Delirium in Hospitalized Older Patients: Recognition and Risk Factors

1998 ◽  
Vol 11 (3) ◽  
pp. 118-125 ◽  
Author(s):  
Sharon K. Inouye

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.

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


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.


2019 ◽  
Vol 13 (3) ◽  
pp. 133-140 ◽  
Author(s):  
Ioannis Leotsakos ◽  
Ioannis Katafigiotis ◽  
Ofer N. Gofrit ◽  
Mordechai Duvdevani ◽  
Dionysios Mitropoulos

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.


Geriatrics ◽  
2019 ◽  
Vol 4 (3) ◽  
pp. 52
Author(s):  
Khor ◽  
Ong ◽  
Tan ◽  
Low ◽  
Saedon ◽  
...  

The detection of delirium in acutely ill older patients is challenging with the lack of informants and the necessity to identify subtle and fluctuating signs. We conducted a cross-sectional study among older patients admitted to a university hospital in Malaysia to determine the presence, characteristics, and mortality outcomes of delirium. Consecutive patients aged ≥65years admitted to acute medical wards were recruited from August to September 2016. Cognitive screening was performed using the mini-mental test examination (MMSE) and the Confusion Assessment Method (CAM). The CAM-Severity (CAM-S) score was also performed in all patients. Of 161 patients recruited, 43 (26.7%) had delirium. At least one feature of delirium from the CAM-S short and long severity scores were present in 48.4% and 67.1%, respectively. Older age (OR: 1.07, 95% CI: 1.01–1.14), immobility (OR: 3.16, 95% CI: 1.18–8.50), cognitive impairment (OR: 5.04, 95% CI: 2.07–12.24), and malnutrition (OR: 3.37; 95% CI: 1.15–9.85) were significantly associated with delirium. Older patients with delirium had a higher risk of mortality (OR: 7.87, 95% CI: 2.42–25.57). Delirium is common among older patients in our setting. A large proportion of patients had altered mental status on admission to hospital although they did not fulfill the CAM criteria of delirium. This should prompt further studies on strategies to identify delirium and the use of newer, more appropriate assessment tools in this group of vulnerable individuals.


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.


2021 ◽  
Author(s):  
Lays Oliveira Carneiro ◽  
Ivã Taiuan Fialho Silva ◽  
Tayla Samanta Silva dos Santos ◽  
Pedro Antonio Pereira de Jesus

Introduction: Delirium is a common disorder in patients after stroke. We designed a study to evaluate the incidence of delirium and risk factors for its occurrence after stroke. Design and setting: Prospective cohort study at Hospital Geral Roberto Santos. Methods: Patients were admitted within 72h of ictus. Delirium was assessed using the Confusion Assessment Method in an Intensive Care Unit scale. Results: 279 patients were enrolled, with a mean age of 61.08 (± 13.05) years, 54.0% of whom were men. The incidence of delirium was 28% (n = 78). Delirium patients were older (68.9 ± 12.6 vs 58.8 ± 12.5; p <0.001) and had a higher NIHSS on admission [11 (7-15) vs 8 (5-12); p <0.001]. The occurrence of delirium was associated with a previous diagnosis of hypertension [RR = 2.62 (1.13-6.09)], hemorrhagic stroke [RR 1.94 (1.13-2.86)], cardioembolic etiology [RR 2.21 (1.22-3.97)] and infection during hospitalization [RR 5.27 (3.54-7.84)]. Independent predictors of delirium: age ≥ 65 years [OR 1.06 (1.02 -1.10)], epileptic seizures in ictus [OR 6.28 (1.65 - 23.91)], infection [OR 14.17 (6.39 - 31.43)] and hemorrhagic stroke [OR 4.04 (1.51-10.78)]. Conclusion: Delirium is a common complication after acute stroke, affecting 28% of patients. In view of the importance of identifying risk factors in the acute setting of stroke, further studies are needed to elucidate the association of the findings with the occurrence of delirium.


2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Koen Milisen ◽  
Bastiaan Van Grootven ◽  
Wim Hermans ◽  
Karen Mouton ◽  
Layth Al Tmimi ◽  
...  

Abstract Background Although many studies have reported numerous risk factors for postoperative delirium, data are scarce about preoperative anxiety as a risk factor. The study aimed to investigate the association between preoperative anxiety and postoperative delirium in older patients undergoing cardiac surgery. Methods Secondary data analysis of a randomized, observer-blind, controlled trial. A total of 190 patients 65 years or older and admitted to the intensive care unit and cardiac surgery unit of a university hospital scheduled for elective on-pump cardiac surgery were included. State anxiety was measured preoperatively using the Amsterdam Preoperative Anxiety and Information Scale and the Visual Analogue Scale for anxiety. Incidence of delirium was measured during the first 5 postoperative days using the Confusion Assessment Method for Intensive Care Unit (when ventilated), or the 3 Minute Diagnostic Interview for Confusion Assessment Method (when extubated) and by daily chart review. Results Preoperative state anxiety was reported by 31% of the patients and 41% had postoperative delirium. A multiple step logistic regression analyses revealed no association between preoperative anxiety and postoperative delirium. Significant risk factors for postoperative delirium were age (OR = 1.10, 95% CI (1.03–1.18)), activities of daily living (0.69, 95% CI (0.50–0.96)), diabetes mellitus (OR = 3.15, 95% CI (1.42–7.00)) and time on cardiopulmonary bypass (OR = 1.01, 95% CI (1.00 to 1.02)). Conclusions No relationship could be found between preoperative anxiety and postoperative delirium.


