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Record W2946251950 · doi:10.24908/pocus.v1i3.13258

Case File: Rapid Diagnosis of Pericardial Effusion

2016· article· en· W2946251950 on OpenAlexvenueno aff
Jeffrey S. Wilkinson, Amer M. Johri

Bibliographic record

VenuePOCUS Journal · 2016
Typearticle
Languageen
FieldMedicine
TopicPericarditis and Cardiac Tamponade
Canadian institutionsnot available
Fundersnot available
KeywordsPericardial effusionMedicinePericardiocentesisCardiac tamponadeParasternal lineTamponadeVentricleCardiologyEmergency departmentRadiologyPericardiumInternal medicineEffusionHeart diseaseSurgery

Abstract

fetched live from OpenAlex

Mr. DB was a 95 year old man who presented to the emergency department with dyspnea progressing over the last 3 months. Chest x-ray demonstrated an enlarged cardiac silhouette.
 He had a past medical history significant for coronary artery disease, hypertension and a lobectomy due to tuberculosis.
 A point of care cardiac ultrasound was conducted by an internal medicine resident as part of his physical examination in the emergency department. A large pericardial effusion was found. There were no clinical signs of tamponade.
 Video 1 (online supplement; Figure 1) demonstrates a parasternal long axis view with the pericardial effusion noted to be posterior to the left ventricle in this view. Video 2 (online supplement; Figure 2) is a short axis view of the heart which is showing that the effusion is surrounding the heart. Video 3 and 4 (online supplements; Figures 3 & 4) demonstrates that the pericardial effusion is present significantly surrounding the apex as well. An echocardiogram confirmed the POCUS findings and cardiology was consulted to conduct a pericardiocentesis, following which the patient’s symptoms resolved. The effusion was thought to be chronic and transudative. In this case, the use of POCUS at the bedside allowed for rapid detection of a large pericardial effusion and subsequent treatment.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.693
Threshold uncertainty score0.991

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)0.0100.000

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 head0.014
GPT teacher head0.256
Teacher spread0.242 · 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.

Study designNot applicable
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

Citations0
Published2016
Admission routes1
Has abstractyes

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