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Record W2012064941 · doi:10.1186/s12916-014-0146-x

Two distinct Do-Not-Resuscitate protocols leaving less to the imagination: an observational study using propensity score matching

2014· article· en· W2012064941 on OpenAlexaff
Yen‐Yuan Chen, Nahida H. Gordon, Alfred F. Connors, Allan Garland, Shan‐Chwen Chang, Stuart J. Youngner

Bibliographic record

VenueBMC Medicine · 2014
Typearticle
Languageen
FieldMedicine
TopicCardiac Arrest and Resuscitation
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsMedicineDo not resuscitatePsychological interventionObservational studyDo Not Resuscitate OrderPropensity score matchingIntensive care unitLogistic regressionEmergency medicineConfoundingIntensive careIntensive care medicineInternal medicineNursing

Abstract

fetched live from OpenAlex

BACKGROUND: Do-Not-Resuscitate (DNR) patients tend to receive less medical care after the order is written. To provide a clearer approach, the Ohio Department of Health adopted the Do-Not-Resuscitate law in 1998, indicating two distinct protocols of DNR orders that allow DNR patients to choose the medical care: DNR Comfort Care (DNRCC), implying DNRCC patients receive only comfort care after the order is written; and DNR Comfort Care-Arrest (DNRCC-Arrest), implying that DNRCC-Arrest patients are eligible to receive aggressive interventions until cardiac or respiratory arrest. The aim of this study was to examine the medical care provided to patients with these two distinct protocols of DNR orders. METHODS: Data were collected from August 2002 to December 2005 at a medical intensive care unit in a university-affiliated teaching hospital. In total, 188 DNRCC-Arrest patients, 88 DNRCC patients, and 2,051 non-DNR patients were included. Propensity score matching using multivariate logistic regression was used to balance the confounding variables between the 188 DNRCC-Arrest and 2,051 non-DNR patients, and between the 88 DNRCC and 2,051 non-DNR patients. The daily cost of intensive care unit (ICU) stay, the daily cost of hospital stay, the daily discretionary cost of ICU stay, six aggressive interventions, and three comfort care measures were used to indicate the medical care patients received. The association of each continuous variable and categorical variable with having a DNR order written was analyzed using Student's t-test and the χ2 test, respectively. The six aggressive interventions and three comfort care measures performed before and after the order was initiated were compared using McNemar's test. RESULTS: DNRCC patients received significantly fewer aggressive interventions and more comfort care after the order was initiated. By contrast, for DNRCC-Arrest patients, the six aggressive interventions provided were not significantly decreased, but the three comfort care measures were significantly increased after the order was initiated. In addition, the three medical costs were not significantly different between DNRCC and non-DNR patients, or between DNRCC-Arrest and non-DNR patients. CONCLUSIONS: When medical care provided to DNR patients is clearly indicated, healthcare professionals will provide the medical care determined by patient/surrogate decision-makers and healthcare professionals, rather than blindly decreasing medical care.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.557

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.282
GPT teacher head0.422
Teacher spread0.140 · 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 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

Citations14
Published2014
Admission routes1
Has abstractyes

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