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Record W2656759171 · doi:10.1161/str.47.suppl_1.204

Abstract 204: Transcranial Doppler Versus Transthoracic Echocardiography for the Detection of Patent Foramen Ovale in Patients With Cryptogenic Cerebral Ischemia: A Systematic Review and Diagnostic Test Accuracy Meta-analysis

2016· review· en· W2656759171 on OpenAlexaff
Georgios Tsivgoulis, Aristeidis H. Katsanos, Θεοδώρα Ψαλτοπούλου, Theodoros Ν. Sergentanis, Alexandra Frogoudaki, Agathi‐Rosa Vrettou, Ignatios Ikonomidis, Ioannis Paraskevaidis, John Parissis, Chrysa Bogiatzi, Jason J. Chang, Athanassios P. Kyritsis, Anne W. Alexandrov, Sotirios Giannopoulos, Andrei V. Alexandrov

Bibliographic record

VenueStroke · 2016
Typereview
Languageen
FieldMedicine
TopicCardiovascular and Diving-Related Complications
Canadian institutionsWestern University
Fundersnot available
KeywordsMedicinePatent foramen ovaleTranscranial DopplerDiagnostic odds ratioConfidence intervalLikelihood ratios in diagnostic testingOdds ratioInternal medicineCardiologyMeta-analysisGold standard (test)Stroke (engine)Prospective cohort studyRadiologyMigraine

Abstract

fetched live from OpenAlex

Background & Purpose: Patent foramen ovale (PFO) can be detected in up to 43% of patients with cryptogenic cerebral ischemia undergoing investigation with transesophageal echocardiography (TEE). The diagnostic value of transthoracic echocardiography (TTE) in the detection of PFO in patients with cryptogenic cerebral ischemia has not been compared with that of transcranial Doppler (TCD) using a comprehensive meta-analytical approach. Methods: We performed a systematic literature review according to PRISMA guidelines to identify all prospective observational studies of patients with cryptogenic cerebral ischemia that provided both sensitivity and specificity measures of TTE, TCD or both compared to the gold standard of TEE. Results: Our literature search identified 35 eligible studies including 3067 patients. The summary sensitivity and specificity for TCD was 96.1% (95% confidence interval: 93.0%-97.8%) and 92.4% (95%CI: 85.5%-96.1%), whereas the respective measures for TTE were 45.1% (95%CI: 30.8-60.3%) and 99.6% (95%CI: 96.5-99.9%). The summary diagnostic odds ratio (DOR) for TCD (DOR=297.97, 95%CI: 131.18-676.83) and TTE (DOR=193.44, 95%CI: 30.38-1231.67) did not significantly differ (z-value=0.418, p=0.676). TTE was superior in terms of higher positive likelihood ratio values (LR+= 106.61, 95%CI: 15.09-753.30 for TTE vs. LR+=12.62, 95%CI: 6.52-24.43 for TCD; p=0.043), while TCD yielded lower negative positive likelihood values (LR- = 0.04, 95%CI: 0.02-0.08) compared to TTE (LR- =0.55, 95%CI: 0.42-0.72; p<0.001). Finally, the area under the summary receiver operating curve was significantly greater (p<0.001) in TCD (AUC=0.98, 95%CI: 0.97-0.99; Figure A) compared to TTE studies (AUC=0.86, 95%CI: 0.82-0.89; Figure B). Conclusions: TCD is more sensitive but less specific compared to TTE for the detection of PFO in patients with cryptogenic cerebral ischemia. The overall diagnostic yield of TCD appears to outweigh that of TTE.

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)0.012
metaresearch head score (Gemma)0.037
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.014
Threshold uncertainty score0.064

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.037
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0140.033
Bibliometrics0.0050.005
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.061
GPT teacher head0.309
Teacher spread0.248 · 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 designMeta-analysis
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".

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Citations0
Published2016
Admission routes1
Has abstractyes

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