Delirium Screening Research Articles

A retrospective comparison of haloperidol and hydroxyzine combination therapy with haloperidol alone in the treatment of overactive delirium

For the treatment of delirium, antipsychotics such as haloperidol are used as standard treatments. However, haloperidol has a little sedative effect and may not be sufficiently effective in controlling overactive delirium. Hydroxyzine, an antihistamine, may be used in combination with haloperidol to supplement its sedative effect. The aim of this study was to investigate the effect of haloperidol alone or in combination with hydroxyzine on the improvement of overactive delirium retrospectively. Delirium was assessed from medical records using the Intensive Care Delirium Screening Checklist (ICDSC). The number of patients and days with an ICDSC score of < 4, indicating an absence of delirium after haloperidol alone or haloperidol and hydroxyzine was surveyed for 6days. A total of 157 patients were diagnosed with delirium from April 2019 to July 2021, of which 18 patients received haloperidol alone, and 21 patients received the combination of haloperidol and hydroxyzine for overactive delirium. The number of patients with a mean ICDSC score of < 4 on days 1-6 was two patients (11%) in the haloperidol groups and two patients (10%) in the combination of haloperidol and hydroxyzine group (P = 0.999). The days within < 4 of the ICDSC score on days 1-6 were 0.8 (1.3) and 0.8 (1.5), respectively (P = 0.848). Haloperidol alone and haloperidol plus hydroxyzine are both effective in the treatment of overactive delirium. However, the concomitant use of hydroxyzine with haloperidol may not improve the efficacy of treatment of overactive delirium compared to haloperidol alone.

Delirium on stroke units: a prospective, multicentric quality-improvement project

BackgroundPost-stroke delirium (POD) in patients on stroke units (SU) is associated with an increased risk for complications and poorer clinical outcome. The objective was to reduce the severity of POD by implementing an interprofessional delirium-management.MethodsMulticentric quality-improvement project on five SU implementing a delirium-management with pre/post-comparison. Primary outcome was severity of POD, assessed with the Nursing Delirium Screening Scale (Nu-DESC). Secondary outcome parameters were POD incidence, duration, modified Rankin Scale (mRS), length of stay in SU and hospital, mortality, and others.ResultsOut of a total of 799 patients, 59.4% (n = 475) could be included with 9.5% (n = 45) being delirious. Implementation of a delirium-management led to reduced POD severity; Nu-DESC median: pre: 3.5 (interquartile range 2.6–4.7) vs. post 3.0 (2.2–4.0), albeit not significant (p = 0.154). Other outcome parameters were not meaningful different. In the post-period, delirium-management could be delivered to 75% (n = 18) of delirious patients, and only 24 (53.3%) of delirious patients required pharmacological treatments. Patients with a more severe stroke and POD remained on their disability levels, compared to similar affected, non-delirious patients who improved.ConclusionsImplementation of delirium-management on SU is feasible and can be delivered to most patients, but with limited effects. Nursing interventions as first choice could be delivered to the majority of patients, and only the half required pharmacological treatments. Delirium-management may lead to reduced severity of POD but had only partial effects on duration of POD or length of stay. POD hampers rehabilitation, especially in patients with more severe stroke.RegistryDRKS, DRKS00021436. Registered 04/17/2020, www.drks.de/DRKS00021436.

Diagnostic accuracy of the Spanish version of the 4AT scale (4AT-ES) for delirium screening in older inpatients

