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Record W1975405805 · doi:10.1097/nhl.0b013e3181c1b542

Respecting Patient Autonomy Versus Protecting the Patient's Health

2009· article· en· W1975405805 on OpenAlexaff
James M. Badger, Rosalind Ekman Ladd, Paul S. Adler

Bibliographic record

VenueJONA s Healthcare Law Ethics and Regulation · 2009
Typearticle
Languageen
FieldHealth Professions
TopicEthics in medical practice
Canadian institutionsAdler
Fundersnot available
KeywordsAutonomyMedicineAspiration pneumoniaObligationDilemmaDutyHealth careNursingDistressDuty to protectMedical emergencyPneumoniaIntensive care medicineLaw

Abstract

fetched live from OpenAlex

A 74-year-old man with multiple chronic medical problems was hospitalized for respiratory distress. He experienced recurrent aspiration and required frequent suctioning and endotracheal intubation on several occasions. The patient was deemed competent and steadfastly refused feeding tube placement. The patient demanded that he be allowed to eat a normal diet despite being told that it could lead to his death. The patient wanted to go home, but there was no one there to care for him. Additionally, neither a nursing home nor hospice would accept him in his present condition. The case is especially interesting because of the symbolic value of food and the plight of the patient who has no alternative to hospitalization. The hospital staff experienced considerable stress at having to care for him. They were uncertain whether their obligation was to respect his autonomy and continue to provide food or to protect his health by avoiding aspiration, pneumonia, and possible death by denying him food. This ethical dilemma posed by the professionals' duty to do what is in the patient's best interest versus the patient's right to decide treatment serves as the focus for this case study. Ethical, legal, and healthcare practitioners' considerations are explored. The case study concludes with specific recommendations for treatment.

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)0.019
metaresearch head score (Gemma)0.011
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.881
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0190.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0160.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.018
Insufficient payload (model declined to judge)0.0000.000

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 head0.177
GPT teacher head0.508
Teacher spread0.331 · 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 designTheoretical or conceptual
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

Citations16
Published2009
Admission routes1
Has abstractyes

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