Publications by authors named "Joan Duer-Hefele"

14 Publications

  • Page 1 of 1

Anhedonic Depression Is Not Associated With Risk of Recurrent Major Adverse Cardiac Events and All-Cause Mortality in Acute Coronary Syndrome Patients.

Ann Behav Med 2021 Oct 12. Epub 2021 Oct 12.

Center for Personalized Health, Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY, USA.

Background: Depression after acute coronary syndrome (ACS) is common and increases risks of adverse outcomes, but it remains unclear which depression features are most associated with major adverse cardiac events (MACE) and all-cause mortality (ACM).

Purpose: To examine whether a subtype of depression characterized by anhedonia and major depressive disorder (MDD) predicts 1-year MACE/ACM occurrence in ACS patients compared to no MDD history. We also consider other depression features in the literature as predictors.

Methods: Patients (N = 1,087) presenting to a hospital with ACS completed a self-report measure of current depressive symptoms in-hospital and a diagnostic interview assessing MDD within 1 week post-hospitalization. MACE/ACM events were assessed at 1-, 6-, and 12-month follow-ups. Cox regression models were used to examine the association of the anhedonic depression subtype and MDD without anhedonia with time to MACE/ACM, adjusting for sociodemographic and clinical covariates.

Results: There were 142 MACE/ACM events over the 12-month follow-up. The 1-year MACE/ACM in patients with anhedonic depression, compared to those with no MDD, was somewhat higher in an age-adjusted model (hazard ratio [HR] = 1.63, p = .08), but was not significant after further covariate adjustment (HR = 1.24, p = .47). Of the additional depression features, moderate-to-severe self-reported depressive symptoms significantly predicted the risk of MACE/ACM, even in covariate-adjusted models (HR = 1.72, p = .04), but the continuous measure of self-reported depressive symptoms did not.

Conclusion: The anhedonic depression subtype did not uniquely predict MACE/ACM as hypothesized. Moderate-to-severe levels of total self-reported depressive symptoms, however, may be associated with increased MACE/ACM risk, even after accounting for potential sociodemographic and clinical confounders.
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http://dx.doi.org/10.1093/abm/kaab092DOI Listing
October 2021

Racial and ethnic minority patient participation in N-of-1 trials: perspectives of healthcare providers and patients.

Per Med 2021 07 28;18(4):347-359. Epub 2021 May 28.

Institute for Health System Science, Center for Personalized Health, Feinstein Institutes for Medical Research, Manhasset, NY 11030, USA.

Patients from racial and ethnic minority backgrounds in the USA have historically been under-represented in research trials. Understanding their viewpoints regarding participation in N-of-1 trials is imperative as we design and implement these studies. We conducted six focus groups of racial and ethnic minority patients (n = 25) and providers (n = 9). We used content analysis to identify themes. Our results noted the importance of considering family members in N-of-1 trial recruitment and participation, patients' desire for education as a design feature, for 'lifestyle' changes as a treatment option and for use of nonevidence-based treatments in the design of future N-of-1 trials. Personalized trials have the potential to change the way we deliver primary care and improve disparities for minorities.
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http://dx.doi.org/10.2217/pme-2020-0166DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8242982PMC
July 2021

Using a multistakeholder collaboratory and patient surveys to inform the conduct of personalized (N-of-1) trials.

Health Psychol 2021 Apr;40(4):230-241

Center for Behavioral Cardiovascular Health.

Objective: Personalized trials have the potential to improve the precision of treatment selection and foster patient involvement in clinical decision making. Little is known about the attitudes of patients with multimorbidities. To address this, stakeholders designed and conducted a national survey that determined general attitudes and features of personalized trials that may increase their use among patients with multimorbidities in clinical and research practice.

Method: A multistakeholder collaboratory of patients, clinicians, scientists, methodologists, statisticians, and research disseminators designed a survey to determine the conditions, symptoms, and design attributes most applicable to personalized trials according to patients. A sample of U.S. patients with two or more prespecified personalized-trial-amenable chronic conditions completed the online survey.

