Evidence map›Paper›PMID 39135588›Full record

ArticleTransactions of the American Clinical and Climatological Association2024

PHENOTYPING REPAIR AFTER ACUTE KIDNEY INJURY: PRECISION MEDICINE TO CLINICAL TRIALS.

Chirag R Parikh, Jeanine Hernandez

Abstract read
In one paragraph

Article in Transactions of the American Clinical and Climatological Association, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

2 authors.

Chirag R ParikhBaltimore, Maryland.
Jeanine HernandezBaltimore, Maryland.

Funding

Novel Kidney Injury Tools in Deceased Organ Donation to Predict Graft OutcomesR01DK093770 · NIDDK · YALE UNIVERSITY · PI Chirag R Parikh · 2012 to 2026
$9.5M
Post-Discharge Nephrology Follow-up for Improved OutcomesU01DK129984 · NIDDK · JOHNS HOPKINS UNIVERSITY · PI Chirag R Parikh · 2021 to 2026
$4.2M
AKI Matched Phenotype Linked Evaluation with Tissue (AMPLE-Tissue)U01DK114866 · NIDDK · JOHNS HOPKINS UNIVERSITY · PI Chirag R Parikh · 2022 to 2026
$2.6M
Leveraging Clinical Trials of Diabetic Kidney Disease to Advance BiomarkersU01DK106962 · NIDDK · YALE UNIVERSITY · PI COCA, STEVEN G, PARIKH, CHIRAG R · 2015 to 2019
$1.3M
NIDDK NIH HHS R01 DK093770NIDDK NIH HHS U01 DK106962NIDDK NIH HHS U01 DK114866NIDDK NIH HHS U01 DK129984
6 · The paper itself

Abstract

Acute kidney injury (AKI) is common during hospitalization and is associated with long-term risk of readmissions and chronic kidney disease (CKD). Preclinical studies and novel urine biomarkers have demonstrated that subclinical inflammation and repair continue for several months after AKI. We conducted three clinical and translational studies to alleviate long-term sequelae after AKI. First, we assessed repair in deceased donor kidneys which can assist with organ allocation and reduce discard. In an ongoing study, organ procurement organizations are measuring repair biomarkers via lateral flow devices to assess organ quality and adding it to their workflow. Second, we performed research biopsies during AKI to interrogate kidney tissue with novel transcriptomic and proteomic techniques to advance therapeutic development. Third, we initiated pragmatic clinical trials to reduce readmissions after an episode of AKI by providing nurse navigator and pharmacist support to optimize blood pressure, fluid, and medication management.

Indexed as

Acute Kidney InjuryBiomarkersPhenotypePrecision MedicineClinical Trials as TopicHumansKidneyProteomicsBiomarkers

Identifiers

PMID39135588
PMCPMC11316880

What OpenQuestion holds

Textmetadata
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.