Matthew A. Breeden, MD Department of Family and Community Medicine

Slides:



Advertisements
Similar presentations
Carol Coupland Paula Dhiman Tony Arthur Richard Morriss Julia Hippisley-Cox University of Nottingham Garry Barton University of East Anglia Antidepressant.
Advertisements

Trademarks may be registered and are the property of their respective owners. Today’s discussion may regard information or indications not evaluated by.
Associations between Obesity and Depression by Race/Ethnicity and Education among Women: Results from the National Health and Nutrition Examination Survey,
Journal Club Alcohol, Other Drugs, and Health: Current Evidence May–June 2010.
Inappropriate clopidogrel adherence explains stent related adverse outcomes Leonardo Tamariz, MD, MPH University of Miami.
1 Lauren E. Finn, 2 Seth Sheffler-Collins, MPH, 2 Marcelo Fernandez-Viña, MPH, 2 Claire Newbern, PhD, 1 Dr. Alison Evans, ScD., 1 Drexel University School.
Journal Club Alcohol, Other Drugs, and Health: Current Evidence January–February 2009.
Journal Club Alcohol, Other Drugs, and Health: Current Evidence November-December 2007.
1 Journal Club Alcohol, Other Drugs, and Health: Current Evidence July–August 2011.
RACIAL DISPARITIES IN PRESCRIPTION DRUG UTILIZATION AN ANALYSIS OF BETA-BLOCKER AND STATIN USE FOLLOWING HOSPITALIZATION FOR ACUTE MYOCARDIAL INFARCTION.
Management of Hypertension according to JNC 7 BY SANDAR KYI, MD.
Emily O’Brien, Emil Fosbol, Andrew Peng, Karen Alexander, Matthew Roe, Eric Peterson The Obesity Paradox: The Importance for Long-term Outcomes in Non-ST-Elevation.
TRANSLATING VISITS INTO PATIENTS USING AMBULATORY VISIT DATA (Hypertensive patient case study) by Esther Hing, M.P.H. and Julia Holmes, Ph.D U.S. DEPARTMENT.
for the Psychiatry Clerkship is proud to present And Now Here Is The Host... Insert Name Here.
Cognitive Impairment: An Independent Predictor of Excess Mortality SACHS, CARTER, HOLTZ, ET AL. ANN INTERN MED, SEP, 2011;155: ZACHARY LAPAQUETTE.
Effect of Hypertension and Dyslipidemia on glycemic control among Type 2 Diabetes patients in Thailand Dr. Mya Thandar Dr.PH. Batch 5 1.
Background Development of Anxiety Among Depressed Veterans After Antidepressant Usage Zhiguo Li, Paul Pfeiffer, Katherine Hoggatt, Kara Zivin, Karen Downing.
Strategies to Switch Antidepressants Brittany Parmentier, PharmD PGY2 Behavioral Care Resident Butler University/Community Health Network This speaker.
Influence of Comorbid Depression and Antidepressant Treatment on Mortality for Medicare Beneficiaries with Chronic Obstructive Pulmonary Disease by SSDI-eligibility.
Can pharmacists improve outcomes in hypertensive patients? Sookaneknun P (1), Richards RME (2), Sanguansermsri J(1), Teerasut C (3) : (1)Faculty of Pharmacy,
Utilization Of Lipid-lowering Therapy In Hypertensive Patients In The United States Simon S.K. Tang, MPH* Sean Candrilli, MS** Lizheng Shi, PhD* *Department.
Antidepressants and Suicide Risk in Children and Adolescents: Weighing the Evidence Jill A. Morris, PA-S.
Effect of Hypertension and Dyslipidemia on glycemic control among Type 2 Diabetes patients in Thailand Dr. Mya Thandar DrPH Batch 5 1.
Prevalence of Poor Glycemic Control and Depression Among Diabetic Adolescent Youth Presented By: Atwater K and Wilson S Prairie View A & M University Prevalence.
Lecture 9: Analysis of intervention studies Randomized trial - categorical outcome Measures of risk: –incidence rate of an adverse event (death, etc) It.
Aubert RE et al. ASCO 2009; Abstract CRA508. (Oral Presentation)
STAR*D Objectives Compare relative efficacy of different treatment options –Goal is REMISSION, not just “response” –Less than half of patients with depression.
Do veterans with spinal cord injury and diabetes have greater risk of macrovascular complications? Ranjana Banerjea, PhD 1, Usha Sambamoorthi, PhD 1,2,3,
