Changes in frailty among ICU survivors and associated factors:Results of a one-year prospective cohort study using the Dutch Clinical Frailty Scale

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Biomarkers associated with delirium in critically ill patients and their relation with long-term subjective cognitive dysfunction; indications for different pathways governing delirium in inflamed and noninflamed patients

Introduction: Delirium occurs frequently in critically ill patients and is associated with disease severity and infection. Although several pathways for delirium have been described, biomarkers associated with delirium in intensive care unit (ICU) patients is not well studied. We examined plasma biomarkers in delirious and nondelirious patients and the role of these biomarkers on long-term cognitive function.Methods: In an exploratory observational study, we included 100 ICU patients with or without delirium and with ("inflamed”) and without ("noninflamed”) infection/systemic inflammatory response syndrome (SIRS). Delirium was diagnosed by using the confusion-assessment method-ICU (CAM-ICU). Within 24 hours after the onset of delirium, blood was obtained for biomarker analysis. No differences in patient characteristics were found between deliriousand nondelirious patients. To determine associations between biomarkers and delirium, univariate and multivariatelogistic regression analyses were performed. Eighteen months after ICU discharge, a cognitive-failure questionnaire was distributed to the ICU survivors.Results: In total, 50 delirious and 50 nondelirious patients were included. We found that IL-8, MCP-1, procalcitonin (PCT), cortisol, and S100-b were significantly associated with delirium in inflamed patients (n = 46). In the noninflamed group of patients (n = 54), IL-8, IL-1ra, IL-10 ratio Ab1-42/40, and ratio AbN-42/40 were significantly associated with delirium. In multivariate regression analysis, IL-8 was independently associated (odds ratio, 9.0; 95% confidence interval (CI), 1.8 to 44.0) with delirium in inflamed patients and IL-10 (OR 2.6; 95% CI 1.1 to 5.9), and Ab1-42/40 (OR, 0.03; 95% CI, 0.002 to 0.50) with delirium in noninflamed patients. Furthermore, levels of several amyloid-b forms, but not human Tau or S100-b, were significantly correlated with self-reported cognitive impairment 18 months after ICU discharge, whereas inflammatory markers were not correlated to impaired longterm cognitive function.Conclusions: In inflamed patients, the proinflammatory cytokine IL-8 was associated with delirium, whereas in noninflamed patients, antiinflammatory cytokine IL-10 and Ab1-42/40 were associated with delirium. This suggests that the underlying mechanism governing the development of delirium in inflamed patients differs from that in noninflamed patients. Finally, elevated levels of amyloid-b correlated with long-term subjective cognitive-impairment delirium may represent the first sign of a (subclinical) dementia process. Future studies must confirm these results

Urinary protein profiling in hyperactive delirium and non-delirium cardiac surgery ICU patients

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The impact of delirium on the prediction of in-hospital mortality in intensive care patients

Introduction: predictive models, such as acute physiology and chronic health evaluation II (APACHE-II), are widely used in intensive care units (ICUs) to estimate mortality. Although the presence of delirium is associated with a higher mortality in ICU patients, delirium is not part of the APACHE-II model. The aim of the current study was to evaluate whether delirium, present within 24 hours after ICU admission, improves the predictive value of the APACHE-II score.Methods: in a prospective cohort study 2116 adult patients admitted between February 2008 and February 2009 were screened for delirium with the confusion assessment method-ICU (CAM-ICU). Exclusion criteria were sustained coma and unable to understand Dutch. Logistic regression analysis was used to estimate the predicted probabilities in the model with and without delirium. Calibration plots and the Hosmer-Lemeshow test (HL-test) were used to assess calibration. The discriminatory power of the models was analyzed by the area under the receiver operating characteristics curve (AUC) and AUCs were compared using the Z-test.Results: 1740 patients met the inclusion criteria, of which 332 (19%) were delirious at the time of ICU admission or within 24 hours after admission. Delirium was associated with in-hospital mortality in unadjusted models, odds ratio (OR): 3.22 (95% confidence interval [CI]: 2.23 - 4.66). The OR between the APACHE-II and in-hospital mortality was 1.15 (95% CI 1.12 - 1.19) per point. The predictive accuracy of the APACHE-II did not improve after adding delirium, both in the total group as well as in the subgroup without cardiac surgery patients. The AUC of the APACHE model without delirium was 0.77 (0.73 - 0.81) and 0.78 (0.74 - 0.82) when delirium was added to the model. The z-value was 0.92 indicating no improvement in discriminative power, and the HL-test and calibration plots indicated no improvement in calibration.Conclusions: although delirium is a significant predictor of mortality in ICU patients, adding delirium as an additional variable to the APACHE-II model does not result in an improvement in its predictive estimate

