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Record W4410122402 · doi:10.24908/pocusj.v10i01.18260

The Prevalence of Systemic Venous Congestion Post Kidney Transplant Detected by Point of Care Ultrasound (POCUS)

2025· article· en· W4410122402 on OpenAlexvenueno aff
Santiago Beltramino, Amanda Bruno, D Alonso Fernández, Javier Walther, Gustavo Werber

Bibliographic record

VenuePOCUS Journal · 2025
Typearticle
Languageen
FieldMedicine
TopicRenal and Vascular Pathologies
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineVenous congestionTransplantationDialysisProspective cohort studyKidney transplantationInternal medicineSurgery

Abstract

fetched live from OpenAlex

Systemic venous congestion is a known cause of acute kidney injury (AKI), but its presence in kidney transplant patients has not been previously described in the literature. The objective of this study was to determine the prevalence of systemic venous congestion in recent kidney transplant recipients. We conducted a prospective, longitudinal, descriptive study including 30 adult patients during the first week post-renal transplant at the Instituto de Trasplante y Alta Complejidad in Buenos Aires, Argentina. Venous congestion was detected in 53% of patients (16/30), but only 13.3% (4/30) presented moderate to severe congestion. Pulmonary congestion was more frequent: 70% (21/30) of the patients presented some degree of pulmonary congestion, and 30% (9/30) had moderate or severe congestion. In the venous congestion group, 75% of patients developed delayed graft function (DGF) compared to 57% in the non-congestion group, although this difference was not statistically significant (p<0.3). Body weight and physical examination-two commonly used methods to guide decisions on dialysis initiation and fluid management-were found to be unreliable for assessing the true volume status. In conclusion, venous congestion was observed during the first week following renal transplantation; however, moderate to severe congestion was uncommon, affecting only 13.3% of patients. While DGF was more frequently observed in patients with congestion, a statistically significant association could not be established. Further studies with larger sample sizes are needed to better evaluate this potential relationship.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.362
Threshold uncertainty score0.253

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.005
GPT teacher head0.238
Teacher spread0.232 · 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 designBench or experimental
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

Citations1
Published2025
Admission routes1
Has abstractyes

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