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 Prevalence and risk factors of delirium and subsyndromal delirium in older adults

2021 ◽  
Vol 33 (1) ◽  
Author(s):  
Maha Hosam El-Din Ibrahim ◽  
Manal Elmasry ◽  
Fady Nagy ◽  
Ahmed Abdelghani
Keyword(s):  
Risk Factors ◽  
Older Adults ◽  
Functional Ability ◽  
Cognitive Assessment ◽  
Length Of Hospital Stay ◽  
Assessment Method ◽  
Assessment Tools ◽  
Subsyndromal Delirium ◽  
Confusion Assessment ◽  
Definition Of

Abstract Background Delirium is a common geriatric problem associated with poor outcomes. Subsyndromal delirium (SSD) is characterized by the presence of certain symptoms of delirium yet, not satisfying the definition of full-blown delirium, defined by categorical elements, and is usually referred to as the presence of one or more symptoms in the confusion assessment method (CAM). This study aimed to investigate the prevalence and risk factors of delirium and SSD in older adults admitted to the hospital. Five hundred eighty-eight elderly (above 65 years) Egyptian patients were recruited from January 2019 to February 2020. After explaining the purpose of the study and assuring the confidentiality of all participants, an informed consent was obtained from the participant or a responsible care giver for those who were not able to give consent. All patients were subjected ‘on admission’ to thorough history taking, clinical examination, and comprehensive geriatric assessment including confusion assessment tools, mini-mental state examination, and functional assessment using Barthel index score. Results The current study showed that 19.6% of patients had delirium and 14.1% of patients had SSD with combined prevalence of 33.7%. Most common causes included metabolic, infection, organic brain syndrome, and dehydration. The current study reported significant proportionate relation between cognitive assessment and functional ability, so patients with a score of 23 MMSE had good functional ability, while cognitive assessment using mini-mental score shows inversed relation to delirium and SSD using CAM score. Conclusion Delirium is independently associated with adverse short-term and long-term outcomes, including an increase in mortality, length of hospital stay, discharge to an institution, and functional decline on discharge. Subsyndromal delirium (SSD) is characterized by the presence of certain symptoms of delirium, not yet satisfying the definition of full-blown delirium but it can identify patients with early cognitive and functional disabilities, and because of high prevalence of delirium and SSD. Efforts to prevent or early detection may identify patients who warrant clinical attention.

scholarly journals Do we know if our Patients are Delirious?

2008 ◽  
Vol 9 (3) ◽  
pp. 269-269
Author(s):  
Callum Kaye
Keyword(s):  
Risk Factors ◽  
Intensive Care Unit ◽  
Confusion Assessment Method ◽  
Assessment Method ◽  
Hospital Length ◽  
Hospital Length Of Stay ◽  
Critically Ill Patient ◽  
Confusion Assessment ◽  
Surgical Icu ◽  
Symptoms And Signs

Delirium in the intensive care unit (ICU) setting is a significant cause of morbidity, mortality and increases ICU, as well as hospital length of stay1,2. Furthermore, with so many of the risk factors being present in the critically ill patient in the ICU environment, it's not surprising that other studies have found that up to 80% of patients will be delirious at some point during admission3,4. We performed a small study in a Toronto Medical-Surgical ICU using the Confusion Assessment Method for the ICU (CAM-ICU)5 to determine the prevalence of delirium in this unit. We concurrently reviewed medical and nursing notes to identify documentation of symptoms and signs that could indicate possible delirium during routine clinical assessment of the patient.

scholarly journals Assessment of delirium in children admitted into the Intensive Care Unit: psCAM-ICU Tool

2020 ◽  
Vol 38 (2) ◽  
pp. 140-148
Author(s):  
Ángela María Henao Castaño ◽  
Edwar Yamith Pinzon Casas
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Critically Ill ◽  
Pediatric Intensive Care ◽  
Confusion Assessment Method ◽  
Assessment Method ◽  
Primary Diagnosis ◽  
Critically Ill Children ◽  
Associated Risk Factors ◽  
Prolonged Hospital

Background: Delirium has been identified as a risk factor for the mortality of critically ill patients, generating great social and economic impacts, since patients require more days of mechanical ventilation and a prolonged hospital stay in the intensive care unit (ICU), thus increasing medical costs. Objective: To describe the prevalence and characteristics of delirium episodes in a sample of 6-month to 5-year-old children who are critically ill. Methods: Cohort study at a Pediatric Intensive Care Unit (PICU) in Bogotá (Colombia). Participants were assessed by the Preschool Confusion Assessment Method for the ICU (psCAM-ICU) within the first twenty-four hours of hospitalization. Results: One quarter of the participants (25.8%) presented some type of delirium. Among them, two sub-types of delirium were observed: 62.5% of the cases were hypoactive and 37.5% hyperactive. Moreover, from them, six were male (75%) and 2 female (25%). Primary diagnosis was respiratory tract infection in 62.55% of the patients, while respiratory failure was diagnosed in the remaining 37.5%. Conclusions: The implementation of delirium monitoring tools in critically ill children provides a better understanding of the clinical manifestation of this phenomenon and associated risk factors in order to contribute to the design of efficient intervention strategies.

