Evidence map›Paper›PMID 33982447›Full record

ArticleClinical and translational science2021

Design and conduct considerations for studies in patients with impaired renal function.

Paulien Ravenstijn, Manoranjenni Chetty, Pooja Manchandani

Open access · goldAbstract read
In one paragraph

Article in Clinical and translational science, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 1 pooled it
3.1field-weighted citation impact, top 9% 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

13 citing papers in PubMed, 1 synthesis or guideline pooled it, 25 citations in OpenAlex.

  1. Pooled it
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  3. Review
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Anticoagulation in Patients with Chronic Kidney Disease.American journal of nephrology · 2024
    Review
  10. Article
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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

3 authors at 2 institutions in 2 countries.

Paulien RavenstijnqPharmetra LLC, Nijmegen, The Netherlands.
Manoranjenni ChettyDiscipline of Pharmaceutical Sciences, College of Health Sciences, University of KwaZulu Natal, Durban, South Africa.
Pooja ManchandaniClinical Pharmacology and Exploratory Development, Astellas Pharma US Inc., Northbrook, Illinois, USA.ORCID 0000-0003-0025-5137
Astellas Pharma (United States) · USUniversity of KwaZulu-Natal · ZA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

An impaired renal function, including acute and chronic kidney disease and end-stage renal disease, can be the result of aging, certain disease conditions, the use of some medications, or as a result of smoking. In patients with renal impairment (RI), the pharmacokinetics (PKs) of drugs or drug metabolites may change and result in increased safety risks or decreased efficacy. In order to make specific dose recommendations in the label of drugs for patients with RI, a clinical trial may have to be conducted or, when not feasible, modeling and simulations approaches, such as population PK modeling or physiologically-based PK modelling may be applied. This tutorial aims to provide an overview of the global regulatory landscape and a practical guidance for successfully designing and conducting clinical RI trials or, alternatively, on applying modeling and simulation tools to come to a dose recommendation for patients with RI in the most efficient manner.

Indexed as

Dose-Response Relationship, DrugModels, BiologicalAcute Kidney InjuryClinical Trials as TopicComputer SimulationGlomerular Filtration RateHumansKidneyKidney Failure, ChronicRenal Elimination

Identifiers

PMID33982447
PMCPMC8504825
OpenAlexW3160681262

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.