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Record W3122734461 · doi:10.6002/ect.2020.0292

Genitourinary Interventions in Autosomal Dominant Polycystic Kidney Disease: Clinical Recommendations for Urologic and Transplant Surgeons

2021· review· en· W3122734461 on OpenAlexaff
Alissar El Chediak, Jad A. Degheili, Raja B. Khauli

Bibliographic record

VenueExperimental and Clinical Transplantation · 2021
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic and Kidney Cyst Diseases
Canadian institutionsChildren's Hospital of Eastern Ontario
Fundersnot available
KeywordsMedicineNephrectomyAutosomal dominant polycystic kidney diseaseDiseasePolycystic kidney diseaseGenitourinary systemNephrologyBilateral NephrectomyIntensive care medicinePsychological interventionKidneyKidney transplantationCystSurgeryTransplantationInternal medicine

Abstract

fetched live from OpenAlex

Autosomal dominant polycystic kidney disease is the fourth most common single cause of end-stage renal disease worldwide with both renal and extrarenal manifestations, resulting in significant morbidity. Approaches to the management of this disease vary widely, with no broadly accepted practice guidelines. Herein, we reviewed the various surgical and interventional management options that are targeted toward treating the symptoms or addressing the resulting kidney failure. Novel treatment modalities such as celiac plexus blockade and renal denervation appear to be promising in pain relief; however, further studies are lacking. Renal cyst decortication seems to have a higher success rate in targeting cyst-related pain compared with aspiration only. In terms of requiring major surgical intervention, such as need and timing of native nephrectomy, there are several considerations when deciding on transplantation with or without a pretransplant native nephrectomy. Patients who are not candidates for native nephrectomy may consider transcatheter arterial embolization. Based on our review of the contemporary indications for genitourinary interventions in the management of autosomal dominant polycystic kidney disease, we propose an algorithm that depicts the decision-making process on assessing the indications and timing of native nephrectomy in patients with end-stage renal disease awaiting transplant.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.939
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
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 head0.090
GPT teacher head0.432
Teacher spread0.342 · 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
GenreReview

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

Citations5
Published2021
Admission routes1
Has abstractyes

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