 318112354 288172230 650319100 40425539 478227
Incidence density ratea80.55121.50100.60121.0997.38193.2084.57191.0965.68176.76
Adjusted rate ratio (95% CI)b1.15 (0.82-1.62)1.33 (1.05-1.70)1.89 (1.51-2.36)2.05 (1.62-2.59)2.13 (1.69-2.67)
P value.42.02<.001<.001<.001
Dabigatran (n = 43 451)
Exposure time (person-years)10 740 55276993 509 54111 0442 363 69113 9561 188 74913 461605 02011 514
No. of events862 319826352 1581474230 1492293101 067210940 2111617
Incidence density ratea80.29107.28100.34133.4797.37164.3085.02156.6766.46140.43
Adjusted rate ratio (95% CI)b1.04 (0.90-1.20)1.44 (1.28-1.62)1.80 (1.63-1.99)1.71 (1.52-1.91)1.62 (1.44-1.83)
P value.60<.001<.001<.001<.001
Rivaroxaban (n = 87 912)
Exposure time (person-years)10 701 60762123 529 45384442 385 50694721 200 5928610607 4027929
No. of events857 232921354 11816292325952008102 285170940 3211405
Incidence density ratea80.10148.25100.33192.9297.50211.9985.20198.4966.38177.19
Adjusted rate ratio (95% CI)b1.46 (1.28-1.70)2.18 (1.97-2.40)2.39 (2.17-2.65)2.35 (2.13-2.60)2.34 (2.09-2.63)
P value<.001<.001<.001<.001<.001
Warfarin (n = 320 347)
Exposure time (person-years)10 233 323122 4663 304 540178 6762 234 599215 2931 163 075199 617641 999171 639
No. of events786 90014 026319 46725 859214 03532 974103 17829 93947 54320 302
Incidence density ratea76.90114.5396.68144.7395.78153.1688.71149.9874.06118.28
Adjusted rate ratio (95% CI)b1.19 (1.15-1.23)1.63 (1.58-1.68)1.79 (1.74-1.84)1.84 (1.78-1.89)1.61 (1.56-1.67)
P value<.001<.001<.001<.001<.001
aIncidence density rates are expressed as the number of events per 1000 person-years.
bModels adjusted for association of participant sex, comorbidity, rurality, income quintile, and geographic region of residence. Among all these variables, a significant interaction was found between age and antithrombotic use (type 3 P <.001). Test for trend using Cochran-Armitage test for age group, P < .001. Rate ratios comparing antithrombotic exposed and unexposed periods, with stratification by patient age due to a significant interaction between these 2 variables.

Patients taking a combination of any antiplatelet agent and any anticoagulant experienced significantly increased rates of hematuria-related complications, particularly for hospitalizations (range of rate ratios, 2.68-4.16) and emergency department visits (range of rate ratios, 6.03-10.48) (Table 5).

Table 5.

