Evidence map›Paper›PMID 34325668›Full record

ArticleBMC nephrology2021

Achieved blood pressure post-acute kidney injury and risk of adverse outcomes after AKI: A prospective parallel cohort study.

Ian McCoy, Sandeep Brar, Kathleen D Liu, Alan S Go, Raymond K Hsu, Vernon M Chinchilli, Steven G Coca, Amit X Garg, Jonathan Himmelfarb, T Alp Ikizler and 9 more

Open access · goldAbstract read
In one paragraph

Article in BMC nephrology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.7field-weighted citation impact, top 31% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 5 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

19 authors at 13 institutions in 2 countries.

Ian McCoyDivision of Nephrology, University of California, San Francisco School of Medicine, San Francisco, CA, USA. ian.mccoy@ucsf.edu.
Sandeep BrarDepartment of Epidemiology and Biostatistics, University of California, San Francisco, CA, USA.
Kathleen D LiuDivision of Nephrology, University of California, San Francisco School of Medicine, San Francisco, CA, USA.
Alan S GoDivision of Nephrology, University of California, San Francisco School of Medicine, San Francisco, CA, USA.
Raymond K HsuDivision of Nephrology, University of California, San Francisco School of Medicine, San Francisco, CA, USA.
Vernon M ChinchilliDepartment of Public Health Sciences, Pennsylvania State University College of Medicine, Hershey, PA, USA.
Steven G CocaDivision of Nephrology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Amit X GargDepartment of Medicine, Epidemiology and Biostatistics, Western University, London, Ontario, Canada.
Jonathan HimmelfarbDivision of Nephrology, University of Washington, Seattle, WA, USA.
T Alp IkizlerDivision of Nephrology & Hypertension and Vanderbilt Center for Kidney Disease, Vanderbilt University Medical Center, Nashville, TN, USA.
James KaufmanRenal Section, Veterans Affairs New York Harbor Health Care System and New York University School of Medicine, NY, New York, USA.
Paul L KimmelDivision of Kidney, Urologic and Hematologic Diseases, Digestive and Kidney Diseases, National Institute of Diabetes, National Institutes of Health, Bethesda, MD, USA.
Julie B LewisDivision of Nephrology & Hypertension and Vanderbilt Center for Kidney Disease, Vanderbilt University Medical Center, Nashville, TN, USA.
Chirag R ParikhDivision of Nephrology, Johns Hopkins School of Medicine, Baltimore, MD, USA.
Edward D SiewTennessee Valley Health Services Nashville Veterans Affairs Hospital, Nashville, TN, USA.
Lorraine B WareDepartments of Medicine and Pathology, Microbiology and Immunology, Vanderbilt University, Nashville, TN, USA.
Hui ZengDepartment of Public Health Sciences, Pennsylvania State University College of Medicine, Hershey, PA, USA.
Chi-Yuan HsuDivision of Nephrology, University of California, San Francisco School of Medicine, San Francisco, CA, USA.
Assessment, Serial Evaluation, and Subsequent Sequelae in Acute Kidney Injury (ASSESS-AKI) study investigators
University of California, San Francisco · USPennsylvania State University · USVanderbilt University Medical Center · USIcahn School of Medicine at Mount Sinai · USJohns Hopkins University · USKaiser Permanente · USNational Institutes of Health · USUniversity of British Columbia · CAUniversity of Washington · USVanderbilt University · USVA NY Harbor Healthcare System · USVA Tennessee Valley Healthcare System · USWestern University · CA

Funding

Yale Clinical and Translational Science Award (U Component)UL1TR001863 · NCATS · YALE UNIVERSITY · PI John H. Krystal, LUCILA OHNO-MACHADO · 2016 to 2026
$102.9M
Data Coordinating Center for the Natural History of AKI ConsortiumU01DK082183 · NIDDK · PENNSYLVANIA STATE UNIV HERSHEY MED CTR · PI CHINCHILLI, VERNON M · 2008 to 2018
$9.7M
Genetic Determinants of Outcomes in Acute Kidney InjuryU01DK084012 · NIDDK · UNIVERSITY OF WASHINGTON · PI HIMMELFARB, JONATHAN, WURFEL, MARK M · 2010 to 2019
$6.2M
NCATS NIH HHS UL1 TR001863NIDDK NIH HHS U01 DK082183NIDDK NIH HHS U01 DK084012
6 · The paper itself

Abstract

backgroundThere has recently been considerable interest in better understanding how blood pressure should be managed after an episode of hospitalized AKI, but there are scant data regarding the associations between blood pressure measured after AKI and subsequent adverse outcomes. We hypothesized that among AKI survivors, higher blood pressure measured three months after hospital discharge would be associated with worse outcomes. We also hypothesized these associations between blood pressure and outcomes would be similar among those who survived non-AKI hospitalizations.

methodsWe quantified how systolic blood pressure (SBP) observed three months after hospital discharge was associated with risks of subsequent hospitalized AKI, loss of kidney function, mortality, and heart failure events among 769 patients in the prospective ASSESS-AKI cohort study who had hospitalized AKI. We repeated this analysis among the 769 matched non-AKI ASSESS-AKI enrollees. We then formally tested for AKI interaction in the full cohort of 1538 patients to determine if these associations differed among those who did and did not experience AKI during the index hospitalization.

resultsAmong 769 patients with AKI, 42 % had subsequent AKI, 13 % had loss of kidney function, 27 % died, and 18 % had heart failure events. SBP 3 months post-hospitalization did not have a stepwise association with the risk of subsequent AKI, loss of kidney function, mortality, or heart failure events. Among the 769 without AKI, there was also no stepwise association with these risks. In formal interaction testing using the full cohort of 1538 patients, hospitalized AKI did not modify the association between post-discharge SBP and subsequent risks of adverse clinical outcomes.

conclusionsContrary to our first hypothesis, we did not observe that higher stepwise blood pressure measured three months after hospital discharge with AKI was associated with worse outcomes. Our data were consistent with our second hypothesis that the association between blood pressure measured three months after hospital discharge and outcomes among AKI survivors is similar to that observed among those who survived non-AKI hospitalizations.

Indexed as

Acute Kidney InjuryHeart FailureHypertensionLong Term Adverse EffectsRisk AssessmentBlood PressureBlood Pressure DeterminationCohort StudiesFemaleHospitalizationHumansMaleMiddle AgedMortalityNorth AmericaOutcome and Process Assessment, Health CareAKIblood pressurehypertension

Identifiers

PMID34325668
PMCPMC8320241
OpenAlexW3185112859

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.