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Severe acute kidney injury in hospitalized cancer patients: epidemiology and predictive model of renal replacement therapy and In-Hospital Mortality

2024-01-28Journal article Open access
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dc.contributor.authorMarques, Roberto Calças
dc.contributor.authorReis, Marina
dc.contributor.authorPimenta, Gonçalo
dc.contributor.authorSala, Inês
dc.contributor.authorChuva, Teresa
dc.contributor.authorCoelho, Inês
dc.contributor.authorFerreira, Hugo
dc.contributor.authorPaiva, Ana
dc.contributor.authorCosta, José Maximino
dc.date.accessioned2024-11-28T13:24:40Z
dc.date.available2024-11-28T13:24:40Z
dc.date.issued2024-01-28
dc.description.abstractBackground: Acute kidney injury (AKI) is a common complication among cancer patients, often leading to longer hospital stays, discontinuation of cancer treatment, and a poor prognosis. This study aims to provide insight into the incidence of severe AKI in this population and identify the risk factors associated with renal replacement therapy (RRT) and in-hospital mortality. Methods: This retrospective cohort study included 3201 patients with cancer and severe AKI admitted to a Comprehensive Cancer Center between January 1995 and July 2023. Severe AKI was defined according to the KDIGO guidelines as grade ≥ 2 AKI with nephrological in-hospital follow-up. Data were analyzed in two timelines: Period A (1995–2010) and Period B (2011–2023). Results: A total of 3201 patients (1% of all hospitalized cases) were included, with a mean age of 62.5 ± 17.2 years. Solid tumors represented 75% of all neoplasms, showing an increasing tendency, while hematological cancer decreased. Obstructive AKI declined, whereas the incidence of sepsis-associated, prerenal, and drug-induced AKI increased. Overall, 20% of patients required RRT, and 26.4% died during hospitalization. A predictive model for RRT (AUC 0.833 [95% CI 0.817–0.848]) identified sepsis and hematological cancer as risk factors and prerenal and obstructive AKI as protective factors. A similar model for overall in-hospital mortality (AUC 0.731 [95% CI 0.71–0.752]) revealed invasive mechanical ventilation (IMV), sepsis, and RRT as risk factors and obstructive AKI as a protective factor. The model for hemato-oncological patients’ mortality (AUC 0.832 [95% CI 0.803–0.861]) included IMV, sepsis, hematopoietic stem cell transplantation, and drug-induced AKI. Mortality risk point score models were derived from these analyses. Conclusions: This study addresses the demographic and clinical features of cancer patients with severe AKI. The development of predictive models for RRT and in-hospital mortality, along with risk point scores, may play a role in the management of this population.eng
dc.identifier.doi10.3390/cancers16030561
dc.identifier.issn2072-6694
dc.identifier.urihttp://hdl.handle.net/10400.1/26360
dc.language.isoeng
dc.peerreviewedyes
dc.publisherMDPI
dc.relation.hasversionhttps://www.mdpi.com/2072-6694/16/3/561
dc.relation.ispartofCancers
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectAcute kidney injury
dc.subjectCancer
dc.subjectEpidemiology
dc.subjectMortality
dc.subjectRenal replacement therapy
dc.titleSevere acute kidney injury in hospitalized cancer patients: epidemiology and predictive model of renal replacement therapy and In-Hospital Mortalityeng
dc.typejournal article
dspace.entity.typePublication
oaire.citation.endPage15
oaire.citation.issue3
oaire.citation.startPage1
oaire.citation.titleCancers
oaire.citation.volume16
oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85

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