Caregiver Burden Assessment in Primary Congenital Glaucoma
Bibliographic record
Abstract
PURPOSE: To assess the magnitude of caregiver burden and depression in primary caregivers of patients with primary congenital glaucoma. METHODS: Fifty-five primary caregivers of children diagnosed with primary congenital glaucoma were evaluated. The magnitude of burden on caregivers was assessed using a Caregiver Burden Questionnaire (CBQ). The overall aggregate burden and burden across 3 domains-socioeconomic, emotional, and psychological-was evaluated. Depressive symptomatology was evaluated using a Patient Health Questionnaire-9 (PHQ-9) standard questionnaire and graded from mild to severe. RESULTS: The mean age of the presenting children was 8.11±46.71 months; all of them were male. The mean age of the study participants was 33.6±8.36 years (53 female, 2 male). Thirty-nine (71%) individuals were identified to have moderate aggregate burden and 3 (5%) had severe aggregate burden. Twelve (22%) subjects were noted to have moderate depression, while 6 of them (11%) had either severe or very severe grades of depression. CONCLUSIONS: Caregivers of patients with primary congenital glaucoma have significant emotional and psychological burden. Moderate to severe depression may be present in one-third of individuals giving primary care to children with congenital glaucoma.
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 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 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".