STABLE Results: Warfarin Home Monitoring
Achieves Excellent INR Control
Grace DeSantis, PhD; Jackie Hogan-Schlientz, RN, BSN; Gary Liska, BS; Shari Kipp, BS;
Ramarion Sallee; Mark Wurster, MD; Kenneth Kupfer, PhD; and Jack Ansell, MD
Point-of-care, home international
normalized ratio (INR) monitoring (patient
self-testing, or PST) provides an opportunity to
pproximately 4 million people in the United States receive
oral anticoagulation therapy with the vitamin K antagonist (VKA) warfarin,1 and require frequent international normal-
optimize warfarin therapy as demonstrated in
ized ratio (INR) monitoring to maintain time in the therapeutic range.2
randomized trials. This study sought to determine
There are several models of warfarin management designed to maintain
the quality of warfarin therapy as determined by time in therapeutic INR range (TTR) in patients
the patients' INR within these desired parameters.3 These include usual
who perform home monitoring outside of a clini-
care (UC), which means an individual physician manages multiple pa-
cal trial setting.
tients without formal systematic monitoring policies or procedures to
Managed Care &
The data base of an independent diag-
focus on dose management; anticoagulation clinic care (AC), which
nostic testing facility was retrospectively queried
Healthcare Communications, LLC
means dose management is overseen by a healthcare provider (usually
over a 2.5-year period (January 2008-June 2011) and patient TTR was analyzed based on frequency
a nurse or pharmacist) under physician leadership with systematic poli-
of testing, age, gender, indication for therapy,
cies and procedures in place; and patient self-testing (PST) or patient
duration of therapy, and critical value occurrence.
self-management (PSM), which means patients perform their own INR
A total of 29,457 patients with multiple
indications for warfarin therapy comprised the
test at home with a portable point-of-care (POC) instrument and re-
database. The mean TTR for the entire group
ceive dose instructions from a healthcare provider (PST) or manage
was 69.7%, with weekly testers achieving a TTR
their own dose (PSM). Under UC or AC, test frequency may be irregu-
of 74% versus 68.9% for variable testers (testing every 2-4 weeks)(P
<.0001). In all categories
lar, and is often determined by a patient's ability to travel to a lab or
analyzed (age, indication for anticoagulation, and
clinic to obtain the INR test result, rather than INR testing frequency
referral site volume), weekly testers performed significantly better than variable testers. Older in-
depending on the pharmacology and metabolism of warfarin.4
dividuals had a higher TTR than younger patients.
Clinical evidence has demonstrated that more frequent testing im-
Weekly testers experienced significantly fewer critical values (INR <1.5 or >5.0) than did variable
proves warfarin safety and reduces risks for thromboembolic and major
bleeding events.5 The advent of POC INR devices and home monitor-
Point-of-care patient self-testing
ing has facilitated more frequent testing, provided greater consistency in
at home achieves high-quality warfarin therapy outside of clinical trials and compares favorably
testing reagents and instrumentation, and increased patient empower-
with the results achieved in randomized trials or
ment. Since 2004, the American College of Chest Physicians (ACCP)
in anticoagulation clinic settings.
Am J Manag Care. 2014;20(3):202-209
has recommended PST as a means of warfarin dose management, and
according to the 2012 ACCP guidelines,6 "for patients who are moti-
vated and can demonstrate competency, PSM is recommended over UC
(Grade 2B)." This recommendation is based on the results of numer-
ous clinical trials of PST/PSM compared with both UC and AC care.
Recently, Heneghan, et al, and Bloomfield, et al, have performed inde-
pendent meta-analyses of a number of clinical trials documenting the
benefit of PST or PSM.7,8 Depending on how the analyses are done, each
investigative group has shown greater efficacy of PST/PSM with a re-
duction in thromboembolism risk and/or major bleeding risk. However,
there is little evidence to date,
outside of randomized clinical
trials (RCTs), to assess outcomes In this article
For author information and disclosures,
Take-Away Points / 203
see end of text.
for patients who perform PST or www.ajmc.com
PSM.9 We evaluated the qual- Full text and PDF
n www.ajmc.com n
Warfarin Home Monitoring
ity of PST anticoagulation management as
reflected by time in therapeutic INR range
Real-world retrospective analysis of over 29,000 patients performing International
(TTR) in a large cross-section of real world
Normalized Ratio (INR) home monitoring for warfarin therapy shows excellent time
(non-study) patients from the United States
in therapeutic range.
