Recovery After AKI: Goals of an AKI!Now Workgroup
Bibliographic record
Abstract
Background: The American Society of Nephrology recently established the AKI!Now initiative. AKI!Now aims to promote excellence in the prevention and treatment of AKI by transforming the delivery of AKI care to improve clinical and patient-centered outcomes. Herein, we describe the focused efforts of AKI!Now on “recovery after AKI.” Methods: Three core objectives were identified in the domain of AKI recovery: 1. To determine areas of priority for mechanistic research focused on recovery after AKI. It is expected that these would include a variety of experimental models suitable for various AKI etiologies and disease severities. 2. To benchmark existing strategies to care for patients after AKI including integrated insights from primary care providers, nephrologists, other subspecialty health care professionals. 3. To facilitate implementation and testing of interventions designed to limit short- and long-term complications of AKI and promote recovery. Dialysis dependent and independent AKI survivors should both be considered for these interventions and clinical trials. Results: The AKI!Now initiative will highlight and clarify challenges and opportunities to improve care after AKI. This work will also inform who is followed after AKI and by whom (i.e., primary care and/or nephrology), options for care delivery (i.e., in-person versus telehealth), and potential practices to improve outcomes (i.e., role of ACEi/ARB and SGLT2 inhibitors after AKI, physical/cognitive rehabilitation). The stakeholder relationships formed, including those with patients, healthcare professionals, industry, and academia, will facilitate a collaborative research and practice agenda necessary to understand and outline best practices after AKI. Conclusions: Survivors of AKI are a high-risk and growing population, and AKI is associated with worse long-term outcomes than an acute myocardial infarction. However, how to care for patients after AKI remains ill-defined with substantial practice variation. This represents an opportunity for the “recovery after AKI” workgroup of AKI!Now to provide leadership by raising awareness and promoting strategies focused on equitable and effective post-AKI care throughout the American Society of Nephrology 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 | 0.060 | 0.023 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.008 | 0.003 |
| Scholarly communication | 0.010 | 0.010 |
| Open science | 0.005 | 0.033 |
| Research integrity | 0.009 | 0.013 |
| Insufficient payload (model declined to judge) | 0.015 | 0.014 |
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".