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Record W113062762

The influence of DNR orders on patient care in adult ICUs: a review of the evidence.

2002· review· en· W113062762 on OpenAlexaff
Chiu‐Wing Winnie Chu, Patricia Hynes-Gay

Bibliographic record

VenuePubMed · 2002
Typereview
Languageen
FieldPsychology
TopicHealthcare Decision-Making and Restraints
Canadian institutionsMount Sinai Hospital
Fundersnot available
KeywordsCINAHLMedicineIntensive careMEDLINEDo not resuscitateIntensive care unitIntensive care medicineCritical care nursingPsychological interventionEnd-of-life careHealth careMechanical ventilationCardiopulmonary resuscitationResuscitationNursingPalliative careEmergency medicinePsychiatry
DOInot available

Abstract

fetched live from OpenAlex

BACKGROUND: Although do-not-resuscitate (DNR) orders have been used in health care for many years, there is controversy about their use and the implications for patient care. A common perception in the intensive care unit (ICU) setting is that life-sustaining interventions such as dialysis or mechanical ventilation may no longer be provided or should be withdrawn on patients who are assigned DNR status. In order to gain insight into the impact of DNR orders on the care provided to adult patients in the ICU, a review of the research conducted on this topic within the last decade was undertaken. OBJECTIVE: To provide an integrated review of recent research examining the effects of DNR orders on the care of adult ICU patients. METHODS: Two large databases, CINAHL and MEDLINE, were used for the search as well as the reference lists from relevant research articles. The search terms used were: DNR orders in adult ICUs, resuscitation orders, critical care, and nursing and/or medical care provided to these patients. Studies were not limited to any one specific research design. The search was restricted to research conducted over the last decade. RESULTS: Five studies were found that met the search criteria. CONCLUSIONS: While the care that critically ill adult patients receive in ICUs is, in some way, influenced by DNR orders, there is no evidence that patients are abandoned as a result. Given the inconsistency in the findings of the five studies and certain weaknesses in methodology, it is not possible to identify a direct impact of DNR orders on patients care at this time. Further investigation is needed.

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)0.001
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.966
Threshold uncertainty score0.708

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.088
GPT teacher head0.391
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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
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

Citations4
Published2002
Admission routes1
Has abstractyes

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