What insights do patients and caregivers have on acute kidney injury and posthospitalisation care? A single-centre qualitative study from Toronto, Canada
Bibliographic record
Abstract
Objectives Hospitalisation with acute kidney injury (AKI) is associated with short-term and long-term adverse events, but patient and caregiver experiences with AKI are not well described. We sought to better understand patient and caregiver perspectives after a hospitalisation with AKI to inform discharge strategies that may improve outcomes for this high-risk population. Design Qualitative study with semistructured interviews. Setting Tertiary care hospital in Toronto, Ontario, Canada. Participants Adult patients (n=15) who survived a hospitalisation with Kidney Disease Improving Global Outcomes stage 2 or 3 AKI from May to December 2016. We also interviewed five patient caregivers. We required patients to have no previous evidence of severe chronic kidney disease (ie, prior receipt of dialysis, previous kidney transplantation or pre-existing estimated glomerular filtration rate (eGFR) under 30 mL/min/1.73 m 2 ). Results We identified three over-arching themes: (1) prioritisation of conditions other than AKI, reflected by the importance placed on other comorbidities and the omission of AKI as part of the ongoing medical history; (2) variability in comprehension of the significance of AKI, represented by minimal knowledge of the causes and symptoms associated with AKI, along with misinformation on the kidneys’ ability to self-repair; and (3) anxiety from discharge planning and competing health demands, illustrated by complicated discharge plans involving multiple specialist appointments. Conclusions Patients and caregivers view AKI as a short-term and reversible condition, giving it little thought during the postdischarge period. As a result, reliance on patients and caregivers to report an episode of AKI to their outpatient physicians is unlikely to be successful. Patient-centred tools and decision aids are needed to bridge the gap between a hospitalisation with AKI and the safe transition to the outpatient setting.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.021 | 0.009 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".