Browsing by Subject "Critically ill"
Now showing items 1-8 of 8
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(2019)Background Mortality rates associated with acute kidney injury (AKI) vary among critically ill patients. Outcomes are often not corrected for severity or duration of AKI. Our objective was to analyse whether a new variable, AKI burden, would outperform 1) presence of AKI, 2) highest AKI stage, or 3) AKI duration in predicting 90-day mortality. Methods Kidney Diseases: Improving Global Outcomes (KDIGO) criteria using creatinine, urine output and renal replacement therapy were used to diagnose AKI. AKI burden was defined as AKI stage multiplied with the number of days that each stage was present (maximum five), divided by the maximum possible score yielding a proportion. The AKI burden as a predictor of 90-day mortality was assessed in two independent cohorts (Finnish Acute Kidney Injury, FINNAKI and Simple Intensive Care Studies I, SICS-I) by comparing four multivariate logistic regression models that respectively incorporated either the presence of AKI, the highest AKI stage, the duration of AKI, or the AKI burden. Results In the FINNAKI cohort 1096 of 2809 patients (39%) had AKI and 90-day mortality of the cohort was 23%. Median AKI burden was 0.17 (IQR 0.07-0.50), 1.0 being the maximum. The model including AKI burden (area under the receiver operator curve (AUROC) 0.78, 0.76-0.80) outperformed the models using AKI presence (AUROC 0.77, 0.75-0.79, p = 0.026) or AKI severity (AUROC 0.77, 0.75-0.79, p = 0.012), but not AKI duration (AUROC 0.77, 0.75-0.79, p = 0.06). In the SICS-I, 603 of 1075 patients (56%) had AKI and 90-day mortality was 28%. Median AKI burden was 0.19 (IQR 0.08-0.46). The model using AKI burden performed better (AUROC 0.77, 0.74-0.80) than the models using AKI presence (AUROC 0.75, 0.71-0.78, p = 0.001), AKI severity (AUROC 0.76, 0.72-0.79. p = 0.008) or AKI duration (AUROC 0.76, 0.73-0.79, p = 0.009). Conclusion AKI burden, which appreciates both severity and duration of AKI, was superior to using only presence or the highest stage of AKI in predicting 90-day mortality. Using AKI burden or other more granular methods may be helpful in future epidemiological studies of AKI.
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(BioMed Central, 2019)Abstract Background Mortality rates associated with acute kidney injury (AKI) vary among critically ill patients. Outcomes are often not corrected for severity or duration of AKI. Our objective was to analyse whether a new variable, AKI burden, would outperform 1) presence of AKI, 2) highest AKI stage, or 3) AKI duration in predicting 90-day mortality. Methods Kidney Diseases: Improving Global Outcomes (KDIGO) criteria using creatinine, urine output and renal replacement therapy were used to diagnose AKI. AKI burden was defined as AKI stage multiplied with the number of days that each stage was present (maximum five), divided by the maximum possible score yielding a proportion. The AKI burden as a predictor of 90-day mortality was assessed in two independent cohorts (Finnish Acute Kidney Injury, FINNAKI and Simple Intensive Care Studies I, SICS-I) by comparing four multivariate logistic regression models that respectively incorporated either the presence of AKI, the highest AKI stage, the duration of AKI, or the AKI burden. Results In the FINNAKI cohort 1096 of 2809 patients (39%) had AKI and 90-day mortality of the cohort was 23%. Median AKI burden was 0.17 (IQR 0.07–0.50), 1.0 being the maximum. The model including AKI burden (area under the receiver operator curve (AUROC) 0.78, 0.76–0.80) outperformed the models using AKI presence (AUROC 0.77, 0.75–0.79, p = 0.026) or AKI severity (AUROC 0.77, 0.75–0.79, p = 0.012), but not AKI duration (AUROC 0.77, 0.75–0.79, p = 0.06). In the SICS-I, 603 of 1075 patients (56%) had AKI and 90-day mortality was 28%. Median AKI burden was 0.19 (IQR 0.08–0.46). The model using AKI burden performed better (AUROC 0.77, 0.74–0.80) than the models using AKI presence (AUROC 0.75, 0.71–0.78, p = 0.001), AKI severity (AUROC 0.76, 0.72–0.79. p = 0.008) or AKI duration (AUROC 0.76, 0.73–0.79, p = 0.009). Conclusion AKI burden, which appreciates both severity and duration of AKI, was superior to using only presence or the highest stage of AKI in predicting 90-day mortality. Using AKI burden or other more granular methods may be helpful in future epidemiological studies of AKI.