Multivariable Negative Binomial Regression Models Assessing the Association Between Exposure to Combined Antithrombotic Therapy and Hematuria-Related Complications
VariableAssociation of Antithrombotic Medication Exposure, Stratified by Age at Prescription
Patients 66-69 yPatients 70-74 yPatients 75-79 yPatients 80-84 yPatients ≥85 y
UnexposedExposedUnexposedExposedUnexposedExposedUnexposedExposedUnexposedExposed
Exposure time (person-years)7 688 13640101 994 04862251 263 2187500630 1706364354 7104867
Any Hematuria-Related Complication
No. of events530 442598174 7711182108 154167950 052121122 855880
Incidence density ratea69.00149.1487.65189.8985.62223.8679.43190.3064.43180.79
Adjusted rate ratio (95% CI)b1.39 (1.18-1.62)1.96 (1.75-2.19)2.36 (2.15-2.60)2.06 (1.83-2.32)2.03 (1.76-2.34)
P value<.001<.001<.001<.001<.001
Emergency Department Visits
No. of events14 749835705137406017623851141455112
Incidence density ratea1.9220.702.8622.013.2123.473.7917.914.1023.01
Adjusted rate ratio (95% CI)b6.03 (4.52-8.05)7.35 (5.95-9.09)8.08 (6.72-9.72)6.94 (5.48-8.79)10.48 (8.16-13.45)
P value<.001<.001<.001<.001<.001
Hospitalizations
No. of events37 5568811 368180732423937941682052119
Incidence density ratea4.8921.955.7028.925.8031.876.0226.405.7924.45
Adjusted rate ratio (95% CI)b2.68 (2.08-3.47)3.68 (3.04-4.45)4.16 (3.51-4.92)3.82 (3.17-4.61)3.75 (2.97-4.75)
P value<.001<.001<.001<.001<.001
Urologic Procedures
No. of events478 127427157 69486396 767126443 87092919 348649
Incidence density ratea62.19106.5079.08138.6476.60168.5369.62145.9954.55133.34
Adjusted rate ratio (95% CI)b1.09 (0.93-1.27)1.56 (1.39-1.76)2.00 (1.82-2.22)1.75 (1.55-1.99)1.65 (1.41-1.93)
P value.30<.001<.001<.001<.001
aIncidence density rates are expressed as the number of events per 1000 person-years.
bModels adjusted for association of participant sex, comorbidity, rurality, income quintile, and geographic region of residence. Rate ratios compare combined antithrombotic exposed and unexposed periods, with stratification by patient age due to a significant interaction between these 2 variables.

Sensitivity Analysis

While clot evacuation, control of bladder bleeding, and cystoscopy are unlikely to be indicated for patients without a history of bladder cancer in the absence of hematuria, urethral catheterization may be indicated owing to urinary retention. Thus, we performed a sensitivity analysis excluding catheterization from the definition of urologic procedures. While the overall event rate was lower, in regression models, the direction and magnitude of association were similar to the primary analysis, with antithrombotic exposure associated with a rate ratio of hematuria-related complications ranging from 1.39 to 2.36, depending on patient age (all P < .001; eTable 5 in the Supplement).

Subgroup Analyses

To examine the association of BPH and medical kidney disease on hematuria, we used surrogate measures including prescriptions of BPH medications and consultations with nephrologists. Prescription of a BPH-related medication in the year prior to antithrombotic prescription was also associated with an increased rate of hematuria-related complications (range of adjusted rate ratios, 1.67-1.93; all P < .001). This association persisted across secondary outcomes and individual antithrombotic medication exposures. Similarly, nephrology consultation was significantly associated with an increased risk of hematuria-related complications (range of adjusted rate ratios, 1.88-2.26; all P < .001).

In addition, 12 108 of 425 350 individuals (2.85%; 95% CI, 2.80%-2.90%) who presented with a hematuria-related complication were subsequently diagnosed as having bladder cancer within 6 months. A significantly higher proportion of patients exposed to antithrombotic agents (0.70%) were diagnosed as having bladder cancer than those who were unexposed to these agents (0.38%; unadjusted odds ratio, 1.85; 95% CI, 1.79-1.92). We calculated the standardized incidence ratio of bladder cancer among patients receiving antithrombotic agents, compared with the general Ontario population, with age and sex adjustment. Those receiving antithrombotic prescriptions had significantly more bladder cancer diagnoses than expected (SIR, 2.38; 95% CI, 2.32-2.44). Among women, the SIR was 2.17 (95% CI, 2.06-2.30) and among men it was 2.33 (95% CI, 2.26-2.40). Standardized incidence ratios of other urologist-managed cancers (prostate cancer: SIR, 0.75; 95% CI, 0.73-0.77, and kidney cancer: SIR, 0.64; 95% CI, 0.59-0.68) were not elevated among patients prescribed antithrombotic agents. The unadjusted odds ratio for being diagnosed as having prostate cancer was 1.65 (95% CI, 1.62-1.73) for patients in the exposed group, compared with the unexposed group, and for kidney cancer was 1.50 (95% CI, 1.4-1.6). Specific frequency of cancers and BPH outcomes are detailed in eTable 6 in the Supplement and the distribution of duration of time for each antithrombotic medication are detailed in eTable 7 in the Supplement.