A Claims Database Approach to Evaluating Cardiovascular Safety of ADHD Medications A. J. Allen, M.D., Ph.D. Child Psychiatrist, Pharmacologist Global Medical.
BASELINE BMI DOES NOT PREDICT SIX MONTH REMISSION RATE FOR DEPRESSION MANAGED UNDER COLLABORATIVE CARE MANAGEMENT Kurt B. Angstman, MS MD Todd W. Wade,
©2015 MFMER | slide-1 PTSD: Worsening outcomes for comorbid depression… even with collaborative care management. Kurt B. Angstman, MS, MD Professor of.
Date of download: 7/7/2016 Copyright © 2016 American Medical Association. All rights reserved. From: Comparative Mortality Risk in Adult Patients With.
Children’s Outcomes Research Program The Children’s Hospital Aurora, CO Children’s Outcomes Research Program The Children’s Hospital Aurora, CO Colorado.
Presenter:Ibishi Nazmie MD, PhD University Clinical Center of Kosovo Clinic Of Psychiatry Mesic Srebrenka, Nebi Musliu.
Copyright restrictions may apply JAMA Pediatrics Journal Club Slides: Preoperative Anemia and Postoperative Mortality in Neonates Goobie SM, Faraoni D,
R. Papani, A. G. Duarte, Y-L. Lin, G. Sharma
Management of Hypertension according to JNC 7
Association Between Serotonergic Antidepressant Use During Pregnancy and Autism Spectrum Disorder in Children Hilary K. Brown, PhD; Joel G. Ray, MD, MSc,
- Higher SBP visit-to-visit variability (SBV) has been associated
Alcohol, Other Drugs, and Health: Current Evidence July–August 2017
Landon Marshall, Pharm. D. , Matt Hill, Pharm. D. , Jim Wilson, Pharm
Instructional Objectives:
UNDERSTANDING THE MENTAL HEALTH SERVICE NEEDS OF DEPRESSED OLDER ADULTS: A STUDY OF AGE DIFFERENCES IN RECEIPT OF EVIDENCE BASED TEREATMENT FOR MAJOR.
Recognize and treat depression in epilepsy Maryam PoursadeghFard Shiraz University of Medical Science (1)Introduction: Depression is a major problem.
John Weeks1, MD Candidate 2017, Justin Hickman1, MD Candidate 2017
Patient Registries and Health Outcomes in Diabetes: A Retrospective Study Nipa Shah, MD1; Fern Webb, PhD1; Liane Hannah, BSH1; Carmen Smotherman, MS2;
Exercise Adherence in Patients with Diabetes: Evaluating the role of psychosocial factors in managing diabetes Natalie N. Young,1, 2 Jennifer P. Friedberg,1,
PCI related in-hospital mortality based on race and gender in the USA
Step 1: recognition and diagnosis Step 2: treatment in primary care
Understanding Associations Between Serious Mental Illness and Hepatitis C among Veterans: A National Multivariate Analysis Seth Himelhoch, MD, MPH,1,2.
Alina M. Allen MD, Patrick S. Kamath MD, Joseph J. Larson,
Introduction to Clinical Pharmacy
College of Nursing ● University of Kentucky ● Lexington, KY
Predictors of good and poor response in GAD
An analysis of the 2015 – 2016 NZ Health Survey
Menachem M Meller,MD, PhD
Progress and Promise in RAAS Blockade
Dr. Muhammad Ajmal Zahid Chairman, Department of Psychiatry,
Rhematoid Rthritis Respiratory disorders
Duloxetine Flavio Guzman, MD.
PHARMACOTHERAPY - I PHCY 310
Chapter 9: Community Pharmacy
Interhospital Transfers to MUSC
Predictors of good and poor response in GAD
Beth Wallace, BSN, RN-BC, FNP-S Fairfield University Summer 2010
M Javanbakht, S Guerry, LV Smith, P Kerndt
Excessive Daytime Sleepiness & Depression
The Research Question Does changing prescription medication labels to conform to the United States Pharmacopeia (USP) patient-centered, more understandable,
Cancer is not a risk factor for bullous pemphigoid
Colorectal cancer survival disparities in California
Presentation transcript:

Association Between Antidepressant Use and Time to Incident Hypertension Matthew A. Breeden, MD Department of Family and Community Medicine Saint Louis University School of Medicine As we all know, these are two very common primary care issues. We were interested in looking into the effects of ADM on blood pressure in a primary care population, given the high prevalence of both HTN and ADM use.

