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Record W1943023144 · doi:10.1002/pd.3926

A fetal telecardiology service: patient preference and socio‐economic factors

2012· article· en· W1943023144 on OpenAlexfundno aff
Brian McCrossan, Andrew J Sands, Theresa Kileen, Nicola Doherty, Frank Casey

Bibliographic record

VenuePrenatal Diagnosis · 2012
Typearticle
Languageen
FieldMedicine
TopicTelemedicine and Telehealth Implementation
Canadian institutionsnot available
FundersMcMaster University
KeywordsPreferenceService (business)MedicineFetusBusinessPregnancyMarketingBiologyEconomics

Abstract

fetched live from OpenAlex

OBJECTIVE: The aims of this study were to evaluate patients' opinions on a fetal cardiology telemedicine service compared with usual outpatient care, the effect of the telemedicine consultation on maternal anxiety and its impact on travel times and time absent from work. METHODS: Prospective study over 20 months. Eligible patients attended for routine anomaly scan followed by fetal echocardiogram transmitted to the regional centre with live guidance by a fetal cardiologist, followed by parental counselling. All patients were offered a fetal cardiology appointment at the regional centre. Structured questionnaires assessing maternal satisfaction, travel times/days off and anxiety scores completed at time of both fetal echocardiograms. RESULTS: Sixty-seven patients were recruited and 66 completed the study. Participants expressed very high satisfaction rates with fetal telecardiology, equivalent to face-to-face consultation. The telecardiology appointments were associated with significantly reduced travel times and days off work (p < 0.01). Expectant mothers expressed a clear inclination for a fetal cardiology appointment at the local hospital facilitated by telemedicine (p < 0.01). CONCLUSIONS: Fetal telecardiology is highly acceptable to patients and is even preferred compared with travelling to a regional centre. There are additional socio-economic benefits that should encourage the development of remote fetal cardiology services.

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 score0.043
Threshold uncertainty score0.483

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 head0.050
GPT teacher head0.314
Teacher spread0.265 · 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

Citations31
Published2012
Admission routes1
Has abstractyes

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