Discussion

In this population-based cohort study among 2 518 064 older adults in Ontario, Canada, treatment with antithrombotic medications, compared with nonuse of these medications, was significantly associated with increased rates of hematuria-related complications (including emergency department visits, hospitalizations, and urologic procedures to manage gross hematuria). While there was variation between medications, this association was present for all medications examined. Readily identifiable factors, including patient age, male sex, comorbidity, and preexistent urologic disease, were significantly associated with rates of gross hematuria. Patients taking antithrombotic agents were more likely to be diagnosed as having bladder cancer, both compared with unexposed individuals and with the general population. As there is no putative mechanistic linkage, these data suggest that use of antithrombotic agents was likely unmasking otherwise clinically silent bladder cancers.

In 1994, a prospective study of 243 patients receiving oral anticoagulation concluded that there was no association between anticoagulant use and hematuria. These data are outdated given the introduction of novel anticoagulant and antiplatelet agents. More recently, observational postmarketing surveillance reports have included other sources of “extracranial bleeding” but none have explicitly examined the association between hematuria and treatment with antithrombotic agents.

Historically, hematuria, particularly among patients taking antithrombotic agents, was associated with a significant burden of clinically significant, and potentially life-threatening, urologic disease. This analysis identified an association of asymptomatic bladder cancer among patients undergoing antithrombotic therapy, with an SIR of 2.4, although the absolute rate of bladder cancer remains low. Compared with the control group, in this study, positive associations for being diagnosed as having prostate and kidney cancer were found between the exposed and unexposed groups, but there was no increase in their SIRs. This is because the SIR was based on comparison with the general population, which is more heterogeneous than the control group that was used in the analysis.

A previous population-based study in Ontario showed that randomized clinical trials significantly underestimate rates of hemorrhage associated with warfarin therapy. Compared with warfarin, recent studies have shown lower rates of intracranial bleeding for each of the direct oral anticoagulants individually and, when combined, major bleeding is also reduced. In contrast, this analysis demonstrated an increased rate of hematuria-related complications associated with rivaroxaban use and comparable rate between warfarin and other newer anticoagulants. A similar result has been observed for gastrointestinal bleeding and abnormal uterine bleeding in menstruating women. There is no clear biologic explanation why there were observed differences in hematuria complications between different antithrombotic agents. Further study into the exact mechanisms of the causes of hematuria from the urinary tract based on their mechanism of action will be necessary.

Long-term antithrombotic decisions often require complex risk-benefit considerations. Among patients with a clear indication for anticoagulation, these medications are associated with improved survival. Over time, significant changes in the prescribing of antithrombotic medications have occurred and overall use has significantly expanded. Gross hematuria can be significantly distressing to patients and may contribute to subsequent poor adherence with antithrombotic therapy, which has been shown to increase the risk of stroke and death. Similarly, antithrombotic discontinuation due to bleeding contributes to increased rates of thrombotic events. Thus, the persistent risk of thrombotic events and relative infrequency of hematuria requiring hospitalization suggest that ongoing anticoagulant use is often warranted. Research to produce patient-specific decision aids based on cost-benefit or cost-effectiveness analyses incorporating reductions in thrombotic events, as well as hematuria and other adverse events, would be valuable.

