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Record W1989028508 · doi:10.1503/cmaj.1041606

Rofecoxib (Vioxx) voluntarily withdrawn from market

2004· article· en· W1989028508 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueCanadian Medical Association Journal · 2004
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicPharmaceutical Economics and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineSepsisSOFA scoreInternal medicinePediatricsEmergency medicine

Abstract

fetched live from OpenAlex

<h3>ABSTRACT</h3> <h3>Objectives</h3> To compare the accuracy of the SOFA and APACHE II scores in predicting short-term mortality among ICU patients with sepsis in an LMIC. <h3>Design</h3> A multicentre, cross-sectional study. <h3>Setting</h3> A total of 15 adult ICUs from 14 hospitals, of which 5 are central hospitals, and 9 are provincial, district, or private hospitals, throughout Vietnam. <h3>Participants</h3> We included all patients aged ≥18 years who were admitted to ICUs for sepsis and who were still in ICUs from 00:00 hour to 23:59 hour of the study days (i.e., 9th January, 3rd April, 3rd July, and 9th October of 2019). <h3>Main outcome measures</h3> Short-term mortality was the main outcome, including hospital and ICU mortality. <h3>Results</h3> Of 252 patients, 40.1% died in hospitals, and 33.3% died in ICUs. SOFA (cut-off value ≥7.5; AUROC: 0.688 [95% CI: 0.618-0.758]; p&lt;0.001) and APACHE II score (cut-off value ≥20.5; AUROC: 0.689 [95% CI: 0.622-0.756]; p&lt;0.001) both had a poor discriminatory ability for predicting hospital mortality. However, the discriminatory ability for predicting ICU mortality of SOFA (cut-off value ≥9.5; AUROC: 0.713 [95% CI: 0.643-0.783]; p&lt;0.001) was better and greater than that of APACHE II score (cut-off value ≥18.5; AUROC: 0.672 [95% CI: 0.603-0.742]; p&lt;0.001). A SOFA score ≥8 (OR: 2.717; 95% CI: 1.371-5.382) and an APACHE II score ≥21 (OR: 2.668; 95% CI: 1.338-5.321) were independently associated with an increased risk of hospital mortality. Additionally, a SOFA score ≥10 (OR: 2.194; 95% CI: 1.017-4.735) was an independent predictor of ICU mortality, in contrast to an APACHE II score ≥19, for which this role did not. <h3>Conclusions</h3> Both SOFA and APACHE II scores were worthwhile in predicting hospital and ICU mortality among ICU patients with sepsis. However, due to good discrimination for predicting ICU mortality, the SOFA was preferable to the APACHE II score in predicting short-term mortality. <h3>Strengths and limitations of this study</h3> An advantage of the present study was data from multicentre, which had little missing data. Due to the absence of a national registry of intensive care units (ICUs) to allow systematic recruitment of units, we used a snowball method to identify suitable units, which might have led to the selection of centres with a greater interest in sepsis management. Due to the study’s real-world nature, we did not make a protocol for microbiological investigations. Moreover, we mainly evaluated resources utilized in ICUs; therefore, the data detailing the point-of-care testing and life-sustaining treatments were not available. To improve the feasibility of conducting the study in busy ICUs, we opted not to collect data on antibiotic resistance and appropriateness. The sample size was relatively small, which might have led to overfitting in the multivariable prediction model.

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.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.498
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0340.003

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 head0.015
GPT teacher head0.229
Teacher spread0.214 · 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