Evidence map›Paper›PMID 37946280›Full record

ReviewCritical care (London, England)2023

Moving toward a contemporary classification of drug-induced kidney disease.

Iman Karimzadeh, Erin F Barreto, John A Kellum, Linda Awdishu, Patrick T Murray, Marlies Ostermann, Azra Bihorac, Ravindra L Mehta, Stuart L Goldstein, Kianoush B Kashani and 1 more

Abstract readReview
In one paragraph

Review in Critical care (London, England), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed, 1 pooled it
–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

23 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  20. Biomarkers in acute kidney injury.Annals of intensive care · 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

11 authors.

Iman KarimzadehDepartment of Clinical Pharmacy, School of Pharmacy, Shiraz University of Medical Sciences, Shiraz, Iran.
Erin F BarretoDepartment of Pharmacy, Mayo Clinic, Rochester, MN, USA.
John A KellumDepartment of Critical Care Medicine, Center for Critical Care Nephrology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.
Linda AwdishuDivision of Clinical Pharmacy, San Diego Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, La Jolla, CA, USA.
Patrick T MurraySchool of Medicine, University College Dublin, Dublin, Ireland.
Marlies OstermannDepartment of Intensive Care, King's College London, Guy's and St Thomas' Hospital, London, UK.
Azra BihoracDepartment of Medicine, University of Florida, Gainesville, FL, USA.
Ravindra L MehtaDepartment of Medicine, University of California, San Diego, CA, USA.
Stuart L GoldsteinCenter for Acute Care Nephrology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA.
Kianoush B KashaniDivision of Nephrology and Hypertension, Division of Pulmonary and Critical Care Medicine, Department of Medicine, Mayo Clinic, Rochester, MN, USA.
Sandra L Kane-GillDepartment of Critical Care Medicine, Center for Critical Care Nephrology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA. Kane-Gill@pitt.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Drug-induced kidney disease (DIKD) accounts for about one-fourth of all cases of acute kidney injury (AKI) in hospitalized patients, especially in critically ill setting. There is no standard definition or classification system of DIKD. To address this, a phenotype definition of DIKD using expert consensus was introduced in 2015. Recently, a novel framework for DIKD classification was proposed that incorporated functional change and tissue damage biomarkers. Medications were stratified into four categories, including "dysfunction without damage," "damage without dysfunction," "both dysfunction and damage," and "neither dysfunction nor damage" using this novel framework along with predominant mechanism(s) of nephrotoxicity for drugs and drug classes. Here, we briefly describe mechanisms and provide examples of drugs/drug classes related to the categories in the proposed framework. In addition, the possible movement of a patient's kidney disease between certain categories in specific conditions is considered. Finally, opportunities and barriers to adoption of this framework for DIKD classification in real clinical practice are discussed. This new classification system allows congruencies for DIKD with the proposed categorization of AKI, offering clarity as well as consistency for clinicians and researchers.

Indexed as

Acute Kidney InjuryDrug-Related Side Effects and Adverse ReactionsBiomarkersConsensusCritical IllnessHumansBiomarkersAcute kidney injuryAdverse drug eventCritical careCritically illDrug-related side effects and adverse reactionsIntensive care units

Identifiers

PMID37946280
PMCPMC10633929

What OpenQuestion holds

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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.