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Record W2323996025 · doi:10.1097/pra.0000000000000137

Key Role of Social Supports in a Cardiac Transplant Treatment Team

2016· review· en· W2323996025 on OpenAlexaff
Obianuju O. Berry, Carisa Kymissis

Bibliographic record

VenueJournal of Psychiatric Practice · 2016
Typereview
Languageen
FieldPsychology
TopicFamily Caregiving in Mental Illness
Canadian institutionsColumbia College
Fundersnot available
KeywordsMultidisciplinary teamMedicineDepression (economics)Multidisciplinary approachSocial supportAnxietyIntensive care medicinePsychiatryPsychologyNursingPsychotherapist

Abstract

fetched live from OpenAlex

Only a limited literature focuses on solid organ transplant outcomes using an integrated care approach connecting the transplant team with psychiatry, other medical specialties, and importantly, the patient's social supports. We present the case of a man with heart failure whom we treated for symptoms of anxiety and depression both precardiac and postcardiac transplant. The patient was managed by a multidisciplinary team for his complex medical, psychiatric, family, and social issues. Most notably, the role and involvement of his primary caregiver at home changed during the crucial period between his pretransplant evaluation and clinical care during the year following his cardiac transplant. Unfortunately our patient succumbed to a poor outcome both socially and medically, dying 1 year posttransplant. Our experience with this patient led us to explore the cardiac transplant presurgical and postsurgical assessment and management process, focusing on the key role of social support in the patient care team.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0020.002
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 head0.021
GPT teacher head0.371
Teacher spread0.350 · 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 designQualitative
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

Citations8
Published2016
Admission routes1
Has abstractyes

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