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Participação da família no processo decisório de limitação de suporte de vida: paternalismo, beneficência e omissão

2007· article· pt· W2002137500 on OpenAlexaff
Patrícia M. Lago, Daniel Garros, Jefferson Pedro Piva

Bibliographic record

VenueRevista Brasileira de Terapia Intensiva · 2007
Typearticle
Languagept
FieldMedicine
TopicPalliative and Oncologic Care
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsIntensivistMedicineHumanitiesNursingIntensive careIntensive care medicine

Abstract

fetched live from OpenAlex

BACKGROUND AND OBJECTIVES: To analyze and discuss the medical aspects related to the family involvement in the decision making process regarding end of life care to children admitted to the pediatric intensive care unit (PICU). CONTENTS: The authors selected articles on end-of-life care published during the last years searching the PubMed, MedLine and LILACS database, with special interest on studies of death conducted in pediatric intensive care units in Brazil, Latin America, Europe and North America, using the following keywords: death, bioethics, PICU, decision-making, terminal care, parents interview and life support limitation (LSL). CONCLUSIONS: Several studies have demonstrated the relevance of the family participation in the decision making process regarding LSL. In our region the family participation in this process is not stimulated and valued, ranging from 20%-55%. The authors present a practical sequence for discussing and defining LSL with the families. Despite of the family participation in the decision making process for LSL be legally, morally and ethically accepted in developed countries, this approach is adopted in a very few cases in our region. To explain this difficulty observed among the Brazilian pediatric intensivist, some studies should be conducted in our region.

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)0.012
metaresearch head score (Gemma)0.036
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.065

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.036
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.003
Scholarly communication0.0030.002
Open science0.0010.002
Research integrity0.0010.001
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 head0.071
GPT teacher head0.357
Teacher spread0.286 · 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".

Quick stats

Citations5
Published2007
Admission routes1
Has abstractyes

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