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(2017)The intestinal microbiota has emerged as a virtual organ with essential functions in human physiology. Antibiotic-induced disruption of the microbiota in critically ill patients may have a negative influence on key energy resources and immunity. We set out to characterize the fecal microbiota composition in critically ill patients both with and without sepsis and to explore the use of microbiota-derived markers for clinical outcome measurements in this setting. In this prospective observational cohort study we analyzed the fecal microbiota of 34 patients admitted to the intensive care unit. Fifteen healthy subjects served as controls. The fecal microbiota was phylogenetically characterized by 16S rRNA gene sequencing, and associations with clinical outcome parameters were evaluated. A marked shift in fecal bacterial composition was seen in all septic and non-septic critically ill patients compared with controls, with extreme interindividual differences. In 13 of the 34 patients, a single bacterial genus made up > 50% of the gut microbiota; in 4 patients this was even > 75%. A significant decrease in bacterial diversity was observed in half of the patients. No associations were found between microbiota diversity, Firmicutes/Bacteroidetes ratio, or Gram-positive/Gram-negative ratio and outcome measurements such as complications and survival. We observed highly heterogeneous patterns of intestinal microbiota in both septic and non-septic critically ill patients. Nevertheless, some general patterns were observed, including disappearance of bacterial genera with important functions in host metabolism. More detailed knowledge of the short- and long-term health consequences of these major shifts in intestinal bacterial communities is needed.
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(2020)Background Acute kidney injury (AKI) is a frequent and clinically relevant problem in critically ill patients. Various randomized controlled trials (RCT) have attempted to assess potentially beneficial treatments for AKI. Different approaches to applying the Kidney Disease Improving Global Outcomes (KDIGO) criteria for AKI make a comparison of studies difficult. The objective of this study was to assess how different approaches may impact estimates of AKI incidence and whether the association between AKI and 90-day mortality varied by the approach used. Methods Consecutive acutely admitted adult intensive care patients were included in a prospective observational study. AKI was determined following the KDIGO criteria during the first 7 days of ICU admission. In this post hoc analysis, we assessed whether AKI incidence differed when applying the KDIGO criteria in 30 different possible methods, varying in (A) serum creatinine (sCr), (B) urine output (UO), and (C) the method of combining these two into an outcome, e.g., severe AKI. We assessed point estimates and 95% confidence intervals for each incidence. Univariable regression was used to assess the associations between AKI and 90-day mortality. Results A total of 1010 patients were included. Baseline creatinine was available in 449 (44%) patients. The incidence of any AKI ranged from 28% (95%CI 25-31%) to 75% (95%CI 72-77%) depending on the approach used. Methods to estimate missing baseline sCr caused a variation in AKI incidence up to 15%. Different methods of handling UO caused a variation of up to 35%. At 90 days, 263 patients (26%) had died, and all 30 variations were associated with 90-day mortality. Conclusions In this cohort of critically ill patients, AKI incidence varied from 28 to 75%, depending on the method used of applying the KDIGO criteria. A tighter adherence to KDIGO definitions is warranted to decrease the heterogeneity of AKI and increase the comparability of future studies.