Disclosures Nothing to disclose

Hypertension Age-adjusted prevalence: 29.6% Approximately 48% achieve control Directly related to heart disease and stroke Which are the first and fourth leading causes of death, respectively Source(s): (Gillespie, Hurvitz et al. 2013)

Antidepressants Several classes Tricyclic Antidepressants (TCAs) Selective Serotonin Reuptake Inhibitors (SSRIs) Serotonin-Norepinephrine Reuptake Inhibitors (SNRIs) Norepinephrine and Dopamine Reuptake Inhibitors (NDRIs) Atypical Antidepressants

Antidepressants Widely used 11% of US population age 12 and up Frequently used for other indications, especially TCAs and SNRIs Varying data regarding influence on blood pressure, some of it conflicting A recent study showed that only ~ 15% of TCA prescriptions were for depression and anxiety indications, with the bulk being written for pain, insomnia, and migraines. Similarly, SNRIs are very commonly written for pain and fibromyalgia. SSRIs are largely written for diagnoses related to depression and anxiety. Source(s): (Olfson and Marcus 2009, Pratt, Brody et al. 2011)

Objectives Investigate whether antidepressant medication (ADM) use in primary care population is associated with development of hypertension Determine if certain classes of drugs, or even individual drugs, have more robust associations

Methods Data source: Primary Care Patient Data Registry 33661 patients Covers July 1, 2008 to June 30, 2015 De-identified data Urban and suburban academic primary care clinics in St. Louis, MO metro area.

Methods Inclusion criteria 18 years old with completed demographic data At least one visit in two-year washout period (July 1, 2008 to June 30, 2010) At least one visit in five-year follow-up period Patients with existing hypertension diagnosis in washout period were removed Final sample size: 6244 adult patients without pre-existing hypertension

Methods Study design Predictor variable Outcome Retrospective cohort, survival model Cox proportional hazards models used to calculate hazard ratios Predictor variable Antidepressant medication treatment One or more prescriptions for any antidepressant Analyzed both by ADM class and individual ADM Three types of treatment defined ADMs with recognized risk of increasing BP ADMs not previously associated with increased risk No prescription for ADM Outcome Time to incident hypertension (using ICD-9 codes)

Methods Covariates Selected based on associations with HTN and/or depression Age, race, gender, marital status, neighborhood socioeconomic status (nSES), high clinic utilization, current smoker, substance use disorder, depression, anxiety disorder, obesity, hyperlipidemia, type II diabetes, vascular disease Utilized clinic utilization to control for selection bias Due to space constraints, we have omitted marital status, nSES, and high clinic utilization from this presentation

Table 1. Distribution of sociodemographics, covariates, and 5-year cumulative incidence of HTN among adult, primary care patients, overall and by ADM exposure (n=6,244)   Variable, no. (%) Total (n=6,244) Hypertension 774 (12.4) Age, mean (sd) 46.4 (15.6) Race: White 4297 (68.8) Sex: Female 3949 (63.2) Current smoker 1164 (18.6) Substance use 190 (3.0) Depression 771 (12.4) Anxiety 665 (10.7) Obese 2365 (37.9) Hyperlipidemia 1429 (22.9) Type II Diabetes 391 (6.3) Vascular Disease 605 (9.7) Note: ADM = antidepressant medication; BP- = No effect on blood pressure; BP+ = Increases blood pressure Highlight 12.4 percent developed hypertension (essentially five year incidence). Consistent with other studies of hypertension. Can point out validity of data, given high proportion of anxiety/depression on ADMs. Minimal age differences.

