Care strategies for pregnant people and women living with hepatitis C in North America
Bibliographic record
Abstract
Hepatitis C is a global health concern, with over 50 million people infected. Marginalized populations, particularly people who inject drugs, may not receive treatment despite an increased infection rate; similarly, there are gender disparities in the hepatitis C cascade of care, leaving some women undertreated. This is especially problematic, as hepatitis C rates are increasing substantially among individuals of childbearing age and pregnant people. While hepatitis C epidemiology and baseline characteristics are well understood, models of care focused on pregnant people that provide solutions to these barriers in attaining care are needed to increase health equity and achieve hepatitis C elimination. The adoption of highly effective, direct-acting antivirals for hepatitis C treatment has helped tremendously, but direct-acting antivirals must be accessible, and their availability must be combined with enhanced screening efforts. We review newly developed models of care for pregnant people who have hepatitis C and provide several case studies (with patient examples) of methods that have improved the care cascade and patient outcomes in our practices. Some models, such as mother-infant collocated care, allow postpartum and infant hepatitis C care to occur simultaneously, minimizing the number of visits and maximizing access to patient care. Other models, such as mobile point-of-care services and peer navigation, help marginalized populations attain access to care regardless of insurance status and transportation accessibility and provide peer support to help overcome treatment barriers, such as stigma and poverty. Additional innovative hepatitis C care models for pregnant people and women include modeling-based response-guided treatment, interdisciplinary collocated care models, and an integrated medical home model. Ultimately, there is no "one size fits all" hepatitis C model of care, as needs differ according to region, population demographics, and individual circumstances. As our review shows, many of the models apply multidisciplinary approaches to provide a range of care options. Reviewing the available models of care will help identify how practitioners can increase patient engagement with care and improve treatment uptake and completion rates among pregnant people and women and thus can contribute to hepatitis C elimination.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".