scholarly journals Incidence and Risk Factors of Delirium in the Intensive Care Unit: A Prospective Cohort

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Farshid Rahimi-Bashar ◽  
Ghazal Abolhasani ◽  
Nahid Manouchehrian ◽  
Nasrin Jiryaee ◽  
Amir Vahedian-Azimi ◽  
...  
Keyword(s):  
Risk Factors ◽  
Intensive Care ◽  
Critically Ill ◽  
Critically Ill Patients ◽  
Prospective Cohort ◽  
Cox Regression ◽  
Cox Model ◽  
Scoring Systems ◽  
Confusion Assessment Method ◽  
Assessment Method

Purpose. The purpose of this study was to determine the incidence, risk factors, and impact of delirium on outcomes in ICU patients. In addition, the scoring systems were measured consecutively to characterize how these scores changed with time in patients with and without delirium. Material and Methods. A prospective cohort study enrolling 400 consecutive patients admitted to the ICU between 2018 and 2019 due to trauma or surgery. Patients were followed up for the development of delirium over ICU days using the Confusion Assessment Method (CAM) for the ICU and Intensive Care Delirium Screening Checklist (ICDSC). Cox model logistic regression analysis was used to explore delirium risk factors. Results. Delirium occurred in 108 (27%) patients during their ICU stay, and the median onset of delirium was 4 (IQR 3–4) days after admission. According to multivariate cox regression, the expected hazard for delirium was 1.523 times higher in patients who used mechanical ventilator as compared to those who did not (HR: 1.523, 95% CI: 1.197-2.388, P < 0.001 ). Conclusion. Our findings suggest that an important opportunity for improving the care of critically ill patients may be the determination of modifiable risk factors for delirium in the ICU. In addition, the scoring systems (APACHE IV, SOFA, and RASS) are useful for the prediction of delirium in critically ill patients.

Feasibility and Effectiveness of a Delirium Prevention Bundle in Critically Ill Patients

2017 ◽  
Vol 26 (1) ◽  
pp. 19-27 ◽  
Author(s):  
Claudia DiSabatino Smith ◽  
Petra Grami
Keyword(s):  
Intensive Care ◽  
Critically Ill ◽  
Critically Ill Patients ◽  
Medical Center ◽  
Early Mobilization ◽  
Sensory Stimulation ◽  
Confusion Assessment Method ◽  
Assessment Method ◽  
Surgical Intensive Care ◽  
Delirium Prevention

BackgroundStrategies for preventing delirium include early identification and avoiding or modifying patient, environmental, and iatrogenic factors. Minimal research exists on a prescriptive delirium prevention bundle that details elements or strategies for each bundle component. Even less research has been focused on nurse-driven interventions or components.ObjectiveTo evaluate the effectiveness of a delirium prevention bundle in decreasing delirium incidence in 2 medical-surgical intensive care units in a large Texas medical center.MethodsResearchers used the Confusion Assessment Method for the Intensive Care Unit to assess delirium incidence by using a controlled interventional cohort design with 447 delirium-negative critically ill patients. Bundle components consist of sedation cessation, pain management, sensory stimulation, early mobilization, and sleep promotion.ResultsThe intervention, analyzed by using a logistic regression model, reduced the odds of delirium by 78% (odds ratio, 0.22; P = .001).ConclusionsThe delirium prevention bundle was effective in reducing the incidence of delirium in critically ill medical-surgical patients. Further validation studies are under way.

Delirium in Critically Ill Patients

2017 ◽  
Author(s):  
Mark van den Boogaard ◽  
Paul Rood
Keyword(s):  
Intensive Care ◽  
Critically Ill ◽  
Hearing Aids ◽  
Critically Ill Patients ◽  
Early Mobilization ◽  
Confusion Assessment Method ◽  
Assessment Method ◽  
Assessment Tools ◽  
Delirium Assessment ◽  
Nighttime Sleep

