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CPR for Patients Labeled DNR

2003· article· en· W2037653753 on OpenAlexaffabout
Niteesh K. Choudhry, Sujit Choudhry, Peter Singer

Bibliographic record

VenueAnnals of Internal Medicine · 2003
Typearticle
Languageen
FieldPsychology
TopicHealthcare Decision-Making and Restraints
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicine

Abstract

fetched live from OpenAlex

Letters21 October 2003CPR for Patients Labeled DNRNiteesh K. Choudhry, MD, FRCPC, Sujit Choudhry, LLB, LLM, and Peter A. Singer, MD, MPH, FRCPCNiteesh K. Choudhry, MD, FRCPCFrom University of Toronto, Toronto, Ontario M5G 2C4, Canada.Search for more papers by this author, Sujit Choudhry, LLB, LLMFrom University of Toronto, Toronto, Ontario M5G 2C4, Canada.Search for more papers by this author, and Peter A. Singer, MD, MPH, FRCPCFrom University of Toronto, Toronto, Ontario M5G 2C4, Canada.Search for more papers by this authorAuthor, Article, and Disclosure Informationhttps://doi.org/10.7326/0003-4819-139-8-200310210-00026 SectionsAboutFull TextPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinkedInRedditEmail IN RESPONSE:Resuscitation orders such as LATOs attempt to bridge the gap between patients' expressed preferences regarding resuscitation and their intended goals. Values-based advance directives highlight this distinction but often fail to provide clinicians with practical guidance on how to act upon their patients' values. In contrast, as pointed out by Dr. Gillick, intervention-specific directives are problematic because they fail to consider patients' goals and often require long lists of clinical scenarios. The LATO is a hybrid that lies between these extremes. By requiring clinicians to explain some of the complexities of resuscitation choices, the LATO clarifies patients' goals and ... Author, Article, and Disclosure InformationAffiliations: From University of Toronto, Toronto, Ontario M5G 2C4, Canada. PreviousarticleNextarticle Advertisement FiguresReferencesRelatedDetailsSee AlsoCPR for Patients Labeled DNR: The Role of the Limited Aggressive Therapy Order Niteesh K. Choudhry , Sujit Choudhry , and Peter A. Singer CPR for Patients Labeled DNR Muriel Gillick CPR for Patients Labeled DNR Jack P. Freer CPR for Patients Labeled DNR Susan B. LeGrand CPR for Patients Labeled DNR Bernard M. Karnath Metrics 21 October 2003Volume 139, Issue 8Page: 705-706KeywordsAdvanced cardiac life supportAlgorithmsCardiopulmonary resuscitationDecision makingDo not resuscitate ordersResuscitation ePublished: 21 October 2003 Issue Published: 21 October 2003 CopyrightCopyright © 2003 by American College of Physicians. All Rights Reserved.PDF DownloadLoading ...

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)0.021
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: none
Teacher disagreement score0.148
Threshold uncertainty score0.496

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.021
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0070.007
Insufficient payload (model declined to judge)0.1480.051

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 head0.112
GPT teacher head0.471
Teacher spread0.358 · 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

Citations2
Published2003
Admission routes2
Has abstractyes

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