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Record W3135753556 · doi:10.1177/2374373521989250

Patient-Reported Cognitive Outcomes Following Cardiac Surgery: A Descriptive Review

2021· review· en· W3135753556 on OpenAlexaff
Amanda Robinson, Edith Pituskin, Colleen M. Norris

Bibliographic record

VenueJournal of Patient Experience · 2021
Typereview
Languageen
FieldMedicine
TopicIntensive Care Unit Cognitive Disorders
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsCognitionMedicineCardiac surgeryQuality of life (healthcare)Patient-reported outcomePopulationDescriptive statisticsIntervention (counseling)Physical therapySurgeryNursingPsychiatry

Abstract

fetched live from OpenAlex

A descriptive review was conducted to evaluate the evidence of cognitive patient-reported outcome measures (PROMs) following cardiac surgery. The search of electronic databases resulted in 400 unique manuscripts. Nine studies met the criteria to be part of the final review. Results of the review suggest that there are few validated PROMs that assess cognitive function in the cardiac surgical population. Furthermore, PROMs have not been used to assess overall cognitive function following cardiac surgery within the past decade. However, one domain of cognitive function-memory-was described, with up to half of patients reporting a decline postoperatively. Perceived changes in cognitive function may impact health-related quality of life and a patient's overall view of the success of their surgery. Early identification of cognitive changes measured with PROMs may encourage earlier intervention and improve patient-centered care. In clinical practice, nurses may be in the best position to administer PROMs preoperatively and postoperatively.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.024
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.011
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.024
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0110.013
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.069
GPT teacher head0.371
Teacher spread0.303 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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

Citations6
Published2021
Admission routes1
Has abstractyes

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