SYMPTOMS AND MENTAL HEALTH SERVICE USE IN CHRONIC KIDNEY DISEASE
Bibliographic record
Abstract
Chronic kidney disease (CKD) is a multifaceted health problem with both physical and psychological manifestations. Increased symptom burden is associated with higher risk of mortality, decreased treatment adherence, and impaired quality of life. Despite the recognition of the importance of symptoms, the symptoms and mental health of individuals with CKD remain poorly understood in terms of their measurement, epidemiology and associated service use. The chapters in this dissertation aim to inform these knowledge gaps. Chapter 2 focusses on the symptom burden of patients receiving maintenance hemodialysis treatment and uses exploratory analyses to identify intra-dialytic symptom clusters associated with prolonged dialysis treatment recovery time. Chapters 3 and 4 are population-based studies examining mental health and addictions service utilization in patients with CKD using administrative data in Ontario, Canada. Chapter 3 is a cross-sectional study evaluating the prevalence of individuals with a history of mental health and addiction service use by levels of kidney function. Chapter 4 is a retrospective cohort study evaluating the rates of mental health and addiction service use over time in patients with CKD. Together, these chapters provide further understanding of how symptoms of dialysis and mental health and addiction service use may be measured in this patient population. They also inform considerations for the design of future symptom management and system-level mental health strategies in CKD.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".