Results: Multimorbid participants (N = 501; M age = 56.1 years) showed that some conditions, symptoms or use cases for personalized trials include pain (57.6%), hypertension (38.8%), diabetes (28.8%), sleep problems (27.4%), and depression (23.0%). Overall, 82.0% of the participants with multimorbidities were interested in participating in personalized trials. The percentage that were interested varied by trial attributes, including physician involvement (86.4%), patient-driven treatment selection (88.0%), clinician blinding (59.2%), placebo treatment options (57.5%), and out-of-pocket costs (41.8%).

Conclusion: Participants with multimorbidities identified prevalent use cases that are suited to personalized trials. Participants also identified design features of such trials, including patient-driven treatment selection, active comparators, and nonblinding. This study demonstrates that eliciting input from a collaboratory and patients with multimorbidities can inform research priorities for this rapidly growing patient population and increase adoption by researchers and clinicians alike. (PsycInfo Database Record (c) 2021 APA, all rights reserved).
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http://dx.doi.org/10.1037/hea0001058DOI Listing
April 2021

Personal preferences for Personalised Trials among patients with chronic diseases: an empirical Bayesian analysis of a conjoint survey.

BMJ Open 2020 06 7;10(6):e036056. Epub 2020 Jun 7.

Center Behavioral Cardiovascular Health, Columbia University Irving Medical Center, New York, New York, USA.

Objective: To describe individual patient preferences for Personalised Trials and to identify factors and conditions associated with patient preferences.

Design: Each participant was presented with 18 conjoint questions via an online survey. Each question provided two choices of Personalised Trials that were defined by up to eight attributes, including treatment types, clinician involvement, study logistics and trial burden on a patient.

Setting: Online survey of adults with at least two common chronic conditions in the USA.

Participants: A nationally representative sample of 501 individuals were recruited from the Chronic Illness Panel by Harris Poll Online. Participants were recruited from several sources, including emails, social media and telephone recruitment of the target population.

Main Outcome Measures: The choice of Personalised Trial design that the participant preferred with each conjoint question.

Results: There was large variability in participants' preferences for the design of Personalised Trials. On average, they preferred certain attributes, such as a short time commitment and no cost. Notably, a population-level analysis correctly predicted 62% of the conjoint responses. An empirical Bayesian analysis of the conjoint data, which supported the estimation of individual-level preferences, improved the accuracy to 86%. Based on estimates of individual-level preferences, patients with chronic pain preferred a long study duration (p≤0.001). Asthma patients were less averse to participation burden in terms of data-collection frequency than patients with other conditions (p=0.002). Patients with hypertension were more cost-sensitive (p<0.001).

Conclusion: These analyses provide a framework for elucidating individual-level preferences when implementing novel patient-centred interventions. The data showed that patient preference in Personalised Trials is highly variable, suggesting that individual differences must be accounted for when marketing Personalised Trials. These results have implications for advancing precise interventions in Personalised Trials by indicating when rigorous scientific principles, such as frequent monitoring, is feasible in a substantial subset of patients.
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http://dx.doi.org/10.1136/bmjopen-2019-036056DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7282396PMC
June 2020

Presenting Characteristics, Comorbidities, and Outcomes Among 5700 Patients Hospitalized With COVID-19 in the New York City Area.

JAMA 2020 05;323(20):2052-2059

Institute of Bioelectronic Medicine, Feinstein Institutes for Medical Research, Northwell Health, Manhasset, New York.

Importance: There is limited information describing the presenting characteristics and outcomes of US patients requiring hospitalization for coronavirus disease 2019 (COVID-19).

Objective: To describe the clinical characteristics and outcomes of patients with COVID-19 hospitalized in a US health care system.

Design, Setting, And Participants: Case series of patients with COVID-19 admitted to 12 hospitals in New York City, Long Island, and Westchester County, New York, within the Northwell Health system. The study included all sequentially hospitalized patients between March 1, 2020, and April 4, 2020, inclusive of these dates.

Exposures: Confirmed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection by positive result on polymerase chain reaction testing of a nasopharyngeal sample among patients requiring admission.

Main Outcomes And Measures: Clinical outcomes during hospitalization, such as invasive mechanical ventilation, kidney replacement therapy, and death. Demographics, baseline comorbidities, presenting vital signs, and test results were also collected.

