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Record W7064973704

Delirium Following Cardiac Surgery: Incidence and Risk Factors

2012· other· en· W7064973704 on OpenAlexaff

Bibliographic record

VenueMspace (University of Manitoba) · 2012
Typeother
Languageen
FieldEngineering
TopicSilicon and Solar Cell Technologies
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsDeliriumIncidence (geometry)Intensive care unitPerioperativeCohortRetrospective cohort studyCohort studyDemographics
DOInot available

Abstract

fetched live from OpenAlex

The purpose of this retrospective study was to determine the incidence of and risk factors for delirium in patients undergoing cardiac surgery. In addition, the influence of different post-surgical intensive care unit (leU) environments on delirium incidence was also studied. A detailed clinical report form was created to collect pertinent data in order to determine the effect of pre-operative, intraoperative and postoperative variables on delirium. Our study identified several risk factors for an increased incidence of delirium: hypertension, preoperative statin use, coronary artery bypass graft (CABO) surgery, aortic valve surgery, advanced age, prolonged bypass time and lowest serum sodium value during surgery. Extubation in the OR was associated with a lower incidence of delirium. In our comparison of the different ICU environments, in the first cohort (environment #1), 19.2% of patients experienced at least one episode of delirium. In the second cohort (environment #2; enhanced by privacy, reduced noise, and natural light), the incidence was reduced to I 1.1 % (p = 0.0582). As the two cohorts had otherwise similar demographics and other perioperative characteristics, it is likely that the reduced incidence of delirium was attributable to the enhanced ICU environment.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.437
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.012
GPT teacher head0.175
Teacher spread0.163 · 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.

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

Citations0
Published2012
Admission routes1
Has abstractyes

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