12: DELIRIUM RISK FACTORS AND OUTCOMES IN CRITICALLY ILL CHILDREN AT A TERTIARY CHILDREN’S HOSPITAL

2016 ◽  
Vol 44 (12) ◽  
pp. 89-89
Author(s):  
Leslie Dervan ◽  
Jane Di Gennaro ◽  
Reid Farris ◽  
R Watson
2021 ◽  
Vol 12 ◽  
Author(s):  
Yingchao Liu ◽  
Chanjuan Hao ◽  
Kechun Li ◽  
Xuyun Hu ◽  
Hengmiao Gao ◽  
...  

ObjectivesWhole exome sequencing (WES) has been widely used to detect genetic disorders in critically ill children. Relevant data are lacking in pediatric intensive care units (PICUs) of China. This study aimed to investigate the spectrum of monogenic disorders, the diagnostic yield and clinical utility of WES from a PICU in a large children’s hospital of China.MethodsFrom July 2017 to February 2020, WES was performed in 169 critically ill children with suspected monogenic diseases in the PICU of Beijing Children’s Hospital. The clinical features, human phenotype ontology (HPO) terms, and assessment of clinical impact were analyzed.ResultsThe media age of the enrolled children was 10.5 months (range, 1 month to 14.8 years). After WES, a total of 43 patients (25%) were diagnosed with monogenic disorders. The most common categories of diseases were metabolic disease (33%), neuromuscular disease (19%), and multiple deformities (14%). The diagnosis yield of children with “metabolism/homeostasis disorder” and “growth delay” or “ocular anomalies” was higher than that of children without these features. In addition, the diagnosis rate increased when more features were observed in children. The results of WES had an impact on the treatment for 30 cases (70%): (1) change of treatment (n = 11), (2) disease monitoring initiation (n = 18), (3) other systemic evaluation (n = 3), (4) family intervention (n = 2), and (5) rehabilitation and redirection of care toward palliative care (n = 12).ConclusionWES can be used as an effective diagnostic tool in the PICU of China and has an important impact on the treatment of patients with suspected monogenic conditions.


2021 ◽  
Vol 29 (Supplement_1) ◽  
pp. i31-i32
Author(s):  
D Semple ◽  
M M Howlett ◽  
J D Strawbridge ◽  
C V Breatnach ◽  
J C Hayden

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


2010 ◽  
Vol 68 (1) ◽  
pp. 52-56 ◽  
Author(s):  
Sheila J. Hanson ◽  
Rowena C. Punzalan ◽  
Rachel A. Greenup ◽  
Hua Liu ◽  
Thomas T. Sato ◽  
...  

2016 ◽  
Vol 17 (9) ◽  
pp. e391-e398 ◽  
Author(s):  
Morgan B. Slater ◽  
Andrea Gruneir ◽  
Paula A. Rochon ◽  
Andrew W. Howard ◽  
Gideon Koren ◽  
...  

2014 ◽  
Vol 24 (1) ◽  
pp. 89-93
Author(s):  
P. Foumane ◽  
V. Mve Koh ◽  
J. Ze Minkande ◽  
E.A. Njofang Ngantcha ◽  
J.S. Dohbit ◽  
...  

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