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Record W2466636645 · doi:10.1007/s10897-016-9991-4

Patient Recall, Interpretation, and Perspective of an Inconclusive Long QT Syndrome Genetic Test Result

2016· article· en· W2466636645 on OpenAlexaff
Sarah Predham, Julie Hathaway, Gurdip Hulait, Laura Arbour, Anna Lehman

Bibliographic record

VenueJournal of Genetic Counseling · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBRCA gene mutations in cancer
Canadian institutionsUniversity of VictoriaUniversity of British Columbia
Fundersnot available
KeywordsRecallGenetic testingAffect (linguistics)Genetic counselingTest (biology)MedicinePerspective (graphical)PopulationClinical psychologyPsychologyPerceptionDiseaseCognitive psychologyInternal medicineGenetics

Abstract

fetched live from OpenAlex

Patients' perceptions of inconclusive results have been previously investigated in cancer genetics. The differences in how patients recall and interpret an uninformative test result compared to a known pathogenic result can affect medical decisions post disclosure. However, there is little to no data available on patients' interpretation and perception of uninformative genetic results in inherited heart disease. We report the results of a qualitative analysis of 16 telephone interviews with participants who received a negative or a variant of unknown significance (VUS) result from Long QT syndrome (LQTS) genetic testing. Our results suggest that the type of result (negative versus VUS) does not affect recall, regardless of the reason for testing. When receiving a negative result, a majority of participants appropriately perceived no change in their diagnosis, while the perception of risk for family members varied. The majority of participants felt they maintained an awareness of their condition after the result disclosure, and that clinical follow-up was similar to that planned prior to the genetic test result. Further work is needed to determine if there are any differences between obtaining a VUS result versus a negative result in this 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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.213
Threshold uncertainty score0.444

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 head0.005
GPT teacher head0.254
Teacher spread0.250 · 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 designBench or experimental
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

Citations17
Published2016
Admission routes1
Has abstractyes

Explore more

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