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Record W2587025365 · doi:10.1097/md.0000000000005924

Antihypertensive medications and risk of death and hospitalizations in US hemodialysis patients

2017· article· en· W2587025365 on OpenAlexaff
Tariq Shafi, Stephen M. Sozio, Jason Luly, Karen Bandeen‐Roche, Wendy L. St. Peter, Patti L. Ephraim, Aidan McDermott, Charles A. Herzog, Deidra C. Crews, Julia J. Scialla, Navdeep Tangri, Dana C. Miskulin, Wieneke M. Michels, Bernard G. Jaar, Philip G. Zager, Klemens B. Meyer, Albert W. Wu, L. Ebony Boulware

Bibliographic record

VenueMedicine · 2017
Typearticle
Languageen
FieldMedicine
TopicBlood Pressure and Hypertension Studies
Canadian institutionsSeven Oaks General HospitalUniversity of Manitoba
FundersNational Institute of Diabetes and Digestive and Kidney DiseasesUniversity of California, San FranciscoCleveland Clinic FoundationCleveland ClinicUniversity of MiamiJohns Hopkins UniversityAgency for Healthcare Research and QualityNational Institutes of HealthNierstichtingU.S. Department of Health and Human Services
KeywordsMedicineHemodialysisHazard ratioCohortInternal medicineDialysisProportional hazards modelCohort studyConfidence interval

Abstract

fetched live from OpenAlex

Antihypertensive medications are commonly prescribed to hemodialysis patients but the optimal regimens to prevent morbidity and mortality are unknown. The goal of our study was to compare the association of routinely prescribed antihypertensive regimens with outcomes in US hemodialysis patients.We used 2 datasets for our analysis. Our primary cohort (US Renal Data System [USRDS]) included adult patients initiating in-center hemodialysis from July 1, 2006 to June 30, 2008 (n = 33,005) with follow-up through December 31, 2009. Our secondary cohort included adult patients from Dialysis Clinic, Inc. (DCI), a national not-for-profit dialysis provider, initiating in-center hemodialysis from January 1, 2003 to June 30, 2008 (n = 11,291) with follow-up through December 31, 2008. We linked the USRDS cohort with Medicare part D prescriptions-fill data and the DCI cohort with USRDS data. Unique aspect of USRDS cohort was pharmacy prescription-fill data and for DCI cohort was detailed clinical data, including blood pressure, weight, and ultrafiltration. We classified prescribed antihypertensives into the following mutually exclusive regimens: β-blockers, renin-angiotensin system blocking drugs-containing regimens without a β-blocker (RAS), β-blocker + RAS, and others. We used marginal structural models accounting for time-updated comorbidities to quantify each regimen's association with mortality (both cohorts) and cardiovascular hospitalization (DCI-Medicare Subcohort).In the USRDS and DCI cohorts there were 9655 (29%) and 3200 (28%) deaths, respectively. In both cohorts, RAS compared to β-blockers regimens were associated with lower risk of death; (hazard ratio [HR]) (95% confidence interval [CI]) for all-cause mortality, (0.90 [0.82-0.97] in USRDS and 0.87 [0.76-0.98] in DCI) and cardiovascular mortality (0.84 [0.75-0.95] in USRDS and 0.88 [0.71-1.07] in DCI). There was no association between antihypertensive regimens and the risk of cardiovascular hospitalizations.In hemodialysis patients undergoing routine care, renin-angiotensin system blocking drugs-containing regimens were associated with a lower risk of death compared with β-blockers-containing regimens but there was no association with cardiovascular hospitalizations. Pragmatic clinical trials are needed to specifically examine the effectiveness of these commonly used antihypertensive regimens in dialysis patients.

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)0.001
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 score0.006
Threshold uncertainty score0.254

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.020
GPT teacher head0.278
Teacher spread0.258 · 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

Citations14
Published2017
Admission routes1
Has abstractyes

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