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Record W4402360586 · doi:10.1002/uog.28368

EP08.40: Determining the hospital costs of macrosomia after diabetes in pregnancy

2024· article· en· W4402360586 on OpenAlexaff
Christy Pylypjuk, Y. Jennifer

Bibliographic record

VenueUltrasound in Obstetrics and Gynecology · 2024
Typearticle
Languageen
FieldMedicine
TopicDiabetes Management and Research
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsPregnancyDiabetes in pregnancyDiabetes mellitusMedicineObstetricsFetal macrosomiaGestational diabetesEndocrinologyGestation

Abstract

fetched live from OpenAlex

To determine the influence of macrosomia on neonatal and maternal hospital resource utilisation following diabetes in pregnancy. This was a retrospective cohort of singleton pregnancies complicated by pre-existing diabetes at a regional maternity hospital (2011 to 2020). Primary exposure was macrosomia (birthweight above the 90 percentile for gestational age). A validated electronic hospital database was used to collate patient demographics, pregnancy complications, birth events, and neonatal outcomes. The main outcome was peripartum hospital resource utilisation for neonates and mothers as measured by length of hospital stay, intensive care unit admission, and resource intensity weight (RIW) - a proxy of healthcare costs. Descriptive and inferential statistics were used to evaluate the relationship between macrosomia and hospital resource utilisation. 1241 pregnancies were included (87.5% with type 2 diabetes). Incidence of macrosomia was 48.5%, including one-third with birthweights above the 97 percentile. Younger maternal age, multiparity, and cigarette smoking were more common in the macrosomia group. Significantly more newborns with macrosomia required NICU admission than compared to appropriately grown controls (42% vs 29%, p < 0.0001), despite no difference in gestational age at birth, Caesarean section, or other neonatal complications. Hospital stays were longer for neonates with macrosomia (10.7 days (SD 20.7) vs 8.4 days (SD 16.8), p = 0.036) and their mothers (4.4 days (SD 3.6) vs 3.8 days (SD 3.0), p = 0.0003), but there was no difference in resource intensity weights for those with macrosomia compared to diabetes alone (p = 0.726). Macrosomia confers an additional burden on hospital resources beyond diabetes in pregnancy alone. Better understanding of the hospital care required after macrosomia will improve allocation of limited healthcare resources and counselling of families experiencing this common pregnancy complication.

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)0.012
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 score0.018
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.003
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.265
Teacher spread0.256 · 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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