enrolled in a home monitoring program and
n This study documents the ability of patients to monitor their own warfarin ther-apy outside of a clinical trial setting.
sought to determine whether INR testing fre-
n The high rate of time in therapeutic range and limited extreme INR values indi-
quency had an impact on TTR.
cates the potential for this model of therapy to reduce adverse events with warfarin therapy.
n This model of therapy has the potential to improve quality of life for patients on warfarin therapy, to reduce physician work, and ultimately lead to an increase in
treatment of patients who are not currently being treated.
Alere Inc, an independent diagnostic testing facility sidering this to be the initiation period,13 thus offering at least
(IDTF), has a database that includes anticoagulation patient 3 months of PST data to evaluate. In addition, we excluded data starting in 1993 and PST data starting in 1998. It in-
patients with results greater than 56 days between tests (DBT)
cludes data from over 68,000 PSTs (>3.1 million INR results) as per the Rosendaal methodology,14 patients with INR target who were referred from a variety of settings ranging from of-
range widths other than 1.0 (to comply with ACCP guide-
fice practices (cardiology, internal medicine, family practice, line ranges that are all 1.0 INR in width [eg, 2.0-3.0, 2.5-3.5]) hematology, oncology) to large organized clinics, and enrolled and patients younger than 18 years (to maintain focus of this in a comprehensive PST support service.
analysis on adults).
Prescribing physicians generally select PST candidates
The PST prescription form requires the physician to direct
based on whether the patient is able, willing, and reli-
the test frequency (TF), with selections that accommodate
able enough to measure their INR on a POC instrument at ACCP Guidelines for weekly, or options for 1 to 4 times per home.10,11 Then, physicians complete prescription forms for month (variable). Since not all patients adhere to their pre-patient submission to the IDTF. Patients are then individually scribed TF, the actual TF for each patient was established and trained. Standardized protocols developed by Alere, based on reported. The definition adopted for this study was based on human factors, support training retention and positive testing the THINRS trial that defined weekly testing as 5 to 9 days behaviors.12 All patients in this analysis were trained by ex-
between tests (7 + 2 DBT).13 The definition of monthly test-
perienced healthcare professionals, and immediate follow-up ing varies in the literature. THINRS defined monthly clinic was provided, as needed. Following physician instructions for testing as 21 to 49 DBT (35 + 14 DBT), but patients showed data and adherence management, Alere helped each patient a very low adherence rate of only 52% in that study. STABLE to initiate PST, become adherent to testing, and remain ad-
adopted a tighter range of 24 to 38 DBT (31 + 7 DBT).
herent to therapy. Clinicians were notified of all INR results,
Patient adherence to PST was used to establish study co-
and if patients were nonadherent.
horts. We defined patients who reported 10 out of 12 weekly tests (83.3%) for at least a 3-month period after the initial
3-month initiation period as those who represented strong
This Self-Testing Analysis Based on Long-term Evalua-
adherence. We also applied the same 83.3% adherence rate
tion (STABLE) is a retrospective cohort analysis of data from to the other TF categories for each patient over the duration real-world PST assessing 2 groups: variable and weekly testing of time the patient performed PST. Patients within any fixed cohorts. A query was developed to collect data on all patients TF who failed to meet this threshold were recategorized to the who were trained on or after January 1, 2008, and who com-
variable TF (1-4 tests/month). In summary, 4 nominal TF cat-
pleted at least 6 months of PST before June 30, 2011 (Figure
egories for all included patients were assigned based on the ad-1
). This window of observation was selected to capture a large herence model: weekly (83.3% of tests with 5-9 DBT), twice
cross-section of patients who qualified for PST before and per month (83.3% of tests with 10-17 DBT), monthly (83.3%
after the Centers for Medicare & Medicaid Services (CMS) of tests with 24-38 DBT), and variable (less than 83.3% of
expanded Medicare coverage to more indications.
tests in any one of the previously defined categories).
