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Record W4391991401 · doi:10.1097/aln.0000000000004957

Candidate Kidney Protective Strategies for Patients Undergoing Major Abdominal Surgery: A Secondary Analysis of the RELIEF Trial Cohort

2024· article· en· W4391991401 on OpenAlexaff
David R. McIlroy, Xiaoke Feng, Matthew S. Shotwell, Sophie Wallace, Rinaldo Bellomo, Amit X. Garg, Kate Leslie, Philip J. Peyton, David Story, Paul S. Myles

Bibliographic record

VenueAnesthesiology · 2024
Typearticle
Languageen
FieldMedicine
TopicAcute Kidney Injury Research
Canadian institutionsLondon Health Sciences Centre
Fundersnot available
KeywordsMedicineCohortAbdominal surgeryCohort studySurgeryGeneral surgeryInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Acute kidney injury (AKI) is common after major abdominal surgery. Selection of candidate kidney protective strategies for testing in large trials should be based on robust preliminary evidence. METHODS: A secondary analysis of the Restrictive versus Liberal Fluid Therapy in Major Abdominal Surgery (RELIEF) trial was conducted in adult patients undergoing major abdominal surgery and randomly assigned to a restrictive or liberal perioperative fluid regimen. The primary outcome was maximum AKI stage before hospital discharge. Two multivariable ordinal regression models were developed to test the primary hypothesis that modifiable risk factors associated with increased maximum stage of postoperative AKI could be identified. Each model used a separate approach to variable selection to assess the sensitivity of the findings to modeling approach. For model 1, variable selection was informed by investigator opinion; for model 2, the Least Absolute Shrinkage and Selection Operator (LASSO) technique was used to develop a data-driven model from available variables. RESULTS: Of 2,444 patients analyzed, stage 1, 2, and 3 AKI occurred in 223 (9.1%), 59 (2.4%), and 36 (1.5%) patients, respectively. In multivariable modeling by model 1, administration of a nonsteroidal anti-inflammatory drug or cyclooxygenase-2 inhibitor, intraoperatively only (odds ratio, 1.77 [99% CI, 1.11 to 2.82]), and preoperative day-of-surgery administration of an angiotensin-converting enzyme inhibitor or angiotensin receptor blocker compared to no regular use (odds ratio, 1.84 [99% CI, 1.15 to 2.94]) were associated with increased odds for greater maximum stage AKI. These results were unchanged in model 2, with the additional finding of an inverse association between nadir hemoglobin concentration on postoperative day 1 and greater maximum stage AKI. CONCLUSIONS: Avoiding intraoperative nonsteroidal anti-inflammatory drugs or cyclooxygenase-2 inhibitors is a potential strategy to mitigate the risk for postoperative AKI. The findings strengthen the rationale for a clinical trial comprehensively testing the risk-benefit ratio of these drugs in the perioperative period.

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 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)0.001
metaresearch head score (Gemma)0.001
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 score0.220
Threshold uncertainty score0.551

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.018
GPT teacher head0.308
Teacher spread0.289 · 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 teacher head, 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

Citations8
Published2024
Admission routes1
Has abstractyes

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