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Patent foramen ovale does not have a negative impact on early outcomes in patients undergoing liver transplantation

2010· article· en· W1939711903 on OpenAlexaff
Ana Carolina Alba, F. Verocai Flaman, John Granton, D. Delgado

Bibliographic record

VenueClinical Transplantation · 2010
Typearticle
Languageen
FieldMedicine
TopicCardiovascular and Diving-Related Complications
Canadian institutionsToronto General Hospital
Fundersnot available
KeywordsMedicineLiver transplantationPatent foramen ovaleLiver diseaseModel for End-Stage Liver DiseaseTransplantationSurgeryIncidence (geometry)Internal medicineGastroenterology

Abstract

fetched live from OpenAlex

OBJECTIVE: To identify the impact of the presence of patent foramen ovale (PFO) in patients undergoing liver transplantation. METHODS: Twenty-seven pre-liver transplant patients who had a PFO (PFO group) were identified and compared with 61 patients without PFO (NoPFO group). Patients were matched according to age, gender and cause of liver disease. The diagnosis of PFO was made by transthoracic echocardiography prior to liver transplantation. Patient baseline characteristics and complications during the early post-transplant period were analyzed. RESULTS: The mean age in the PFO group was 47 ± 14 (range 18-68) yr and 50 ± 11 (range 12-65) yr in the NoPFO group. The PFO group had a mean model for end-stage liver disease (MELD) score of 15 ± 10 whereas in the NoPFO group the MELD score was 19 ± 10 (p = 0.08). There were non-significant differences in echocardiographic parameters between groups. Duration of mechanical ventilation and the incidence of neurological complications were similar. Thirty-day mortality rate was similar in both groups; only one patient in the NoPFO group died within the first 30 days post-transplantation. CONCLUSIONS: The presence of PFO in patients with end-stage liver disease undergoing liver transplantation does not appear to affect patient outcomes during the peri-operative period.

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 score0.009
Threshold uncertainty score0.623

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
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)0.0000.000

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 head0.050
GPT teacher head0.344
Teacher spread0.294 · 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

Citations22
Published2010
Admission routes1
Has abstractyes

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