Table 2. Distribution of sociodemographics and covariates among adult, primary care patients by 5-year cumulative HTN incidence outcome (n=6,244)   Variable, no. (%) HTN – No (n=5,470) HTN – Yes (n=774) HR (95% CI)a Age, mean (sd) 44.7 (15.2) 58.1 (13.4) 1.04 (1.03-1.05) Race: White 3867 (70.7) 430 (55.6) 0.57 (0.49-0.65) Sex: Female 3478 (63.6) 471 (60.9) 0.90 (0.78-1.04) Current smoker 963 (17.6) 201 (26.0) 1.56 (1.32-1.83) Substance use 162 (3.0) 28 (3.6) 1.64 (1.12-2.39) Depression 681 (12.5) 90 (11.6) 1.05 (0.85-1.32) Anxiety disorder 603 (11.0) 62 (8.0) 0.85 (0.66-1.11) Obese 1973 (36.1) 392 (50.6) 2.16 (1.87-2.49) Hyperlipidemia 1152 (21.1) 277 (35.8) 2.11 (1.82-2.45) Type II Diabetes 267 (4.9) 124 (16.0) 3.40 (2.81-4.12) Vascular Disease 482 (8.8) 123 (15.9) 2.12 (1.75-2.58) Note: HTN = hypertension; HR=hazard ratio; CI=confidence interval, a Unadjusted hazard ratios. Comorbidities treated as time dependent variables

Substance use disorder 1.19 (0.80-1.76) Depression 0.88 (0.68-1.13) Table 3. Survival models, hazard ratios and 95% confidence intervals of the relationship of ADM treatment group and time to incident HTN among adult primary care patients (n=6,244)a   Unadjusted HR (95% CI) Overall adjusted ADM No ADM 1.00 ADM-BP- 1.10 (0.90-1.34) 1.08 (0.87-1.33) ADM-BP+ 1.30 (1.08-1.57) 1.20 (0.97-1.49) Age 1.04 (1.03-1.05) Race: White 0.60 (0.52-0.71) Sex: Female 0.93 (0.80-1.08) Current smoker 1.43 (1.21-1.70) Substance use disorder 1.19 (0.80-1.76) Depression 0.88 (0.68-1.13) Any anxiety disorder 0.90 (0.68-1.18) Obese 1.78 (1.54-2.07) Hyperlipidemia 1.07 (0.91-1.26) Type II Diabetes 1.62 (1.31-1.99) Vascular Disease 0.99 (0.81-1.22) Note: ADM=antidepressant medication; BP- = No effect on blood pressure; BP+ = Increases blood pressure ; a ADM treatment and Comorbidities treated as time dependent variables

Table 4. Distribution of ADM drug class and type among primary care patients by 5-year cumulative hypertension incidence outcome, and hazard ratios (95% CI) (n=6,244) a   Drug class/type, no. (%) HTN – No (n=5,470) HTN – Yes (n=774) HR (95% CI)a Any TCA 322 (5.9) 60 (7.8) 1.53 (1.17-1.99) Amitriptyline 238 (4.4) 48 (6.2) 1.64 (1.23-2.20) Desipramine 13 (0.2) 6 (0.8) 3.09 (1.38-6.89) Any SSRI 1237 (22.6) 161 (20.8) 1.02 (0.86-1.21) Citalopram 430 (7.9) 59 (7.6) 1.14 (0.87-1.48) Escitalopram 314 (5.7) 37 (4.8) 0.91 (0.65-1.26) Fluoxamine 260 (4.8) 27 (2.5) 0.84 (0.57-1.23) Paroxetine 194 (3.6) 21 (2.7) 0.82 (0.53-1.27) Sertraline 354 (6.5) 46 (5.9) 1.05 (0.78-1.41) Note: HTN = hypertension; HR=hazard ratio; CI=confidence interval; a Unadjusted hazard ratios from survival model. Drug type/class treated as time dependent variables