Background and objectivesThe 4AT scale is a sensitive tool for screening delirium, which can be applied rapidly in clinical settings without any specific training. It has not been translated, adapted, and validated to assess Spanish older adults. The aims of the study are: to translate and adapt to Spanish culture the 4AT scale, to present evidence of the diagnostic accuracy of this version (4AT-ES) when applied in non-specialized hospital wards, and to assess the loss of diagnostic accuracy in presence of risk factors. MethodsA prospective sample was independently assessed on the 4AT-ES and the reference standard. One hundred and twenty-one inpatients (70+ years) for whom a psychiatric assessment was requested were included. Out of them, 50 were diagnosed with delirium. Nurses without specific training applied the 4AT-ES, and experienced psychiatrists cast the reference standard diagnosis (DSM-V criteria). ResultsPatients with delirium were older and had more risk factors (more previous delirium episodes, a higher likelihood of prior dementia/cognitive impairment) than controls. The 4AT-ES had excellent validity, sensitivity (96%) , and specificity (83.1%). The area under the curve was 0.918; in the subsample with any of those risk factors, its value did not decrease. ConclusionThe 4AT-ES version of the 4AT scale was developed. When applied by non-specifically trained, nursing staff it showed excellent validity, sensitivity, and specificity, even in a subsample with previous risk factors. All indices were comparable to the original version. We recommend its use for efficient delirium screening in hospitalized older patients with suspected delirium.

Current status of delirium assessment tools in the intensive care unit: a prospective multicenter observational survey

Delirium is a critical challenge in the intensive care unit (ICU) or high care unit (HCU) setting and is associated with poor outcomes. There is not much literature on how many patients in this setting are assessed for delirium and what tools are used. This study investigated the status of delirium assessment tools of patients in the ICU/HCU. We conducted a multicenter prospective observational study among 20 institutions. Data for patients who were admitted to and discharged from the ICU/HCU during a 1-month study period were collected from each institution using a survey sheet. The primary outcome was the usage rate of delirium assessment tools on an institution- and patient-basis. Secondary outcomes were the delirium prevalence assessed by each institution’s assessment tool, comparison of delirium prevalence between delirium assessment tools, delirium prevalence at the end of ICH/HCU stay, and the relationship between potential factors related to delirium and the development of delirium. Result showed that 95% of institutions used the Intensive Care Delirium Screening Checklist (ICDSC) or the Confusion Assessment Method for the ICU (CAM-ICU) to assess delirium in their ICU/HCU, and the remaining one used another assessment scale. The usage rate (at least once during the ICU/HCU stay) of the ICDSC and the CAM-ICU among individual patients were 64.5% and 25.1%, and only 8.2% of enrolled patients were not assessed by any delirium assessment tool. The prevalence of delirium during ICU/HCU stay was 17.9%, and the prevalence of delirium at the end of the ICU/HCU stay was 5.9%. In conclusion, all institutions used delirium assessment tools in the ICU/HCU, and most patients received delirium assessment. The prevalence of delirium was 17.9%, and two-thirds of patients had recovered at discharge from ICU/HCU.Trial registration number: UMIN000037834.

Improving delirium screening and recognition in UK hospitals: results of a multi-centre quality improvement project.

Backgrounddelirium is an acute severe neuropsychiatric condition associated with adverse outcomes, particularly in older adults. However, it is frequently under-recognised.Methodsthis multi-centre quality improvement project utilised a collaborative approach to implementation of changes at sites, with the aim to improve delirium screening, recognition and documentation on discharge summaries. Resources, including delirium guidelines and presentations, were shared between sites, and broad details of local interventions were collected. Three timepoints of data collection (14 March 2018, 14 September 2018 and 13 March 2019) were conducted to assess screening, recognition and documentation of delirium in unscheduled admissions of adults aged ≥65 years old. The impact of local interventions and site-specific factors was assessed using logistic regression analysis, adjusting for patient factors.Resultsa total of 3,013 patients (mean age 80.2, 53.8% females) were recruited across the three timepoints. Screening for delirium was associated with increased odds of recognition (aOR 4.75, CI 2.98–7.56; P < 0.001); this was not affected by grade/profession of screener. Rates of screening, recognition and discharge documentation improved across the three timepoints of data collection. The presence of a local delirium specialist team was associated with increased rates of screening for delirium (aOR 1.75, CI 1.41–2.18; P < 0.001), and the presence of a geriatric medicine team embedded into the admissions unit was associated with increased recognition rates (aOR 1.78, CI 1.09–2.92; P = 0.022).Conclusiondelirium screening is associated with improved recognition. Interventions that strive to improve screening within a culture of delirium awareness are encouraged.

