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Record W4383535946 · doi:10.3390/diagnostics13132304

Multidetector CT Imaging Biomarkers as Predictors of Prognosis in Shock: Updates and Future Directions

2023· review· en· W4383535946 on OpenAlexaff
Tullio Valente, Giorgio Bocchini, Candida Massimo, Gaetano Rea, Roberta Lieto, Salvatore Guarino, Emanuele Muto, Ahmad Abu-Omar, Mariano Scaglione, Giacomo Sica

Bibliographic record

VenueDiagnostics · 2023
Typereview
Languageen
FieldMedicine
TopicCardiac Arrest and Resuscitation
Canadian institutionsVancouver General Hospital
Fundersnot available
KeywordsMedicineShock (circulatory)RadiologySequelaResuscitationMultidetector computed tomographyCardiologyIntensive care medicineInternal medicineSurgeryComputed tomography

Abstract

fetched live from OpenAlex

A severe mismatch between the supply and demand of oxygen is the common sequela of all types of shock, which present a mortality of up to 80%. Various organs play a protective role in shock and contribute to whole-body homeostasis. The ever-increasing number of multidetector CT examinations in severely ill and sometimes unstable patients leads to more frequently encountered findings leading to imminent death, together called "hypovolemic shock complex". Features on CT include dense opacification of the right heart and major systemic veins, venous layering of contrast material and blood, densely opacified parenchyma in the right hepatic lobe, decreased enhancement of the abdominal organ, a dense pulmonary artery, contrast pooling in dependent lungs, and contrast stasis in pulmonary veins. These findings are biomarkers and prognostic indicators of paramount importance which stratify risk and improve patient outcomes. In this review, we illustrate the various CT patterns in shock and review the spectrum and prognostic significance of thoraco-abdominal vascular and visceral alarming signs of impending death with the intention of increasing awareness among radiologists and radiographers to prepare for immediate resuscitation when required.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.950
Threshold uncertainty score0.882

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
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 head0.017
GPT teacher head0.318
Teacher spread0.301 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations3
Published2023
Admission routes1
Has abstractyes

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