Impact of neighbourhood-level social determinants of health on healthcare utilisation and perinatal outcomes in pregnant women with NAFLD cirrhosis: a population-based study in Ontario, Canada
Bibliographic record
Abstract
BACKGROUND: Cirrhosis is rising in North America, driven partly by the epidemic of non-alcoholic fatty liver disease (NAFLD), most in women of reproductive age. Little is known about factors that impact perinatal outcomes and healthcare utilisation in pregnant women with NAFLD cirrhosis. OBJECTIVES: We investigated the association between population-level social determinants, health outcomes and healthcare utilisation. METHODS: We retrospectively analysed healthcare utilisation and perinatal outcomes in a cohort of pregnant women with NAFLD cirrhosis from Ontario, Canada from 2000 to 2016 and followed for 90 days postdelivery. We compared utilisation and health outcomes according to income, residential instability, material deprivation, dependency and ethnic diversity. A Cochran-Armitage test for trend was done to assess whether utilisation patterns were linear across quintiles. RESULTS: 3320 pregnant women with NAFLD cirrhosis formed the study cohort. Decreasing income quintile associated with a higher proportion of women with at least one emergency department (ED) visit. Increasing residential instability, material deprivation and dependency were associated with a higher frequency of ED visitation, with no compelling differences in the rates of perinatal complications or adverse outcomes in pregnant women with NAFLD cirrhosis. Using multiple population-level proxies for social determinants of health, this study demonstrates an association between marginalisation and increased ED visitation. CONCLUSIONS: As the incidence rate of pregnancies among women with NAFLD cirrhosis continues to rise, understanding how this population uses healthcare services will help coordinate care for these patients.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".