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Record W4391192175 · doi:10.58837/chula.cmj.63.1.2

Effect of preoperative cognitive dysfunction on postoperative outcomes in cardiac surgery

2019· article· en· W4391192175 on OpenAlexaboutno aff
Anantachote Vimuktanandana

Bibliographic record

VenueChulalongkorn Medical Journal · 2019
Typearticle
Languageen
FieldMedicine
TopicCardiac, Anesthesia and Surgical Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsPostoperative cognitive dysfunctionMedicineCardiac surgeryCognitionSurgeryPsychiatry

Abstract

fetched live from OpenAlex

Background: Preoperative cognitive dysfunction (PreOCD) has not been well described as a risk factor forpoor outcomes in cardiac surgery. This study was aimed to demonstrate the effects of PreOCD on postoperative outcomes in cardiac surgery.Methods: One hundred adult patients undergoing elective open cardiac surgery at King ChulalongkornMemorial Hospital were recruited. The Montreal Cognitive Assessment (MoCA) was used to evaluate cognitivefunction the evening before surgery and defined a score of less than 26 as cognitive impairment. We compared postoperative outcome data between patients with PreOCD group and no PreOCD group.Results: One patient in PreOCD group withdrew from our study. Sixty nine out of 99 patients (68.31%) had PreOCD. In the PreOCD group, the postoperative mechanical ventilation period was significantly longer (15.9 gif.latex?\pm 26.6 vs. 7.4 gif.latex?\pm 8.76 hours, gif.latex?\rho = 0.018), ICU stay was significantly longer (39.9 gif.latex?\pm 43.7 vs. 27.6 gif.latex?\pm 15.0 hours, gif.latex?\rho = 0.039), and cost of hospital stay was significantly higher (13,540 gif.latex?\pm 6,355 vs. 11,264 gif.latex?\pm 5,229 baht, gif.latex?\rho = 0.014). However, the length of hospital stay was not significantly different (10.1 gif.latex?\pm 3.8 vs. 9.3 gif.latex?\pm 4.4 days, gif.latex?\rho = 0.384).Conclusions: We demonstrated the adverse effects of PreOCD on patients outcomes after cardiac surgery.Identifying PreOCD may be useful in risk stratification during preoperative assessment to improve surgicaloutcomes.

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)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.008
GPT teacher head0.282
Teacher spread0.274 · 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

Citations2
Published2019
Admission routes1
Has abstractyes

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