Please use this identifier to cite or link to this item: https://ahro.austin.org.au/austinjspui/handle/1/19563
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dc.contributor.authorMurugan, Raghavan-
dc.contributor.authorBalakumar, Vikram-
dc.contributor.authorKerti, Samantha J-
dc.contributor.authorPriyanka, Priyanka-
dc.contributor.authorChang, Chung-Chou H-
dc.contributor.authorClermont, Gilles-
dc.contributor.authorBellomo, Rinaldo-
dc.contributor.authorPalevsky, Paul M-
dc.contributor.authorKellum, John A-
dc.date2018-09-24-
dc.date.accessioned2018-10-11T02:50:06Z-
dc.date.available2018-10-11T02:50:06Z-
dc.date.issued2018-09-24-
dc.identifier.citationCritical Care 2018; 22(1): 223-
dc.identifier.urihttps://ahro.austin.org.au/austinjspui/handle/1/19563-
dc.description.abstractAlthough net ultrafiltration (UFNET) is frequently used for treatment of fluid overload in critically ill patients with acute kidney injury, the optimal intensity of UFNET is unclear. Among critically ill patients with fluid overload receiving renal replacement therapy (RRT), we examined the association between UFNET intensity and risk-adjusted 1-year mortality. We selected patients with fluid overload ≥ 5% of body weight prior to initiation of RRT from a large academic medical center ICU dataset. UFNET intensity was calculated as the net volume of fluid ultrafiltered per day from initiation of either continuous or intermittent RRT until the end of ICU stay adjusted for patient hospital admission body weight. We stratified UFNET as low (≤ 20 ml/kg/day), moderate (> 20 to ≤ 25 ml/kg/day) or high (> 25 ml/kg/day) intensity. We adjusted for age, sex, body mass index, race, surgery, baseline estimated glomerular filtration rate, oliguria, first RRT modality, pre-RRT fluid balance, duration of RRT, time to RRT initiation from ICU admission, APACHE III score, mechanical ventilation use, suspected sepsis, mean arterial pressure on day 1 of RRT, cumulative fluid balance during RRT and cumulative vasopressor dose during RRT. We fitted logistic regression for 1-year mortality, Gray's survival model and propensity matching to account for indication bias. Of 1075 patients, the distribution of high, moderate and low-intensity UFNET groups was 40.4%, 15.2% and 44.2% and 1-year mortality was 59.4% vs 60.2% vs 69.7%, respectively (p = 0.003). Using logistic regression, high-intensity compared with low-intensity UFNET was associated with lower mortality (adjusted odds ratio 0.61, 95% CI 0.41-0.93, p = 0.02). Using Gray's model, high UFNET was associated with decreased mortality up to 39 days after ICU admission (adjusted hazard ratio range 0.50-0.73). After combining low and moderate-intensity UFNET groups (n = 258) and propensity matching with the high-intensity group (n = 258), UFNET intensity > 25 ml/kg/day compared with ≤ 25 ml/kg/day was associated with lower mortality (57% vs 67.8%, p = 0.01). Findings were robust to several sensitivity analyses. Among critically ill patients with ≥ 5% fluid overload and receiving RRT, UFNET intensity > 25 ml/kg/day compared with ≤ 20 ml/kg/day was associated with lower 1-year risk-adjusted mortality. Whether tolerating intensive UFNET is just a marker for recovery or a mediator requires further research.-
dc.language.isoeng-
dc.subjectDialysis-
dc.subjectFluid overload-
dc.subjectIntensity-
dc.subjectMortality-
dc.subjectNet ultrafiltration-
dc.subjectRenal replacement therapy-
dc.titleNet ultrafiltration intensity and mortality in critically ill patients with fluid overload.-
dc.typeJournal Article-
dc.identifier.journaltitleCritical Care-
dc.identifier.affiliationRenal Section, Veterans Affairs Pittsburgh Healthcare System, Pittsburgh, PA, USAen
dc.identifier.affiliationDepartment of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USAen
dc.identifier.affiliationDepartment of Biostatistics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USAen
dc.identifier.affiliationDepartment of Intensive Care, Austin Health, Heidelberg, Victoria, Australiaen
dc.identifier.affiliationDepartment of Critical Care Medicine, The Center for Critical Care Nephrology, CRISMA, University of Pittsburgh School of Medicine, Pittsburgh, PA, USAen
dc.identifier.affiliationDepartment of Critical Care Medicine, The Clinical Research, Investigation, and Systems Modeling of Acute Illness (CRISMA) Center, University of Pittsburgh School of Medicine, Pittsburgh, PA, USAen
dc.identifier.affiliationCritical Care Medicine, and Clinical & Translational Science, University of Pittsburgh, Suite 220, Room 206, 3347 Forbes Avenue, Pittsburgh, PA, 15261, USAen
dc.identifier.affiliationThe University of Melbourne, Melbourne, Victoria, Australiaen
dc.identifier.doi10.1186/s13054-018-2163-1-
dc.identifier.orcid0000-0002-1650-8939en
dc.identifier.orcid0000-0002-6823-6365en
dc.identifier.pubmedid30244678-
dc.type.austinJournal Article-
local.name.researcherBellomo, Rinaldo
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.cerifentitytypePublications-
item.fulltextNo Fulltext-
item.grantfulltextnone-
item.languageiso639-1en-
item.openairetypeJournal Article-
crisitem.author.deptIntensive Care-
crisitem.author.deptData Analytics Research and Evaluation (DARE) Centre-
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