Evidence map›Paper›PMID 38934040›Full record

ArticleKidney research and clinical practice2024

Biomarkers in pursuit of precision medicine for acute kidney injury: hard to get rid of customs.

Kun-Mo Lin, Ching-Chun Su, Jui-Yi Chen, Szu-Yu Pan, Min-Hsiang Chuang, Cheng-Jui Lin, Chih-Jen Wu, Heng-Chih Pan, Vin-Cent Wu

Abstract read
In one paragraph

Article in Kidney research and clinical practice, 2024. 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
–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

4 citing papers in PubMed.

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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

9 authors.

Kun-Mo LinDivision of Nephrology, Department of Internal Medicine, Mackay Memorial Hospital, Taipei, Taiwan.
Ching-Chun SuDivision of Nephrology, Department of Internal Medicine, Chi-Mei Medical Center, Tainan, Taiwan.
Jui-Yi ChenDivision of Nephrology, Department of Internal Medicine, Chi-Mei Medical Center, Tainan, Taiwan.
Szu-Yu PanDivision of Nephrology, Department of Internal Medicine, National Taiwan University Hospital, Taipei, Taiwan.
Min-Hsiang ChuangDivision of Nephrology, Department of Internal Medicine, Chi-Mei Medical Center, Tainan, Taiwan.
Cheng-Jui LinDivision of Nephrology, Department of Internal Medicine, Mackay Memorial Hospital, Taipei, Taiwan.
Chih-Jen WuDivision of Nephrology, Department of Internal Medicine, Mackay Memorial Hospital, Taipei, Taiwan.
Heng-Chih PanDivision of Nephrology, Department of Internal Medicine, Keelung Chang Gung Memorial Hospital, Taiwan.
Vin-Cent WuDivision of Nephrology, Department of Internal Medicine, National Taiwan University Hospital, Taipei, Taiwan.

Funding

Ministry of Science and Technology (MOST) of the Republic of China (Taiwan) MOST 107-2314-B-002-026-MY3, 108-2314B-002-058, 110-2314-B-002-241, 110-2314-B-002-239National Health Research Institutes PH-102-SP-09National Science and Technology Council NSTC 109-2314-B-002-174-MY3, 110-2314-B-002124-MY3, 111-2314-B-002-046, 111-2314-B-002-058National Taiwan University Hospital 109-S4634, PC-1246, PC-1309, VN109-09, UN109-041, UN110-030, 111-FTN0011
6 · The paper itself

Abstract

Traditional acute kidney injury (AKI) classifications, which are centered around semi-anatomical lines, can no longer capture the complexity of AKI. By employing strategies to identify predictive and prognostic enrichment targets, experts could gain a deeper comprehension of AKI's pathophysiology, allowing for the development of treatment-specific targets and enhancing individualized care. Subphenotyping, which is enriched with AKI biomarkers, holds insights into distinct risk profiles and tailored treatment strategies that redefine AKI and contribute to improved clinical management. The utilization of biomarkers such as N-acetyl-β-D-glucosaminidase, tissue inhibitor of metalloprotease-2·insulin-like growth factor-binding protein 7, kidney injury molecule-1, and liver fatty acid-binding protein garnered significant attention as a means to predict subclinical AKI. Novel biomarkers offer promise in predicting persistent AKI, with urinary motif chemokine ligand 14 displaying significant sensitivity and specificity. Furthermore, they serve as predictive markers for weaning patients from acute dialysis and offer valuable insights into distinct AKI subgroups. The proposed management of AKI, which is encapsulated in a structured flowchart, bridges the gap between research and clinical practice. It streamlines the utilization of biomarkers and subphenotyping, promising a future in which AKI is swiftly identified and managed with unprecedented precision. Incorporating kidney biomarkers into strategies for early AKI detection and the initiation of AKI care bundles has proven to be more effective than using care bundles without these novel biomarkers. This comprehensive approach represents a significant stride toward precision medicine, enabling the identification of high-risk subphenotypes in patients with AKI.

Indexed as

Acute kidney injuryBiomarkersDialysisPrecision medicine

Identifiers

PMID38934040
PMCPMC11237332

What OpenQuestion holds

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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.