Endotoxemia-induced inflammation and the effect on the human brain

Introduction: Effects of systemic inflammation on cerebral function are not clear, as both inflammation-induced encephalopathy as well as stress-hormone mediated alertness have been described.Methods: Experimental endotoxemia (2 ng/kg Escherichia coli lipopolysaccharide [LPS]) was induced in 15 subjects, whereas 10 served as controls. Cytokines (TNF-?, IL-6, IL1-RA and IL-10), cortisol, brain specific proteins (BSP), electroencephalography (EEG) and cognitive function tests (CFTs) were determined.Results: Following LPS infusion, circulating pro- and anti inflammatory cytokines, and cortisol increased (P < 0.0001). BSP changes stayed within the normal range, in which neuron specific enolase (NSE) and S100-? changed significantly. Except in one subject with a mild encephalopathic episode, without cognitive dysfunction, endotoxemia induced no clinically relevant EEG changes. Quantitative EEG analysis showed a higher state of alertness detected by changes in the central region, and peak frequency in the occipital region. Improved CFTs during endotoxemia was found to be due to a practice effect as CFTs improved to the same extent in the reference group. Cortisol significantly correlated with a higher state of alertness detected on the EEG. Increased IL-10 and the decreased NSE both correlated with improvement of working memory and with psychomotor speed capacity. No other significant correlations between cytokines, cortisol, EEG, CFT and BSP were found.Conclusions: Short-term systemic inflammation does not provoke or explain the occurrence of septic encephalopathy, but primarily results in an inflammation-mediated increase in cortisol and alertness

Delirium prediction in the intensive care unit: comparison of two delirium prediction models

Background: Accurate prediction of delirium in the intensive care unit (ICU) may facilitate efficient use of early preventive strategies and stratification of ICU patients by delirium risk in clinical research, but the optimal delirium prediction model to use is unclear. We compared the predictive performance and user convenience of the prediction model for delirium (PRE-DELIRIC) and early prediction model for delirium (E-PRE-DELIRIC) in ICU patients and determined the value of a two-stage calculation. Methods: This 7-country, 11-hospital, prospective cohort study evaluated consecutive adults admitted to the ICU who could be reliably assessed for delirium using the Confusion Assessment Method-ICU or the Intensive Care Delirium Screening Checklist. The predictive performance of the models was measured using the area under the receiver operating characteristic curve. Calibration was assessed graphically. A physician questionnaire evaluated user convenience. For the two-stage calculation we used E-PRE-DELIRIC immediately after ICU admission and updated the prediction using PRE-DELIRIC after 24 h. Results: In total 2178 patients were included. The area under the receiver operating characteristic curve was significantly greater for PRE-DELIRIC (0.74 (95% confidence interval 0.71-0.76)) compared to E-PRE-DELIRIC (0.68 (95% confidence interval 0.66-0.71)) (z score of -2.73 (p < 0.01)). Both models were well-calibrated. The sensitivity improved when using the two-stage calculation in low-risk patients. Compared to PRE-DELIRIC, ICU physicians (n = 68) rated the E-PRE-DELIRIC model more feasible. Conclusions: While both ICU delirium prediction models have moderate-to-good performance, the PRE-DELIRIC model predicts delirium better. However, ICU physicians rated the user convenience of E-PRE-DELIRIC superior to PRE-DELIRIC. In low-risk patients the delirium prediction further improves after an update with the PRE-DELIRIC model after 24 h

Haemodynamic performance of 16–20-mm extracardiac Goretex conduits in adolescent Fontan patients at rest and during simulated exercise

