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Modification of cardiovascular risk in hemodialysis patients: An evidence‐based review

2007· review· en· W2161118320 on OpenAlexvenueno aff
David W. Johnson, Ann-Maree S. Craven, Nicole M. Isbel

Bibliographic record

VenueHemodialysis International · 2007
Typereview
Languageen
FieldMedicine
TopicDialysis and Renal Disease Management
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineDialysisPopulationIntensive care medicineKidney diseaseInternal medicineDiseaseHemodialysisClinical trialRisk factor

Abstract

fetched live from OpenAlex

Cardiovascular disease accounts for 40% to 50% of deaths in dialysis populations. Overall, the risk of cardiac mortality is 10-fold to 20-fold greater in dialysis patients than in age and sex-matched controls without chronic kidney disease. The aim of this paper is to review critically the evidence that cardiac outcomes in dialysis patients are modified by cardiovascular risk factor interventions. There is limited, but as yet inconclusive controlled trial evidence that cardiovascular outcomes in dialysis populations may be improved by antioxidants (vitamin E or acetylcysteine), ensuring that hemoglobin levels do not exceed 120 g/L (especially in the setting of known cardiovascular disease), prescribing carvedilol in the setting of dilated cardiomyopathy, and by using cinacalcet in uncontrolled secondary hyperparathyroidism. Similarly, there are a number of negative controlled trials, which have demonstrated that statins, high-dose folic acid, angiotensin-converting enzyme inhibitors, multiple risk factor intervention via multidisciplinary clinics, and high-dose or high-flux dialysis are ineffective in preventing cardiovascular disease. Although none of these studies could be considered conclusive, the negative trials to date should raise significant concerns about the heavy reliance of current clinical practice guidelines on extrapolation of findings from cardiovascular intervention trials in the general population. It may be that cardiovascular disease in dialysis populations is less amenable to intervention, either because of the advanced stage of chronic kidney disease or because the pathogenesis of cardiovascular disease in dialysis patients is different from that in the general population. Large, well-conducted, multicenter randomized-controlled trials in this area are urgently required.

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)0.003
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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.972
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0040.005
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.094
GPT teacher head0.375
Teacher spread0.280 · 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 designOther design
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

Citations87
Published2007
Admission routes1
Has abstractyes

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