Challenges in the Care of Patients with AKI Receiving Outpatient Dialysis: AKINow Recovery Workgroup Report
Bibliographic record
Abstract
BACKGROUND: Up to one third of survivors of AKI that required dialysis (AKI-D) during hospitalization remain dialysis dependent at hospital discharge. Of these, 20%-60%, depending on the clinical setting, eventually recover enough kidney function to stop dialysis, and the remainder progress to ESKD. METHODS: To describe the challenges facing those still receiving dialysis on discharge, the AKINow Committee conducted a group discussion comprising 59 participants, including physicians, advanced practitioners, nurses, pharmacists, and patients. The discussion was framed by a patient who described gaps in care delivery at different transition points and miscommunication between care team members and the patient. RESULTS: Group discussions collected patient perspectives of ( 1 ) being often scared and uncertain about what is happening to and around them and ( 2 ) the importance of effective and timely communication, a comfortable physical setting, and attentive and caring health care providers for a quality health care experience. Provider perspectives included ( 1 ) the recognition of the lack of evidence-based practices and quality indicators, the significant variability in current care models, and the uncertain reimbursement incentives focused on kidney recovery and ( 2 ) the urgency to address communication barriers among hospital providers and outpatient facilities. CONCLUSIONS: The workgroup identified key areas for future research and policy change to ( 1 ) improve communication among hospital providers, dialysis units, and patients/care partners; ( 2 ) develop tools for risk classification, subphenotyping, and augmented clinical decision support; ( 3 ) improve education to providers, staff, and patients/care partners; ( 4 ) identify best practices to improve relevant outcomes; ( 5 ) validate quality indicators; and ( 6 ) assess the effect of social determinants of health on outcomes. We urge all stakeholders involved in the process of AKI-D care to align goals and work together to fill knowledge gaps and optimize the care to this highly vulnerable patient population.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.012 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| 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".