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

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.

2019 ◽  
Vol 161 (5) ◽  
pp. 807-813 ◽  
Author(s):  
Yiru Wang ◽  
Huiqian Yu ◽  
Hui Qiao ◽  
Chan Li ◽  
Kaizheng Chen ◽  
...  

Objective To explore the risk factors and incidence of postoperative delirium (POD) in patients undergoing laryngectomy for laryngeal cancer. Study Design Prospective cohort study. Setting Shanghai Eye, Ear, Nose, and Throat Hospital, Fudan University. Subjects and Methods A total of 323 patients underwent laryngectomy from April 4, 2018, to December 28, 2018. Perioperative data were collected. The primary outcome was the presence of POD as defined by the Confusion Assessment Method diagnostic algorithm. Univariate and multivariable logistic regression analyses were used to identify risk factors associated with POD. Results Of the patients who underwent laryngectomy during the study period, 99.1% were male, with a mean age of 60.0 years. Of these patients, 28 developed POD, with most episodes (88.1%) occurring during the first 3 postoperative days. The type of POD was hyperactive in 7 cases and hypoactive in 21 cases. The mean duration of POD was 1 day. The mean Delirium Rating Scale-Revised-98 score (a measure of POD severity) was 11.5. For the multivariable analysis, risk factors associated with POD included advanced cancer stage, lower educational level, higher American Society of Anesthesiologists classification, and intraoperative hypotension lasting at least 30 minutes. Intraoperative dexmedetomidine use was protective against POD. Conclusion This study identified risk factors associated with POD, providing a target population for quality improvement initiatives. Furthermore, intraoperative dexmedetomidine use can reduce POD.


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.


1999 ◽  
Vol 11 (4) ◽  
pp. 431-438 ◽  
Author(s):  
Darryl B. Rolfson ◽  
Janet E. McElhaney ◽  
Gian S. Jhangri ◽  
Kenneth Rockwood

In this prospective cohort of 71 elderly patients undergoing cardiac surgery, each subject was interviewed before and after surgery to detect incident delirium using the Confusion Assessment Method (CAM), the Mini-Mental State Examination (MMSE), the Clock Test, and a health record review. The first 41 were assessed by a physician and the remaining 30 by two study nurses. Delirium was then diagnosed by a physician using DSM-III-R criteria. Delirium was present in 23 subjects (32.4%). The sensitivity of the CAM differed significantly when administered by physicians compared to nurses (1.00 vs. .13). When standard cutoffs were used, neither the MMSE nor the Clock Test were found to be sensitive markers for delirium (.30 and .09, respectively). Recognition of delirium by charting was superior in nurses compared to physicians (.83 vs. .30). We conclude that the sensitivity of markers for delirium, such as the CAM and health record documentation, is dependent on the training background of the operator.


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.


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.


Author(s):  
Layth Al Tmimi ◽  
Marc Van de Velde ◽  
Bart Meyns ◽  
Bart Meuris ◽  
Paul Sergeant ◽  
...  

AbstractBackground:To investigate the predictive value of S100 (biochemical marker of neuroglial injury) for the occurrence of postoperative delirium (POD) in patients undergoing off-pump coronary artery bypass (OPCAB)-surgery.Methods:We enrolled 92 patients older than 18 years undergoing elective OPCAB-surgery. Serum-levels of S100 were determined at baseline (BL), end of surgery (EOS) and on the first postoperative day (PD1). Postoperatively, all-patients were evaluated daily until PD5 for the presence of POD using the confusion assessment method (CAM) or the confusion assessment method for the intensive care unit (CAM-ICU) for patients in the intensive care unit (ICU).Results:The overall incidence of POD was 21%. S100-values on PD1 significantly predicted the occurrence of POD during the later hospital stay [area under the curve (AUC)=0.724 (95% confidence interval (CI): 0.619–0.814); p=0.0001] with an optimal cut-off level of 123 pg mLConclusions:S100-levels <123 pg mL


2002 ◽  
Vol 94 (6) ◽  
pp. 1628-1632 ◽  
Author(s):  
Khwaja J. Zakriya ◽  
Colleen Christmas ◽  
James F. Wenz ◽  
Shawn Franckowiak ◽  
Ross Anderson ◽  
...  

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.


2017 ◽  
Vol 7 (2) ◽  
pp. 240-248 ◽  
Author(s):  
Gideon A. Caplan ◽  
JIan Tai ◽  
Fazrul Mohd Hanizan ◽  
Catherine L. McVeigh ◽  
Mark A. Hill ◽  
...  

Background/Aims: Delirium and the apolipoprotein E ε4 allele are risk factors for late-onset Alzheimer disease (LOAD), but the connection is unclear. We looked for an association. Methods: Inpatients with delirium (n = 18) were compared with LOAD outpatients (n = 19), assaying blood and cerebrospinal fluid (CSF) using multiplex ELISA. Results: The patients with delirium had a higher Confusion Assessment Method (CAM) score (5.6 ± 1.2 vs. 0.0 ± 0.0; p < 0.001) and Delirium Index (13.1 ± 4.0 vs. 2.9 ± 1.2; p = 0.001) but a lower Mini-Mental State Examination (MMSE) score (14.3 ± 6.8 vs. 20.8 ± 4.6; p = 0.003). There was a reduction in absolute CSF apolipoprotein E level during delirium (median [interquartile range]: 9.55 μg/mL [5.65–15.05] vs. 16.86 μg/mL [14.82–20.88]; p = 0.016) but no differences in apolipoprotein A1, B, C3, H, and J. There were no differences in blood apolipoprotein levels, and no correlations between blood and CSF apolipoprotein levels. CSF apolipoprotein E correlated negatively with the CAM score (r = –0.354; p = 0.034) and Delirium Index (r = –0.341; p = 0.042) but not with the Acute Physiology and Chronic Health Evaluation (APACHE) index, or the MMSE or Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE). Conclusion: Reduced CSF apolipoprotein E levels during delirium may be a mechanistic link between two important risk factors for LOAD.


Sign in / Sign up

Export Citation Format

Share Document