Quality of life and care burden of people living with amyotrophic lateral sclerosis who need home-based medical care in Korea and their family caregivers
Bibliographic record
Abstract
Objective: Advanced neurodegenerative diseases (NDDs) lead to severe mobility limitations, creating significant challenges for patients and caregivers at home. We aimed to investigate the quality of life (QOL) and care burden of people living with amyotrophic lateral sclerosis (ALS, pALS) and other NDDs and their family caregivers in Korea. Methods: This prospective survey study included people living with NDDs with mobility restrictions and their caregiver enrolled in a home-based medical care (HBMC) program at one tertiary hospital in South Korea from 2022 to 2024. Data collected included demographics, clinical characteristics, care burden (the Zarit Caregiver Burden Interview Short Form, ZBI-12), QOL (EQ-5D-5L), and depression (Patient Health Questionnaire-9). The results were compared between ALS and other NDDs (non-ALS). Results: Of 44 patients requiring HBMC, 70.5% (31) were pALS. pALS were younger than non-ALS (median age, 65 vs. 79 years); more often, the caregiver was a spouse (64.5% vs. 46.1%, p = 0.30). One-fourth (25.8%) of pALS were on polypharmacy (>10 medications a day). One-third (29%) of pALS and 22.6% of their caregivers experienced moderate or severe depression. Half of pALS caregivers experienced high caregiving burden (ZBI-12 score ≥17). The mean EQ-5D-5L index score was 0.48 for pALS and 0.84 for their caregivers, which was lower than the results for the Korean general population. Conclusions: Patients with severe NDD and caregivers experienced low QOL and high caregiving burden, with pALS caregivers particularly vulnerable to depression and heavy burden. Designing optimal HBMC programs to support pALS and home caregivers is warranted.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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".