To eliminate potential bias as a result of individual differ-
The TTR determined by the Rosendaal method14 was used
ences in learning aptitude and time to mastery, we excluded as the primary surrogate end point for clinical outcomes. A the first 3 months of PST results after the training date, con-
stratified analysis was also performed, separating patients into
n THE AMERICAN JOURNAL OF MANAGED CARE n
n Figure 1.
Patients referred for PST;the entire Alere database
Patients excluded if they fell outside the observation
window (January 1, 2008-June 30, 2011), completed
less than 6 months of PST, or had more than 56 days between tests
Patients <18 years of age or with an INR target range
greater or less than 1 INR unit in width
INR indicates international normalized ratio; PST, patient self-testing.
2 groups: low TTR and high TTR. The incidence of criti-
within each observation period were included; intervals con-
cal INR values (INR <1.5 or INR >5.0)15 in each group was taining no critical values were considered censored observa-computed as the secondary surrogate end point. These sur-
tions; repeat test results within a single day were excluded).
rogate end points were categorized by actual testing frequen-
Statistical analysis was conducted in MATLAB version 7.5
cies. Four primary patient characteristics were evaluated: age,
(MathWorks, Natick, Massachusetts).
primary indication for warfarin, gender, and duration of PST.
Role of the Funding Source
The study was designed by clinical quality assurance and
The mean TTR for each subject was calculated based on research and development teams from Alere Inc, in collabo-
all INR test results within the observation period. The dis-
ration with outside experts in the field. All funding was pro-
tribution of mean TTR over all subjects (and within groups vided by Alere, which conducted the query and data analysis. of subjects) was characterized by the mean and the standard To maintain the privacy of all patients' identifiable health deviation (SD). The distribution of mean TTRs between sub-
information, and following Health Insurance Portability and
ject groups was compared via the Wilcoxon rank sum test. Accountability Act privacy rules, only de-identified patient Mean TTR was also treated as a dichotomous variable (low-
data were evaluated, and institutional review board approval
mean TTR <60% vs high-mean TTR >60%). The odds ra-
was granted (Western IRB).
tio (OR) was used to characterize the strength of association between dichotomous variables. The significance of associa-
tion between categorical variables was assessed via the χ² test. The correlation of an ordinal variable (eg, referral clinic size)
PST Patient Population Characteristics
with mean TTR was characterized by the Spearman corre-
A total of 29,457 patients met the criteria described in the
lation coefficient. The incidence of critical values (per unit query (Figure 1), and ranged in age from 18 to 105 years at time) was characterized by Kaplan-Meier cumulative prob-
the time they started PST, with a mean age of 70.5 years
ability curves and by Cox proportional hazard regression of (Table
). Of all the patients, 80% were at least 65 years or
the time between critical values (multiple critical values older, 56.0% were male, and atrial fibrillation (AF) was the
n www.ajmc.com n
Warfarin Home Monitoring
Mean and Standard Deviation of the Distribution of Mean Therapeutic Range (Units of Percent) for All
Patients Also Broken Out by Demographics and by Test Frequency (with P
value for the comparison of weekly vs
Variable (non-weekly) TF
No. referrals per sitea
AF indicates atrial fibrillation; DVT, deep vein thrombosis; MHV, mechanical heart valve; SD, standard deviation; TF, test frequency; TTR, therapeutic range.
Each numerical grouping represents the number of patients referred per site (eg, 6301 patients were referred from sites, each of which referred <10
patients; 11,593 patients came from sites, each of which referred >100 patients).
primary diagnosis for anticoagulation. Patient follow-up PST Patient Population Performance
ranged from 3 to 38 months with weekly and variable testers
The overall mean TTR was 69.7% (standard deviation
having an average of 17.2 and 14.5 months of follow-up data [SD] 18.6) for all 29,457 patients (Table). The majority of available, respectively. All patients were considered to have patients fell within 2 of our previously defined TF categories: performed self-testing and not self-management because the variable (n = 24,480; 83.1%) and weekly (n = 4550; 15.4%). prescription form does not indicate whether caregiver support The remaining 1.4% (n = 427) tested at a fixed TF of 2 tests is needed or whether PSM was to be followed.
