INCIDENCE, RISK FACTORS AND IMPACT ON OUTCOME IN OBSERVATIONAL STUDY OF DELIRIUM IN CARDIAC ICU.

2021 ◽  
pp. 36-39
Author(s):  
Rohan Ainchwar ◽  
Harshawardhan Dhanraj Ramteke ◽  
Saniya Sheikh

Introduction: Many Patients admitted to Cardiac ICU (CICU) are easily prone to Delirium, that can lead to potentially severe consequences like Cognitive Impairment and increased risks of mortality. Delirium depends on the duration of hospital stay and discharge, contrary mainly affected to the patients on mechanical ventilation, which becomes the potential reason for longer duration. Studies suggest, Delirium is a widely discussed topic, when comes to the management of the patient in Cardiac ICU. During the Rounds, it is mandatory to focus on the diagnosis of delirium and must be validated using Confusion Assessment Method (CAM). These methods not only prevent the risk of the delirium and also enhances the use of the other preventive measures like the basis of the treatment, environmental factors, quiet time, sleep promotion, family support, communication with the patient, pain and dyspnea. When conrmed with delirium, pharmacological prophylaxis must be used as soon as possible. Most often, communication between Doctor, Nurse and Patient drives the most of the depression and acute delirium, but when delirium becomes critical with severe agitation or weaning from invasive mechanical ventilation. Thus, it is very important to identify the risk, complexity of the patients and clinical case scenarios of delirium in Cardiac ICU. Strategic Efforts were done to improve the identication of the patient at risk during admission, during stay at Cardiac ICU and during discharge and orders to improve the mental state of delirium patient. In this article, we provide a panorama of the incidence, risk factors, and impact on outcome of delirium in a Cardiac Intensive Care Unit (CICU). Methods: In this case study, total of 211 patients were observed for sign and symptoms in Cardiac ICU for Delirium. We aimed to determine the incidence, risk factors, and impact on outcome of delirium in a Cardiac Intensive Care Unit (CICU) in CHLMultispeciality Hospital and Research Center, Chandrapur using a prospective observational study. Patients:All consecutive patients admitted to the CICU between April 2021 and June 2021 were included if they were aged more than 18 years, had an CICU stay of more than 24 h and no psychiatric history. Patients eligible for the study were evaluated by the medical staff to detect delirium using the CAM. Results: In a 3-month period, 211 Patients were admitted in Cardiac ICU of CHLMultispeciality Hospital and Research Center. Out of which 198 were included in our observational study. The incidence of delirium at the end of the study was 21%. The number of delirious patients were 43 and non-delirious were 155. Age played an Important factor where 86% of Delirious patients were old aged. The LOS (Length of Stay) for Delirious and non-delirious patients were 6±1 vs 5±1 respectively. The SAS (Riker Agitation Scale) has the value of 4±1 vs 3±0.5, CAM (Confusion Assessment Method) has the value of 6±1 vs 3±1 and DDS (Delirium Detection Score) was 5±1 vs 3±1 for delirious vs non-delirious patients. The SAPS II (Simplied Acute Physiology Score II) Score for delirious patients was 23±1 and 20±2. The Incidences like Removal of Catheters were more frequent in this study with 20% in delirious patients and <1% Incidence in non-delirious patients. Removal of ET Tube had the Incidence of 5% vs <1%, Removal of Urinary Catheter 7% vs <1%, Removal of Ryle's Tube 7% vs <1%, respectively for delirious vs non-delirious patients.

2008 ◽  
Vol 9 (3) ◽  
pp. 269-269
Author(s):  
Callum Kaye

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.


2021 ◽  
Vol 33 (4) ◽  
pp. 251-260
Author(s):  
Eiad Habib ◽  
Abdul Hakim Almakadma ◽  
Mohieddin Albarazi ◽  
Somiya Jaimon ◽  
Rayd Almehizia ◽  
...  