Strengths

This sample was larger than recent nationwide cohort studies assessing bleeding events from antithrombotic treatment in Denmark and France. In addition to the large sample size, this study has significant strengths owing to its population-based nature. First, this study was performed in Ontario, Canada, a jurisdiction in which all relevant medications and health services are available free of cost to seniors and are systematically tracked in administrative databases. Second, as all patients older than the age of 66 years in the largest province of Canada were identified, these results are generalizable. Unlike randomized clinical trials with strict inclusion and exclusion criteria or institutional reports representing tertiary care patterns, these results represent the population spectrum of clinical practice. Third, all hospitalizations and emergency department visits occurring anywhere in the province of Ontario were captured. This eliminates recall bias and minimizes selection bias. Thus, the outcome ascertainment is more robust than institutional studies. Fourth, as patients may stop antithrombotic medications owing to adverse events, they may transition from exposed to unexposed states and back. The use of a time-varying exposure used herein allows for accurate attribution of exposure for each patient at the time of each hematuria-related event. For this reason, survival analysis could not be conducted with competing risk analysis with morbidity and mortality, which would cause the exposure to cease.

Limitations

This study had 5 limitations. First, owing to funding eligibility for prescription medications in Ontario, the cohort was restricted to patients aged 66 years and older. Given the interaction between age and the association of antithrombotic therapies with hematuria-related complications, these results are not directly applicable to younger patients. Second, the databases preclude capture of the use of over-the-counter low-dose aspirin and nonsteroidal anti-inflammatories. Low-dose aspirin has been associated with lower rates of major bleeding compared with higher-dose therapy. Thus, as high-dose aspirin (≥82 mg) had the lowest rate ratio for hematuria-related complications of all agents examined, low-dose aspirin is unlikely to be associated with a clinically significant risk of hematuria. Low-molecular-weight heparins were not included in the analysis owing to differing indications and their typical short durations of use. Thus, these results should only be applied to oral antithrombotic agents. Third, exposure ascertainment relied on data on prescriptions filled as a surrogate for medication use without verification of medication consumption. Nonadherence estimates have ranged from 25% to 55% and would bias these results toward the null. Fourth, the outcome definition was restricted to hospitalizations and emergency department visits, excluding outpatient office physician interactions. Hospitalizations, emergency department visits, and urologic interventions are likely to capture most significant episodes of gross hematuria and the validity of these diagnoses has been well established in Ontario, while this is not true for diagnostic fields associated with outpatient consultations. However, the specific diagnoses and procedures examined in this study have not been directly validated. For urological procedures, these were used as surrogates for actual complications without an ability to ascertain the indication for each intervention. While there are alternative indications for urethral catheterization (namely, acute urinary retention), few alternatives exist for cystoscopy, clot removal/irrigation, or control of bladder bleeding in the absence of a history of bladder cancer. A sensitivity analysis removing urethral catheterization from the outcome definition did not substantively change the findings. Fifth, the available data sets lacked information on the doses of antithrombotic medications, cumulative dose exposure, patient weight or body mass index, international normalized ratio values for patients taking warfarin, and alcohol consumption. However, within the study, a proportion of patients served as their own controls for the time they were not taking an antithrombotic medication, which would minimize this bias.

Conclusions

Among older adults in Ontario, Canada, use of antithrombotic medications, compared with nonuse of these medications, was significantly associated with higher rates of hematuria-related complications (including emergency department visits, hospitalizations, and urologic procedures to manage gross hematuria).

Notes

Supplement.

eFigure. Schematic of Time-Varying Intermittent Exposure to Antithrombotic Medications, Illustrating the Calculation of Incidence Density Rates.

eTable 1. Medications Included in Exposure Definition.

eTable 2. Outcome Definitions.

eTable 3. Validation of Administrative Data Sources.

eTable 4. Medications Included in BPH Medication Exposure.

eTable 5. Sensitivity Analysis: Multivariable Negative Binomial Regression Models Assessing the Association Between Exposure to Antithrombotic Agents (Primary Exposure) and Hematuria-Related Complications, Using a limited definition of Urologic Procedures (Study Interval Between 2002-2014).

eTable 6. Standardized Incidence Ratios (SIR) of Potential Outcomes of Hematuria-Related Investigations (Study Interval Between 2002-2014).

eTable 7. Continuous Length of Time That Patients Spend on Each Drug.