This chapter addresses delirium in critically ill patients in the intensive care unit (ICU), especially the mixed subtype (alternating hyperactivity and hypoactivity). The Confusion Assessment Method for the ICU and the Intensive Care Delirium Screening Checklist are discussed as useful delirium assessment tools in this setting. Several neurotransmitter pathways have been implicated in delirium, including cholinergic, GABAergic, and serotonergic pathways; cytokines and glucocorticoids also appear relevant. Risk factors for delirium in the ICU include older age, prior cognitive impairment, worse illness severity, recent delirium or coma, mechanical ventilation, admission category (especially trauma or neurological/neurosurgical admission), infection, metabolic acidosis, morphine and sedative administration, urea concentration, respiratory failure, and admission urgency. Prevention and treatment of delirium are discussed, including nonpharmacological interventions (frequent reorientation, providing eyeglasses and hearing aids if needed, promoting nighttime sleep, and early mobilization) and judicious use of opiate, sedative, and antipsychotic medications.

scholarly journals Serum melatonin concentration in critically ill patients randomized to sedation or non-sedation

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jakob Oxlund ◽  
Torben Knudsen ◽  
Thomas Strøm ◽  
Jørgen T. Lauridsen ◽  
Poul J. Jennum ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Critically Ill ◽  
Critically Ill Patients ◽  
Confusion Assessment Method ◽  
Assessment Method ◽  
Secondary Outcome ◽  
Melatonin Level ◽  
Melatonin Concentration ◽  
Mechanically Ventilated

Abstract Background Abolished circadian rhythm is associated with altered cognitive function, delirium, and as a result increased mortality in critically ill patients, especially in those who are mechanically ventilated. The causes are multifactorial, of which changes in circadian rhythmicity may play a role. Melatonin plays a crucial role as part of the circadian and sleep/wake cycle. Whether sedation effects circadian regulation is unknown. Hence, the objective of this study was to evaluate the melatonin concentration in critically ill patients randomized to sedation or non-sedation and to investigate the correlation with delirium. Methods All patients were included and randomized at the intensive care unit at the hospital of southwest Jutland, Denmark. Seventy-nine patients completed the study (41 sedated and 38 non-sedated). S-melatonin was measured 3 times per day, (03.00, 14.00, and 22.00), for 4 consecutive days in total, starting on the second day upon randomization/intubation. The study was conducted as a sub-study to the NON-SEDA study in which one hundred consecutive patients were randomized to sedation or non-sedation with a daily wake-up call (50 in each arm). Primary outcome: melatonin concentration in sedated vs. non-sedated patients (analyzed using linear regression). Secondary outcome: risk of developing delirium or non-medically induced (NMI) coma in sedated vs. non-sedated patients, assessed by CAM-ICU (Confusion Assessment Method for the Intensive Care Unit) analyzed using logistic regression. Results Melatonin concentration was suppressed in sedated patients compared to the non-sedated. All patients experienced an elevated peak melatonin level early on in the course of their critical illness (p = 0.01). The risk of delirium or coma (NMI) was significantly lower in the non-sedated group (OR 0.42 CI 0.27; 0.66 p < 0.0001). No significant relationship between delirium development and suppressed melatonin concentration was established in this study (OR 1.004 p = 0.29 95% CI 0.997; 1.010). Conclusion Melatonin concentration was suppressed in sedated, critically ill patients, when compared to non-sedated controls and the frequency of delirium was elevated in sedated patients. Trail registration Clinicaltrials.gov (NCT01967680) on October 23, 2013.

scholarly journals Cystatin C predicts long term mortality better than creatinine in a nationwide study of intensive care patients

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Johanna Helmersson-Karlqvist ◽  
Miklos Lipcsey ◽  
Johan Ärnlöv ◽  
Max Bell ◽  
Bo Ravn ◽  
...  
Keyword(s):  
Intensive Care ◽  
Critically Ill ◽  
Risk Prediction ◽  
Cystatin C ◽  
Mortality Risk ◽  
Critically Ill Patients ◽  
Cox Regression ◽  
Sample Tube ◽  
Long Term Mortality

