Kidney Disease Awareness and Knowledge among Survivors ofAcute Kidney Injury
Bibliographic record
Abstract
BACKGROUND: Acute kidney injury (AKI) survivors are at risk for chronic kidney disease, recurrent AKI, and cardiovascular disease. The transition from hospital to ambulatory care is an opportunity to reduce these sequelae by launching self-care plans through effective patient education. How well AKI survivors are informationally prepared to apply kidney-specific self-care is unknown. The purpose of this study was to identify awareness and disease-specific knowledge among AKI survivors. METHODS: We performed a cross-sectional survey of AKI-related awareness and knowledge in 137 patients with Kidney Disease Improving Global Outcomes Stage II or III AKI near the time of hospital discharge. Patients were asked (1) "Did you experience AKI while in the hospital?" and (2) "Do you have a problem with your kidney health?" Objective knowledge of AKI was evaluated with a 15-item adapted version of the validated Kidney Knowledge Survey that included topics such as common causes, risk factors, and how AKI is diagnosed. RESULTS: Median age was 54 (interquartile range 43-63) and 81% were white. Eighty percent of patients were unaware that they had experienced AKI and 53% were both unaware they had experienced AKI or had a "problem with their kidneys." Multivariable logistic regression identified being male and lack of nephrology consult as predictors of unawareness with ORs of 3.92 (95% CI 1.48-10.33) and 5.10 (95% CI 1.98-13.13), respectively. Less than 50% recognized nonsteroidal anti-inflammatory drugs, contrast, or phosphate-based cathartics as risk factors for AKI. Two-thirds of patients did not agree that they knew a lot about AKI and more than 80% desired more information. CONCLUSIONS: Most patients with moderate to severe AKI are unaware of their condition, lack understanding of risk factors for recurrent AKI, and desire more information. Patient-centered communication to optimize awareness, understanding, and care will require coordinated educational strategies throughout the continuum of AKI care.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".