References

1. National Center for Health Statistics Health, United States, 2015. Hyattsville, MD: Centers for Disease Control and Prevention; 2016. [Google Scholar]
2. Hart RG, Pearce LA, Aguilar MI. Meta-analysis: antithrombotic therapy to prevent stroke in patients who have nonvalvular atrial fibrillation. Ann Intern Med. 2007;146(12):857-867. [Abstract] [Google Scholar]
3. Baigent C, Blackwell L, Collins R, et al. ; Antithrombotic Trialists’ (ATT) Collaboration . Aspirin in the primary and secondary prevention of vascular disease: collaborative meta-analysis of individual participant data from randomised trials. Lancet. 2009;373(9678):1849-1860. [Europe PMC free article] [Abstract] [Google Scholar]
4. Shehab N, Lovegrove MC, Geller AI, Rose KO, Weidle NJ, Budnitz DS. US emergency department visits for outpatient adverse drug events, 2013-2014. JAMA. 2016;316(20):2115-2125. [Abstract] [Google Scholar]
5. Budnitz DS, Lovegrove MC, Shehab N, Richards CL. Emergency hospitalizations for adverse drug events in older Americans. N Engl J Med. 2011;365(21):2002-2012. [Abstract] [Google Scholar]
6. Ruff CT, Giugliano RP, Braunwald E, et al. Comparison of the efficacy and safety of new oral anticoagulants with warfarin in patients with atrial fibrillation: a meta-analysis of randomised trials. Lancet. 2014;383(9921):955-962. [Abstract] [Google Scholar]
7. Gaist D, García Rodríguez LA, Hellfritzsch M, et al. Association of antithrombotic drug use with subdural hematoma risk. JAMA. 2017;317(8):836-846. [Abstract] [Google Scholar]
8. Culclasure TF, Bray VJ, Hasbargen JA. The significance of hematuria in the anticoagulated patient. Arch Intern Med. 1994;154(6):649-652. [Abstract] [Google Scholar]
9. Matulewicz RS, Meeks JJ. Blood in the urine (hematuria). JAMA. 2016;316(14):1508. [Abstract] [Google Scholar]
10. von Elm E, Altman DG, Egger M, Pocock SJ, Gøtzsche PC, Vandenbroucke JP; STROBE Initiative . The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. Ann Intern Med. 2007;147(8):573-577. [Abstract] [Google Scholar]
11. Benchimol EI, Smeeth L, Guttmann A, et al. ; RECORD Working Committee . The REporting of studies Conducted using Observational Routinely-collected health Data (RECORD) statement. PLoS Med. 2015;12(10):e1001885. [Europe PMC free article] [Abstract] [Google Scholar]
12. Ontario's Local Health Integration Networks. http://www.lhins.on.ca/. Accessed March 17, 2017.
13. Johns Hopkins Bloomberg School of Public Health The Johns Hopkins ACG Case-Mix System Reference Manual Version 7.0. Baltimore, MD: The Johns Hopkins University Bloomberg School of Public Health; 2005. [Google Scholar]
14. Austin PC, van Walraven C, Wodchis WP, Newman A, Anderson GM. Using the Johns Hopkins Aggregated Diagnosis Groups (ADGs) to predict mortality in a general adult population cohort in Ontario, Canada. Med Care. 2011;49(10):932-939. [Europe PMC free article] [Abstract] [Google Scholar]
15. Levy AR, O’Brien BJ, Sellors C, Grootendorst P, Willison D. Coding accuracy of administrative drug claims in the Ontario Drug Benefit database. Can J Clin Pharmacol. 2003;10(2):67-71. [Abstract] [Google Scholar]
16. Juurlink DN, Preyra C, Croxford R, et al. Canadian Institute for Health Information Discharge Abstract Database: A Validation Study. Toronto, ON, Canada: Institute for Clinical Evaluation Sciences; 2006. [Google Scholar]
