Evidence map›Paper›PMID 30270578›Full record

ArticleCPT: pharmacometrics & systems pharmacology2018

A Quantitative Systems Pharmacology Kidney Model of Diabetes Associated Renal Hyperfiltration and the Effects of SGLT Inhibitors.

Pavel Balazki, Stephan Schaller, Thomas Eissing, Thorsten Lehr

Abstract read
In one paragraph

Article in CPT: pharmacometrics & systems pharmacology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
–field-weighted citation impact
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

10 citing papers in PubMed.

  1. Article
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  4. Heliyon · 2024
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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

4 authors.

Pavel BalazkiClinical Pharmacometrics, Bayer AG, Leverkusen, Germany.
Stephan SchalleresqLABS GmbH, Saterland, Germany.
Thomas EissingClinical Pharmacometrics, Bayer AG, Leverkusen, Germany.
Thorsten LehrClinical Pharmacy, Saarland University, Saarbrücken, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The early stage of diabetes mellitus is characterized by increased glomerular filtration rate (GFR), known as hyperfiltration, which is believed to be one of the main causes leading to renal injury in diabetes. Sodium-glucose cotransporter 2 inhibitors (SGLT2i) have been shown to be able to reverse hyperfiltration in some patients. We developed a mechanistic computational model of the kidney that explains the interplay of hyperglycemia and hyperfiltration and integrates the pharmacokinetics/pharmacodynamics (PK/PD) of the SGLT2i dapagliflozin. Based on simulation results, we propose kidney growth as the necessary process for hyperfiltration progression. Further, the model indicates that renal SGLT1i could significantly improve hyperfiltration when added to SGTL2i. Integrated into a physiologically based PK/PD (PBPK/PD) Diabetes Platform, the model presents a powerful tool for aiding drug development, prediction of hyperfiltration risk, and allows the assessment of the outcomes of individualized treatments with SGLT1-inhibitors and SGLT2-inhibitors and their co-administration with insulin.

Indexed as

Models, BiologicalDiabetes Mellitus, Type 2Glomerular Filtration RateHumansKidney DiseasesSodium-Glucose Transporter 2 InhibitorsSodium-Glucose Transporter 2 Inhibitors

Identifiers

PMID30270578
PMCPMC6310870

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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.