Evidence map›Paper›PMID 25725615›Full record

SynthesisMedical science monitor : international medical journal of experimental and clinical research2015

Performance of screening tools in detecting major depressive disorder among patients with coronary heart disease: a systematic review.

Yanping Ren, Hui Yang, Colette Browning, Shane Thomas, Meiyan Liu

Abstract readMeta-AnalysisSystematic Review
In one paragraph

Synthesis in Medical science monitor : international medical journal of experimental and clinical research, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed, 3 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

22 citing papers in PubMed, 3 syntheses or guidelines pooled it.

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  4. Parental Depression is Prospectively Associated With Lower Smoking Cessation Rates and Poor Child Asthma Outcomes.Annals of behavioral medicine : a publication of the Society of Behavioral Medicine · 2018
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Yanping RenDepartment of Cardiology, First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China (mainland).
Hui YangSchool of Primary Health Care, Faculty of Medicine, Nursing and Health Sciences, Monash University, Victoria, Australia.
Colette BrowningSchool of Primary Health Care, Faculty of Medicine, Nursing and Health Sciences, Monash University, Victoria, Australia.
Shane ThomasSchool of Primary Health Care, Faculty of Medicine, Nursing and Health Sciences, Monash University, Victoria, Australia.
Meiyan LiuDepartment of Cardiology, Affiliated Beijing Anzhen Hospital of Capital Medical University, Beijing, China (mainland).

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundEligible studies published before 31 Dec 2013 were identified from the following databases: Ovid Medline, EMBASE, PsycINFO, Scopus, Cochrane Library, CINAHL Plus, and Web of Science. MATERIAL AND

methodsEligible studies published before 31, Dec 2013 were identified from the following databases: Ovid Medline, EMBASE, psycINFO, Scopus, Cochrane Library, CINAHL Plus, and Web of Science.

resultsEight studies aiming to identify MDD in CHD patients were included, and there were 10 self-reporting questionnaires (such as PHQ-2, PHQ-9, PHQ categorical algorithm, HADS-D, BDI, BDI-II, BDI-II-cog, CES-D, SCL-90, 2 simple yes/no items) and 1 observer rating scale (Ham-D). For MDD alone, the sensitivity and specificity of various screening tools at the validity and optimal cut-off point varied from 0.34 [0.19, 0.52] to 0.96 [0.78, 1.00] and 0.69 [0.65, 0.73] to 0.97 [0.93, 0.99]. Results showed PHQ-9 (≥10), BDI-II (³14 or ≥16), and HADS-D (≥5 or ≥4) were widely used for screening MDD in CHD patients.

conclusionsThere is no consensus on the optimal screening tool for MDD in CHD patients. When evaluating the performance of a screening tool, balancing the high sensitivity and negative predictive value (NPV) between specificity and positive predictive value (PPV) for screening or diagnostic purpose should be considered. After screening, further diagnosis, appropriate management, and necessary referral may also improve cardiovascular outcomes.

Indexed as

AgedCoronary DiseaseFemaleHumansMajor Depressive DisorderMaleMass ScreeningMiddle AgedQuality Assurance, Health Care

Identifiers

PMID25725615
PMCPMC4354444

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.