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Record W2774071133 · doi:10.1183/13993003.01611-2017

Prognostic value of right ventricular dilatation in patients with low-risk pulmonary embolism

2017· article· en· W2774071133 on OpenAlexaff
Benoît Côté, David Jiménez, Benjamin Planquette, Anne Roche, Jonathan Marey, Jean Pastré, Guy Meyer, Olivier Sanchez

Bibliographic record

VenueEuropean Respiratory Journal · 2017
Typearticle
Languageen
FieldMedicine
TopicVenous Thromboembolism Diagnosis and Management
Canadian institutionsUniversité LavalHôpital de l'Enfant-Jésus
Fundersnot available
KeywordsMedicinePulmonary embolismCardiologyValue (mathematics)Internal medicineRadiology

Abstract

fetched live from OpenAlex

The prognosis of multidetector computed tomography (MDCT) assessed right ventricular dilatation (RVD) is unclear in patients with pulmonary embolism (PE) and a simplified Pulmonary Embolism Severity Index (sPESI) of 0. We investigated in these patients whether MDCT-assessed RVD, defined by a right to left ventricular ratio (RV/LV) ≥0.9 or ≥1.0, is associated with worse outcomes. We combined data from three prospective cohorts of patients with PE. The main study outcome was the composite of 30-day all-cause mortality, haemodynamic collapse or recurrent PE in patients with sPESI of 0. Among 779 patients with a sPESI 0, 420 (54%) and 299 (38%) had a RV/LV ≥0.9 and ≥1.0 respectively. No difference in primary outcome was observed, 0.95% (95% CI 0.31–2.59) versus 0.56% (95% CI 0.10–2.22; p=0.692) and 1.34% (95% CI 0.43–3.62) versus 0.42% (95% CI 0.07–1.67; p=0.211) with RV/LV ≥0.9 and ≥1.0 respectively. Increasing the RV/LV threshold to ≥1.1, the outcome occurred more often in patients with RVD (2.12%, 95% CI 0.68–5.68 versus 0.34%, 95% CI 0.06–1.36; p=0.033). MDCT RV/LV ratio of ≥0.9 and ≥1.0 in sPESI 0 patients is frequent but not associated with a worse prognosis but higher cut-off values might be associated with worse outcome in these patients.

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)0.000
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 score0.010
Threshold uncertainty score0.478

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.008
GPT teacher head0.233
Teacher spread0.225 · 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

Citations72
Published2017
Admission routes1
Has abstractyes

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