OBJECTIVES: To date, it is not known if 16–20-mm extracardiac conduits are outgrown during somatic growth from childhood to adolescence. This study aims to determine total cavopulmonary connection (TCPC) haemodynamics in adolescent Fontan patients at rest and during simulated exercise and to assess the relationship between conduit size and haemodynamics. METHODS: Patient-specific, magnetic resonance imaging-based computational fluid dynamic models of the TCPC were performed in 51 extracardiac Fontan patients with 16–20-mm conduits. Power loss, pressure gradient and normalized resistance were quantified in rest and during simulated exercise. The cross-sectional area (CSA) (mean and minimum) of the vessels of the TCPC was determined and normalized for flow rate (mm2/l/min). Peak (predicted) oxygen uptake was assessed. RESULTS: The median age was 16.2 years (Q1–Q3 14.0–18.2). The normalized mean conduit CSA was 35–73% smaller compared to the inferior and superior vena cava, hepatic veins and left/right pulmonary artery (all P &lt; 0.001). The median TCPC pressure gradient was 0.7 mmHg (Q1–Q3 0.5–0.8) and 2.0 (Q1–Q3 1.4–2.6) during rest and simulated exercise, respectively. A moderate–strong inverse nonlinear relationship was present between normalized mean conduit CSA and TCPC haemodynamics in rest and exercise. TCPC pressure gradients of &gt;_1.0 at rest and &gt;_3.0 mmHg during simulated exercise were observed in patients with a conduit CSA &lt;_ 45 mm2/l/min and favourable haemodynamics (&lt;1 mmHg during both rest and exercise) in conduits &gt;_125 mm2/l/min. Normalized TCPC resistance correlated with (predicted) peak oxygen uptake. CONCLUSIONS: Extracardiac conduits of 16–20 mm have become relatively undersized in most adolescent Fontan patients leading to suboptimal haemodynamics.</p

Colección José Arencibia [Material gráfico]

Copia digital. Madrid : Ministerio de Educación, Cultura y Deporte. Subdirección General de Coordinación Bibliotecaria, 201

Retrospective cohort study on factors associated with mortality in high-risk pediatric critical care patients in the Netherlands

Background: High-risk patients in the pediatric intensive care unit (PICU) contribute substantially to PICU-mortality. Complex chronic conditions (CCCs) are associated with death. However, it is unknown whether CCCs also increase mortality in the high-risk PICU-patient. The objective of this study is to determine if CCCs or other factors are associated with mortality in this group. Methods: Retrospective cohort study from a national PICU-database (2006-2012, n = 30,778). High-risk PICU-patients, defined as patients 30% according to either the recalibrated Pediatric Risk of Mortality-II (PRISM) or the Paediatric Index of Mortality 2 (PIM2), were included. Patients with a cardiac arrest before PICU-admission were excluded. Results: In total, 492 high-risk PICU patients with mean predicted risk of 24.8% (SD 22.8%) according to recalibrated PIM2 and 40.0% (SD 23.8%) according to recalibrated PRISM were included of which 39.6% died. No association was found between CCCs and non-survival (odds ratio 0.99; 95% CI 0.62-1.59). Higher Glasgow coma scale at PICU admission was associated with lower mortality (odds ratio 0.91; 95% CI 0.87-0.96). Conclusio

The Delphi Delirium Management Algorithms. A practical tool for clinicians, the result of a modified Delphi expert consensus approach

Delirium is common in hospitalised patients, and there is currently no specific treatment. Identifying and treating underlying somatic causes of delirium is the first priority once delirium is diagnosed. Several international guidelines provide clinicians with an evidence-based approach to screening, diagnosis and symptomatic treatment. However, current guidelines do not offer a structured approach to identification of underlying causes. A panel of 37 internationally recognised delirium experts from diverse medical backgrounds worked together in a modified Delphi approach via an online platform. Consensus was reached after five voting rounds. The final product of this project is a set of three delirium management algorithms (the Delirium Delphi Algorithms), one for ward patients, one for patients after cardiac surgery and one for patients in the intensive care unit.</p