Abstract 92: Delirium In-hospital Leads To Poor Short And Long-term Outcomes Among Treated And Non-treated Patients With Acute Ischemic Stroke

Background: Delirium in-hospital (DIH) is common among the critically ill. However, DIH incidence and outcomes are not well characterized among ischemic stroke (IS) patients, particularly those treated with intravenous tissue plasminogen activator (tPA) and / or mechanical thrombectomy (MT). Methods: Utilizing data from a healthcare system with standardized delirium screening protocols, DIH was determined by a positive 4AT / CAM-ICU screen or diagnosis codes. IS patients with tPA or MT were flagged and a subset with available 90-day modified Rankin Scale (mRS) were analyzed for shifts in mRS scores associated with DIH, via ordinal logistic regression models adjusted for age, stroke severity, tPA or MT, Charlson Comorbidity Index [CCI], prior stroke and sepsis / infections. Common odds ratios (OR) and 95% confidence intervals (CI) are reported. Results: Between May 2016 and June 2021, IS was the primary discharge diagnosis in 12,415 encounters (10,878 unique patients). DIH was documented in 41.6% of IS encounters, compared to 20.0% of non-IS encounters. Stroke-DIH patients (vs no-DIH Stroke) were older (median: 75 vs 65 years), more frequently female (53.3% vs 48.7%), with higher comorbidity burden (median CCI: 7 vs 5), longer hospital stays (median: 6 vs 3 days), higher in-hospital mortality (3.1% vs 0.5%), and fewer home discharges (36.2% vs 75.2%). Among a sub-cohort of 2,785 IS patients with 90-day mRS, fully adjusted model indicated lower mRS (OR, CI: 0.48, 0.41-0.57) for those with tPA or MT, and worse outcomes for DIH patients (OR, CI: 2.70, 2.26-3.23). Among 948 treated IS patients, DIH remained a significant risk for worse outcomes (OR, CI: 2.54, 1.89-3.43). Conclusion: Delirium was twice as common in IS patients and was a negative prognostic indicator of short and long-term outcomes among non-treated and treated IS patients. Active screening and management of DIH is critically important to improve stroke outcomes.

Abstract WP116: A Pilot Study Of The Fluctuating Mental Status Evaluation: A Novel Delirium Screening Tool For Patients With Stroke

Background: Delirium occurs frequently in patients with stroke but is often underrecognized. We aimed to develop a novel delirium screening tool designed specifically for stroke patients, and to test its feasibility and accuracy in a pilot study. Methods: We designed an easy-to-use 5-point instrument called the Fluctuating Mental Status Evaluation (FMSE) and tested it in a cohort of patients with intracerebral hemorrhage (ICH) who had daily delirium assessments throughout their admission. Expert ratings were performed by an attending neurointensivist or behavioral neurologist each afternoon using DSM-5 criteria, and were derived from bedside assessments and clinical data from the preceding 24 hours. Paired FMSE assessments were performed by patients’ clinical nurses after brief training on the use of the tool. Nursing assessments were aggregated over 24-hour periods (including day and night shifts), and accuracy of the FMSE was analyzed on both a per-assessment day and per-patient basis. Results: Among the 40 enrolled patients (mean age 71.1±12.2, median initial NIHSS score 16.5 [IQR 12-20]), 34 experienced delirium during their hospitalization. There were 306 total coma-free days with paired assessments, of which 208 (68%) were rated as days with delirium. Compared to expert ratings, an FMSE score ≥1 had 86% sensitivity and 74% specificity on a per-day basis, while a score ≥2 had 68% sensitivity and 83% specificity. On a per-patient basis, a score ≥1 at any point during admission had 97% sensitivity and 67% specificity in identifying patients who experienced delirium, while a score ≥2 had 94% sensitivity and 67% specificity. Conclusion: The FMSE is a feasible delirium screening tool in ICH patients, with high real-world sensitivity and specificity. Based on these results, we plan to validate the tool in a larger, more diverse cohort of stroke patients, using score cutoffs of ≥1 as “possible” delirium and ≥2 as “probable” delirium.

