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Record W2463557538

Renal dysfunction after cardiac surgery.

2001· article· en· W2463557538 on OpenAlexaff
Dan Abrahamov, Miguel Tamariz, Stephen E. Fremes, Satoshi Tobe, George T. Christakis, Guru, Jeri Sever, Bernard S. Goldman

Bibliographic record

VenuePubMed · 2001
Typearticle
Languageen
FieldMedicine
TopicAcute Kidney Injury Research
Canadian institutionsSunnybrook Health Science Centre
Fundersnot available
KeywordsMedicineRenal functionCreatinineDialysisDiabetes mellitusCardiac surgerySurgeryKidney diseaseIncidence (geometry)Myocardial infarctionCardiologyInternal medicineEndocrinology
DOInot available

Abstract

fetched live from OpenAlex

OBJECTIVE: To assess the causes and outcomes of patients with postcardiac surgery renal dysfunction. PATIENTS AND METHODS: A large cardiovascular data- base including pre-, peri- and postoperative serum creatinine concentrations from 2214 consecutive cardiac surgery patients was analyzed. RESULTS: Sixty-nine patients developed postoperative renal dysfunction, defined as at least a 15 mL/min decline in the creatinine clearance rate resulting in a value of less than 40 mL/min. These patients were significantly older, and had a higher incidence of previous cardiac surgery, diabetes, obesity, peripheral vascular disease, hypertension and poor ventricular function. Postoperatively, these patients had a higher occurrence of low output syndrome and myocardial infarction. Stepwise logistic regression predictors of postoperative renal dysfunction included the following: postoperative low output syndrome; repeat cardiac surgery; being older than 65 years; having diabetes; having poor left ventricular function; and having had valve surgery. Preoperative renal dysfunction (defined as a creatinine clearance of less than 40 mL/min) was not found to be one of the predictors. The mean creatinine concentrations of patients with mild postoperative renal dysfunction (defined as a creatinine concentration of less than 200 mmol/L on the fourth or fifth postoperative day) decreased significantly at the fifth postoperative day, while that of patients with severe postoperative renal dysfunction rose to a mean of 300 mmol/L six months postoperatively. The incidence of late dialysis (defined as a need for dialysis after postoperative day 10) approached 30% among patients with severe postoperative renal dysfunction and only 2% among patients with mild postoperative renal dysfunction. The early mortality rate (during the first postoperative month) was similar in both groups and approached 30%. CONCLUSIONS: Patients who develop postoperative renal dysfunction have a high mortality rate. Postoperative low cardiac output is the most important cause of postoperative renal dysfunction and, therefore, should be avoided. Patients with creatinine concentrations of less than 200 mmol/L at postoperative day 4 or 5 will probably resume normal renal function. Patients with creatinine concentrations of more than 200 mmol/L at days 4 and 5 have a 30% chance of needing long term dialysis.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.279
Threshold uncertainty score0.775

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.035
GPT teacher head0.266
Teacher spread0.231 · 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

Citations20
Published2001
Admission routes1
Has abstractyes

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