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Record W2762267137 · doi:10.1111/jpc.13625

Australian guide to the diagnosis of foetal alcohol spectrum disorder: A summary

2017· article· en· W2762267137 on OpenAlexaboutno aff
Carol Bower, Elizabeth Elliott, Marcel Zimmet, Juanita Doorey, Amanda Wilkins, Vicki Russell, Doug Shelton, James Fitzpatrick, Rochelle Watkins

Bibliographic record

VenueJournal of Paediatrics and Child Health · 2017
Typearticle
Languageen
FieldMedicine
TopicPrenatal Substance Exposure Effects
Canadian institutionsnot available
Fundersnot available
KeywordsFetal Alcohol Spectrum DisorderMedicineGuidelinePediatricsPsychiatryPathologyPregnancy

Abstract

fetched live from OpenAlex

Foetal alcohol spectrum disorder (FASD) is a complex neurodevelopmental disorder caused by prenatal alcohol exposure (PAE). In some individuals, characteristic facial features result from the teratogenic effect of first trimester PAE. In response to limited training opportunities in FASD, lack of a nationally adopted diagnostic instrument and confusion about diagnostic criteria, The Australian Guide to the Diagnosis of Fetal Alcohol Spectrum Disorder has been developed, funded by the Commonwealth Department of Health (DoH). Building on a literature review of diagnostic criteria and guidelines from Canada and the USA,1-4 Delphi surveys5-9 and a consensus workshop using the GRADE approach,10, 11 an Australian diagnostic instrument was developed in 2012. In 2015–2016, with additional funding from the DoH, a feasibility trial was conducted, and the instrument, guide and e-learning modules were finalised and harmonised with the new Canadian guideline for diagnosis of FASD.12 The Australian Guide to the Diagnosis of Fetal Alcohol Spectrum Disorder and e-learning modules were released in mid-2016 and are freely available at http://alcoholpregnancy.telethonkids.org.au/australian-fasd-diagnostic-instrument/australian-guide-to-the-diagnosis-of-fasd/. This includes clinical forms that can be used during evaluation. A key recommendation in the guide is the adoption of FASD as a diagnostic term, with two subcategories: FASD with three sentinel facial features and FASD with less than three sentinel facial features. Diagnostic criteria relate to PAE, severe neurodevelopmental impairment in 3 out of 10 domains and sentinel facial features (small palpebral fissures, smooth philtrum and thin upper lip) (Table 1; Fig. 1). FASD with three sentinel facial features replaces the diagnosis of foetal alcohol syndrome, but without a requirement for growth impairment.11 FASD with less than three sentinel facial features encompasses the previous categories of partial foetal alcohol syndrome and neurodevelopmental disorder-alcohol exposed.11 Co-existing or alternative diagnoses including genetic conditions (e.g. microdeletions or duplications), effects of other teratogens and prenatal exposures, as well as the effects of postnatal exposures such as early life trauma and brain injury should be considered. Neurodevelopmental domains Sentinel facial features The diagnosis of FASD requires multidisciplinary assessment including comprehensive physical and developmental assessment, as well as psychometric testing, preferably by a multidisciplinary diagnostic team, and typically led by a medical specialist such as a paediatrician, psychiatrist or geneticist. The assessment process may be confronting for the individual or caregiver who should provide informed consent beforehand, and receive appropriate support as required. This is particularly salient when biological parents or family are involved. An assessment report outlining the individual's strengths and difficulties, and recommendations should be provided to the family and referring clinician or agency. The value of sharing this information with relevant service providers (including teachers) should be discussed. If FASD is diagnosed, written information about the condition and contact details for the National Organisation for FASD (http://www.nofasd.org/) should be provided. Dissemination of the guide and the e-learning modules aims to standardise FASD diagnosis. We hope that it will provide clinicians with increased confidence to consider a diagnosis of FASD, the knowledge to refer for or make the diagnosis, and the information needed to manage and support individuals and families living with FASD. The guide will be updated as new evidence emerges, to ensure it reflects current knowledge and best practice in the evolving field of FASD. Having national, standardised criteria for diagnosis will also improve our ability to advocate for services, monitor FASD prevalence, and support efforts to reduce PAE and hence enable primary prevention of FASD. The trial and implementation phase of the diagnostic instrument for foetal alcohol spectrum disorder (FASD) in Australia was funded through a contract from the Commonwealth Department of Health and benefited from the contribution of time, intellectual input and commitment by members of the Expert Review Panel (Professor EJ Elliott (Chair), Professor C Bower, Dr J Fitzpatrick, Ms V Russell, Dr D Shelton, Dr A Wilkins and Dr M Zimmet) and the Steering Group (Professor C Bower (Chair), Mr Scott Avery, Dr Felicity Collins, Dr Jennifer Delima, Professor EJ Elliott, Dr J Fitzpatrick, Ms Andrea Lammel, Ms V Russell, Dr D Shelton, Dr Lydia So, Dr David Thomas, Dr A Wilkins and Dr M Zimmet). We thank members of the Telethon Kids Institute's Alcohol, Pregnancy and FASD Research Program (Roslyn Giglia, Noni Walker, Heather Jones and Eliza Offereins). We are grateful to Dr Jocelynn Cooke and colleagues, who provided valuable advice and further detail on the Canadian Guidelines. The online modules were developed by Dr M Zimmet, Professor EJ Elliott, J Doorey and Professor C Bower. We acknowledge the technical expertise of Dr Rob Phillips, Dave Wheeler, Rob Bull and Pete Phillips in the development of the modules, and Melanie Hogan, Reverb Pty Ltd for use of her DVD 'The Story of Alcohol Use in Pregnancy and Fetal Alcohol Spectrum Disorders'. We also thank the clinicians, parents and carers who participated in the trial. EJ Elliott is supported by an NHMRC Practitioner Fellowship (no. 1021480).

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.186
Threshold uncertainty score0.318

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)0.0000.000

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 head0.017
GPT teacher head0.320
Teacher spread0.303 · 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".

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Citations63
Published2017
Admission routes1
Has abstractyes

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