Evidence map›Paper›PMID 31792155›Full record

ArticleJournal of the American Society of Nephrology : JASN2020

BP Fluctuations and the Real-Time Dynamics of Renal Blood Flow Responses in Conscious Rats.

Anil K Bidani, Aaron J Polichnowski, Hector Licea-Vargas, Jianrui Long, Stephanie Kliethermes, Geoffrey A Williamson, Karen A Griffin

Open access · bronzeAbstract read
In one paragraph

Article in Journal of the American Society of Nephrology : JASN, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.2field-weighted citation impact, top 22% 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

8 citing papers in PubMed, 10 citations in OpenAlex.

  1. Article
  2. Efficacy of Dynamics-based Features for Machine Learning Classification of Renal Hemodynamics.Proceedings of the ... European Signal Processing Conference (EUSIPCO). EUSIPCO (Conference) · 2023
    Article
  3. Review
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  7. Article
  8. Autoregulatory Efficiency Assessment in Kidneys Using Deep Learning.Proceedings of the ... European Signal Processing Conference (EUSIPCO). EUSIPCO (Conference) · 2020
    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

7 authors at 4 institutions in 1 country.

Anil K BidaniDivision of Nephrology, Department of Medicine, Loyola University Medical Center and abidani@lumc.edu.
Aaron J PolichnowskiDivision of Nephrology, Department of Medicine, Loyola University Medical Center and.
Hector Licea-VargasDivision of Nephrology, Department of Medicine, Loyola University Medical Center and.
Jianrui LongDepartment of Electrical and Computer Engineering, Illinois Institute of Technology, Chicago, Illinois; and.
Stephanie KliethermesDepartment of Orthopedics and Rehabilitation, University of Wisconsin, Madison, Wisconsin.
Geoffrey A WilliamsonDepartment of Electrical and Computer Engineering, Illinois Institute of Technology, Chicago, Illinois; and.ORCID 0000-0002-9538-9658
Karen A GriffinDivision of Nephrology, Department of Medicine, Loyola University Medical Center and.
Loyola University Medical Center · USIllinois Institute of Technology · USEast Tennessee State University · USUniversity of Wisconsin–Madison · US

Funding

PATHOLOGY OF HYPERTENSIVE INJURY IN REMNANT KIDNEYSR01DK040426 · NIDDK · RUSH UNIVERSITY MEDICAL CENTER · PI BIDANI, ANIL K · 1990 to 2011
$2.8M
Dynamic BP load and diabetic nephropathy phenotype.R01DK061653 · NIDDK · LOYOLA UNIVERSITY CHICAGO · PI GRIFFIN, KAREN A. · 2002 to 2014
$2.1M
BLRD VA IK2 BX001285NIDDK NIH HHS R01 DK040426NIDDK NIH HHS R01 DK061653
6 · The paper itself

Abstract

backgroundRenal autoregulation maintains stable renal function despite BP fluctuations and protects glomerular capillaries from hypertensive injury. However, real-time dynamics of renal autoregulation in conscious animals have not been characterized.

methodsTo develop novel analytic methods for assessing renal autoregulation, we recorded concurrent BP and renal blood flow in conscious rats, comparing animals with renal autoregulation that was intact versus impaired (from 3/4 nephrectomy), before and after additional impairment (from the calcium channel blocker amlodipine). We calculated autoregulatory indices for adjacent short segments of increasing length (0.5, 1, 2.5, 5, 10, and 20 seconds) that exhibited a mean BP difference of at least 5 mm Hg.

resultsAutoregulatory restoration of renal blood flow to baseline after BP changes in conscious rats occurs rapidly, in 5-10 seconds. The response is significantly slower in states of impaired renal autoregulation, enhancing glomerular pressure exposure. However, in rats with severe renal autoregulation impairment (3/4 nephrectomy plus amlodipine), renal blood flow in conscious animals (but not anesthetized animals) was still restored to baseline, but took longer (15-20 seconds). Consequently, the ability to maintain overall renal blood flow stability is not compromised in conscious rats with impaired renal autoregulation.

conclusionsThese novel findings show the feasibility of renal autoregulation assessment in conscious animals with spontaneous BP fluctuations and indicate that transient increases in glomerular pressure may play a greater role in the pathogenesis of hypertensive glomerulosclerosis than previously thought. These data also show that unidentified mechanosensitive mechanisms independent of known renal autoregulation mechanisms and voltage-gated calcium channels can maintain overall renal blood flow and GFR stability despite severely impaired renal autoregulation.

Indexed as

AnimalsBlood PressureHomeostasisHypertensionMaleRatsRats, Sprague-DawleyRenal Circulationglomerulosclerosishypertensionnephrosclerosisrenal hemodynamics

Identifiers

PMID31792155
PMCPMC7003298
OpenAlexW2993875294

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

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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.