AbstractDecreased glomerular filtration rate (GFR) is linked to poor survival. The predictive value of creatinine estimated GFR (eGFR) and cystatin C eGFR in critically ill patients may differ substantially, but has been less studied. This study compares long-term mortality risk prediction by eGFR using a creatinine equation (CKD-EPI), a cystatin C equation (CAPA) and a combined creatinine/cystatin C equation (CKD-EPI), in 22,488 patients treated in intensive care at three University Hospitals in Sweden, between 2004 and 2015. Patients were analysed for both creatinine and cystatin C on the same blood sample tube at admission, using accredited laboratory methods. During follow-up (median 5.1 years) 8401 (37%) patients died. Reduced eGFR was significantly associated with death by all eGFR-equations in Cox regression models. However, patients reclassified to a lower GFR-category by using the cystatin C-based equation, as compared to the creatinine-based equation, had significantly higher mortality risk compared to the referent patients not reclassified. The cystatin C equation increased C-statistics for death prediction (p < 0.001 vs. creatinine, p = 0.013 vs. combined equation). In conclusion, this data favours the sole cystatin C equation rather than the creatinine or combined equations when estimating GFR for risk prediction purposes in critically ill patients.

scholarly journals A Systematic Review and Pooled Prevalence of Paediatric Delirium in Critically Ill Children

2021 ◽  
Vol 29 (Supplement_1) ◽  
pp. i31-i32
Author(s):  
D Semple ◽  
M M Howlett ◽  
J D Strawbridge ◽  
C V Breatnach ◽  
J C Hayden
Keyword(s):  
Risk Factors ◽  
Critical Care ◽  
Critically Ill ◽  
Observational Studies ◽  
Confusion Assessment Method ◽  
Assessment Method ◽  
Assessment Tools ◽  
Critically Ill Children ◽  
Confusion Assessment ◽  
Pooled Prevalence

Abstract Introduction Paediatric Delirium (PD) is a neuropsychiatric complication that occurs during the management of children in the critical care environment (Paediatric Intensive Care (PICU) and Neonatal Intensive Care (NICU). Delirium can be classified as hypoactive (decreased responsiveness and withdrawal), hyperactive (agitation and restlessness), and mixed (combined) (1). PD can be assessed using a number of assessment tools. PD has been historically underdiagnosed or misdiagnosed, having many overlapping symptoms with other syndrome such as pain and iatrogenic withdrawal syndrome (2). An appreciation of the extent of PD would help clinicians and policy makers drive interventions to improve recognition, prevention and management of PD in clinical practice. Aim To estimate the pooled prevalence of PD using validated assessment tools, and to identify risk factors including patient-related, critical-care related and pharmacological factors. Methods A systematic search of PubMed, EMBASE and CINAHL databases was undertaken. Eligible articles included observational studies or trials that estimated a prevalence of PD in a NICU/PICU population using a validated PD assessment tool. Validated tools are the paediatric Confusion Assessment Method-ICU (pCAM-ICU), the Cornell Assessment of Pediatric Delirium (CAPD), the PreSchool Confusion Assessment Method for the ICU (psCAM-ICU), pCAM-ICU severity scale (sspCAM-ICU), and the Sophia Observation Withdrawal Symptoms scale Paediatric Delirium scale (SOS-PD) (1). Only full text studies were included. No language restrictions were applied. Two reviewers independently screened records. Data was extracted using a pre-piloted form and independently verified by another reviewer. Quality was assessed using tools from the National Institutes of Health. A pooled prevalence was calculated from the studies that estimated PD prevalence using the most commonly applied tool, the CAPD (1). Results Data from 23 observational studies describing prevalence and risk factors for PD in critically ill children were included (Figure 1). Variability in study design and outcome reporting was found. Study quality was generally good. Using the validated tools prevalence ranged from 10–66% of patients. Hypoactive delirium was the most prevalent sub-class identified. Using the 13 studies that used the CAPD tool, a pooled prevalence of 35% (27%-43% 95%CI) was calculated. Younger ages, particularly less than two years old, sicker patients, particularly those undergoing mechanical and respiratory ventilatory support were more at risk for PD. Restraints, the number of sedative medications, including the cumulative use of benzodiazepines and opioids were identified as risk factors for the development of PD. PD was associated with longer durations of mechanical ventilation, longer stays and increased costs. Data on association with increased mortality risk is limited and conflicting. Conclusion PD affects one third of critical care admissions and is resource intense. Routine assessment in clinical practice may facilitate earlier detection and management strategies. Modifiable risk factors such as the class and number of sedative and analgesic medications used may contribute to the development of PD. Early mobility and lessening use of these medications present strategies to prevent PD occurrence. Longitudinal prospective multi-institutional studies to further investigate the presentations of the different delirium subtypes and modifiable risk factors that potentially contribute to the development of PD, are required. References 1. Semple D (2020) A systematic review and pooled prevalence of PD, including identification of the risk factors for the development of delirium in critically ill children. doi: 10.17605/OSF.IO/5KFZ8 2. Ista E, te Beest H, van Rosmalen J, de Hoog M, Tibboel D, van Beusekom B, et al. Sophia Observation withdrawal Symptoms-Paediatric Delirium scale: A tool for early screening of delirium in the PICU. Australian Critical Care. 2018;31(5):266–73

scholarly journals Risk factors for death among critically ill patients with acute renal failure