Results: A total of 5700 patients were included (median age, 63 years [interquartile range {IQR}, 52-75; range, 0-107 years]; 39.7% female). The most common comorbidities were hypertension (3026; 56.6%), obesity (1737; 41.7%), and diabetes (1808; 33.8%). At triage, 30.7% of patients were febrile, 17.3% had a respiratory rate greater than 24 breaths/min, and 27.8% received supplemental oxygen. The rate of respiratory virus co-infection was 2.1%. Outcomes were assessed for 2634 patients who were discharged or had died at the study end point. During hospitalization, 373 patients (14.2%) (median age, 68 years [IQR, 56-78]; 33.5% female) were treated in the intensive care unit care, 320 (12.2%) received invasive mechanical ventilation, 81 (3.2%) were treated with kidney replacement therapy, and 553 (21%) died. As of April 4, 2020, for patients requiring mechanical ventilation (n = 1151, 20.2%), 38 (3.3%) were discharged alive, 282 (24.5%) died, and 831 (72.2%) remained in hospital. The median postdischarge follow-up time was 4.4 days (IQR, 2.2-9.3). A total of 45 patients (2.2%) were readmitted during the study period. The median time to readmission was 3 days (IQR, 1.0-4.5) for readmitted patients. Among the 3066 patients who remained hospitalized at the final study follow-up date (median age, 65 years [IQR, 54-75]), the median follow-up at time of censoring was 4.5 days (IQR, 2.4-8.1).

Conclusions And Relevance: This case series provides characteristics and early outcomes of sequentially hospitalized patients with confirmed COVID-19 in the New York City area.
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http://dx.doi.org/10.1001/jama.2020.6775DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7177629PMC
May 2020

The Impact of Cardiac-induced Post-traumatic Stress Disorder Symptoms on Cardiovascular Outcomes: Design and Rationale of the Prospective Observational Reactions to Acute Care and Hospitalizations (ReACH) Study.

Health Psychol Bull 2019 14;3:10-20. Epub 2019 Jan 14.

Columbia University Medical Center, US.

Aims: As many as 1 in 8 acute coronary syndrome (ACS) patients develop posttraumatic stress disorder (PTSD) due to the ACS, and ACS-induced PTSD may increase secondary cardiovascular disease (CVD) risk. However, prior studies have been small and underpowered to test plausible behavioral or biological mechanisms of the hypothesized PTSD-secondary CVD risk association. In this paper, we describe the design and methods of a large prospective observational cohort study to estimate the prognostic significance of ACS-induced PTSD, mechanisms for its association with CVD risk, and emergency department (ED) factors that may increase PTSD risk, in a cohort of patients evaluated for acute coronary syndrome (ACS) in the ED of a large, urban academic medical center.

Methods: The Reactions to Acute Care and Hospitalization (ReACH) study follows 1,741 racially, ethnically, and socioeconomically diverse patients initially presenting to the ED with ACS symptoms. Psychosocial factors are assessed at baseline. Medication adherence is monitored by electronic pill bottle (eCAP). Participants are contacted by phone at 1-, 6-, and 12-months post-hospitalization to assess PTSD symptoms, hospital readmission, and recurrent CVD events/mortality (proactively searched and confirmed by medical records).

Conclusion: This study will provide the most accurate estimates to date of PTSD's association with recurrent CVD events and mortality and will test whether medication adherence mediates that association. Further, it will provide estimates of the contribution of ED and hospital factors to PTSD risk in ACS patients. If our hypotheses are supported, we will have identified PTSD as a novel target for secondary risk reduction.
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http://dx.doi.org/10.5334/hpb.16DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6941797PMC
January 2019

Effect of Depression Screening After Acute Coronary Syndromes on Quality of Life: The CODIACS-QoL Randomized Clinical Trial.

JAMA Intern Med 2020 01;180(1):45-53

Department of Medicine, Northwell Health, New York, New York.

Importance: Patients with acute coronary syndrome (ACS) and elevated depressive symptoms are at increased risk for recurrent cardiovascular events and mortality, worse quality of life, and higher health care costs. These observational findings prompted multiple scientific panels to advise universal depression screening in survivors of ACS prior to evidence from randomized screening trials.

