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Record W4225275230 · doi:10.1177/08968608221096556

The rationale for the need to study sodium-glucose co-transport 2 inhibitor usage in peritoneal dialysis patients

2022· review· en· W4225275230 on OpenAlexaff
Megan Borkum, Abeed Jamal, Rajinder Singh, Adeera Levin

Bibliographic record

VenuePeritoneal Dialysis International · 2022
Typereview
Languageen
FieldMedicine
TopicDiabetes Treatment and Management
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsPeritoneal dialysisMedicineIntensive care medicineDialysisInternal medicineUrology

Abstract

fetched live from OpenAlex

. However, dialysis patients are at the highest risk of cardiovascular disease and would benefit most from effective cardioprotective therapies. There is emerging evidence from experimental studies and post hoc analyses of randomised clinical trials that SGLT2 inhibitors are well tolerated and may also be effective in preventing cardiovascular and mortality outcomes in patients with severe chronic kidney disease, including patients receiving dialysis. As such, extending the usage of SGLT2 inhibitors to dialysis patients could provide a major advancement in their care. Peritoneal dialysis (PD) patients have an additional unmet need for effective pharmacotherapy to preserve their residual kidney function (RKF), with its associated mortality benefits, and for treatment options that help reduce the risk of transfer to haemodialysis. Experimental data suggest that SGLT2 inhibitors, via various mechanisms, may preserve RKF and protect the peritoneal membrane. There is sound physiological rationale and an urgent clinical need to execute robust randomised control trials to study the use of SGLT2 inhibitors in PD patients to answer important questions of relevance to patients and healthcare systems.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.983
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.038
GPT teacher head0.338
Teacher spread0.300 · 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

Citations18
Published2022
Admission routes1
Has abstractyes

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