Delirium and long-term psychopathology following surgery in older adults

ObjectiveTo describe the risk of postoperative delirium and long-term psychopathology (depression, anxiety or post-traumatic stress syndrome (PTSS)) in older adults. Methods255 elderly patients (≥ 65 years) undergoing major surgery (planned surgical time > 60 min) in a tertiary hospital were compared to 76 non-surgical controls from general practice. Patients were assessed twice daily for postoperative delirium using the Confusion Assessment Method (CAM(-ICU)), nursing delirium screening scale (NuDESC) and validated chart review. Before surgery and 3 and 12 months thereafter, the participants filled in the Hospital Anxiety and Depression Scale (HADS), the Geriatric Depression Scale (GDS-15) and the Post-Traumatic Stress Syndrome-14-Questions Inventory (PTSS-14). Non-surgical controls filled in the same questionnaires with similar follow-up. ResultsPatients were more often male, had higher American Society of Anesthesiologists scores and more often had a spouse compared to controls (p < 0.005). Forty-three patients (18%) developed postoperative delirium, who were significantly older, had higher ASA scores and lower estimated IQ scores compared to the patients who did not develop delirium (p < 0.05). There were no differences in psychopathology at baseline and 3-month follow-up between patients and controls. At 12-months, surgical patients less frequently scored positive for depression (7% versus 16%) and anxiety (2% versus 10%) compared to nonsurgical controls (p < 0.05). We did not observe differences in occurrence of psychopathology between patients who had and had not developed postoperative delirium. ConclusionOur results suggest that the older surgical population, with or without postoperative delirium, does not appear to be at greater risk of developing psychopathology. Why does this paper matter?The older surgical population does not appear to be at greater risk of developing psychopathology, neither seems this risk influenced by the occurrence of postoperative delirium

Psychoactive medication therapy and delirium screening in skilled nursing facilities.

A positive delirium screen at skilled-nursing facility (SNF) admission can trigger a simultaneous diagnosis of Alzheimer's Disease or related dementia (AD/ADRD) and lead to psychoactive medication treatment despite a lack of evidence supporting use. This was a nationwide historical cohort study of 849,086 Medicare enrollees from 2011-2013 who were admitted to the SNF from a hospital without a history of dementia. Delirium was determined through positive Confusion Assessment Method screen and incident AD/ADRD through active diagnosis or claims. Cox proportional hazard models predicted the risk of receiving one of three psychoactive medications (i.e., antipsychotics, benzodiazepines, antiepileptics) within 7 days of SNF admission and within the entire SNF stay. Of 849,086 newly-admitted SNF patients (62.6% female, mean age 78), 6.1% had delirium (of which 35.4% received an incident diagnosis of AD/ADRD); 12.6% received antipsychotics, 30.4% benzodiazepines, and 5.8% antiepileptics. Within 7 days of admission, patients with delirium and incident dementia were more likely to receive an antipsychotic (relative risk [RR] 3.09; 95% confidence interval [CI] 2.99 to 3.20), or a benzodiazepine (RR 1.23; 95% CI 1.19 to 1.27) than patients without either condition. By the end of the SNF stay, patients with both delirium and incident dementia were more likely to receive an antipsychotic (RR 3.04; 95% CI 2.95 to 3.14) and benzodiazepine (RR 1.32; 95% CI 1.29 to 1.36) than patients without either condition. In this historical cohort, a positive delirium screen was associated with a higher risk of receiving psychoactive medication within 7 days of SNF admission, particularly in patients with an incident AD/ADRD diagnosis. Future research should examine strategies to reduce inappropriate psychoactive medication prescribing in older adults admitted with delirium to SNFs.

Ketamine-Associated Intraoperative Electroencephalographic Signatures of Elderly Patients With and Without Preoperative Cognitive Impairment.

