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Record W2947593637 · doi:10.1186/s12882-018-1191-z

Bilateral renal artery stenosis as a cause of refractory intradialytic hypertension in a patient with end stage renal disease

2019· article· en· W2947593637 on OpenAlexaff
Zachary Wolfmueller, Kunal Goyal, Bhanu Prasad

Bibliographic record

VenueBMC Nephrology · 2019
Typearticle
Languageen
FieldMedicine
TopicRenal and Vascular Pathologies
Canadian institutionsRegina General HospitalUniversity of Regina
Fundersnot available
KeywordsMedicineFibromuscular dysplasiaCardiologyInternal medicineAngioplastyNephrologyDialysisRenal artery stenosisEnd stage renal diseaseRenal arteryStenosisBlood pressureStroke (engine)Renovascular hypertensionHemodialysisKidney

Abstract

fetched live from OpenAlex

BACKGROUND: We report a 61-year-old female with end-stage renal disease (ESRD) secondary to polycystic kidney disease (PKD) complicated by intradialytic hypertension (IDH). Increased sympathetic drive leading to increased stroke volume and/or vasoconstriction with an inappropriate increase in peripheral vascular resistance (PVR) has been postulated to be the cause of IDH. CASE PRESENTATION: Attempts to control her blood pressure by reducing her goal weight; increasing dialysis times/ frequency and decreasing her sodium concentrate in the dialysis fluid were unsuccessful. Acting upon literature evidence suggesting renovascular disease as a cause of IDH, we referred her to an interventional radiologist for evaluation of the renal arteries. Selective angiogram of both renal arteries revealed right sided atherosclerotic renal artery stenosis (RAS) treated with insertion of a balloon mounted 6 mm stent and left sided fibromuscular dysplasia (FMD) treated with 5 mm balloon angioplasty. CONCLUSIONS: This case highlights the need for interrogating the renal arteries radiologically for a potential cause in difficult to control IDH and comments on the association between PKD and FMD that has not yet been reported.

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 score0.329
Threshold uncertainty score0.486

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)0.0000.000

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 head0.021
GPT teacher head0.238
Teacher spread0.217 · 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

Citations3
Published2019
Admission routes1
Has abstractyes

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