Acknowledging differences in Acute Kidney Injury:a complex clinical syndrome in critically ill patients

In the Netherlands, approximately 80,000 people (1 per 200 inhabitants) are admitted to an intensive care unit (ICU) every year. The reasons for IC admission can be very different; after major surgery, a major accident or, for example, an infection. Despite all possibilities regarding treatment and support, IC patients are at risk for organ failure. The kidneys are very susceptible to this failure. IC patients whose kidneys fail have an increased risk of death, not only during ICU admission, but also (long) afterwards. This thesis shows that it is difficult to predict the occurrence of renal failure during ICU admission. This is probably explained by the large differences in the characteristics of patients with renal failure, with different underlying causal mechanisms for renal failure. This differences also seem to explain that the occurrence of acute renal failure in IC patients cannot be prevented or reduced in severity by measures that are the same for all IC patients

Clinical examination findings as predictors of acute kidney injury in critically ill patients

Background Acute Kidney Injury (AKI) in critically ill patients is associated with a markedly increased morbidity and mortality. The aim of this study was to establish the predictive value of clinical examination for AKI in critically ill patients. Methods This was a sub-study of the SICS-I, a prospective observational cohort study of critically ill patients acutely admitted to the Intensive Care Unit (ICU). Clinical examination was performed within 24 hours of ICU admission. The occurrence of AKI was determined at day two and three after admission according to the KDIGO definition including serum creatinine and urine output. Multivariable regression modeling was used to assess the value of clinical examination for predicting AKI, adjusted for age, comorbidities and the use of vasopressors. Results A total of 1003 of 1075 SICS-I patients (93%) were included in this sub-study. 414 of 1003 patients (41%) fulfilled the criteria for AKI. Increased heart rate (OR 1.12 per 10 beats per minute increase, 98.5% CI 1.04-1.22), subjectively cold extremities (OR 1.52, 98.5% CI 1.07-2.16) and a prolonged capillary refill time on the sternum (OR 1.89, 98.5% CI 1.01-3.55) were associated with AKI. This multivariable analysis yielded an area under the receiver-operating curve (AUROC) of 0.70 (98.5% CI 0.66-0.74). The model performed better when lactate was included (AUROC of 0.72, 95%CI 0.69-0.75), P = .04. Conclusion Clinical examination findings were able to predict AKI with moderate accuracy in a large cohort of critically ill patients. Findings of clinical examination on ICU admission may trigger further efforts to help predict developing AKI.Peer reviewe

Bedside lung ultrasound in the critically ill patient with pulmonary pathology:different diagnoses with comparable chest X-ray opacification

The differential diagnosis and treatment of opacifications on the chest X-ray in critically ill patients may be challenging. This holds in particular the patient that suffers from respiratory failure with hemodynamic instability. Opacification in the chest X-ray could be the result of hematothorax, pleural effusion, atelectasis, or consolidation. Physical examination of such patients may not always indicate what the cause of the opacification is and thus may not always help indicate the correct therapeutic approach. In such cases, bedside ultrasound may be very helpful. We present two cases with similar chest X-ray opacifications but different diagnoses established with the help of a bedside lung ultrasound. There is documented accuracy of ultrasound in differentiating pleural effusions from consolidation. Ultrasound is safe and may be an alternative for computed tomography scan in a hemodynamically or respiratory unstable intensive care patient

Burden of acute kidney injury and 90-day mortality in critically ill patients

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.Peer reviewe

Burden of acute kidney injury and 90-day mortality in critically ill patients

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.Peer reviewe

Acute Kidney Injury is Associated with Lowered Plasma-Free Thiol Levels

Acute kidney injury (AKI) is associated with the abrupt loss of kidney function. Oxidative stress plays an important role in the pathophysiology of AKI. Free thiols (R-SH) are crucial components of the extracellular antioxidant machinery and reliably reflect systemic oxidative stress. Lower levels of thiols represent higher levels of oxidative stress. In this preliminary study, we hypothesized that plasma-free thiols are associated with AKI upon admission to the intensive care unit (ICU). In this study, 301 critically ill patients were included. Plasma samples were taken upon admission, and albumin-adjusted plasma-free thiols were determined. Albumin-adjusted plasma-free thiols were lower in patients with AKI (n = 43, median (interquartile range) 7.28 mu mol/g (3.52, 8.95)) compared to patients without AKI (8.50 mu mol/g (5.82, 11.28); p < 0.05) upon admission to the ICU. Higher age (B = -0.72), higher levels of neutrophil gelatinase-associated lipocalin (B = -0.002), creatinine (B = -0.01) and lower serum albumin (B = 0.47) were associated with lower free thiol levels. Further, albumin-adjusted free thiol levels were significantly reduced in patients with sepsis (8.30 (5.52-10.64) mu mol/g) compared to patients without sepsis (6.95 (3.72-8.92) mu mol/g; p < 0.05). Together, albumin-adjusted plasma-free thiols were significantly reduced in patients with AKI and patients with sepsis compared with patients without AKI and sepsis

Associations between tricuspid annular plane systolic excursion to reflect right ventricular function and acute kidney injury in critically ill patients : a SICS-I sub-study

Abstract Background Acute kidney injury (AKI) occurs in up to 50% of all critically ill patients and hemodynamic abnormalities are assumed to contribute, but their nature and share is still unclear. We explored the associations between hemodynamic variables, including cardiac index and right ventricular function, and the occurrence of AKI in critically ill patients. Methods In this prospective cohort study, we included all patients acutely admitted to an intensive care unit (ICU). Within 24 h after ICU admission clinical and hemodynamic variables were registered including ultrasonographic measurements of cardiac index and right ventricular function, assessed using tricuspid annular plane systolic excursion (TAPSE) and right ventricular systolic excursion (RV S’). Maximum AKI stage was assessed according to the KDIGO criteria during the first 72 h after admission. Multivariable logistic regression modeling was used including both known predictors and univariable significant predictors of AKI. Secondary outcomes were days alive outside ICU and 90-day mortality. Results A total of 622 patients were included, of which 338 patients (54%) had at least AKI stage 1 within 72 h after ICU admission. In the final multivariate model higher age (OR 1.01, 95% CI 1.00–1.03, for each year), higher weight (OR 1.03 CI 1.02–1.04, for each kg), higher APACHE IV score (OR 1.02, CI 1.01–1.03, per point), lower mean arterial pressure (OR 1.02, CI 1.01–1.03, for each mmHg decrease) and lower TAPSE (OR 1.05, CI 1.02–1.09 per millimeter decrease) were all independent predictors for AKI in the final multivariate logistic regression model. Sepsis, cardiac index, RV S’ and use of vasopressors were not significantly associated with AKI in our data. AKI patients had fewer days alive outside of ICU, and their mortality rate was significantly higher than those without AKI. Conclusions In our cohort of acutely admitted ICU patients, the incidence of AKI was 54%. Hemodynamic variables were significantly different between patients with and without AKI. A worse right ventricle function was associated with AKI in the final model, whereas cardiac index was not