2. • Atrial fibrillation, the most common cardiac arrhythmia, predisposes
patients to an increased risk of embolic stroke and has a higher mortality
than sinus rhythm. 1
• Until 2009, vitamin K antagonists (warfarin) were the only class of oral
anticoagulants available.
• Although highly effective in prevention of thromboembolism
• But narrow therapeutic index, need frequent monitoring and dose
adjustments, hence poor adherence.
• DOACs are recommended over warfarin in the 2019 American College of
Cardiology/American Heart Association/Heart Rhythm Society guideline for
the management of patients with AF.
Background
1. Camm AJ, Kirchhof P, Lip GY, et al: Guidelines for the management of atrial fibrillation: the Task Force for the Management of Atrial Fibrillation of the European Society of Cardiology (ESC).
Eur Heart J 2010; 31: pp. 2369-2429
8. Problem statement
Survivors of stroke have identified “being alive at home, without recurrent stroke, or
being hospitalized for complications” as the most desirable outcome.
Such patient-centered outcomes have not been well studied as an end point in
research on DOACs.
The PROSPER study builds on the GWTG-Stroke program, a national stroke registry and
quality-improvement initiative sponsored by the AHA/ASA
9. AIM
• To examine the clinical effectiveness of DOACs (dabigatran,
rivoroxaban, or apixaban) vs warfarin after ischemic stroke in
patients with AF.
10. Primary objectives
• To compare the baseline characteristics between ischemic stroke patients
with atrial fibrillation who were prescribed with warfarin vs. those
prescribed direct oral anticoagulants (DOACs) at discharge.
• To identify factors associated with prescription of DOACs at discharge.
• To evaluate the association between discharge DOACs vs. warfarin
treatment and longitudinal outcomes in the general population, as well as
among clinically relevant subgroups.
• To calculate follow-up times in ischemic stroke patients by discharge OAC
and by discharge year
11. MATERIALS AND METHODS
STUDY DEISGN:
• Retrospective cohort study
• STUDY POPULATION:
Ischemic stroke patients discharged between Oct 2011 and Dec 2014 (AHA
GWTG-Stroke July 2016 Harvest)
They linked GWTG-Stroke data to Medicare claims by matching the data
on a series of indirect identifiers, including admission date, discharge date,
the patient’s age or date of birth, and sex. This linkage method has been
successfully completed and validated using Medicare inpatient claims.
12. INCLUSION CRITERIA
1) Age >= 65
2) Linked to CMS 2015
3) Index (first) admissions
4) Eligible for FFS at discharge
5) Patients with MedHx or Dx of AF
6) Discharged Alive
EXCLUSION CRITERIA
1) Discharged to hospice/transferred
out/LAMA/disposition unknown
2) CRCL missing
3) Renal Insufficiency/On Dialysis/CRCL<15
4) Contradictions to OAC
5) Patients on OAC prior to admission
6) Patients missing discharge Warf/DOACs info
7) Patients not on Warf/DOACs at discharge
8) Patients with 2+ Warf/DOACs at discharge
9) Not recorded NIHSS
13. Home time within 1 year after discharge
MACE (composite of death and cardiovascular,
cerebrovascular readmission)
• Falsification Endpoints (all diagnosis fields):
Readmissions with Pneumonia;
Readmissions with Sepsis.
Home time is defined as the total
number of days alive and out of the
hospital or a skilled nursing facility
during the first year after the index
hospital discharge, reflecting a
patient’s desire of “being alive at
home, without recurrent stroke, or
being hospitalized for complications.
Home time represents a patient-centered
outcome measure for an episode of
stroke care and is highly correlated with
modified Rankin scale score.
The MACE end point is a composite
measure of all-cause mortality,
cardiovascular, or cerebrovascular
readmission.
Primary Outcomes:
14. They determined the date of death through the Medicare denominator files and ascertained the date and
cause of readmission from the Medicare hospital claims data, as has been done previously.
Mortality: All-cause
Readmissions:
• All-cause
• Cardiovascular
• Ischemic stroke
• Haemorrhagic stroke/ICH
• Systemic embolism
Readmissions with bleeding
Fatal bleeding (all diagnosis fields, readmissions
with bleeding diagnosis and recorded in-hospital
death).
Secondary Outcomes:
15. Statistical method
Incidence rates were calculated as the number of new events divided by person-time in years at risk.
Negative binomial model for the continuous outcome of home time
Cox proportional hazards model for binary outcomes such as MACE.
Propensity score–overlap weighting approach to control for potential selection bias.
The overlap weighting is an extension of the propensity score method to balance covariates between 2 treatment groups.
We also reported hospital readmission with pneumonia and sepsis (either primary or secondary diagnosis) as negative
outcome controls (falsification end points) to account for potential treatment selection bias. We selected
these 2 conditions because they are expected to be unassociated with anticoagulant choice and common enough to
provide sufficient power to detect false positives.
All P values were 2-sided,with P < .01 as the significance threshold for primary outcomes of home time and MACE and P <
.05 as the threshold for secondary and negative outcome controls.
16. Each individual’s statistical weight is proportional to the probability of that individual being assigned to the opposite
treatment group, derived from a generalized logistic regression model with treatment (DOACs vs warfarin) as the
dependent variable, all observed patient-level and hospital-level characteristics as the independent variables, and
generalized estimating equations to account for within-hospital correlations. The overlap weighting method
minimizes the asymptotic variance of the nonparametric estimate of the weighted average treatment effect
within the class of balancing weights and yields balance between treatment groups in the means of each covariate
included in the model.