Ketamine is typically used by anesthesiologists as an adjunct for general anesthesia and as a nonopioid analgesic. It has been explored for prevention of postoperative delirium, although results have been contradictory. In this study, we investigated the association of ketamine with postoperative delirium and specific encephalographic signatures. Furthermore, we examined these associations in the context of baseline neurocognition as measured by a validated assessment. We conducted a prospective observational study from January 2019 to December 2020. Ninety-eight patients aged ≥65 years and undergoing spine surgery scheduled for ≥3 hours were included in the study. All participants who completed the University of California San Francisco (UCSF) Brain Health Assessment preoperatively and postoperatively were assessed with the confusion assessment method for intensive care unit (CAM-ICU) and/or the Nursing Delirium Screening Scale (NuDESC). Patients had frontal electroencephalogram (EEG) recordings (SedLine Root, Masimo, Corp) quantitatively analyzed. We used 60 seconds of artifact-free EEG (without burst suppression) extracted from the middle of the maintenance period to calculate the normalized power spectral density (PSD). Comparisons were made between those who did or did not receive ketamine and according to results from neurocognitive assessments. Ninety-eight patients (of a total of 155, enrolled and consented) had EEG of sufficient quality for analysis (42 women). Overall, we found a significant increase in the EEG power in the moderate frequency range (10-20 Hz) in patients that received ketamine. When the patients were divided by their preoperative cognitive status, this result in the ketamine group only held true for the cognitively normal patients. Patients that were cognitively impaired at baseline did not demonstrate a significant change in EEG characteristics based on ketamine administration, but impaired patients that received ketamine had a significantly higher rate of postoperative delirium (52% ketamine versus 20% no ketamine) (odds ratio [OR], 4.36; confidence interval [CI], 1.02-18.22; P = .048). In patients determined to be preoperatively cognitively normal, the incidence of postoperative delirium was not significantly associated with ketamine administration (19% ketamine versus 17% no ketamine) (OR, 1.10; CI, 0.30-4.04; P = .5833). Ketamine-related changes in EEG are observed in a heterogeneous group of patients receiving spine surgery. This result was driven primarily by the effect of ketamine on cognitively normal patients and not observed in patients that were cognitively impaired at baseline. Furthermore, patients who were cognitively impaired at baseline and who had received ketamine were more likely to develop postoperative delirium, suggesting that cognitive vulnerability might be predicted by the lack of a neurophysiologic response to ketamine.

Comparison of delirium detection tools in acute care : Arapid review.

BackgroundDelirium is a frequent psychopathological syndrome in geriatric patients. It is sometimes the only symptom of acute illness and bears a high risk for complications. Therefore, feasible assessments are needed for delirium detection.Objective and methodsRapid review of available delirium assessments based on a current Medline search and cross-reference check with a special focus on those implemented in acute care hospital settings.ResultsA total of 75 delirium detection tools were identified. Many focused on inattention as well as acute onset and/or fluctuating course of cognitive changes as key features for delirium. A range of assessments are based on the confusion assessment method (CAM) that has been adapted for various clinical settings. The need for a collateral history, time resources and staff training are major challenges in delirium assessment. Latest tests address these through a two-step approach, such as the ultrabrief (UB) CAM or by optional assessment of temporal aspects of cognitive changes (4 As test, 4AT). Most delirium screening assessments are validated for patient interviews, some are suitable for monitoring delirium symptoms over time or diagnosing delirium based on collateral history only.ConclusionBesides the CAM the 4AT has become well-established in acute care because of its good psychometric properties and practicability. There are several other instruments extending and improving the possibilities of delirium detection in different clinical settings.Supplementary InformationThe online version of this article (10.1007/s00391-021-02003-5) contains supplementary material, which is available to authorized users.

Incidence and Risk Factors of Ventilator-Associated Pneumonia among Patients with Delirium in the Intensive Care Unit: A Prospective Observational Study.

