Evidence map›Paper›PMID 34176087›Full record

ArticleInfection2022

Longitudinal prediction of hospital-acquired acute kidney injury in COVID-19: a two-center study.

Justin Y Lu, Wei Hou, Tim Q Duong

Abstract read
In one paragraph

Article in Infection, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
35citing 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

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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

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

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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

3 authors.

Justin Y LuDepartment of Radiology, Montefiore Medical Center, Albert Einstein College of Medicine, 111 E 210th St, Bronx, NY, 10467, USA.
Wei HouDepartment of Family, Population & Preventive Medicine, Stony Brook Medicine, 101 Nicolls Rd, Stony Brook, NY, USA.
Tim Q DuongDepartment of Radiology, Montefiore Medical Center, Albert Einstein College of Medicine, 111 E 210th St, Bronx, NY, 10467, USA. Tim.duong@einsteinmed.org.ORCID http://orcid.org/0000-0001-6403-2827

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTo investigate the temporal characteristics of clinical variables of hospital-acquired acute kidney injury (AKI) in COVID-19 patients and to longitudinally predict AKI onset.

methodsThere were 308 hospital-acquired AKI and 721 non-AKI (NAKI) COVID-19 patients from Stony Brook Hospital (New York, USA) data, and 72 hospital-acquired AKI and 303 NAKI COVID-19 patients from Tongji Hospital (Wuhan, China). Demographic, comorbidities, and longitudinal (3 days before and 3 days after AKI onset) clinical variables were used to compute odds ratios for and longitudinally predict hospital-acquired AKI onset.

resultsCOVID-19 patients with AKI were more likely to die than NAKI patients (31.5% vs 6.9%, adjusted p < 0.001, OR = 4.67 [95% CI 3.1, 7.0], Stony Brook data). AKI developed on average 3.3 days after hospitalization. Procalcitonin was elevated prior to AKI onset (p < 0.05), peaked, and remained elevated (p < 0.05). Alanine aminotransferase, aspartate transaminase, ferritin, and lactate dehydrogenase peaked the same time as creatinine, whereas D-dimer and brain natriuretic peptide peaked a day later. C-reactive protein, white blood cell and lymphocyte showed group differences - 2 days prior (p < 0.05). Top predictors were creatinine, procalcitonin, white blood cells, lactate dehydrogenase, and lymphocytes. They predicted AKI onset with areas under curves (AUCs) of 0.78, 0.66, and 0.56 at 0, - 1, and - 2 days prior, respectively. When tested on the Tongji Hospital data, the AUCs were 0.80, 0.79, and 0.77, respectively.

conclusionsTime-locked longitudinal data provide insight into AKI progression. Commonly clinical variables reasonably predict AKI onset a few days prior. This work may lead to earlier recognition of AKI and treatment to improve clinical outcomes.

Indexed as

Acute Kidney InjuryCOVID-19HospitalsHumansRetrospective StudiesRisk FactorsSARS-CoV-2AKIChronic kidney diseaseCytokine stormD-DimerLactate dehydrogenaseMultiorgan failurePredictive modelSARS-CoV-2

Identifiers

PMID34176087
PMCPMC8235913

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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.