Objective: To determine whether systematically screening for depression in survivors of ACS improves quality of life and depression compared with usual care.

Design, Setting, And Participants: A 3-group multisite randomized trial enrolled 1500 patients with ACS from 4 health care systems between November 1, 2013, and March 31, 2017, with follow-up ending July 31, 2018. Patients were eligible if they had been hospitalized for ACS in the previous 2 to 12 months and had no prior history of depression. All analyses were performed on an intention-to-treat basis.

Interventions: Patients with ACS were randomly assigned 1:1:1 to receive (1) systematic depression screening using the 8-item Patient Health Questionnaire, with notification of primary care clinicians and provision of centralized, patient-preference, stepped depression care for those with positive screening results (8-item Patient Health Questionnaire score ≥10; screen, notify, and treat, n = 499); (2) systematic depression screening, with notification of primary care clinicians for those with positive screening results (screen and notify, n = 501); and (3) usual care (no screening, n = 500).

Main Outcomes And Measures: The primary outcome was change in quality-adjusted life-years. The secondary outcome was depression-free days. Adverse effects and mortality were assessed by patient interview and hospital records.

Results: A total of 1500 patients (424 women and 1076 men; mean [SD] age, 65.9 [11.5] years) were randomized in the 18-month trial. Only 71 of 1000 eligible survivors of ACS (7.1%) had elevated 8-item Patient Health Questionnaire scores indicating depressive symptoms at screening. There were no differences in mean (SD) change in quality-adjusted life-years (screen, notify and treat, -0.06 [0.20]; screen and notify, -0.06 [0.20]; no screen, -0.06 [0.18]; P = .98) or cumulative mean (SD) depression-free days (screen, notify and treat, 343.1 [179.0] days; screen and notify, 351.3 [175.0] days; no screen, 339.0 [176.6] days; P = .63). Harms including death, bleeding, or sleep difficulties did not differ among groups.

Conclusions And Relevance: In patients with ACS without a history of depression, systematic depression screening with or without providing depression treatment did not alter quality-adjusted life-years, depression-free days, or harms.

Trial Registration: ClinicalTrials.gov identifier: NCT01993017.
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http://dx.doi.org/10.1001/jamainternmed.2019.4518DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6806435PMC
January 2020

Rationale, design, and baseline data for a multicenter randomized clinical trial comparing depression screening strategies after acute coronary syndrome: The comparison of depression identification after acute Coronary Syndromes-Quality of Life and Cost Outcomes (CODIACS-QOL) trial.

Contemp Clin Trials 2019 09 13;84:105826. Epub 2019 Aug 13.

Columbia University Medical Center, New York, NY, United States of America.

Background: Elevated depressive symptoms among survivors of acute coronary syndromes (ACS) confer recurrent cardiovascular events and mortality, worse quality of life, and higher healthcare costs. While multiple scientific groups advise routine depression screening for ACS survivors, no randomized trials exist to inform this screening recommendation. We aimed to assess the effect of screening for depression on change in quality of life over 18 months among ACS patients.

Methods: The Comparison of Depression Identification after Acute Coronary Syndrome on Quality of Life and Cost Outcomes (CODIACS-QoL) trial is a pragmatic, 3-arm trial that randomized ACS patients to 1) systematic depression screening using the 8-item Patient Health Questionnaire (PHQ-8) and if positive screen (PHQ-8 ≥ 10), notification of primary care providers (PCPs) and invitation to participate in centralized, patient-preference, stepped depression care (Screen, Notify, and Treat, N = 499); 2) systematic depression screening and PCP notification only (Screen and Notify, N = 501); and 3) usual care (No Screen, N = 500). Adults hospitalized for ACS in the previous 2-12 months without prior history of depression were eligible for participation. Key outcomes will be quality-adjusted life years (primary), cost of health care utilization, and depression-free days across 18 months.

Results: A total of 1500 patients were randomized in the CODIACS-QOL trial (28.3% women; 16.3% Hispanic; mean age 65.9 (11.5) years). Only 7% of ACS survivors had elevated depressive symptoms.

Conclusions: Using a novel randomization schema and pragmatic design principles, the CODIACS-QoL trial achieved its enrollment target. Eventual results of this trial will inform future depression screening recommendations in cardiac patients.