Introduction The incidence and risk factors for ventilator-related pneumonia (VAP) in patients with delirium are deficient, and there is a lack of in-depth knowledge of the impact of VAP on outcomes in this population. We investigated the incidence, risk factors, and outcomes of VAP in patients with delirium. Materials and Methods This prospective observational study was performed in a surgical ICU at Be'sat Hospital in Hamadan, Iran, between 2018 and 2019. A total of 108 patients with delirium were identified using the Confusion Assessment Method (CAM) for the ICU and Intensive Care Delirium Screening Checklist (ICDSC) and enrolled in this study. The association between VAP and delirium, risk factors, and outcomes (ICU length of stay and ICU mortality) for VAP were investigated using the Cox proportional hazards model and logistic and simple linear regression analyses with a 95% confidence interval. Results Of 108 delirium patients, 86 patients (79.6%) underwent mechanical ventilation (MV) and 16 patients (18.6%) experienced VAP during ICU stay. The median onset of VAP was 6.5 (IQR 4.2–7.7) days after intubation. Delirium patients with VAP stayed longer in the ICU (21.68 ± 4.26 vs.12.93 ± 1.71, P < 0.001) and also had higher ICU mortality (31.25% vs. 0%, P < 0.001) than subjects without VAP. According to multivariate cox regression, the expected HR for VAP was 53.5% lower for patients with early-onset delirium than in patients with late-onset delirium (HR: 0.465, 95% CI: 0.241–0.894, P=0.022). However, the expected hazard for VAP was 1.854 times and 4.604 times higher in patients with longer ICU stay (HR: 1.854, 95% CI: 1.689–3.059, P=0.032) and in patients with a prolonged MV duration (HR: 4.604, 95%CI: 1.567–6.708, P=0.023). Conclusion According to the results, there seems to be an inverse relationship between early onset of delirium and VAP. This finding cannot be conclusively cited, and more studies in this filed should be conducted with a larger sample size. Furthermore, VAP in delirium patients is associated with increases in poor outcomes (higher ICU mortality) and the use of medical resources (longer stay in the ICU and MV duration).

Effect of earplug/eye mask on sleep and delirium in intensive care patients.

Environmental factors such as loud sounds and bright lights in intensive care units can cause sleep disorders and delirium. The present study aims to investigate the effects of the overnight use of earplugs and eye masks by intensive care patients on their sleep quality and the degree of delirium. This randomized controlled experimental study was conducted on the patients admitted to a coronary intensive care unit. The patients in the experimental group used earplugs and eye masks during the night, while those in the control group received only routine care. Data were collected using an information form, the Richards-Campbell sleep questionnaire (RCSQ), and the intensive care delirium screening checklist (ICDSC). The study included a total of 84 patients, 42 in the experimental group and 42 in the control group. The baseline average score of the patients in the experiment group on the RCSQ was 40.11 ± 16.55, with a Time 1 average score of 64.09 ± 14.07 and a Time 2 average score of 72.07 ± 11.75; their baseline average score on the ICDSC was 0.47 ± 0.50, with a Time 1 average score of 0.33 ± 065 and a Time 2 average score of 0.19 ± 039. The baseline average score of the patients in the control group on the RCSQ was 44.07 ± 7.30, with a Time 1 average score of 46.97 ± 9.22 and a Time 2 average score of 47.04 ± 11.53; the baseline average score of the control group on the ICDSC was 0.42 ± 0.50, with a Time 1 average score of 0.50 ± 0.70 and a Time 2 average score of 0.57 ± 0.66. A statistically significant difference was found between the Time 1 and Time 2 average scores of the experimental and control groups on the RCSQ and between the Time 2 average scores of the experimental and control groups on the ICDSC (U=198.00, P< .001; U=70.000, P< .001; U=614.000, P=·004 respectively). The earplugs and eye masks used by the intensive care patients overnight were associated with an increase in sleep quality and a decrease in the degree of delirium. The use of earplugs and eye masks is recommended for intensive care units in supporting sleep quality and preventing delirium.

