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Record W2615059421 · doi:10.1080/24750573.2017.1328095

Depression, anxiety, alexithymia and somatosensory sensitivity in patients with benign palpitation

2017· article· en· W2615059421 on OpenAlexaboutno aff
Nurten Sayar, Ömer Yanartaş, Kürşat Tigen, Beste Özben, Serhat Ergün, Alper Kepez, Altuǧ Çinçin

Bibliographic record

VenuePsychiatry and Clinical Psychopharmacology · 2017
Typearticle
Languageen
FieldMedicine
TopicPsychosomatic Disorders and Their Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsAlexithymiaToronto Alexithymia ScaleAnxietyDepression (economics)MedicineSomatizationBeck Anxiety InventoryCardiologyBeck Depression InventoryInternal medicinePopulationCoronary artery diseaseOdds ratioPsychiatry

Abstract

fetched live from OpenAlex

Objective: The aim of this study is to compare the frequency of depression, anxiety, alexithymia and somatosensory sensitivity in patients with benign palpitation with healthy controls.Method: Sixty-one patients with palpitation and 59 age- and sex-matched control subjects were enrolled. All study subjects were undergone thorough cardiac evaluation, and patients with palpitation also had echocardiography and 24-hour ECG monitoring to rule out significant arrhythmias, coronary artery disease and structural heart disease. All subjects were assessed by Beck Depression Inventory (BDI), Beck Anxiety Inventory (BAI), Toronto Alexithymia scale, Whiteley Index (WI) and Somatosensory Amplification Scale (SAS).Results: Patients with benign palpitation had significantly increased BAI, BDI, WI and SAS scores. Anxiety is the only independent predictor of benign palpitation (odds ratio = 1.12, 95% confidence interval = 1.05–1.19, p < 0.001).Conclusion: This study shows that patients with benign palpitation had increased anxiety levels and somatization disorders. So an integrated psycho-cardiological approach is needed in this special population.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.022
Threshold uncertainty score0.649

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.344
Teacher spread0.330 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations3
Published2017
Admission routes1
Has abstractyes

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