scholarly journals Postoperative Delirium after Urological Surgery: A Literature Review

2019 ◽  
Vol 13 (3) ◽  
pp. 133-140 ◽  
Author(s):  
Ioannis Leotsakos ◽  
Ioannis Katafigiotis ◽  
Ofer N. Gofrit ◽  
Mordechai Duvdevani ◽  
Dionysios Mitropoulos
Keyword(s):  
Risk Factors ◽  
Literature Search ◽  
Postoperative Delirium ◽  
Mini Mental State Examination ◽  
Confusion Assessment Method ◽  
Assessment Method ◽  
Factors Associated ◽  
Confusion Assessment ◽  
Urological Surgery ◽  
State Examination

Purpose: We aimed to thoroughly search and identify studies referring to risk factors associated with postoperative delirium (POD) in patients undergoing open as well as en-doscopic urological surgery. Methods: The review after a systematic literature search included 5 studies. Results: The incidence of POD was reported to be between 7.8 and 30% depending on the type of the urologic surgery, while in the majority of the studies the onset happened on the first postoperative day and the symptoms lasted 3 ± 0.8 days. Seventeen different risk factors for POD were identified and presented in detail. Conclusion: The Mini-Mental State Examination score and older age were significantly associated with the development of POD. However, the Confusion Assessment Method is very well validated against the diagnosis of delirium from the specialists.

Delirium in Hospitalized Older Patients: Recognition and Risk Factors

1998 ◽  
Vol 11 (3) ◽  
pp. 118-125 ◽  
Author(s):  
Sharon K. Inouye
Keyword(s):  
Risk Factors ◽  
High Risk ◽  
Older Patients ◽  
Confusion Assessment Method ◽  
Assessment Method ◽  
Precipitating Factors ◽  
Acute Confusional State ◽  
Confusional State ◽  
Confusion Assessment ◽  
Simplified Algorithm

Delirium, or acute confusional state, represents a common, serious, potentially preventable and increasing problem for older hospitalized patients. This study is intended to improve overall understanding of the problem of delirium and thus to lessen its adverse impact on the older population. The specific aims of this study are (1) to examine the epidemiology of delirium in older patients; (2) to evaluate barriers to recognition; (3) to present the Confusion Assessment Method (CAM) simplified algorithm to improve recognition; (4) to elucidate predisposing and precipitating factors for delirium; and (5) to propose preventive strategies. Delirium occurs in 10-60% of the older hospitalized population and is unrecognized in 32-66% of cases. The CAM algorithm provides a sensitive (94-100%), specific (90-95%), reliable, and easy to use means for identification of delirium. Four predisposing and five precipitating factors were identified and validated to identify patients at high risk for development of delirium. Primary prevention of delirium should address important delirium risk factors and target patients at intermediate to high risk for delirium at admission.

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.

Sedation in the Intensive Care Setting

2019 ◽  
Author(s):  
William John Wallisch IV ◽  
Ata Murat Kaynar
Keyword(s):  
Care Setting ◽  
Confusion Assessment Method ◽  
Assessment Method ◽  
Assessment Tools ◽  
Intensive Care Setting ◽  
Sedation Scale ◽  
Richmond Agitation Sedation Scale ◽  
Confusion Assessment ◽  
The Past ◽  
Sedation Program

The recent clinical trials on sedation and delirium in the ICU shifted the scales dramatically in the past 10 to 20 years and less sedation is now the accepted norm with titration goals. Now the art of sedation is in the hands of the clinicians to achieve a balance between alleviation of pain and anxiety while keeping patients calm, cooperative, and part of daily activities in the ICU. In this chapter we summarize the various assessment tools for optimal sedation in the ICU as well as the medications used to achieve sedation. However, the clinicians should not forget the nonpharmacologic approaches such as prevention of sleep interruption as part of a successful comprehensive sedation program in the ICU. This review contains 3 tables, and 22 references. Key Words: confusion assessment method, delirium, dexmedetomidine, etomidate, fentanyl, GABA, ketamine, propofol, Richmond agitation-sedation scale (RASS), sedation-agitation scale (SAS)

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