Barriers and facilitators to nursing delirium screening in older emergency patients: a qualitative study using the theoretical domains framework.

delirium is common in older emergency department (ED) patients, but vastly under-recognised, in part due to lack of standardised screening processes. Understanding local context and barriers to delirium screening are integral for successful implementation of a delirium screening protocol. we sought to identify barriers and facilitators to delirium screening by nurses in older ED patients. we conducted 15 semi-structured, face-to-face interviews based on the Theoretical Domains Framework with bedside nurses, nurse educators and managers at two academic EDs in 2017. Two research assistants independently coded transcripts. Relevant domains and themes were identified. a total of 717 utterances were coded into 14 domains. Three dominant themes emerged: (i) lack of clinical prioritisation because of competing demands, lack of time and heavy workload; (ii) discordance between perceived capabilities and knowledge and (iii) hospital culture. this qualitative study explored nursing barriers and facilitators to delirium screening in older ED patients. We found that delirium was recognised as an important clinical problem; however, it was not clinically prioritised; there was a false self-perception of knowledge and ability to recognise delirium and hospital culture was a strong influencer of behaviour. Successful adoption of a delirium screening protocol will only be realised if these issues are addressed.

Delirium screening tools in the post-anaesthetic care unit: a systematic review and meta-analysis.

Delirium is a serious neurocognitive disorder among surgical patients in the post-anaesthetic care unit (PACU). Despite the development of screening tools to identify delirium, it is not clear which tool is the most accurate and reliable in assessing delirium in the PACU. To examine the diagnostic accuracy of delirium screening tools used in the PACU. A systematic literature search of CINAHL, MEDLINE, Embase, PsycINFO and Scopus was conducted, using MeSH terms and relevant keywords, from databases establishment to 23 April 2021. Studies were assessed for methodological quality using the Standards for Reporting of Diagnostic Accuracy Studies (STARD) tool. A total of 1503 studies were screened from the database search, four studies met the inclusion criteria for this review. Six delirium screening tools used in the PACU were identified in the selected studies. Three studies evaluated screening tools in adult surgical patients without cognitive impairment and dementia. Two studies evaluated screening tools among patients who were scheduled for elective surgery. Review results indicated that two tools, the 4A's test (4AT; sensitivity 96%; specificity 99%) and the 3min diagnostic interview for the Confusion Assessment Method (3D-CAM; sensitivity 100%; specificity 88%), had greatest validity and reliability as a screening tool for detecting delirium in the PACU. Results indicate the 4AT and the 3D-CAM are most accurate screening tools to detect delirium in the PACU. Further research is required to validate those tools among a broader surgical population, including patients with cognitive impairment, dementia and those undergoing emergency surgical procedures.

Postoperative delirium prediction using machine learning models and preoperative electronic health record data

BackgroundAccurate, pragmatic risk stratification for postoperative delirium (POD) is necessary to target preventative resources toward high-risk patients. Machine learning (ML) offers a novel approach to leveraging electronic health record (EHR) data for POD prediction. We sought to develop and internally validate a ML-derived POD risk prediction model using preoperative risk features, and to compare its performance to models developed with traditional logistic regression.MethodsThis was a retrospective analysis of preoperative EHR data from 24,885 adults undergoing a procedure requiring anesthesia care, recovering in the main post-anesthesia care unit, and staying in the hospital at least overnight between December 2016 and December 2019 at either of two hospitals in a tertiary care health system. One hundred fifteen preoperative risk features including demographics, comorbidities, nursing assessments, surgery type, and other preoperative EHR data were used to predict postoperative delirium (POD), defined as any instance of Nursing Delirium Screening Scale ≥2 or positive Confusion Assessment Method for the Intensive Care Unit within the first 7 postoperative days. Two ML models (Neural Network and XGBoost), two traditional logistic regression models (“clinician-guided” and “ML hybrid”), and a previously described delirium risk stratification tool (AWOL-S) were evaluated using the area under the receiver operating characteristic curve (AUC-ROC), sensitivity, specificity, positive likelihood ratio, and positive predictive value. Model calibration was assessed with a calibration curve. Patients with no POD assessments charted or at least 20% of input variables missing were excluded.ResultsPOD incidence was 5.3%. The AUC-ROC for Neural Net was 0.841 [95% CI 0. 816–0.863] and for XGBoost was 0.851 [95% CI 0.827–0.874], which was significantly better than the clinician-guided (AUC-ROC 0.763 [0.734–0.793], p < 0.001) and ML hybrid (AUC-ROC 0.824 [0.800–0.849], p < 0.001) regression models and AWOL-S (AUC-ROC 0.762 [95% CI 0.713–0.812], p < 0.001). Neural Net, XGBoost, and ML hybrid models demonstrated excellent calibration, while calibration of the clinician-guided and AWOL-S models was moderate; they tended to overestimate delirium risk in those already at highest risk.ConclusionUsing pragmatically collected EHR data, two ML models predicted POD in a broad perioperative population with high discrimination. Optimal application of the models would provide automated, real-time delirium risk stratification to improve perioperative management of surgical patients at risk for POD.