per month (n = 320) or 1 test per month (n = 107). Due to the
Many physician specialties prescribed PST (cardiology, very small sample size for the 1-test-per-month and 2-tests-per-
internal medicine, family practice, general practice, hema-
month TF patients, we merged those patient populations with
tology, and oncology) for patients representing all major the large variable TF group to create a variable/non-weekly indications for warfarin (data not shown). Referral sites are group (n = 24,907; 904,687 INR results). The mean TTR for categorized as to whether they referred only a few patients this group was 68.9% (SD 19.1). Weekly testing, the single per site for PST training (<10 per site) to many patients per most commonly observed fixed TF (n = 4550; 333,068 INR site (>100 per site) for PST. Weekly testing was performed by results), provided a significantly higher mean TTR of 74.0% 15.4% of the patients.
(SD 15.1). These patients were at least 83.3% adherent to
n THE AMERICAN JOURNAL OF MANAGED CARE n
n Figure 2.
Time in Therapeutic Range (%) by Age Group
Time in Rang
THINRS13 and Bloomfield8 represent the mean TTR from the 2 studies.
weekly testing by definition. The Table also shows the TTR for ded by the total number of critical values. Patients with low subjects comparing variable versus weekly, and broken out by TTR had a dramatically increased incidence of critical val-demographic and baseline characteristics. Significantly higher ues (higher mean FCV) when compared with patients with mean TTR in weekly TF compared with variable TF groups high TTR (lower mean FCV). Patients with low TTR ex-was sustained across all patient demographics. A positive cor-
perienced a critical value every 4.46 months, while patients
relation was also found between the TTR and the number of with high TTR only experienced a critical value every 18.7 patients referred per site; patients who came from practices months, indicating a hazard ratio (HR) of 3.16 with 95% that referred a larger number of patients showed higher mean confidence interval (CI) of 1.89 to 2.22 from Cox regres-TTR with smaller standard deviations.
sion. Variable/non-weekly testers had a significantly higher probability of being in the low TTR group when compared
Performance by Age
with weekly testers (29.8% vs 17.1%, OR = 2.05, 95% CI,
Patients aged 65 to 74 years (71.5% TTR, SD 18.0; all TF) 1.89-2.22). When Cox regression model is adjusted for test
had higher TTR than the younger population of 46 to 64 years frequency, the HR of high versus low TTR strengthens (HR
(67.0%, SD 20.0; all TF) (Table). Patients older than 75 years = 3.20, 95% CI, 3.14-3.27) and the HR of weekly versus
also achieved relatively high TTR (75-79 years: 70.8%, SD variable test frequency is relatively weak (HR = 1.15, 95%
17.4; 80-84 years: 68.9%, SD 17.8; all TF). Figure 2
illustrates CI, 1.12-1.17). The Cox regression model shows that when
a summary of TTR achieved by age in this study, with TTR both TTR and test frequency are considered independent
from published controlled trials such as THINRS (TTR = variables, weekly testers have a higher probability of detect-
66.2% weekly PST) and Bloomfield's 22-study meta-analysis ing a critical value and thus are able to respond appropriately
(TTR = 66.1%) shown as warfarin control comparators.
to return to the therapeutic range.
Critical Value Incidence Analysis
A total of 49.8% of patients from the entire data set had
We performed a duration analysis to evaluate how pa-
one or more critical values (INR <1.5, or INR >5.0) dur-
tients perform over time. Patients in the weekly TF catego-
ing the observation period. The Kaplan-Meier curves ry achieved greater than 72% TTR in their first 3 months
) characterize the frequency of critical values postinitiation, and maintained or improved TTR over time
(FCV) in months based on whether patients had a high (Figure 4
). The TTR for weekly testers exceeded the TTR
(mean TTR >60%) or low (mean TTR <60%) TTR, and for variable TF patients for each 3-month period throughout
whether patients were weekly or variable testers. Mean FCV the study. Patients in the variable TF began at a lower TTR
is the total exposure (patient months of observation) divi-
of 65.5% and steadily increased their overall TTR over time.
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Warfarin Home Monitoring
n Figure 3.
Kaplan-Meier Curves Showing Cumulative Probability of a Critical Value in High Versus Low TTR
Groups and Weekly Versus Variable Testers
obability of a Cr
Low TTR, Weekly TF
Low TTR, Variable TF
High TTR, Weekly TF
High TTR, Variable TF
Weekly testers had a greater probability of being in the high TTR group (defined as TTR >60%).
n Figure 4.
