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Record W3016510004 · doi:10.14740/jmc3446

A Rare Case of Pericardial Decompression Syndrome in a Filipino Female Patient With Suspected Malignant Pericardial Effusion

2020· article· en· W3016510004 on OpenAlexvenueno aff
D L Villanueva, Joseph Justin Regalado, Celia Catherine C. Uy-Agbayani

Bibliographic record

VenueJournal of Medical Cases · 2020
Typearticle
Languageen
FieldMedicine
TopicPericarditis and Cardiac Tamponade
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePericardial effusionDecompressionSurgeryEffusionRadiology

Abstract

fetched live from OpenAlex

Pericardial decompression syndrome (PDS) is a rare, under-reported and potentially fatal complication of pericardial drainage characterized by paradoxical hemodynamic deterioration. The onset ranges from immediate to as long as 48 h post drainage. We present a case of a 51-year-old woman admitted due to progressive dyspnea. She was hemodynamically stable but with signs of cardiac tamponade. On two-dimensional echocardiography (2D-echo) there was a massive pericardial effusion in tamponade physiology. Immediate surgical drainage was done but intra-operatively there was depressed cardiac contractility necessitating inotropic support. Post-operative 2D-echo showed right ventricular (RV) and left ventricular (LV) systolic dysfunction. She was admitted in the intensive care unit (ICU) for 72 h. Repeat 2D-echo showed marked improvement in RV and LV systolic function. She was then discharged improved on the fifth hospital day. The pathophysiology of PDS is still not very clear. The simplest mechanism is that sudden removal of compressing pericardial fluid causes increased venous return with expansion of the RV at the expense of the LV leading to acute heart failure. There are no published studies to propose preventive measures and treatment remains supportive. There has been only one published case reported here in our country. We report this case of a patient who successfully recovered from PDS.

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: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.071
Threshold uncertainty score0.660

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0010.000

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 head0.017
GPT teacher head0.275
Teacher spread0.258 · 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 designCase report
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

Citations3
Published2020
Admission routes1
Has abstractyes

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