Evidence map›Paper›PMID 35008760›Full record

ReviewInternational journal of molecular sciences2021

OMICS in Chronic Kidney Disease: Focus on Prognosis and Prediction.

Michele Provenzano, Raffaele Serra, Carlo Garofalo, Ashour Michael, Giuseppina Crugliano, Yuri Battaglia, Nicola Ielapi, Umberto Marcello Bracale, Teresa Faga, Giulia Capitoli and 2 more

Abstract readReview
In one paragraph

Review in International journal of molecular sciences, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
21citing 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

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

  1. Pooled it
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  15. Personalized Antifibrotic Therapy in CKD Progression.Journal of personalized medicine · 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

12 authors.

Michele ProvenzanoDepartment of Medical and Surgical Sciences, University Magna Graecia of Catanzaro, Viale Europa, 88100 Catanzaro, Italy.ORCID 0000-0002-2168-702X
Raffaele SerraDepartment of Medical and Surgical Sciences, University Magna Graecia of Catanzaro, Viale Europa, 88100 Catanzaro, Italy.ORCID 0000-0003-4477-7412
Carlo GarofaloDepartment of Advanced Medical and Surgical Sciences, University of Campania Luigi Vanvitelli, 80138 Napoli, Italy.
Ashour MichaelDepartment of Health Sciences, Magna Graecia University, 88100 Catanzaro, Italy.
Giuseppina CruglianoDepartment of Health Sciences, Magna Graecia University, 88100 Catanzaro, Italy.
Yuri BattagliaDivision of Nephrology and Dialysis, St. Anna University-Hospital, 44124 Ferrara, Italy.ORCID 0000-0003-3947-1814
Nicola IelapiDepartment of Public Health and Infectious Disease, Sapienza University of Rome, 00185 Roma, Italy.ORCID 0000-0002-1011-9844
Umberto Marcello BracaleVascular Surgery Unit, Department of Public Health, University Federico II of Naples, 80131 Napoli, Italy.ORCID 0000-0001-9507-9791
Teresa FagaDepartment of Health Sciences, Magna Graecia University, 88100 Catanzaro, Italy.
Giulia CapitoliBicocca Bioinformatics Biostatistics and Bioimaging B4 Center, School of Medicine and Surgery, University of Milano-Bicocca, 20100 Milano, Italy.ORCID 0000-0002-8178-2440
Stefania GalimbertiBicocca Bioinformatics Biostatistics and Bioimaging B4 Center, School of Medicine and Surgery, University of Milano-Bicocca, 20100 Milano, Italy.ORCID 0000-0003-1504-7242
Michele AndreucciDepartment of Health Sciences, Magna Graecia University, 88100 Catanzaro, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Chronic kidney disease (CKD) patients are characterized by a high residual risk for cardiovascular (CV) events and CKD progression. This has prompted the implementation of new prognostic and predictive biomarkers with the aim of mitigating this risk. The 'omics' techniques, namely genomics, proteomics, metabolomics, and transcriptomics, are excellent candidates to provide a better understanding of pathophysiologic mechanisms of disease in CKD, to improve risk stratification of patients with respect to future cardiovascular events, and to identify CKD patients who are likely to respond to a treatment. Following such a strategy, a reliable risk of future events for a particular patient may be calculated and consequently the patient would also benefit from the best available treatment based on their risk profile. Moreover, a further step forward can be represented by the aggregation of multiple omics information by combining different techniques and/or different biological samples. This has already been shown to yield additional information by revealing with more accuracy the exact individual pathway of disease.

Indexed as

GenomicsAnimalsHumansModels, BiologicalPrecision MedicinePrognosisRenal Insufficiency, Chronicalbuminuriachronic renal failuregenomicsmetabolomicsprecision medicineproteomicsSNP

Identifiers

PMID35008760
PMCPMC8745343

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.