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Assessment and Treatment of Depression in Patients With Cardiovascular Disease: National Heart, Lung, and Blood Institute Working Group Report

2006· article· en· W2331972648 on OpenAlexaff
Karina W. Davidson, David J. Kupfer, J. Thomas Bigger, Robert M. Califf, Robert M. Carney, James C. Coyne, Susan M. Czajkowski, Ellen Frank, Nancy Frasure‐Smith, Kenneth E. Freedland, Erika Sivarajan Froelicher, Alexander H. Glassman, Wayne Katon, Peter Kaufmann, Ronald C. Kessler, Helena C. Kraemer, Kousik Krishnan, François Lespérance, Nina Rieckmann, David S. Sheps, Jerry Suls

Bibliographic record

VenuePsychosomatic Medicine · 2006
Typearticle
Languageen
FieldMedicine
TopicCardiac Health and Mental Health
Canadian institutionsMcGill UniversityCentre Hospitalier de l’Université de MontréalMontreal Heart Institute
Fundersnot available
KeywordsBeck Depression InventoryDepression (economics)Randomized controlled trialRating scaleMedicineHamilton Rating Scale for DepressionMoodPhysical therapyPsychiatryInterpersonal psychotherapyPsychologyClinical psychologyInternal medicineMajor depressive disorderAnxiety

Abstract

fetched live from OpenAlex

Objective: The National Heart, Lung, and Blood Institute convened an interdisciplinary working group of experts to develop recommendations for the assessment and treatment of depression in patients with coronary heart disease (CHD). Method: Consensus of experts. Results: Our current recommendations are that the Beck Depression Inventory-I be employed for epidemiological studies of depression and CHD, that the Patient Health Questionnaire 2-item version be employed for screening for trial eligibility, that the Depression Interview and Structured Hamilton (DISH) be employed for diagnostic ascertainment for trial inclusion, and that the Hamilton rating scale, which is part of the DISH, be employed for both depression symptom reduction and the remission criterion in any trial. We further recommend that a randomized controlled trial be undertaken to determine whether selective serotonin reuptake inhibitors, psychotherapy, or combined treatment can reduce the risk of CHD events and mortality associated with depression in CHD patients. Conclusions: This report summarizes the recommendations made by the working group and discusses the rationale for each recommendation, the strengths and weaknesses of alternative approaches to assessment and treatment, and the implications for future research in this area. ACS = acute coronary syndrome; BDI = Beck Depression Inventory; CBASP = Cognitive Behavioral Analysis System of Psychotherapy; CBT = cognitive behavior therapy; CIDI = Composite International Diagnostic Interview; CHD = coronary heart disease; CVD = cardiovascular disease; DISH = Depression Interview and Structured Hamilton; ENRICHD = Enhancing Recovery in Coronary Heart Disease; HAM-D = Hamilton Rating Scale for Depression; IDS-SR = Inventory of Depressive Symptomatology, self-report; IMPACT = Improving Mood–Promoting Access to Collaborative Treatment; IPT = interpersonal therapy; MI = myocardial infarction; NHLBI = National Heart, Lung, and Blood Institute; PHQ = Patient Health Questionnaire; RCT = randomized controlled trial; SADHART = Sertraline Antidepressant Heart Attack Randomized Trial; SCID = Structured Clinical Interview for DSM-IV; SSRI = selective serotonin reuptake inhibitor; STAR*D = Sequenced Treatment Alternatives to Relieve Depression.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.053
metaresearch head score (Gemma)0.040
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.053
Threshold uncertainty score0.278

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0530.040
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0040.002
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0020.003

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.017
GPT teacher head0.323
Teacher spread0.307 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations155
Published2006
Admission routes1
Has abstractyes

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