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Record W4389383778 · doi:10.34067/kid.0000000000000332

Challenges in the Care of Patients with AKI Receiving Outpatient Dialysis: AKINow Recovery Workgroup Report

2023· article· en· W4389383778 on OpenAlex
Javier A. Neyra, Leslie S. Gewin, Jia Hwei Ng, Erin F. Barreto, Bonnie Freshly, Jeff Willett, Emaad M. Abdel‐Rahman, Ian E. McCoy, Yuenting Diana Kwong, Samuel A. Silver, Jorge Cerdá, Anitha Vijayan

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueKidney360 · 2023
Typearticle
Languageen
FieldMedicine
TopicDialysis and Renal Disease Management
Canadian institutionsQueen's University
FundersNational Institute of Diabetes and Digestive and Kidney DiseasesNational Institute of Allergy and Infectious DiseasesDaiichi Sankyo EuropeAgency for Healthcare Research and QualityNational Institutes of HealthAstraZenecaCanadian Society of NephrologyNxStageVifor PharmaAcelRx PharmaceuticalsSatellite HealthcareAmerican Heart AssociationAmerican Society of NephrologyNovo NordiskPatient-Centered Outcomes Research InstituteU.S. Department of Veterans Affairs
KeywordsWorkgroupDialysisMedicineIntensive care medicineMedical emergencyEmergency medicineInternal medicineComputer science

Abstract

fetched live from OpenAlex

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.228
Threshold uncertainty score0.351

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.027
GPT teacher head0.258
Teacher spread0.232 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it