Risk of Hospital Readmission Among People with CKD: A Population-Based Cohort Study
Bibliographic record
Abstract
Background: Hospital readmissions affect people with greater medical and social complexity and are a significant challenge for healthcare systems. With the high burden of comorbidities and resultant complications faced by people with chronic kidney disease (CKD), these individuals experience high risk of hospitalization and mortality compared to the general population. With about 30% of unplanned readmissions estimated to be avoidable, identifying individuals with CKD at risk of readmissions may inform decision-making during discharge planning to reduce this risk.Thus, we aimedto compare the differences in readmission risk and causes among individuals with varying glomerular filtration rates (GFR). Methods: Adults discharged from hospitals in Alberta, Canada, from 2005-2021 were included. Baseline estimated GFR before the index hospitalization was categorized into seven groups (in mL/min/1.73 m2): ≥60 (G1-2), 45-59 (G3a), 30-44 (G3b), 15-29 (G4), <15 not on dialysis (G5ND), on dialysis (G5D), and kidney transplant recipients (G1-5T). The primary outcome was unplanned readmission or death within 30 days of discharge. Logistic regression was used to investigate differences in odds of the primary outcome, using G1-2 as the reference group. Causes of readmission were examined for each GFR category. Results: This study included 1,231,442 participants with a median age of 62 years, of whom 51% were female. Within 30 days of discharge, 17% of participants experienced an unplanned readmission or death. With lower GFR categories, heart failure became the most common cause of unplanned readmission, followed by acute kidney injury. Compared to the G1-2 category, each progressively lower GFR group had significantly higher odds of 30-day unplanned readmission or death, with the highest odds experienced by the G1T-5T group (OR: 1.78; 95% CI: 1.43, 2.21) and G5D group (OR: 1.41; 95% CI: 1.33, 1.51). Conclusion: These findings highlight the increased risk of 30-day unplanned readmission or mortality with lower GFR, suggesting that CKD severity may be helpful to inform risk-based discharge planning to improve patient outcomes. Funding: Government Support – Non-U.S.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".