2021 ◽  
pp. 088506662110668
Author(s):  
Andrew M. Koth ◽  
Titus Chan ◽  
Yuen Lie Tjoeng ◽  
R. Scott Watson ◽  
Leslie A. Dervan

Objective Delirium is an increasingly recognized hospital complication associated with poorer outcomes in critically ill children. We aimed to evaluate risk factors for screening positive for delirium in children admitted to a pediatric cardiac intensive care unit (CICU) and to examine the association between duration of positive screening and in-hospital outcomes. Study design Retrospective cohort study in a single-center quaternary pediatric hospital CICU evaluating children admitted from March 2014-October 2016 and screened for delirium using the Cornell Assessment of Pediatric Delirium. Statistical analysis used multivariable logistic and linear regression. Results Among 942 patients with screening data (98% of all admissions), 67% of patients screened positive for delirium. On univariate analysis, screening positive was associated with younger age, single ventricle anatomy, duration of mechanical ventilation, continuous renal replacement therapy, extracorporeal life support, and surgical complexity, as well as higher average total daily doses of benzodiazepines, opioids, and dexmedetomidine. On multivariable analysis, screening positive for delirium was independently associated with age <2 years, duration of mechanical ventilation, and greater than the median daily doses of benzodiazepine and opioid. In addition to these factors, duration of screening positive was also independently associated with higher STAT category (3-5) or medical admission, organ failure, acute kidney injury (AKI), and higher dexmedetomidine exposure. Duration of positive delirium screening was associated with both increased CICU and hospital length of stay (each additional day of positive screening was associated with a 3% longer CICU stay [95% CI = 1%-6%] and 2% longer hospital stay [95% CI = 0%-4%]). Conclusions Screening positive for delirium is common in the pediatric CICU and is independently associated with prolonged intensive care unit (ICU) and hospital stay. Longer duration of mechanical ventilation and higher sedative doses are independent risk factors for screening positive for delirium. Efforts aimed at reducing these exposures may decrease the burden of delirium in this population.


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


Author(s):  
Andrea Kirfel ◽  
Jan Menzenbach ◽  
Vera Guttenthaler ◽  
Johanna Feggeler ◽  
Andreas Mayr ◽  
...  

Abstract Background Postoperative delirium (POD) is a relevant and underdiagnosed complication after cardiac surgery that is associated with increased intensive care unit (ICU) and hospital length of stay (LOS). The aim of this subgroup study was to compare the frequency of tested POD versus the coded International Statistical Classification of Diseases and Related Health Problems (ICD) diagnosis of POD and to evaluate the influence of POD on LOS in ICU and hospital. Methods 254 elective cardiac surgery patients (mean age, 70.5 ± 6.4 years) at the University Hospital Bonn between September 2018 and October 2019 were evaluated. The endpoint tested POD was considered positive, if one of the tests Confusion Assessment Method for ICU (CAM-ICU) or Confusion Assessment Method (CAM), 4 'A's Test (4AT) or Delirium Observation Scale (DOS) was positive on one day. Results POD occurred in 127 patients (50.0%). LOS in ICU and hospital were significantly different based on presence (ICU 165.0 ± 362.7 h; Hospital 26.5 ± 26.1 days) or absence (ICU 64.5 ± 79.4 h; Hospital 14.6 ± 6.7 days) of POD (p < 0.001). The multiple linear regression showed POD as an independent predictor for a prolonged LOS in ICU (48%; 95%CI 31–67%) and in hospital (64%; 95%CI 27–110%) (p < 0.001). The frequency of POD in the study participants that was coded with the ICD F05.0 and F05.8 by hospital staff was considerably lower than tests revealed by the study personnel. Conclusion Approximately 50% of elderly patients who underwent cardiac surgery developed POD, which is associated with an increased ICU and hospital LOS. Furthermore, POD is highly underdiagnosed in clinical routine.


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