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Record W2793282617 · doi:10.1111/anae.14274

Pre‐operative anaemia, intra‐operative hepcidin concentration and acute kidney injury after cardiac surgery: a retrospective observational study

2018· article· en· W2793282617 on OpenAlexafffund
Keyvan Karkouti, Paul S. F. Yip, Christopher T. Chan, Lakhmir S. Chawla, Vivek Rao

Bibliographic record

VenueAnaesthesia · 2018
Typearticle
Languageen
FieldMedicine
TopicIron Metabolism and Disorders
Canadian institutionsToronto General HospitalUniversity of TorontoUniversity Health Network
FundersUniversity of TorontoLa Jolla Pharmaceutical Company
KeywordsHepcidinMedicineAcute kidney injuryCardiopulmonary bypassCreatinineKidneyDialysisCardiac surgeryInternal medicineGastroenterologyUrologyAnemiaSurgery

Abstract

fetched live from OpenAlex

Summary Acute kidney after cardiac surgery is more common in anaemic patients, whereas haemolysis during cardiopulmonary bypass may lead to iron‐induced renal injury. Hepcidin promotes iron sequestration by macrophages: hepcidin concentration is reduced by anaemia and increased by inflammation. We analysed the associations in 525 patients between pre‐operative anaemia (haemoglobin < 130 g.l −1 in men and < 120 g.l −1 in women), intra‐operative hepcidin concentration and acute kidney injury (dialysis or > 26.4 μmol.l −1 or > 50% creatinine increase during the first two days after cardiac surgery. Rates of pre‐operative anaemia and postoperative kidney injury were 109/525 (21%) and 36/525 (7%), respectively. The median ( IQR [range]) intra‐operative hepcidin concentration was 20 (10–33 [0–125]) μg.l −1 and was lower in anaemic patients than those who were not: 15 (4–28 [0–125]) μg.l −1 vs. 21 (12–33 [0–125]) μg.l −1 , respectively, p = 0.002. Four variables were independently associated with postoperative kidney injury, for which the beta‐coefficients ( SE ) were: minutes on cardiopulmonary bypass, 0.016 (0.004), p < 0.001; intra‐operative hepcidin concentration, 0.032 (0.008), p < 0.001; pre‐operative anaemia, 1.97 (0.56), p < 0.001; and Cleveland clinic risk score, 0.88 (0.35), p = 0.005. Contrary to generally increased rates of kidney injury in patients with higher hepcidin concentrations, rates of kidney injury in anaemic patients were lower in patients with higher hepcidin concentrations, beta‐coefficient ( SE ) −0.037 (0.01), p = 0.007. In cardiac surgical patients the rate of postoperative acute kidney injury predicted by the Cleveland risk score might be adjusted for pre‐operative anaemia and intra‐operative cardiopulmonary bypass time and hepcidin concentration. Pre‐operative correction of anaemia, reduction in intra‐operative bypass time and modification of iron homeostasis and hepcidin concentration might reduce acute kidney injury.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
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 head0.019
GPT teacher head0.302
Teacher spread0.283 · 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

Citations15
Published2018
Admission routes2
Has abstractyes

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