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Persistent Postoperative Cognitive Decline?

2016· article· en· W2283076615 on OpenAlexaboutno aff
Michael S. Avidan, Alex S. Evers

Bibliographic record

VenueAnesthesiology · 2016
Typearticle
Languageen
FieldMedicine
TopicIntensive Care Unit Cognitive Disorders
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineCognitive declinePostoperative cognitive dysfunctionCognitionIntensive care medicineInternal medicinePsychiatryDementiaDisease

Abstract

fetched live from OpenAlex

Complex Information for Anesthesiologists Presented Quickly and ClearlyThe hierarchy of evidence showing studies that have found a link (top right) and have not found a link (top left) between surgery or anesthesia and dementia or postoperative cognitive decline (POCD) lasting longer than 6 months. More details and a complete list of the studies referenced can be found in the Editorial View by Avidan and Evers in this issue of Anesthesiology.1 A hypothetical preoperative (Preop) and postoperative (Postop) cognitive trajectory (bottom panel) is illustrated that depicts the course of cognitive decline over time. If a surgical episode occurs at a time when the rate of cognitive decline is already accelerating, postoperative cognitive decline that was already predestined may be mistakenly attributed to surgery. CSHA = Canadian Study on Health and Aging. Infographic concept and data provided by Michael S. Avidan and Alex S. Evers, Department of Anesthesiology, Washington University School of Medicine. Illustration by Annemarie Johnson, Vivo Visuals.

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)0.004
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 score0.112
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.004
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)0.0010.001

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 head0.020
GPT teacher head0.282
Teacher spread0.262 · 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
Published2016
Admission routes1
Has abstractyes

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