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Record W3158405664 · doi:10.1097/ccm.0000000000005073

Cumulative Application of Creatinine and Urine Output Staging Optimizes the Kidney Disease: Improving Global Outcomes Definition and Identifies Increased Mortality Risk in Hospitalized Patients With Acute Kidney Injury

2021· article· en· W3158405664 on OpenAlexaff
Scott M. Sutherland, Ahmad Kaddourah, Scott Gillespie, Danielle E. Soranno, Robert P. Woroniecki, Rajit K. Basu, Michael Zappitelli

Bibliographic record

VenueCritical Care Medicine · 2021
Typearticle
Languageen
FieldMedicine
TopicAcute Kidney Injury Research
Canadian institutionsHospital for Sick Children
Fundersnot available
KeywordsAcute kidney injuryMedicineKidney diseaseRenal replacement therapyCreatinineIntensive care medicineInternal medicineOliguriaRenal function

Abstract

fetched live from OpenAlex

OBJECTIVES: Acute kidney injury is diagnosed according to creatinine and urine output criteria. Traditionally, both are applied, and a severity stage (1-3) is conferred based upon the more severe of the two; information from the other criteria is discarded. Physiologically, however, rising creatinine and oliguria represent two distinct types of renal dysfunction. We hypothesized that using the information from both criteria would more accurately characterize acute kidney injury severity and outcomes. DESIGN: Prospective cohort study. SETTING: Multicenter, international collaborative of ICUs. PATIENTS: Three thousand four hundred twenty-nine children and young adults admitted consecutively to ICUs as part of the Assessment of the Worldwide Acute Kidney Injury, Renal Angina and Epidemiology Study. MEASUREMENTS AND MAIN RESULTS: The Kidney Disease: Improving Global Outcomes creatinine and urine output acute kidney injury criteria were applied sequentially, and the two stages were summed, generating an Acute Kidney Injury (AKI) Score ranging from 1 to 6. The primary outcome was 28-day mortality; secondary outcomes were time until ICU discharge and nonrecovery from acute kidney injury. Models considered associations with AKI Score, assessing the relationship unadjusted and adjusted for covariates. Twenty-eight-day mortality and nonrecovery from acute kidney injury were modeled using logistic regression. For 28-day ICU discharge, competing risks analysis was performed. Although AKI Scores 1-3 had similar mortality to no Acute Kidney Injury, AKI Scores 4-6 were associated with increased mortality. Relative to No Acute Kidney Injury, AKI Scores 1-6 were less likely to be discharged from the ICU within 28 days. Relative to AKI Score 1, AKI Scores 2-6 were associated with higher risk of nonrecovery. Within the traditional Kidney Disease: Improving Global Outcomes Stage 3 acute kidney injury cohort, when compared with AKI Score 3, AKI Scores 4-6 had increased mortality, AKI Scores 5-6 had prolonged time to ICU discharge, and AKI Score 6 experienced higher nonrecovery rates. CONCLUSIONS: Cumulative application of the creatinine and urine output criteria characterizes renal excretory and fluid homeostatic dysfunction simultaneously. This Acute Kidney Injury score more comprehensively describes the outcome implications of severe acute kidney injury than traditional staging methods.

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 imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.017
GPT teacher head0.342
Teacher spread0.325 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations25
Published2021
Admission routes1
Has abstractyes

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