Evidence map›Paper›PMID 42328006›Full record

ReviewInfectious diseases & immunity2025

COVID-19 associated acute kidney injury.

Praveen Kumar Chandra Sekar, Ramakrishnan Veerabathiran

Abstract readReview
In one paragraph

Review in Infectious diseases & immunity, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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.

Praveen Kumar Chandra SekarHuman Cytogenetics and Genomics Laboratory, Faculty of Allied Health Sciences, Chettinad Hospital and Research Institute, Chettinad Academy of Research and Education, Kelambakkam, Tamil Nadu 603103, India.
Ramakrishnan VeerabathiranHuman Cytogenetics and Genomics Laboratory, Faculty of Allied Health Sciences, Chettinad Hospital and Research Institute, Chettinad Academy of Research and Education, Kelambakkam, Tamil Nadu 603103, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Acute kidney injury (AKI) associated with Coronavirus Disease 2019 (COVID-19) is a notable complication of COVID-19 that is difficult to diagnose and treat. This review summarizes the prevalence, pathophysiology, clinical presentation, and management of COVID-19-associated AKI (hereafter COVID-19 AKI). COVID-19 AKI is linked to a multisystem inflammatory syndrome and presents symptoms similar to those of AKI, which is associated with increased morbidity and death rates. The pathophysiological mechanisms of AKI include direct viral injury, cytokine storms, and systemic effects on the renin-angiotensin-aldosterone system. The diagnostic assessment of patients at risk for AKI involves screening for symptoms such as decreased urine output, fluid retention, and fatigue. In contrast, biomarkers like serum creatinine and blood urea nitrogen are used for early detection. The management strategies for COVID-19 AKI, such as avoiding nephrotoxic medications, are similar to those for AKI of other causes. Renal replacement therapy may be considered as a treatment option for severe COVID-19 AKI, particularly in cases of fluid overload, or electrolyte imbalances that cannot be managed with conservative treatments. Future research is essential to elucidate the pathophysiology, optimize diagnostic criteria, and develop targeted therapies for COVID-19 AKI. A multidisciplinary approach focusing on physical and mental health is crucial for comprehensive patient care. Addressing these gaps will necessitate substantial funding support to propel research efforts and improve patient outcomes.

Indexed as

Acute kidney injuryCOVID-19Future directionPathophysiologyTreatment

Identifiers

PMID42328006
PMCPMC13277620

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.