Identifying Key Challenges and Opportunities in the Care of AKI Survivors Not on Dialysis: AKINow Workgroup
Bibliographic record
Abstract
Background: ASN recently established the AKINow initiative aiming to promote excellence in the prevention and treatment of AKI. One of the core policy, practice and research objectives of this workgroup is to identify gaps in the care of AKI survivors post hospitalization and develop quality evidence and benchmark existing strategies to care for these patients including insights from other stakeholders Methods: We held a focus group with key stakeholders that included nephrologists, primary care providers, advanced practice providers (APP), intensivists, pediatric providers, community providers, patients and allied health personnel. We sought perspectives on optimal plans for hospital discharge of AKI survivors, challenges and opportunities in their care, communication strategies across diverse stakeholders, patient and care partner education and activation, and preferred interventions Results: While 54% of the participants (n=57) identified integrated care delivery among providers to be the biggest barrier for care of AKI survivors, 23% thought that education and awareness among patients are the main challenge. 79% of the participants recommended RAAS blockers resumption should be after serum creatinine returns to baseline/ new baseline. They further suggested that currently 95% of the care of AKI survivors is shouldered by nephrologists. This care is shared by Internists (51%), pharmacists (51%), RN (43%), APP (43%) and by other allied health personnel (8-22%). AKI patients’ survivor testimonial about their experiences highlighted some of the gaps encountered in their care. Four breakout sessions (12-15/session) suggested specific recommendations to inform who is currently followed after AKI and by whom, different options for care delivery, and potential interventions/practices that may improve clinical and patient-centered outcomes Conclusions: The stakeholder relationships formed, including those with patients, industry, and academia, will facilitate a collaborative research and practice agenda to advise the best and efficient practices after AKI. This represents an opportunity for the “recovery after AKI” workgroup of AKINow to provide leadership by raising awareness and promoting strategies focused on equitable and effective post-AKI care throughout the ASN and wider nephrology community
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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 | 0.020 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.014 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.015 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 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".