17. Williams JI, Young W. A summary of studies on the quality of health care administrative databases in Canada In: Goel V, Williams J, Anderson G, et al. , eds. Patterns of Health Care in Ontario, Canada: The ICES Practice Atlas. Ottawa, ON, Canada: Canadian Medical Association; 1996:339-345. [Google Scholar]
18. Robles SC, Marrett LD, Clarke EA, Risch HA. An application of capture-recapture methods to the estimation of completeness of cancer registration. J Clin Epidemiol. 1988;41(5):495-501. [Abstract] [Google Scholar]
19. Iron K, Zagorski BM, Sykora K, Manuel DG. Living and Dying in Ontario: An Opportunity for Improved Health Information. Toronto, ON, Canada: ICES Investigative Report; 2008. [Google Scholar]
20. Diehr P, Yanez D, Ash A, Hornbrook M, Lin DY. Methods for analyzing health care utilization and costs. Annu Rev Public Health. 1999;20:125-144. [Abstract] [Google Scholar]
21. Moineddin R, Meaney C, Agha M, Zagorski B, Glazier RH. Modeling factors influencing the demand for emergency department services in Ontario: a comparison of methods. BMC Emerg Med. 2011;11:13. [Europe PMC free article] [Abstract] [Google Scholar]
22. Vasdev N, Kumar A, Veeratterapillay R, Thorpe AC. Hematuria secondary to benign prostatic hyperplasia: retrospective analysis of 166 men identified in a single one stop hematuria clinic. Curr Urol. 2013;6(3):146-149. [Europe PMC free article] [Abstract] [Google Scholar]
23. Moreno JA, Martín-Cleary C, Gutiérrez E, et al. Haematuria: the forgotten CKD factor? Nephrol Dial Transplant. 2012;27(1):28-34. [Abstract] [Google Scholar]
24. Yao X, Abraham NS, Sangaralingham LR, et al. Effectiveness and safety of dabigatran, rivaroxaban, and apixaban versus warfarin in nonvalvular atrial fibrillation. J Am Heart Assoc. 2016;5(6):e003725. [Europe PMC free article] [Abstract] [Google Scholar]
25. Larsen TB, Skjøth F, Nielsen PB, Kjældgaard JN, Lip GY. Comparative effectiveness and safety of non-vitamin K antagonist oral anticoagulants and warfarin in patients with atrial fibrillation: propensity weighted nationwide cohort study. BMJ. 2016;353:i3189. [Europe PMC free article] [Abstract] [Google Scholar]
26. Mariani AJ, Mariani MC, Macchioni C, Stams UK, Hariharan A, Moriera A. The significance of adult hematuria: 1,000 hematuria evaluations including a risk-benefit and cost-effectiveness analysis. J Urol. 1989;141(2):350-355. [Abstract] [Google Scholar]
27. Avidor Y, Nadu A, Matzkin H. Clinical significance of gross hematuria and its evaluation in patients receiving anticoagulant and aspirin treatment. Urology. 2000;55(1):22-24. [Abstract] [Google Scholar]
28. Gomes T, Mamdani MM, Holbrook AM, Paterson JM, Hellings C, Juurlink DN. Rates of hemorrhage during warfarin therapy for atrial fibrillation. CMAJ. 2013;185(2):E121-E127. [Europe PMC free article] [Abstract] [Google Scholar]
29. Chai-Adisaksopha C, Crowther M, Isayama T, Lim W. The impact of bleeding complications in patients receiving target-specific oral anticoagulants: a systematic review and meta-analysis. Blood. 2014;124(15):2450-2458. [Abstract] [Google Scholar]
30. Holster IL, Valkhoff VE, Kuipers EJ, Tjwa ET. New oral anticoagulants increase risk for gastrointestinal bleeding: a systematic review and meta-analysis. Gastroenterology. 2013;145(1):105-112.e15. [Abstract] [Google Scholar]
31. Martinelli I, Lensing AW, Middeldorp S, et al. Recurrent venous thromboembolism and abnormal uterine bleeding with anticoagulant and hormone therapy use. Blood. 2016;127(11):1417-1425. [Europe PMC free article] [Abstract] [Google Scholar]
