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Record W4399332337 · doi:10.21203/rs.3.rs-4441088/v1

Which neonates should have a pre-operative echocardiography? Findings from a national survey and a retrospective tertiary single-centre analysis in the United Kingdom

2024· preprint· en· W4399332337 on OpenAlexaff
Joel W. E. Chin, Anthony WR Kelsall, Danny Jenkins, Abha Khushu, Daniel J. Stubbs, Johanne Lynch

Bibliographic record

VenueResearch Square · 2024
Typepreprint
Languageen
FieldMedicine
TopicCongenital Heart Disease Studies
Canadian institutionsSt. Thomas Hospital
Fundersnot available
KeywordsTertiary careMedicineRetrospective cohort studyPediatricsFamily medicineGeneral surgeryInternal medicine

Abstract

fetched live from OpenAlex

Abstract Purpose The detection of congenital heart disease (CHD) before neonatal surgery is crucial for anaesthetic and perioperative management. There are no established criteria for preoperative echocardiography in neonates. We aimed to survey current practice in the United Kingdom and evaluate the reliability of antenatal screening and postnatal clinical assessment in detecting CHD before surgery. Method A 9-point questionnaire was sent to all paediatric surgical centres in the United Kingdom to assess their practice. Subsequently, a single-centre retrospective review of all neonatal surgery over 5 years (2015–2020) was conducted in our tertiary paediatric/neonatal hospital. Data included preoperative clinical assessment, performance of chest radiograph and echocardiography. Indications for echocardiography were categorised and assessed using sensitivity, specificity, positive predictive value and negative predictive value. Results All 26 paediatric surgical centres responded to our survey. 23/26 (88.5%) did not have established criteria or guidelines for preoperative echocardiography. There was a large variation in which surgical conditions required a preoperative scan and whether a normal clinical examination was considered sufficient to not require one. For the retrospective review, 454 patients were identified. There were 40 cases with CHDs (8.8%), 13 were classed as major. Indications for echocardiography were categorised into abnormal fetal cardiac screening, medical/surgical conditions associated with CHD and an abnormal cardiorespiratory examination. Sensitivity, specificity, positive predictive value and negative predictive value for major CHD was 46%, 99%, 67%, 98% for abnormal fetal screening, 46%, 97%, 35%, 98% for associated medical conditions, 62%, 66%, 6%, 98% for associated surgical conditions, and 100%, 66%, 9%, 100% for abnormal clinical examination. Conclusion The use of preoperative echocardiography in neonates is not standardised across the UK.. The results from our cohort demonstrates that fetal echocardiography is not sufficient to capture all major CHDs, but the absence of abnormal clinical examination is highly reliable in ruling out major CHD. Specifying a list of medical/surgical of conditions associated with CHD warranting preoperative echocardiography may improve yield, but this depends on the availability of resources and expertise.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.024
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
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 head0.112
GPT teacher head0.418
Teacher spread0.306 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2024
Admission routes1
Has abstractyes

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