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Record W2023599315 · doi:10.1081/cbi-200053576

Does Circadian and Seasonal Variation in Occurrence of Acute Aortic Dissection Influence in‐Hospital Outcomes?

2005· article· en· W2023599315 on OpenAlexaff
Rajendra H. Mehta, Roberto Manfredini, Eduardo Bossone, Stuart J. Hutchison, Arturo Evangelista, Benedetta Boari, Jeanna V. Cooper, Dean E. Smith, Patrick T. O’Gara, Dan Gilon, Linda Pape, Christoph Nienaber, Eric M. Isselbacher, Kim A. Eagle

Bibliographic record

VenueChronobiology International · 2005
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate Change and Health Impacts
Canadian institutionsSt. Michael's Hospital
Fundersnot available
KeywordsMorningEveningCircadian rhythmMedicineChronobiologyIncidence (geometry)Aortic dissectionInternal medicineSeasonalityDemographyBiologyAorta

Abstract

fetched live from OpenAlex

The risk of acute aortic dissection (AAD) exhibits chronobiological variations with peak onset in the morning and in winter. However, it is not known whether the time of day or season of the year of the AAD affects clinical outcomes. We studied 1,032 patients enrolled in the International Registry of Acute Aortic Dissection from January 1997 to December 2001. For circadian and seasonal analysis, the time and date of symptom onset were available for 741 and 1,007 patients, respectively, and were grouped into four 6h periods (morning, afternoon, evening, and night) and four seasons (winter, spring, summer, and autumn). The chi2 test for goodness of fit was used to evaluate non-uniformity of the time of day and time of year for critical in-hospital clinical events, including death. While highest incidence of AAD occurred in the morning and winter, clinical events (including mortality) were similar during the four different periods of the 24 h (chi2 = 1.9, p = 0.60) and seasonal (chi2 = 1.2, p = 0.75) periods.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.004
Threshold uncertainty score0.823

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0010.000

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 head0.010
GPT teacher head0.299
Teacher spread0.289 · 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

Citations55
Published2005
Admission routes1
Has abstractyes

Explore more

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