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(BioMed Central, 2020)Abstract Background Acute kidney injury (AKI) is a frequent and clinically relevant problem in critically ill patients. Various randomized controlled trials (RCT) have attempted to assess potentially beneficial treatments for AKI. Different approaches to applying the Kidney Disease Improving Global Outcomes (KDIGO) criteria for AKI make a comparison of studies difficult. The objective of this study was to assess how different approaches may impact estimates of AKI incidence and whether the association between AKI and 90-day mortality varied by the approach used. Methods Consecutive acutely admitted adult intensive care patients were included in a prospective observational study. AKI was determined following the KDIGO criteria during the first 7 days of ICU admission. In this post hoc analysis, we assessed whether AKI incidence differed when applying the KDIGO criteria in 30 different possible methods, varying in (A) serum creatinine (sCr), (B) urine output (UO), and (C) the method of combining these two into an outcome, e.g., severe AKI. We assessed point estimates and 95% confidence intervals for each incidence. Univariable regression was used to assess the associations between AKI and 90-day mortality. Results A total of 1010 patients were included. Baseline creatinine was available in 449 (44%) patients. The incidence of any AKI ranged from 28% (95%CI 25–31%) to 75% (95%CI 72–77%) depending on the approach used. Methods to estimate missing baseline sCr caused a variation in AKI incidence up to 15%. Different methods of handling UO caused a variation of up to 35%. At 90 days, 263 patients (26%) had died, and all 30 variations were associated with 90-day mortality. Conclusions In this cohort of critically ill patients, AKI incidence varied from 28 to 75%, depending on the method used of applying the KDIGO criteria. A tighter adherence to KDIGO definitions is warranted to decrease the heterogeneity of AKI and increase the comparability of future studies.
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(2021)Purpose We compared a restrictive fluid management strategy to usual care among critically ill patients with acute kidney injury (AKI) who had received initial fluid resuscitation. Methods This multicenter feasibility trial randomized 100 AKI patients 1:1 in seven ICUs in Europe and Australia. Restrictive fluid management included targeting negative or neutral daily fluid balance by minimizing fluid input and/or enhancing urine output with diuretics administered at the discretion of the clinician. Fluid boluses were administered as clinically indicated. The primary endpoint was cumulative fluid balance 72 h from randomization. Results Mean (SD) cumulative fluid balance at 72 h from randomization was - 1080 mL (2003 mL) in the restrictive fluid management arm and 61 mL (3131 mL) in the usual care arm, mean difference (95% CI) - 1148 mL (- 2200 to - 96) mL, P = 0.033. Median [IQR] duration of AKI was 2 [1-3] and 3 [2-7] days, respectively (median difference - 1.0 [- 3.0 to 0.0], P = 0.071). Altogether, 6 out of 46 (13%) patients in the restrictive fluid management arm and 15 out of 50 (30%) in the usual care arm received renal replacement therapy (RR 0.42; 95% CI 0.16-0.91), P = 0.043. Cumulative fluid balance at 24 h and 7 days was lower in the restrictive fluid management arm. The dose of diuretics was not different between the groups. Adverse events occurred more frequently in the usual care arm. Conclusions In critically ill patients with AKI, a restrictive fluid management regimen resulted in lower cumulative fluid balance and less adverse events compared to usual care. Larger trials of this intervention are justified.
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(2022)Acute kidney injury (AKI) is a frequently encountered syndrome especially among the critically ill. Current diagnosis of AKI is based on acute deterioration of kidney function, indicated by an increase in creatinine and/or reduced urine output. However, this syndromic definition encompasses a wide variety of distinct clinical features, varying pathophysiology, etiology and risk factors, and finally very different short- and long-term outcomes. Lumping all AKI together may conceal unique pathophysiologic processes specific to certain AKI populations, and discovering these AKI subphenotypes might help to develop targeted therapies tackling unique pathophysiological processes. In this review, we discuss the concept of AKI subphenotypes, current knowledge regarding both clinical and biomarker-driven subphenotypes, interplay with AKI subphenotypes and other ICU syndromes, and potential future and clinical implications.
