Assessment of Worldwide Acute Kidney Injury Epidemiology in Neonates: Design of a Retrospective Cohort Study
Bibliographic record
Abstract
INTRODUCTION: Acute kidney injury (AKI) affects ~30% of hospitalized neonates. Critical to advancing our understanding of neonatal AKI is collaborative research among neonatologists and nephrologists. The Neonatal Kidney Collaborative (NKC) is an international, multidisciplinary group dedicated to investigating neonatal AKI. The AWAKEN study (Assessment of Worldwide Acute Kidney injury Epidemiology in Neonates) was designed to describe the epidemiology of neonatal AKI, validate the definition of neonatal AKI, identify primary risk factors for neonatal AKI, and investigate the contribution of fluid management to AKI events and short-term outcomes. METHODS AND ANALYSIS: The NKC was established with at least one pediatric nephrologist and neonatologist from 24 institutions in 4 countries (USA, Canada, Australia, and India). A Steering Committee and four subcommittees were created. The database subcommittee oversaw the development of the web-based database (MediData Rave™) that captured all NICU admissions from 1/1/14 to 3/31/14. Inclusion and exclusion criteria were applied to eliminate neonates with a low likelihood of AKI. Data collection included: (1) baseline demographic information; (2) daily physiologic parameters and care received during the first week of life; (3) weekly "snapshots"; (4) discharge information including growth parameters, final diagnoses, discharge medications, and need for renal replacement therapy; and (5) all serum creatinine values. ETHICS AND DISSEMINATION: AWAKEN was proposed as human subjects research. The study design allowed for a waiver of informed consent/parental permission. NKC investigators will disseminate data through peer-reviewed publications and educational conferences. DISCUSSION: The purpose of this publication is to describe the formation of the NKC, the establishment of the AWAKEN cohort and database, future directions, and a few "lessons learned." The AWAKEN database includes ~325 unique variables and >4 million discrete data points. AWAKEN will be the largest, most inclusive neonatal AKI study to date. In addition to validating the neonatal AKI definition and identifying risk factors for AKI, this study will uncover variations in practice patterns related to fluid provision, renal function monitoring, and involvement of pediatric nephrologists during hospitalization. The AWAKEN study will position the NKC to achieve the long-term goal of improving the lives, health, and well-being of newborns at risk for kidney disease.
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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 | 0.025 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".