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Record W2046925651 · doi:10.1177/0036933012474603

An audit of the management of heart murmurs on the postnatal wards

2013· article· en· W2046925651 on OpenAlexfundno aff
KM O’Reilly, F M Hall, Trevor Richens, Charles Cunningham, JH Simpson

Bibliographic record

VenueScottish Medical Journal · 2013
Typearticle
Languageen
FieldMedicine
TopicPhonocardiography and Auscultation Techniques
Canadian institutionsnot available
FundersHospital for Sick Children
KeywordsMedicineGuidelineHeart murmurAuditPediatricsPopulationIntensive care medicineInternal medicinePathology

Abstract

fetched live from OpenAlex

BACKGROUND: Investigation and management of neonatal heart murmurs varies widely and is dependent on local resources. In order to standardise the management of heart murmurs in our hospital a guideline (based on clinical examination with selective cardiology review) was introduced. AIMS: To establish adherence to and safety of the guideline; to review workload implications and to define the causes of neonatal heart murmurs in our population. METHODS: Patients were prospectively identified over a 2-year period (August 2006 to July 2008). Case notes were reviewed and examination findings, investigations, follow up and diagnosis recorded. RESULTS: 89 babies were identified. The guideline was generally well adhered to. In total 51 (57%) of babies were referred for cardiology assessment. In 40 babies this assessment included an echocardiogram. 30 babies (34%) had an underlying cardiac malformation: 25 were identified before discharge home. 15/30 (50%) of the babies with a cardiac malformation remain under cardiology follow up at the age of 1 year. No baby discharged from follow up without cardiology review subsequently presented with a cardiac problem. CONCLUSION: A significant minority of babies with a heart murmur have an underlying cardiac malformation. Our guideline appears to ensure the timely identification of these babies and rationalises our use of specialist 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.888
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0010.000

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 head0.010
GPT teacher head0.283
Teacher spread0.273 · 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.

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

Citations2
Published2013
Admission routes1
Has abstractyes

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