Caregiver Network and Caregiving Needs in Women With Pulmonary Arterial Hypertension (PAH)
Bibliographic record
Abstract
Abstract BACKGROUND: Pulmonary arterial hypertension (PAH) is a progressive debilitating disease that disproportionately impacts young women. The aim of this study is to explore caregiver networks and support around these women. METHODS: This is an interim descriptive analysis of data from an online survey of women (age 21-50) with PAH living in the US and UK. De novo questions and validated instruments of social support and interpersonal support evaluation were included in the survey. Institutional Review Board/Ethics Committee exemption was obtained in all countries. Final analysis which includes ∼120 more patients from Canada, Germany, France, and Italy will be available for presentation at the conference. RESULTS: This analysis includes 150 women patients (US=120, UK=30). Regarding the make-up of informal caregiver networks, in the US patients most frequently reported spouses (58%), children (53%) and friend(s) (51%) as their caregivers, while in UK patients most frequently reported spouse (53%), relatives (30%) and parent(s) (23%). In the US patients required support from their spouse almost every day to provide financial support (49%), check in how they were doing (46%) and household duties (47%), while in the UK patients required support almost every day with household duties (25%), taking care of important people in life (31%) and making efforts to cheer up the patient (31%). Participants were asked to indicate the amount of support they needed versus the amount of support they receive. In the past four weeks patients reported ‘needing support' with household duties, 88% (US) and 100% (UK); caring for their parents and children, 64% (US) and 83% (UK); and finances, 72% (US) and 67% (UK). Patients reported ‘having reliable support’ with household duties, 88% (US) and 87% (UK); caring for their parents or children, 79% (US) and 90% (UK); and finances 72% (US) and 90% (UK). CONCLUSIONS: This study highlights that women with PAH require a strong network of caregivers and most burden of caregiving falls on family members. Despite these networks of care, there may be areas where more support is needed. Further research is warranted to investigate areas where patients don't have full coverage from their informal caregiver network and explore to what extent these patients are linked to formal support programs to cover those needs.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".