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Record W1815828991 · doi:10.1136/bmjopen-2015-009742

Diagnostic accuracy of the Edinburgh Postnatal Depression Scale (EPDS) for detecting major depression in pregnant and postnatal women: protocol for a systematic review and individual patient data meta-analyses

2015· review· en· W1815828991 on OpenAlexafffund
Brett D. Thombs, Andrea Benedetti, Lorie A. Kloda, Brooke Levis, Kira E. Riehm, Marleine Azar, Pim Cuijpers, Simon Gilbody, John P. A. Ioannidis, Dean McMillan, Scott B. Patten, Ian Shrier, Russell Steele, Roy C. Ziegelstein, Marcello Tonelli, Nicholas Mitchell, Liane Comeau, Joy Schinazi, Simone N. Vigod

Bibliographic record

VenueBMJ Open · 2015
Typereview
Languageen
FieldMedicine
TopicMaternal Mental Health During Pregnancy and Postpartum
Canadian institutionsWomen's College HospitalUniversity of TorontoInstitut National de Santé Publique du QuébecUniversité de MontréalUniversity of AlbertaMcGill UniversityUniversity of CalgaryMcGill University Health CentreJewish General Hospital
FundersCanadian Institutes of Health ResearchArthritis Society
KeywordsMedicineEdinburgh Postnatal Depression ScaleDepression (economics)Meta-analysisProtocol (science)PsychiatryScale (ratio)Alternative medicineDepressive symptomsInternal medicinePathologyCognition

Abstract

fetched live from OpenAlex

INTRODUCTION: Studies of the diagnostic accuracy of depression screening tools often used data-driven methods to select optimal cut-offs. Typically, these studies report results from a small range of cut-off points around whatever cut-off score is identified as most accurate. When published data are combined in meta-analyses, estimates of accuracy for different cut-off points may be based on data from different studies, rather than data from all studies for each cut-off point. Thus, traditional meta-analyses may exaggerate accuracy estimates. Individual patient data (IPD) meta-analyses synthesise data from all studies for each cut-off score to obtain accuracy estimates. The 10-item Edinburgh Postnatal Depression Scale (EPDS) is commonly recommended for depression screening in the perinatal period. The primary objective of this IPD meta-analysis is to determine the diagnostic accuracy of the EPDS to detect major depression among women during pregnancy and in the postpartum period across all potentially relevant cut-off scores, accounting for patient factors that may influence accuracy (age, pregnancy vs postpartum). METHODS AND ANALYSIS: Data sources will include Medline, Medline In-Process & Other Non-Indexed Citations, PsycINFO, and Web of Science. Studies that include a diagnosis of major depression based on a validated structured or semistructured clinical interview administered within 2 weeks of (before or after) the administration of the EPDS will be included. Risk of bias will be assessed with the Quality Assessment of Diagnostic Accuracy Studies-2 tool. Bivariate random-effects meta-analysis will be conducted for the full range of plausible cut-off values. Analyses will evaluate data from pregnancy and the postpartum period separately, as well as combining data from all women in a single model. ETHICS AND DISSEMINATION: This study does not require ethics approval. Dissemination will include journal articles and presentations to policymakers, healthcare providers and researchers. SYSTEMATIC REVIEW REGISTRATION: PROSPERO 2015:CRD42015024785.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Protocol · Consensus signal: none
Teacher disagreement score0.385
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0040.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.003
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.407
GPT teacher head0.541
Teacher spread0.135 · 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 teacher head, not a consensus.

Study designSystematic review
Domainnot available
GenreProtocol

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

Citations58
Published2015
Admission routes2
Has abstractyes

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