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Record W4387331300 · doi:10.1002/jgc4.1808

Perinatal palliative care for family with prenatal diagnosis of <scp>Matthew‐Wood</scp> syndrome

2023· article· en· W4387331300 on OpenAlexaff
Aleksandra Korzeniewska, Hanna Moczulska

Bibliographic record

VenueJournal of Genetic Counseling · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicOcular Disorders and Treatments
Canadian institutionsHealth Care Foundation
Fundersnot available
KeywordsPalliative careMedicinePregnancyGenetic counselingDiseaseMedical geneticsPediatricsIntensive care medicineNursingFamily medicineGeneticsGeneInternal medicineBiology

Abstract

fetched live from OpenAlex

Matthew-Wood syndrome (MWS) is a rare autosomal recessive disorder caused by pathogenic variants of the STRA6 gene. Several studies in the available literature comprise patients with pathogenic variants of gene STRA6 with various phenotypic expressions: from lethal forms of MWS to non-lethal anophthalmia. These reports mainly describe new pathogenic variants and phenotypic expression but do not describe medical or paramedical care for the affected families. In our case report, we describe the second case of MWS in the same family and the benefits of including the patient's family in the perinatal palliative care program. The first pregnancy was terminated with a cesarean section; the boy was intubated in the delivery room and died soon after. The mother was not allowed to say farewell or keep any remembrances of her child. In the second pregnancy, the family was involved in the perinatal palliative care program, and all paramedical aspects, crucial from the parent's perspective, were planned and implemented. Palliative perinatal care enables complex care for the pregnant woman and her family. The possibility of palliative perinatal care is significant in decision-making in families with a high risk of lethal disease in subsequent pregnancies.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.265
Threshold uncertainty score0.516

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 head0.009
GPT teacher head0.249
Teacher spread0.239 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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