Trial Registration: ClinicalTrials.gov (NCT01993017).
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http://dx.doi.org/10.1016/j.cct.2019.105826DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6754099PMC
September 2019

Patient preferences for personalized (N-of-1) trials: a conjoint analysis.

J Clin Epidemiol 2018 10 30;102:12-22. Epub 2018 May 30.

Columbia University Medical Center, New York, NY, USA.

Objective: Despite their promise for increasing treatment precision, Personalized Trials (i.e., N-of-1 trials) have not been widely adopted. We aimed to ascertain patient preferences for Personalized Trials.

Study Design And Setting: We recruited 501 adults with ≥2 common chronic conditions from Harris Poll Online. We used Sawtooth Software to generate 45 plausible Personalized Trial designs comprising combinations of eight key attributes (treatment selection, treatment type, clinician involvement, blinding, time commitment, self-monitoring frequency, duration, and cost) at different levels. Conditional logistic regression was used to assess relative importance of different attributes using a random utility maximization model.

Results: Overall, participants preferred Personalized Trials with no costs vs. $100 cost (utility difference 1.52 [standard error 0.07], P < 0.001) and with less vs. more time commitment/day (0.16 [0.07], P < 0.015) but did not hold preferences for the other six attributes. In subgroup analyses, participants ≥65 years, white, and with income ≤$50,000 were more averse to costs than their counterparts (P all <0.05).

Conclusion: To optimize dissemination, Personalized Trial designers should seek to minimize out-of-pocket costs and time burden of self-monitoring. They should also consider adaptive designs that can accommodate subgroup differences in design preferences.
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http://dx.doi.org/10.1016/j.jclinepi.2018.05.020DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6119511PMC
October 2018

Patients and primary care providers identify opportunities for personalized (N-of-1) trials in the mobile health era.

J Clin Epidemiol 2017 09 23;89:236-237. Epub 2017 Jun 23.

Department of Medicine, Center for Behavioral Cardiovascular Health, Columbia University Medical Center, 622 W. 168th Street, PH9-321, New York, NY 10032, USA.

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http://dx.doi.org/10.1016/j.jclinepi.2017.06.008DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5774675PMC
September 2017

Does Stress Result in You Exercising Less? Or Does Exercising Result in You Being Less Stressed? Or Is It Both? Testing the Bi-directional Stress-Exercise Association at the Group and Person (N of 1) Level.

Ann Behav Med 2017 Dec;51(6):799-809

Center for Behavioral Cardiovascular Health, Columbia University Medical Center, New York, NY, USA.

Background: Psychosocial stress contributes to heart disease in part by adversely affecting maintenance of health behaviors, while exercise can reduce stress. Assessing the bi-directional relationship between stress and exercise has been limited by lack of real-time data and theoretical and statistical models. This lack may hinder efforts to promote exercise maintenance.

Purpose: We test the bi-directional relationship between stress and exercise using real-time data for the average person and the variability-individual differences-in this relationship.

Methods: An observational study was conducted within a single cohort randomized controlled experiment. Healthy young adults, (n = 79) who reported only intermittent exercise, completed 12 months of stress monitoring by ecological momentary assessment (at the beginning of, end of, and during the day) and continuous activity monitoring by Fitbit. A random coefficients linear mixed model was used to predict end-of-day stress from the occurrence/non-occurrence of exercise that day; a logistic mixed model was used to predict the occurrence/non-occurrence of exercise from ratings of anticipated stress. Separate regression analyses were also performed for each participant. Sensitivity analysis tested all models, restricted to the first 180 days of observation (prior to randomization).

Results: We found a significant average inverse (i.e., negative) effect of exercise on stress and of stress on exercise. There was significant between-person variability. Of N = 69, exercise was associated with a stress reduction for 15, a stress increase for 2, and no change for the remainder. We also found that an increase in anticipated stress reported the previous night or that morning was associated with a significant 20-22% decrease (OR = 0.78-0.80) in the odds of exercising that day. Of N = 69, this increase in stress reduced the likelihood of exercise for 17, increased the odds for 1, and had no effect for the remainder. We were unable to identify psychosocial factors that moderate the individual differences in these effects.

