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Record W3032740180 · doi:10.1097/hco.0000000000000758

Review – current opinion in cardiology hypertension in chronic kidney disease

2020· article· en· W3032740180 on OpenAlexaff
Muhannad Alqudsi, Swapnil Hiremath, Juan Carlos Q. Velez

Bibliographic record

VenueCurrent Opinion in Cardiology · 2020
Typearticle
Languageen
FieldMedicine
TopicBlood Pressure and Hypertension Studies
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsMedicineKidney diseaseBlood pressureIntensive care medicineDialysisRandomized controlled trialPopulationInternal medicineDiseaseClinical trialCardiology

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: Hypertension is a major risk factor for cardiovascular disease, cerebrovascular events, and progression to end-stage kidney disease (ESKD). The kidneys play a causative role in hypertension, but they are also organs vulnerable to hypertensive injury. Thus far, goals for optimal blood pressure in chronic kidney disease (CKD) and ESKD patients are not fully elucidated. Herein, we critically review the existing evidence. RECENT FINDINGS: Large randomized controlled trials (RCTs) continue to be deemed as the best source of evidence to guide optimal blood pressure goals in CKD and ESKD patients. Despite recent advances, the growing body of literature does not permit drawing definitive conclusions. Few adequately powered RCTs have specifically assessed goals for treatment of hypertension in patients with CKD. The most recent large RCT in hypertension, the Systolic Blood Pressure Intervention Trial, included a subset of patients with CKD and provided some insights. For the ESKD population, trials to evaluate blood pressure goals are even more scarce. The Blood Pressure in Dialysis Trial was a relatively small pilot study that can be deemed as hypothesis generating. SUMMARY: Management of hypertension in CKD is essential for optimization of cardiovascular, cerebrovascular and renal outcomes. To date, the existing evidence does not fully clarify ideal targets for blood pressure control in this patient population.

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)0.001
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: Not applicable
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.238
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
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 head0.143
GPT teacher head0.375
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.

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

Citations7
Published2020
Admission routes1
Has abstractyes

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