32. Adelborg K, Grove EL, Sundbøll J, Laursen M, Schmidt M. Sixteen-year nationwide trends in antithrombotic drug use in Denmark and its correlation with landmark studies. Heart. 2016;102(23):1883-1889. [Abstract] [Google Scholar]
33. Groninger H, Phillips JM. Gross hematuria: assessment and management at the end of life. J Hosp Palliat Nurs. 2012;14(3):184-188. [Europe PMC free article] [Abstract] [Google Scholar]
34. Raparelli V, Proietti M, Cangemi R, Lip GY, Lane DA, Basili S. Adherence to oral anticoagulant therapy in patients with atrial fibrillation: focus on non-vitamin K antagonist oral anticoagulants. Thromb Haemost. 2017;117(2):209-218. [Abstract] [Google Scholar]
35. Jackevicius CA, Tsadok MA, Essebag V, et al. Early non-persistence with dabigatran and rivaroxaban in patients with atrial fibrillation. Heart. 2017;103(17):1331-1338. [Abstract] [Google Scholar]
36. Sengupta N, Feuerstein JD, Patwardhan VR, et al. The risks of thromboembolism vs. recurrent gastrointestinal bleeding after interruption of systemic anticoagulation in hospitalized inpatients with gastrointestinal bleeding: a prospective study. Am J Gastroenterol. 2015;110(2):328-335. [Abstract] [Google Scholar]
37. Maura G, Blotière PO, Bouillon K, et al. Comparison of the short-term risk of bleeding and arterial thromboembolic events in nonvalvular atrial fibrillation patients newly treated with dabigatran or rivaroxaban versus vitamin K antagonists: a French nationwide propensity-matched cohort study. Circulation. 2015;132(13):1252-1260. [Europe PMC free article] [Abstract] [Google Scholar]
38. Yu J, Mehran R, Dangas GD, et al. Safety and efficacy of high- versus low-dose aspirin after primary percutaneous coronary intervention in ST-segment elevation myocardial infarction: the HORIZONS-AMI (Harmonizing Outcomes With Revascularization and Stents in Acute Myocardial Infarction) trial. JACC Cardiovasc Interv. 2012;5(12):1231-1238. [Abstract] [Google Scholar]
39. Huang ES, Strate LL, Ho WW, Lee SS, Chan AT. Long-term use of aspirin and the risk of gastrointestinal bleeding. Am J Med. 2011;124(5):426-433. [Europe PMC free article] [Abstract] [Google Scholar]
40. Rodriguez RA, Carrier M, Wells PS. Non-adherence to new oral anticoagulants: a reason for concern during long-term anticoagulation? J Thromb Haemost. 2013;11(2):390-394. [Abstract] [Google Scholar]

Full text links 

Read article at publisher's site: https://doi.org/10.1001/jama.2017.13890

Read article for free, from open access legal sources, via Unpaywall: https://europepmc.org/articles/pmc5818855Unpaywall

Citations & impact 

Impact metrics

18
Citations
Jump to Citations

Citations of article over time

Alternative metrics

Altmetric item for https://www.altmetric.com/details/26970756
Altmetric
Discover the attention surrounding your research
https://www.altmetric.com/details/26970756

Article citations

Go to all (18) article citations

Data 

Data behind the article

This data has been text mined from the article, or deposited into data resources.

BioStudies: supplemental material and supporting data

Similar Articles 

To arrive at the top five similar articles we use a word-weighted algorithm to compare words from the Title and Abstract of each citation.

Funding 

Funders who supported this work.

CIHR