Time in Therapeutic Range (%) According to Duration of Patient Self-Testing (PST)
00-03 04-06 07-09 10-12 13-15 16-18 19-21 22-24 25-27 28-30 31+
Duration of Patient Self-Testing (months)
However, it took the variable TF group 20 months longer to over a 42-month observation window. This study is the first achieve TTR greater than 70%, while never achieving the to show that patients perform well with self-testing as an ad-level of control attained by weekly testers.
junct to warfarin therapy outside of clinical trial settings. The analysis confirmed that in the United States, a wide variety of patients successfully perform PST and sustain high surrogate
end points of high TTR with low incidence of critical INR
STABLE is the largest observational retrospective analy-
values over time.
sis published to date, characterizing 29,457 real-world warfa-
The overall mean TTR was high (69.7%), exceeding
rin patients who self-test, and evaluating their performance the TTR of published RCTs16 and meta-analyses,7,8 as well
n THE AMERICAN JOURNAL OF MANAGED CARE n
n Figure 5.
Comparison of Alere Real-World STABLE Time in Therapeutic Range Versus Recent Large Controlled
Trials or Meta-analyses
Alere, Weekly PST
Retrospective PST analysis
THNRS trial,13 2010
RCT with VKA control
RCT with PST vs ACC
Time in Target Range, %
ACC indicates anticoagulation clinic; PST, patient self-testing; RCT, randomized controlled trial; UC, usual care; VKA, vitamin K antagonist.
as warfarin control comparators in studies of new target-
monthly intervals, but POC monitoring at home makes this
specific oral anticoagulants (Figure 5
).17-19 Even the lowest option easily available and manageable for both physicians
performing TF category of variable testers in this analysis and patients.
performed better than the best TTR among warfarin-treat-
The elderly are often considered to be at higher risk of
ed patients in randomized trials of the new target-specific bleeding during warfarin therapy3 and fewer than half of those oral anticoagulants. Studies have shown a strong correla-
patients who would benefit from warfarin actually receive it.
tion between the TTR as well as the distance of a result Given that an increasing number of elderly patients could from the therapeutic range and the occurrence of adverse benefit from warfarin, it is significant that in this STABLE events.20 It is therefore important to see that critical values, analysis, patients 75 years and older performed well, with a a quality measure of control and risk, used by an increas-
mean TTR above 73% for weekly testers.
ing number of clinicians, showed a significant difference
between the 2 major test frequencies evaluated. Patients Limitations and Strengths
with a higher TTR (>60%) had a lower probability of hav-
Strengths of this retrospective analysis include a large
ing a critical value compared with those with a lower TTR study population of nearly 30,000 real-world patients of (<60%) (mean FCV 18.7 months per critical value for TTR all ages, indications for warfarin, and care settings over a >60% vs 4.46 months for those with TTR <60%), and 38-month period. There are limitations of this analysis, weekly testers were less likely to be in the low TTR group however. Patients referred for PST may represent a select (17.1% vs 29.8%; OR = 2.05). The data also showed that population of patients who are reliable, adherent, and al-weekly testers achieved and maintained a high TTR ear-
ready stable on warfarin therapy, although in many of the
lier than non-weekly or variable testers. This triple benefit large RCTs, large cohorts of patients were also warfarin of early control, high TTR, and occurrence of low critical experienced. Time in therapeutic range is also time-value suggests that INR testing conducted on a structured dependent from the start of therapy21 and the elimination weekly and non-variable schedule promotes a higher degree of the first 3 months of start-up time eliminates initial of better clinical outcomes than variable testing schedules non-therapeutic INRs. In 4 non-POC randomized trials based on these surrogate outcome indicators. A weekly TF where the first 3 months were eliminated, TTR was mea-may represent a challenge to clinicians who are accustomed sured between 65% and 80%.21 These results, therefore, to and trained on counseling and titrating at traditional indicate that non-study patients can achieve a therapeutic
n www.ajmc.com n
Warfarin Home Monitoring
quality that is at least as good as well-designed prospective randomized trials. Furthermore, only patients who suc-
cessfully achieved competency and completed at least 6 1. Nutescu E, Bathija S, Sharp L, Gerber BS, Schumock GT, Fitzgibbon
ML. Anticoagulation patient self-monitoring in the United States: con-
months of PST were included, but it has previously been siderations for clinical practice adoption. Pharmacotherapy.