2020 ◽  
Vol 38 (15_suppl) ◽  
pp. e24024-e24024
Author(s):  
Rawad Elias ◽  
Ilene Staff ◽  
Stephen Thompson ◽  
Christine Waszynski ◽  
Jennifer Zanchi ◽  
...  

e24024 Background: Older adults are at increased risk for postoperative delirium (POD). This risk might be higher in patients with cancer as underlying malignancy and its complications predispose individuals to develop delirium. Therefore, it is important to evaluate the onset of delirium in this patient population especially as POD is associated with increased risk of rehospitalization, decline in cognitive function, morbidity and mortality. Methods: We performed a retrospective review of patients aged ≥ 70 years admitted January 2017 through July 2019 to a tertiary care referral center for a high-risk surgery, defined as associated with a mortality risk greater than 1%. Cancer related surgeries (CRS) were identified through cross matching with Cancer Registry. Patients who had delirium assessment in the postoperative setting using the Confusion Assessment Method (CAM) were included. Chi-square tests of proportion, Wilcoxon Ranked Sum and multivariate logistic regression analyses were conducted. Results: A total of 2340 patients were included in this analysis, 315 of whom had (CRS). Overall, the age (median, IQR) of patients at surgery was 76 years (72-80) and the length of stay (LOS) was 7 (4-11) days. Patients receiving CRS were younger (75, 72-79) than those with non-CRS (76, 72-81) (p = 0.022); had a shorter post-operative LOS (4, 2-7 vs. 5, 3-8; p > 0.001), and were less likely to develop POD (7.6% vs. 16.1%; p < 0.001). Among patients receiving CSR, those who developed POD were older (78 vs. 74; p = 0.008) and had longer post-operative LOS (14.0 vs. 4.0; p < 0.001). Those having experienced radiotherapy (RT) for cancer within the year before the surgery, were more likely to develop POD (40.0% vs. 6.6% p. < 0.001). Chemotherapy in the year prior to surgery did not increase the risk of POD (6.1% vs. 7.8%; p = 0.721). Among those having non-CRS, a cancer diagnosis did not affect POD. A logistic regression predicting POD indicated that the lower likelihood of POD following CRS was independent of age or gender (OR = 0.40; p < .001); RT within one year prior was independent predictor of higher POD (OR = 5.48; p = 0.003). Our data presentation will include further analysis of POD risk factors. Conclusions: Although older adults receiving CRS were significantly less likely to develop delirium than patients with other high-risk surgeries, it is still important to evaluate POD in this population due to its impact of patients’ outcomes. Further understanding of POD risk factors, such as preoperative RT, would allow the development of targeted interventions that might lessen the risk.


2013 ◽  
Vol 2013 ◽  
pp. 1-8 ◽  
Author(s):  
C. Travers ◽  
G. J. Byrne ◽  
N. A. Pachana ◽  
K. Klein ◽  
L. Gray

Objectives. Australian data regarding delirium in older hospitalized patients are limited. Hence, this study aimed to determine the prevalence and incidence of delirium among older patients admitted to Australian hospitals and assess associated outcomes.Method. A prospective observational study (n=493) of patients aged ≥70 years admitted to four Australian hospitals was undertaken. Trained research nurses completed comprehensive geriatric assessments using standardized instruments including the Confusion Assessment Method to assess for delirium. Nurses also visited the wards daily to assess for incident delirium and other adverse outcomes. Diagnoses of dementia and delirium were established through case reviews by independent physicians.Results. Overall, 9.7% of patients had delirium at admission and a further 7.6% developed delirium during the hospital stay. Dementia was the most important predictor of delirium at (OR=3.18, 95% CI: 1.65–6.14) and during the admission (OR=4.82; 95% CI: 2.19–10.62). Delirium at and during the admission predicted increased in-hospital mortality (OR=5.19, 95% CI: 1.27–21.24;OR=31.07, 95% CI: 9.30–103.78).Conclusion.These Australian data confirm that delirium is a common and serious condition among older hospital patients. Hospital clinicians should maintain a high index of suspicion for delirium in older patients.


2021 ◽  
Vol 4 (12) ◽  
pp. e2137267
Author(s):  
Jordan Oberhaus ◽  
Wei Wang ◽  
Angela M. Mickle ◽  
Jennifer Becker ◽  
Catherine Tedeschi ◽  
...  

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