The Association Between Estimated Glomerular Filtration Rate and Hospitalization for Fatigue: A Population-Based Cohort Study
Bibliographic record
Abstract
Background: Fatigue is a pervasive symptom among patients with chronic kidney disease (CKD) that is associated with several adverse outcomes, but the incidence of hospitalization for fatigue is unknown. Objective: To explore the association between estimated glomerular filtration rate (eGFR) and incidence of hospitalization for fatigue. Design: Population-based retrospective cohort study using a provincial administrative dataset. Setting: Alberta, Canada. Patients: People above age 18 who had at least 1 outpatient serum creatinine measurement taken in Alberta between January 1, 2009, and December 31, 2016. Measurements: The first outpatient serum creatinine was used to estimate GFR. Hospitalization for fatigue was identified using International Classification of Diseases, Tenth Revision (ICD-10) code R53.x. Methods: Patients were stratified by CKD category based on their index eGFR. We used negative binomial regression to determine if there was an increased incidence of hospitalization for fatigue by declining kidney function (reference eGFR ≥ 60 mL/min/1.73m 2 ). Estimates were stratified by age, and adjusted for age, sex, socioeconomic status, and comorbidity. Results: The study cohort consisted of 2 823 270 adults, with a mean age of 46.1 years and median follow-up duration of 6.0 years; 5 422 hospitalizations for fatigue occurred over 14 703 914 person-years of follow-up. Adjusted rates of hospitalization for fatigue increased with decreasing kidney function, across all age strata. The highest rates were seen in adults on dialysis (adjusted incident rate ratios 24.47, 6.66, and 3.13 for those aged 18 to 64, 65 to 74, and 75+, respectively, compared with eGFR ≥ 60 mL/min/1.73m 2 ). Limitations: Fatigue hospitalization codes have not been validated; reference group limited to adults with at least 1 outpatient serum creatinine measurement; remaining potential for residual confounding. Conclusions: Declining kidney function was associated with increased incidence of hospitalization for fatigue. Further research into ways to address fatigue in the CKD population is warranted. Trial Registration: Not applicable (not a clinical trial).
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".