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Record W2017648852 · doi:10.1001/jama.2009.1673

Does This Patient With Palpitations Have a Cardiac Arrhythmia?

2009· review· en· W2017648852 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJAMA · 2009
Typereview
Languageen
FieldMedicine
TopicCardiovascular Syncope and Autonomic Disorders
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPalpitationsMedicineCardiac arrhythmiaInternal medicineCardiologyConfidence intervalMedical historyPhysical examinationAtrial fibrillation

Abstract

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CONTEXT: Many patients have palpitations and seek advice from general practitioners. Differentiating benign causes from those resulting from clinically significant cardiac arrhythmia can be challenging and the clinical examination may aid in this process. OBJECTIVE: To systematically review the accuracy of historical features, physical examination, and cardiac testing for the diagnosis of cardiac arrhythmia in patients with palpitations. Data Source, Study Selection, and DATA EXTRACTION: MEDLINE (1950 to August 25, 2009) and EMBASE (1947 to August 2009) searches of English-language articles that compared clinical features and diagnostic tests in patients with palpitations with a reference standard for cardiac arrhythmia. Of the 277 studies identified by the search strategy, 7 studies were used for accuracy analysis and 16 studies for diagnostic yield analysis. Two authors independently reviewed articles for study data and quality and a third author resolved disagreements. DATA SYNTHESIS: Most data were obtained from single studies with small sample sizes. A known history of cardiac disease (likelihood ratio [LR], 2.03; 95% confidence interval [CI], 1.33-3.11), having palpitations affected by sleeping (LR, 2.29; 95% CI, 1.33-3.94), or while the patient is at work (LR, 2.17; 95% CI, 1.19-3.96) slightly increase the likelihood of a cardiac arrhythmia. A known history of panic disorder (LR, 0.26; 95% CI, 0.07-1.01) or having palpitations lasting less than 5 minutes (LR, 0.38; 95% CI, 0.22-0.63) makes the diagnosis of cardiac arrhythmia slightly less likely. The presence of a regular rapid-pounding sensation in the neck (LR, 177; 95% CI, 25-1251) or visible neck pulsations (LR, 2.68; 95% CI, 1.25-5.78) in association with palpitations increases the likelihood of a specific type of arrhythmia (atrioventricular nodal reentry tachycardia). The absence of a regular rapid-pounding sensation in the neck makes detecting the same arrhythmia less likely (LR, 0.07; 95% CI, 0.03-0.19). No other features significantly alter the probability of clinically significant arrhythmia. Diagnostic tests for prolonged periods of electrocardiographic monitoring vary in their yield depending on the modality used, duration of monitoring, and occurrence of typical symptoms during monitoring. Loop monitors have the highest diagnostic yield (34%-84%) for identifying an arrhythmia. CONCLUSIONS: While the presence of a regular rapid-pounding sensation in the neck or visible neck pulsations associated with palpitations makes the diagnosis of atrioventricular nodal reentry tachycardia likely, the reviewed studies suggest that the clinical examination is not sufficiently accurate to exclude clinically significant arrhythmias in most patients. Thus, prolonged electrocardiographic monitoring with demonstration of symptom-rhythm correlation is required to make the diagnosis of a cardiac arrhythmia for most patients with recurrent palpitations.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.989
Threshold uncertainty score0.753

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.013
GPT teacher head0.269
Teacher spread0.256 · 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