2011;31 documented that 80% of patients are able to achieve suc-
2. Centers for Medicare & Medicaid Services. Decision memo for pro-
cess in PST performance.13 Finally, Alere, the study spon-
thrombin time (INR) monitor for home anticoagulation management
sor, provided patient support in the form of education and (CAG-00087C, 2001; CAG-00087R, 2008). [memorandum]. Baltimore,
3. Ansell J, Hirsh J, Hylek E, et al. Pharmacology and management
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JD. The business case for quality improvement: oral anticoagulation
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This retrospective analysis offers the first insights into 5. Samsa GP, Matchar DB. Relationship between test frequency and
outcomes of anticoagulation: a literature review and commentary with
surrogate outcomes for patients on warfarin who were man-
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ment service in a real-world setting. With close to 30,000 ment of anticoagulant therapy. Chest.
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7. Heneghan C, Ward A, Perera R, et al. Self-monitoring of oral anti-
coagulation: systematic review and meta-analysis of individual data.
all mean TTR of 69.7%, higher than that observed for PST Lancet.
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in RCT. Weekly testing proved to be the optimal frequency patient self-testing and self-management of long-term anticoagulation for achieving the greatest TTR. Across several analyses (age, on major clinical outcomes. Ann Intern Med.
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13. Matchar DB, Jacobson A, Dolor R, et al. Effect of home testing of
international normalized ratio on clinical events. N Eng J Med.
The corresponding author has had full access to all of the data in the study
14. Rosendaal R, Cannegieter S, van der Meer F, van der Meer F, Briet
and takes responsibility for the integrity of the data and the accuracy of the
E. A method to determine the optimal intensity of oral anticoagulant
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therapy. Thromb Haemost.
Diego, Inc, for his ongoing guidance and critical review of this manuscript.
15. Guyatt GH, Akl EA, Crowther M, Gutterman DD, Schunemann JH.
Executive summary: antithrombotic therapy and prevention of
Alere Inc, San Diego, CA (GD, KK); Alere Home
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Westport, CT (MW); Lenox Hill Hospital, New York, NY (JA).
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Source of Funding:
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funded this study.
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Drs DeSantis, Wurster, and Kupfer, and Ms Hogan-
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Schlientz, Mr Liska, Ms Kipp, and Mr Sallee all report employment with Alere
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20. Hylek E, Skates S, Sheehan M, Singer DE. An analysis of the lowest
of data (GD, JH-S, GL, SK, RS, MW, KK, JA); drafting of the manuscript
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portant intellectual content (GD, JH-S, GL, SK, MW, JA); statistical analysis
21. Erkens PMG, ten Cate H, Buller HR, Prins MH. Benchmark for time
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Address correspondence to:
Jack Ansell, MD, 401 E 60th St, New York,
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NY 10022. E-mail: [email protected]
n THE AMERICAN JOURNAL OF MANAGED CARE n
International Journal of Ophthalmology & Eye Science (IJOES) Epidemiology of Eales Disease in the Central Western India Shah MA*, Shah SM, Kalyani PJ, Shah AH, Shah PD, Pandya JS Drashti Netralaya, Dahod, Gujarat, India. Objective: To investigate the clinical features and propose a new staging system based on the clinicopathological correla-
11700 • The Journal of Neuroscience, October 24, 2007 • 27(43):11700 –11711 Neurobiology of Disease Cannabinoids Elicit Antidepressant-Like Behavior andActivate Serotonergic Neurons through the MedialPrefrontal Cortex Francis Rodriguez Bambico,1 Noam Katz,1,2 Guy Debonnel,1† and Gabriella Gobbi1,21Neurobiological Psychiatry Unit, Department of Psychiatry, McGill University, Montre´al, Quebec, Canada H3A 1A1, and 2Department of Psychiatry, Centrede Recherche Fernand Seguin, Hoˆpital L.H. Lafontaine, Universite´ de Montre´al, Quebec, Canada H1N 3V2