Conclusions: The relationship of stress to exercise can be uni- or bi-directional and varies from person to person. A precision medicine approach may improve exercise uptake.
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http://dx.doi.org/10.1007/s12160-017-9902-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5597451PMC
December 2017

Posttraumatic stress disorder symptoms and hypercoagulability during emergency department evaluation for acute coronary syndrome.

IJC Metab Endocr 2016 Jun 8;11:1-2. Epub 2016 May 8.

Center for Behavioral Cardiovascular Health, Columbia University Medical Center, New York, NY, United States.

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http://dx.doi.org/10.1016/j.ijcme.2016.03.002DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5649627PMC
June 2016

Centralized, stepped, patient preference-based treatment for patients with post-acute coronary syndrome depression: CODIACS vanguard randomized controlled trial.

JAMA Intern Med 2013 Jun;173(11):997-1004

Importance: Controversy remains about whether depression can be successfully managed after acute coronary syndrome (ACS) and the costs and benefits of doing so.

Objective: To determine the effects of providing post-ACS depression care on depressive symptoms and health care costs.

Design: Multicenter randomized controlled trial.

Setting: Patients were recruited from 2 private and 5 academic ambulatory centers across the United States.

Participants: A total of 150 patients with elevated depressive symptoms (Beck Depression Inventory [BDI] score ≥10) 2 to 6 months after an ACS, recruited between March 18, 2010, and January 9, 2012.

Interventions: Patients were randomized to 6 months of centralized depression care (patient preference for problem-solving treatment given via telephone or the Internet, pharmacotherapy, both, or neither), stepped every 6 to 8 weeks (active treatment group; n = 73), or to locally determined depression care after physician notification about the patient's depressive symptoms (usual care group; n = 77).

Main Outcome Measures: Change in depressive symptoms during 6 months and total health care costs.

Results: Depressive symptoms decreased significantly more in the active treatment group than in the usual care group (differential change between groups, -3.5 BDI points; 95% CI, -6.1 to -0.7; P = .01). Although mental health care estimated costs were higher for active treatment than for usual care, overall health care estimated costs were not significantly different (difference adjusting for confounding, -$325; 95% CI, -$2639 to $1989; P = .78).

Conclusions: For patients with post-ACS depression, active treatment had a substantial beneficial effect on depressive symptoms. This kind of depression care is feasible, effective, and may be cost-neutral within 6 months; therefore, it should be tested in a large phase 3 pragmatic trial.

Trial Registration: clinicaltrials.gov Identifier: NCT01032018.
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http://dx.doi.org/10.1001/jamainternmed.2013.915DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3681929PMC
June 2013

Design and baseline data from the vanguard of the Comparison of Depression Interventions after Acute Coronary Syndrome (CODIACS) randomized controlled trial.

Contemp Clin Trials 2012 Sep 25;33(5):1003-10. Epub 2012 May 25.

Columbia University Medical Center, New York, NY, USA.

This paper describes the rationale and design of the vanguard for the Comparison of Depression Interventions after Acute Coronary Syndrome (CODIACS), a multicenter, randomized, controlled trial of a patient preference-based, stepped care protocol for persistent depressive symptoms after acute coronary syndrome (ACS). The overall aim of the vanguard phase was to determine whether the patient-preference, stepped care protocol, which is based on the intervention used in the recent Coronary Psychosocial Evaluation Studies (COPES) trial, was feasible in patients with recent ACS who were recruited from 5 geographically diverse sites. Innovative design features of this trial include randomization to either initial patient-preference of treatment or to a referred care arm in which the primary care provider decided upon care. Additionally, delivery of psychotherapy was accomplished by telephone, or webcam, depending upon patient preference. The vanguard phase provides estimates of eligibility and screening/enrollment ratios, patient acceptance of screening, and retention. In this report, we describe the innovative features and the baseline results of the vanguard phase of CODIACS. The data from this vanguard study will be used to finalize planning for a large, phase III clinical trial designed to evaluate the effect of treatment on depressive symptoms, coronary events, and death.
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http://dx.doi.org/10.1016/j.cct.2012.05.005DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3408827PMC
September 2012
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