Using Telehealth to Improve the Accuracy of Delirium Screening by Bedside Critical Care Nurses.

Delirium affects up to 80% of patients in the intensive care unit (ICU) but is missed in up to 75% of cases. Telehealth in the ICU (tele-ICU) has become the standard for providing timely, expert care to remotely located ICUs. This pilot study assessed the feasibility and acceptability of using tele-ICU to increase the accuracy of delirium screening and recognition by ICU nurses. The pilot sites included 4 ICUs across 3 hospitals. A geriatrician with delirium expertise remotely observed 13 bedside ICU nurses administering the Confusion Assessment Method for the ICU (CAM-ICU) to patients in real time via the tele-ICU platform and subsequently provided training on CAM-ICU performance and delirium management. Training evaluation consisted of a validated spot check form, a 2-item satisfaction/change-of-practice survey, and a qualitative question on acceptability. Thirteen ICU nurses were observed performing 26 bedside delirium assessments. The top observed barriers to accurate delirium screening were CAM-ICU knowledge deficits, establishment of baseline cognition, and inappropriate use of the "unable to assess" designation. The mean percentage of correct observations improved from 40% (first observation) to 90% (second observation) (P < .001). All 13 nurses strongly agreed that the training was beneficial and practice changing. The use of tele-ICU to improve the accuracy of delirium screening by ICU nurses appears to be feasible and efficient for leveraging delirium expertise across multiple ICUs. Future studies should evaluate the effects of tele-ICU delirium training on patient-centered outcomes.

Acute peri-operative neurocognitive disorders: a narrative review.

Peri-operative neurocognitive disorders are the most common complication experienced by older individuals undergoing anaesthesia and surgery. Peri-operative neurocognitive disorders, particularly postoperative delirium, result in long-term poor outcomes including: death; dementia; loss of independence; and poor cognitive and functional outcomes. Recent changes to the nomenclature of these disorders aims to align peri-operative neurocognitive disorders with cognitive disorders in the community, with consistent definitions and clinical diagnosis. Possible mechanisms include: undiagnosed neurodegenerative disease; inflammation and resulting neuroinflammation; neuronal damage; and comorbid systemic disease. Pre-operative frailty represents a significant risk for poor postoperative outcomes; it is associated with an increase in the incidence of cognitive decline at 3 and 12 months postoperatively. In addition to cognitive decline, frailty is associated with poor functional outcomes following elective non-cardiac surgery. It was recently shown that 29% of frail patients died or experienced institutionalisation or new disability within 90 days of major elective surgery. Identification of vulnerable patients before undergoing surgery and anaesthesia is the key to preventing peri-operative neurocognitive disorders. Current approaches include: pre-operative delirium and cognitive screening; blood biomarker analysis; intra-operative management that may reduce the incidence of postoperative delirium such as lighter anaesthesia using processed electroencephalography devices; and introduction of guidelines which may reduce or prevent delirium and postoperative neurocognitive disorders. This review will address these issues and advocate for an approach to care for older peri-operative patients which starts in the community and continues throughout the pre-operative, intra-operative, postoperative and post-discharge phases of care management, involving multidisciplinary medical teams, as well as family and caregivers wherever possible.

Management of psychiatric disorders in patients with cancer.

Management of psychiatric disorders in patients with cancer.

Psychiatric management of Patients in intensive care units.

Psychiatric management of Patients in intensive care units.