2006 ◽  
Vol 124 (5) ◽  
pp. 257-263 ◽  
Author(s):  
Geraldo Bezerra da Silva Júnior ◽  
Elizabeth De Francesco Daher ◽  
Rosa Maria Salani Mota ◽  
Francisco Albano Menezes
Keyword(s):  
Risk Factors ◽  
Blood Pressure ◽  
Mechanical Ventilation ◽  
Renal Failure ◽  
Acute Renal Failure ◽  
Intensive Care ◽  
Liver Failure ◽  
Critically Ill ◽  
Critically Ill Patients ◽  
Urine Volume

CONTEXT AND OBJECTIVE: Acute renal failure is a common medical problem, with a high mortality rate. The aim of this work was to investigate the risk factors for death among critically ill patients with acute renal failure. DESIGN AND SETTING: Retrospective cohort at the intensive care unit of Hospital Universitário Walter Cantídio, Fortaleza. METHODS: Survivors and non-survivors were compared. Univariate and multivariate analyses were performed to establish risk factors for death. RESULTS: Acute renal failure occurred in 128 patients (33.5%), with mean age of 49 ± 20 years (79 males; 62%). Death occurred in 80 (62.5%). The risk factors most frequently associated with death were hypotension, sepsis, nephrotoxic drug use, respiratory insufficiency, liver failure, hypovolemia, septic shock, multiple organ dysfunction, need for vasoactive drugs, need for mechanical ventilation, oliguria, hypoalbuminemia, metabolic acidosis and anemia. There were negative correlations between death and: prothrombin time, hematocrit, hemoglobin, systolic blood pressure, diastolic blood pressure, arterial pH, arterial bicarbonate and urine volume. From multivariate analysis, the independent risk factors for death were: need for mechanical ventilation (OR = 3.15; p = 0.03), hypotension (OR = 3.48; p = 0.02), liver failure (OR = 5.37; p = 0.02), low arterial bicarbonate (OR = 0.85; p = 0.005), oliguria (OR = 3.36; p = 0.009), vasopressor use (OR = 4.83; p = 0.004) and sepsis (OR = 6.14; p = 0.003). CONCLUSIONS: There are significant risk factors for death among patients with acute renal failure in intensive care units, which need to be identified at an early stage for early treatment.

scholarly journals Risk Factors For Kidney Damage In COVID-19 Patients Admitted To The Intensive Care Unit

2021 ◽  
Vol 10 (2) ◽  
Author(s):  
Diana K. Sarkisian ◽  
Natalia V. Chebotareva ◽  
Valerie McDonnell ◽  
Armen V. Oganesyan ◽  
Tatyana N. Krasnova ◽  
...  
Keyword(s):  
Risk Factors ◽  
Intensive Care Unit ◽  
Intensive Care ◽  
Critically Ill ◽  
Critically Ill Patients ◽  
Kidney Injury ◽  
Kidney Damage ◽  
Elderly Age ◽  
Total Blood ◽  
Independent Risk Factors

Background — Acute kidney injury (AKI) reaches 29% in the intensive care unit (ICU). Our study aimed to determine the prevalence, features, and the main AKI factors in critically ill patients with coronavirus disease 2019 (COVID-19). Material and Methods — The study included 37 patients with COVID-19. We analyzed the total blood count test results, biochemical profile panel, coagulation tests, and urine samples. We finally estimated the markers of kidney damage and mortality. Result — All patients in ICU had proteinuria, and 80.5% of patients had hematuria. AKI was observed in 45.9% of patients. Independent risk factors were age more than 60 years, increased C-reactive protein (CRP) level, and decreased platelet count. Conclusion — Kidney damage was observed in most critically ill patients with COVID-19. The independent risk factors for AKI in critically ill patients were elderly age, a cytokine response with a high CRP level.

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