Table 4. Distribution of ADM drug class and type among primary care patients by 5-year cumulative hypertension incidence outcome, and hazard ratios (95% CI) (n=6,244) a   Drug class/type, no. (%) HTN – No (n=5,470) HTN – Yes (n=774) HR (95% CI)a Any SNRI 356 (6.5) 54 (7.0) 1.26 (0.95-1.66) Desvenlafaxine 41 (0.8) 5 (0.7) 1.08 (0.45-2.59) Venlafaxine 194 (3.6) 22 (2.8) 1.02 (0.67-1.56) Duloxetine 150 (2.7) 30 (3.9) 1.55 (1.08-2.24) Any other 699 (12.8) 94 (12.1) 1.03 (0.83-1.28) Bupropion 427 (7.8) 58 (7.5) 1.08 (0.83-1.42) Trazodone 285 (5.2) 39 (5.0) 0.98 (0.71-1.35) Mirtazapine 84 (1.5) 12 (1.6) 1.09 (0.62-1.93) Note: HTN = hypertension; HR=hazard ratio; CI=confidence interval; a Unadjusted hazard ratios from survival model. Drug type/class treated as time dependent variables

Table 4. Distribution of ADM drug class and type among primary care patients by 5-year cumulative hypertension incidence outcome, and hazard ratios (95% CI) (n=6,244) a   Drug class/type, no. (%) HTN – No (n=5,470) HTN – Yes (n=774) HR (95% CI)a Any TCA 322 (5.9) 60 (7.8) 1.53 (1.17-1.99) Amitriptyline 238 (4.4) 48 (6.2) 1.64 (1.23-2.20) Desipramine 13 (0.2) 6 (0.8) 3.09 (1.38-6.89) Any SNRI 356 (6.5) 54 (7.0) 1.26 (0.95-1.66) Desvenlafaxine 41 (0.8) 5 (0.7) 1.08 (0.45-2.59) Venlafaxine 194 (3.6) 22 (2.8) 1.02 (0.67-1.56) Duloxetine 150 (2.7) 30 (3.9) 1.55 (1.08-2.24) Note: HTN = hypertension; HR=hazard ratio; CI=confidence interval; a Unadjusted hazard ratios from survival model. Drug type/class treated as time dependent variables

In Summary TCAs have significant association with development of HTN Duloxetine, but not other SNRIs, associated with development of HTN All other ADMs lack significant association

Discussion SSRIs continue to maintain safe profile in relation to HTN More informed understanding of SNRIs, including appropriate vigilance Renewed vigilance with TCAs Need for further investigation into area

Limitations Retrospective Limited by health record prescription data, impossible to ensure adherence No control for pain as co-morbidity, which could affect blood pressure

References "Effexor(R) [package insert]. Wyeth Pharmaceuticals, Inc., Philadelphia, PA; February 2008.". Carvalho, A. F., M. S. Sharma, A. R. Brunoni, E. Vieta and G. A. Fava (2016). "The Safety, Tolerability and Risks Associated with the Use of Newer Generation Antidepressant Drugs: A Critical Review of the Literature." Psychother Psychosom 85(5): 270-288. Gillespie, C. D., K. A. Hurvitz, C. Centers for Disease and Prevention (2013). "Prevalence of hypertension and controlled hypertension - United States, 2007-2010." MMWR Suppl 62(3): 144-148. Olfson, M. and S. C. Marcus (2009). "National patterns in antidepressant medication treatment." Arch Gen Psychiatry 66(8): 848-856. Pratt, L. A., D. J. Brody and Q. Gu (2011). "Antidepressant use in persons aged 12 and over: United States, 2005-2008." NCHS Data Brief(76): 1-8. Thase, M. E. (1998). "Effects of venlafaxine on blood pressure: a meta-analysis of original data from 3744 depressed patients." J Clin Psychiatry 59(10): 502-508. Westanmo, A. D., J. Gayken and R. Haight (2005). "Duloxetine: a balanced and selective norepinephrine- and serotonin-reuptake inhibitor." Am J Health Syst Pharm 62(23): 2481-2490. Wohlreich, M. M., C. H. Mallinckrodt, A. Prakash, J. G. Watkin and W. P. Carter (2007). "Duloxetine for the treatment of major depressive disorder: safety and tolerability associated with dose escalation." Depress Anxiety 24(1): 41-52. Wong, J., A. Motulsky, T. Eguale, D. L. Buckeridge, M. Abrahamowicz and R. Tamblyn (2016). "Treatment Indications for Antidepressants Prescribed in Primary Care in Quebec, Canada, 2006-2015." JAMA 315(20): 2230-2232.

Please evaluate this presentation using the conference mobile app Please evaluate this presentation using the conference mobile app! Simply click on the "clipboard" icon on the presentation page.