Covariates included baseline patient sociodemographic and clinical factors, aswell as hospital characteristics, that are
expected to be associated with outcome and have been used in prior GWTG-Stroke analyses.27,41,42 These included
patient age, sex, self-reported race/ethnicity (as recorded by admission staff, medical staff, or both, usually during the
registration), and zip code–level socioeconomic status; medical history; emergency medical services transportation; on-hour
arrival (defined asMonday through Friday from7 AM to 6 PM, except for holidays) or off-hour arrival (defined as all other
times); NIHSS score at presentation; first measure of creatinine clearance, heart rate, and systolic blood pressure at
admission; and body mass index (calculated as weight in kilograms divided by height in meters squared).
22. Variables for risk adjustment in propensity score model:
• Demographics: Age, sex, race/ethnicity
• Medical history: A Fib/Flutter, prior MI/CAD, prior stroke, prior TIA, heart failure, carotid
stenosis,PVD, hypertension, dyslipidemia, diabetes, smoking
• Presentation: EMS, on/off arrival, NIHSS
• Hospital: Bed size, annual ischemic stroke volume, stroke center (PSC or CSC), academic status,
rural/urban location, region
• Additional: Zip code-based SES variables, creatinine clearance, heart rate, SBP, BMI;
• From CMS: Anemia, COPD, cirrhosis/liver disease, alcohol abuse, sleep apnea
23.
24.
25.
26.
27. Results:
• Patients discharged with DOACs (vs warfarin) had more days at home (mean [SD],
287.2 [114.7] vs 263.0 [127.3] days; adjusted difference, 15.6 [99% CI, 9.0-22.1] days)
during the first year post discharge.
• Less major adverse cardiovascular events (adjusted hazard ratio [aHR], 0.89 [99% CI,
0.83-0.96]).
• Fewer deaths (aHR, 0.88 [95% CI, 0.82-0.95]; P < .001), all-cause readmissions (aHR,
0.93 [95% CI, 0.88-0.97]; P = .003), cardiovascular readmissions (aHR, 0.92 [95% CI,
0.86-0.99]; P = .02), hemorrhagic strokes (aHR, 0.69 [95% CI, 0.50-0.95]; P = .02), and
hospitalizations with bleeding (aHR, 0.89 [95% CI, 0.81-0.97]; P = .009)
• Higher risk of gastrointestinal bleeding (aHR, 1.14 [95% CI, 1.01-1.30]; P = .03).
28. Retrospective observational analysis.
GWTG-Stroke registry only includes patients who experienced stroke.
Primary analysis focused on individuals with complete NIHSS scores: selection bias.
This study analyzed patients in the GWTG-Stroke and Medicare linked database, with complete renal function information;
excluded younger patients, those with impaired renal function, those treated in non–GWTG-Stroke hospitals, or those in
other countries.
Exclusion of patients with missing creatinine clearance: selection bias.
In patients with a severe stroke, physicians may wait 1 to 2weeks and then start anticoagulation shortly after discharge.
Exclusion of individuals who did not receive warfarin or DOACs at discharge may introduce selection bias.
Unlike DOACs, patients treated with warfarin need dosage adjustment: biased Home time. (But MACE and readmissions).
Compared warfarin with all other DOACs: not designed as a comparative study of each individual agent or associated dosage
strategies.
Limitations
30. CRITICAL APRAISAL
1. What question did the systematic review address?
The main question should be clear and focused. It should describe the population, intervention/exposure, and outcomes of
interest.
P:
I:
C:
O
2. Is it likely that all relevant studies (published and unpublished) were identified?
31. 3. Were the criteria used to select articles for inclusion predetermined, clearly stated, and appropriate?
4. Were the included studies sufficiently valid?
32. 5. Most importance drawback of the study?
6. Were the results similar from study to study?
7. Conflict of interest
33. 8. Clinical Importance
8a. What were the results of the review?
(Are the results of all included studies clearly displayed? Are the results similar from study to study? Is there a clinical
bottom line? If the study results were combined, was it appropriate to do so?)
8b. How precise are the results?
(What is the confidence interval? p-value?)
34. TAKE HOME MESSAGE
• Patients with acute ischemic stroke and AF, DOAC use at discharge
was associated with better long-term outcomes relative to warfarin.
Editor's Notes
Briefly, we excluded patients who were discharged to hospice; transferred to another hospital; received comfort measures only; had documented contraindications for anticoagulation treatment; had a medical history of renal insufficiency, dialysis, or creatinine clearance less than 15 mL/min; or with data missing, since these patients might not be eligible for DOACs. To avoid prevalent user bias, we further excluded those receiving chronic anticoagulation treatment before the index stroke admission. he National Institutes of Health Stroke Scale (NIHSS) score is a critical factor associated with outcomes in acute ischemic stroke, so we further excluded individuals with missing NIHSS scores (n = 2531) for the primary analysis
In Table 1, p-values less than 0.05 indicate statistically significant difference of the row 116 variables across discharge OAC groups in the IS population. It is important to note that, given large 117 study population size, we would expect to detect many statistically significant differences in the data, 118 but these differences might not be clinically meaningful. Percent standardized difference greater than 119 10 can be used as an alternative reference.
Excluded individuals with AF who take oral anticoagulation for primary stroke prevention.
given that renal function is a crucial factor for treatment decisions and dosages of the DOACs.
The addition of steroids to the AZA regimen is understandable owing to
the delayed onset of action of AZA that is due to the protracted plasma
half-life and theoretical slow accumulation of the biologic active metabolites
of AZA in the cells (Sahasranaman et al., 2008). It should be
noted that the sole administration of steroids may reduce relapses in
NMO (Watanabe et al., 2007). Therefore, cautious interpretation of
efficacy data should be performed due to variability of the interventions.
