Urinary Tubular Biomarkers As Predictors of Death in Critically Ill Patients with Covid-19

Bezerra, Gabriela Freire; Meneses, Gdayllon Cavalcante; Albuquerque, Polianna Lemos Moura Moreira; Lopes, N; Santos, Ranieri Sales de Souza; Silva, Juliana C da; Mota, Sandra Mara Brasileiro; Guimarães, Rodrigo R; Guimarães, Fábio R; Adamian, Caio Manuel Caetano; Lima, Paula Roberta de; Bandeira, Izabel CJ; Dantas, Márcia Maria Pinheiro; Silva, Geraldo Bezerra da; Oriá, Reinaldo B.; Daher, Elizabeth De Francesco; Martins, Alice Maria Costa

doi:10.2217/bmm-2021-0631

Cited by 8 publications

(2 citation statements)

References 36 publications

(38 reference statements)

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“…[ 85 ] demonstrated that the NGAL level was an independent predictor in predicting AKI. Recently, a series of studies have shown that NGAL displayed acceptable performance for predicting AKI, the need for RRT, and death [ 14 , 46 , 86 , 87 ]. In addition, one clinical trial was established to study the role of NGAL and CysC in the prediction of AKI in COVID-19 infection ( NCT04603664 ) .…”

Section: Kidney Injury Biomarkersmentioning

confidence: 99%

The role of kidney injury biomarkers in COVID-19

Zhang

Peng

2022

Renal Failure

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The coronavirus disease-2019 (COVID-19) outbreak has been declared a global pandemic. COVID-19-associated acute kidney injury (COVID-19 AKI) is related to a high mortality rate and serves as an independent risk factor for hospital death in patients with COVID-19. Early diagnosis would allow for earlier intervention and potentially improve patient outcomes. The goal of early identification of AKI has been the primary impetus for AKI biomarker research, and several kidney injury biomarkers have been demonstrated to be beneficial in predicting COVID-19 AKI as well as disease progression in COVID-19. Furthermore, such data provide valuable insights into the molecular mechanisms underlying this complex and unique disease and serve as a molecular phenotyping tool that could be utilized to direct clinical intervention. This review focuses on a number of kidney injury biomarkers, such as CysC, NAGAL, KIM-1, L-FABP, IL-18, suPAR, and [TIMP-2] • [IGFBP7], which have been widely studied in common clinical settings, such as sepsis, cardiac surgery, and contrast-induced AKI. We explore the role of kidney injury biomarkers in COVID-19 and discuss what remains to be learned.

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Section: Kidney Injury Biomarkersmentioning

confidence: 99%

The role of kidney injury biomarkers in COVID-19

Zhang

Peng

2022

Renal Failure

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“…Bezerra and colleagues 54 investigated the association of urinary biomarkers of kidney injury with death in patients admitted to the ICU with COVID-19. They measured urinary levels of neutrophil gelatinase-associated lipocalin (NGAL), kidney injury molecule-1 (KIM-1), monocyte chemoattractant protein-1 (MCP-1), and nephrin in patients admitted to the ICU with COVID-19.…”

Section: Identifying Patients At Highest Risk For Make and Evaluation...mentioning

confidence: 99%

COVID-19 and the Kidney: Recent Advances and Controversies

Menez

Parikh

2022

Seminars in Nephrology

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Prognostic models in COVID-19 infection that predict severity: a systematic review

et al. 2023

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Current evidence on COVID-19 prognostic models is inconsistent and clinical applicability remains controversial. We performed a systematic review to summarize and critically appraise the available studies that have developed, assessed and/or validated prognostic models of COVID-19 predicting health outcomes. We searched six bibliographic databases to identify published articles that investigated univariable and multivariable prognostic models predicting adverse outcomes in adult COVID-19 patients, including intensive care unit (ICU) admission, intubation, high-flow nasal therapy (HFNT), extracorporeal membrane oxygenation (ECMO) and mortality. We identified and assessed 314 eligible articles from more than 40 countries, with 152 of these studies presenting mortality, 66 progression to severe or critical illness, 35 mortality and ICU admission combined, 17 ICU admission only, while the remaining 44 studies reported prediction models for mechanical ventilation (MV) or a combination of multiple outcomes. The sample size of included studies varied from 11 to 7,704,171 participants, with a mean age ranging from 18 to 93 years. There were 353 prognostic models investigated, with area under the curve (AUC) ranging from 0.44 to 0.99. A great proportion of studies (61.5%, 193 out of 314) performed internal or external validation or replication. In 312 (99.4%) studies, prognostic models were reported to be at high risk of bias due to uncertainties and challenges surrounding methodological rigor, sampling, handling of missing data, failure to deal with overfitting and heterogeneous definitions of COVID-19 and severity outcomes. While several clinical prognostic models for COVID-19 have been described in the literature, they are limited in generalizability and/or applicability due to deficiencies in addressing fundamental statistical and methodological concerns. Future large, multi-centric and well-designed prognostic prospective studies are needed to clarify remaining uncertainties.

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Urinary Tubular Biomarkers As Predictors of Death in Critically Ill Patients with Covid-19

Cited by 8 publications

References 36 publications

The role of kidney injury biomarkers in COVID-19

The role of kidney injury biomarkers in COVID-19

COVID-19 and the Kidney: Recent Advances and Controversies

Prognostic models in COVID-19 infection that predict severity: a systematic review

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