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Survival and recovery modeling of acute kidney injury in critically ill adults

OBJECTIVES: Acute kidney injury is common among the critically ill. However, the incidence, medication use, and outcomes of acute kidney injury have been variably described. We conducted a single-center, retrospective cohort study to examine the risk factors and correlates associated with acute kidn...

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Autores principales: Brothers, Todd N, Strock, Jacob, LeMasters, Traci J, Pawasauskas, Jayne, Reed, Ronald C, Al-Mamun, Mohammad A
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9150243/
https://www.ncbi.nlm.nih.gov/pubmed/35652035
http://dx.doi.org/10.1177/20503121221099359
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author Brothers, Todd N
Strock, Jacob
LeMasters, Traci J
Pawasauskas, Jayne
Reed, Ronald C
Al-Mamun, Mohammad A
author_facet Brothers, Todd N
Strock, Jacob
LeMasters, Traci J
Pawasauskas, Jayne
Reed, Ronald C
Al-Mamun, Mohammad A
author_sort Brothers, Todd N
collection PubMed
description OBJECTIVES: Acute kidney injury is common among the critically ill. However, the incidence, medication use, and outcomes of acute kidney injury have been variably described. We conducted a single-center, retrospective cohort study to examine the risk factors and correlates associated with acute kidney injury in critically ill adults with a particular focus on medication class usage. METHODS: We reviewed the electronic medical records of all adult patients admitted to an intensive care unit between 1 February and 30 August 2020. Acute kidney injury was defined by the 2012 Kidney Disease: Improving Global Outcomes guidelines. Data included were demographics, comorbidities, symptoms, laboratory parameters, interventions, and outcomes. The primary outcome was acute kidney injury incidence. A Least Absolute Shrinkage and Selection Operator regression model was used to determine risk factors associated with acute kidney injury. Secondary outcomes including acute kidney injury recovery and intensive care unit mortality were analyzed using a Cox regression model. RESULTS: Among 226 admitted patients, 108 (47.8%) experienced acute kidney injury. 37 (34.3%), 39 (36.1%), and 32 patients (29.6%) were classified as acute kidney injury stages I–III, respectively. Among the recovery and mortality cohorts, analgesics/sedatives, anti-infectives, and intravenous fluids were significant (p-value < 0.05). The medication classes IV-fluid electrolytes nutrition (96.7%), gastrointestinal (90.2%), and anti-infectives (81.5%) were associated with an increased odds of developing acute kidney injury, odd ratios: 1.27, 1.71, and 1.70, respectively. Cox regression analyses revealed a significantly increased time-varying mortality risk for acute kidney injury-stage III, hazard ratio: 4.72 (95% confidence interval: 1–22.33). In the recovery cohort, time to acute kidney injury recovery was significantly faster in stage I, hazard ratio: 9.14 (95% confidence interval: 2.14–39.06) cohort when compared to the stage III cohort. CONCLUSION: Evaluation of vital signs, laboratory, and medication use data may be useful to determine acute kidney injury risk stratification. The influence of particular medication classes further impacts the risk of developing acute kidney injury, necessitating the importance of examining pharmacotherapeutic regimens for early recognition of renal impairment and prevention.
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spelling pubmed-91502432022-05-31 Survival and recovery modeling of acute kidney injury in critically ill adults Brothers, Todd N Strock, Jacob LeMasters, Traci J Pawasauskas, Jayne Reed, Ronald C Al-Mamun, Mohammad A SAGE Open Med Original Research Article OBJECTIVES: Acute kidney injury is common among the critically ill. However, the incidence, medication use, and outcomes of acute kidney injury have been variably described. We conducted a single-center, retrospective cohort study to examine the risk factors and correlates associated with acute kidney injury in critically ill adults with a particular focus on medication class usage. METHODS: We reviewed the electronic medical records of all adult patients admitted to an intensive care unit between 1 February and 30 August 2020. Acute kidney injury was defined by the 2012 Kidney Disease: Improving Global Outcomes guidelines. Data included were demographics, comorbidities, symptoms, laboratory parameters, interventions, and outcomes. The primary outcome was acute kidney injury incidence. A Least Absolute Shrinkage and Selection Operator regression model was used to determine risk factors associated with acute kidney injury. Secondary outcomes including acute kidney injury recovery and intensive care unit mortality were analyzed using a Cox regression model. RESULTS: Among 226 admitted patients, 108 (47.8%) experienced acute kidney injury. 37 (34.3%), 39 (36.1%), and 32 patients (29.6%) were classified as acute kidney injury stages I–III, respectively. Among the recovery and mortality cohorts, analgesics/sedatives, anti-infectives, and intravenous fluids were significant (p-value < 0.05). The medication classes IV-fluid electrolytes nutrition (96.7%), gastrointestinal (90.2%), and anti-infectives (81.5%) were associated with an increased odds of developing acute kidney injury, odd ratios: 1.27, 1.71, and 1.70, respectively. Cox regression analyses revealed a significantly increased time-varying mortality risk for acute kidney injury-stage III, hazard ratio: 4.72 (95% confidence interval: 1–22.33). In the recovery cohort, time to acute kidney injury recovery was significantly faster in stage I, hazard ratio: 9.14 (95% confidence interval: 2.14–39.06) cohort when compared to the stage III cohort. CONCLUSION: Evaluation of vital signs, laboratory, and medication use data may be useful to determine acute kidney injury risk stratification. The influence of particular medication classes further impacts the risk of developing acute kidney injury, necessitating the importance of examining pharmacotherapeutic regimens for early recognition of renal impairment and prevention. SAGE Publications 2022-05-26 /pmc/articles/PMC9150243/ /pubmed/35652035 http://dx.doi.org/10.1177/20503121221099359 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by-nc/4.0/This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage).
spellingShingle Original Research Article
Brothers, Todd N
Strock, Jacob
LeMasters, Traci J
Pawasauskas, Jayne
Reed, Ronald C
Al-Mamun, Mohammad A
Survival and recovery modeling of acute kidney injury in critically ill adults
title Survival and recovery modeling of acute kidney injury in critically ill adults
title_full Survival and recovery modeling of acute kidney injury in critically ill adults
title_fullStr Survival and recovery modeling of acute kidney injury in critically ill adults
title_full_unstemmed Survival and recovery modeling of acute kidney injury in critically ill adults
title_short Survival and recovery modeling of acute kidney injury in critically ill adults
title_sort survival and recovery modeling of acute kidney injury in critically ill adults
topic Original Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9150243/
https://www.ncbi.nlm.nih.gov/pubmed/35652035
http://dx.doi.org/10.1177/20503121221099359
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