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Cognitive Function, Mental Health, and Health-related Quality of Life after Lung Transplantation

2014· article· en· W2051141093 on OpenAlexaboutno aff
David G. Cohen, Jason D. Christie, Brian J. Anderson, Joshua M. Diamond, Ryan Judy, Rupal Shah, Edward Cantu, Scarlett L. Bellamy, Nancy P. Blumenthal, Ejigayehu Demissie, Ramona O. Hopkins, Mark E. Mikkelsen

Bibliographic record

VenueAnnals of the American Thoracic Society · 2014
Typearticle
Languageen
FieldMedicine
TopicTransplantation: Methods and Outcomes
Canadian institutionsnot available
FundersNational Institute of Neurological Disorders and StrokeNational Heart, Lung, and Blood InstituteUniversity of PennsylvaniaNational Institutes of HealthVanderbilt University
KeywordsMedicineTransplantationCognitionDepression (economics)Quality of life (healthcare)AnxietyLung transplantationInternal medicinePsychiatry

Abstract

fetched live from OpenAlex

RATIONALE: Cognitive and psychiatric impairments are threats to functional independence, general health, and quality of life. Evidence regarding these outcomes after lung transplantation is limited. OBJECTIVES: Determine the frequency of cognitive and psychiatric impairment after lung transplantation and identify potential factors associated with cognitive impairment after lung transplantation. METHODS: In a retrospective cohort study, we assessed cognitive function, mental health, and health-related quality of life using a validated battery of standardized tests in 42 subjects post-transplantation. The battery assessed cognition, depression, anxiety, resilience, and post-traumatic stress disorder (PTSD). Cognitive function was assessed using the Montreal Cognitive Assessment, a validated screening test with a range of 0 to 30. We hypothesized that cognitive function post-transplantation would be associated with type of transplant, cardiopulmonary bypass, primary graft dysfunction, allograft ischemic time, and physical therapy post-transplantation. We used multivariable linear regression to examine the relationship between candidate risk factors and cognitive function post-transplantation. MEASUREMENTS AND MAIN RESULTS: Mild cognitive impairment (score, 18-25) was observed in 67% of post-transplant subjects (95% confidence interval [CI]: 50-80%) and moderate cognitive impairment (score, 10-17) was observed in 5% (95% CI, 1-16%) of post-transplant subjects. Symptoms of moderate to severe anxiety and depression were observed in 21 and 3% of post-transplant subjects, respectively. No transplant recipients reported symptoms of PTSD. Higher resilience correlated with less psychological distress in the domains of depression (P < 0.001) and PTSD (P = 0.02). Prolonged graft ischemic time was independently associated with worse cognitive performance after lung transplantation (P = 0.001). The functional gain in 6-minute-walk distance achieved at the end of post-transplant physical rehabilitation (P = 0.04) was independently associated with improved cognitive performance post-transplantation. CONCLUSIONS: Mild cognitive impairment was present in the majority of patients after lung transplantation. Prolonged allograft ischemic time may be associated with cognitive impairment. Poor physical performance and cognitive impairment are linked, and physical rehabilitation post-transplant and psychological resilience may be protective against the development of long-term impairment. Further study is warranted to confirm these potential associations and to examine the trajectory of cognitive function after lung transplantation.

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)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.119
GPT teacher head0.458
Teacher spread0.340 · 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 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".

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Citations75
Published2014
Admission routes1
Has abstractyes

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