Medication Intervention for Chronic Kidney Disease Patients Transitioning from Hospital to Home: Study Design and Baseline Characteristics
Bibliographic record
Abstract
BACKGROUND: The hospital readmission rate in the population with chronic kidney disease (CKD) is high and strategies to reduce this risk are urgently needed. METHODS: The CKD-Medication Intervention Trial (CKD-MIT; www.clinicaltrials.gov; NCTO1459770) is a single-blind (investigators), randomized, clinical trial conducted at Providence Health Care in Spokane, Washington. Study participants are hospitalized patients with CKD stages 3-5 (not treated with kidney replacement therapy) and acute illness. The study intervention is a pharmacist-led, home-based, medication management intervention delivered within 7 days after hospital discharge. The primary outcome is a composite of hospital readmissions and visits to emergency departments and urgent care centers for 90 days following hospital discharge. Secondary outcomes are achievements of guideline-based targets for CKD risk factors and complications. RESULTS: Enrollment began in February 2012 and ended in May 2015. At baseline, the age of participants was 69 ± 11 years (mean ± SD), 50% (77 of 155) were women, 83% (117 of 141) had hypertension and 56% (79 of 141) had diabetes. At baseline, the estimated glomerular filtration rate was 41 ± 14 ml/min/1.73 m2 and urine albumin-to-creatinine ratio was 43 mg/g (interquartile range 8-528 mg/g). The most frequent diagnosis category for the index hospital admission was cardiovascular diseases at 34% (53 of 155), but the most common single diagnosis for admission was community-acquired acute kidney injury at 10% (16 of 155). CONCLUSION: Participants in CKD-MIT are typical of acutely ill hospitalized patients with CKD. A medication management intervention after hospital discharge is under study to reduce post-hospitalization acute care utilization and to improve CKD management.
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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 | 0.006 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".