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Record W1972873769 · doi:10.1016/s1474-5151(09)60151-1

SP40 Potential Predictors of Seizure-Like Phenomena in Cardiac Surgery Patients

2009· article· en· W1972873769 on OpenAlexaboutno aff
Manzoor Parry, Monica Cleghorn, L Buck, S R Strachan

Bibliographic record

VenueEuropean Journal of Cardiovascular Nursing · 2009
Typearticle
Languageen
FieldMedicine
TopicCardiac, Anesthesia and Surgical Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineCardiac surgeryEpilepsy surgeryCardiologyIntensive care medicineEpilepsyInternal medicinePsychiatry

Abstract

fetched live from OpenAlex

Purpose: Propofol is a sedative-hypnotic that is widely used for anaesthesia and sedation in patients undergoing cardiac surgery. Despite its favourable characteristics, early clinical reports suggest a drug-induced excitation of the CNS, including seizure-like phenomena [SLP] in susceptible patients. SLP have been classified according to their occurrence during anaesthesia/sedation and according to their clinical presentation. The purpose of this retrospective descriptive study was to identify predictors of SLP in patients undergoing cardiac surgery. Methods: Chart reviews were undertaken for all cardiac surgery patients identified as having SLP from January 2000 to February 2008 at a single site in Ontario, Canada. Data abstraction was done by all authors, who read all relevant reports and assessed the adequacy of extracted data. Preoperative (age, sex, weight, height, BMI and comorbid factors), intraoperative (number of bypass grafts, number of arterial grafts, valve type, aortic cross clamping time and CPB duration), and early postoperative variables (haemodynamic indices, duration of tracheal intubation, inotropic/vasoconstrictive support and details of adverse events in the ICU) were included. Statistical analyses were undertaken using SPSS ® (version 15).

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)0.003
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 score0.811
Threshold uncertainty score0.763

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.004
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 head0.008
GPT teacher head0.210
Teacher spread0.201 · 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

Citations0
Published2009
Admission routes1
Has abstractyes

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