An online delirium detection tool: Cross-cultural adaptation of a Chinese version of the Family Confusion Assessment Method.

BACKGROUND: Intensive care unit (ICU) delirium is a common complication in older critically ill patients that has a significant impact. The Family Confusion Assessment Method (FAM-CAM) is a vital tool for assisting family members in identifying delirium; however, no study has yet been reported on the Chinese version of the scale. OBJECTIVES: The objective of this study was to translate the FAM-CAM into a Chinese version and to verify its effectiveness for delirium detection in an online patient visit setting. METHODS: This was a cross-sectional study. The FAM-CAM was translated to Chinese according to the International Society for Pharmacoeconomics and Outcomes Research guidelines. Patients and family members were recruited to participate in delirium assessments in three ICUs of one hospital. Family members then used the Chinese version of the FAM-CAM to assess for delirium via online visitation, and ICU nurses assessed patients for delirium using the Intensive Care Delirium Screening Checklist (ICDSC). Results were then compared between family members' and nurses' assessments. RESULTS: Overall, 190 critically ill patients and 190 family members were included, of whom 117 (61.6%) were assessed for delirium using the Intensive Care Delirium Screening Checklist. The Cohen's kappa coefficient between the Intensive Care Delirium Screening Checklist and FAM-CAM was 0.759 (P < 0.01). The sensitivity of the Chinese version of the FAM-CAM was 0.880, specificity was 0.890, positive predictive value was 0.928, negative predictive value was 0.823, and area under the receiver operating characteristic curve was 0.881 (95% confidence interval: 0.872-0.935, P < 0.01). CONCLUSION: The Chinese version of the FAM-CAM was shown to effectively help families detect delirium and was suggested as a crucial tool for assisting ICU nurses in the early identification of delirium. This tool may effectively be used to assess delirium during online visits.

Incidence and Risk Factors for ICU-Associated Delirium in the Alert Geriatric Trauma Population.

BACKGROUND: This study analyzed the overall incidence of delirium, comorbid conditions, injury patterns, and pharmacological risk factors for the development of delirium in an alert, geriatric trauma population. METHODS: IRB-approved, prospective, consecutive cohort series at two Southeastern Level 1 trauma centers from June 11 to August 15, 2023. Delirium was assessed using the Confusion Assessment Method (CAM) score. Comorbidities and medications were detailed from electronic medical records. Inclusion criteria: age ≥55, GCS ≥14, and ICU admission for trauma. Patients on a ventilator were excluded. Data was analyzed using SPSS version 28 (Armonk, NY: IBM Corp). RESULTS: In total, 196 patients met inclusion criteria. Incidences of delirium for Hospital 1 (n = 103) and Hospital 2 (n = 93) were 15.5% and 12.9%, respectively, with an overall incidence of 14.3% and with no statistical differences between hospitals (P = .599). CAD, CKD, dementia, stroke history, and depression were statistically significant risk factors for developing delirium during ICU admission. Inpatient SSRI/SNRIs, epinephrine/norepinephrine, and lorazepam were significant risk factors. Injury patterns, operative intervention, and use of lidocaine infusions and gabapentin were not statistically significant in delirium development. Using binary linear regression (BLR) analysis, independent risk factors for delirium were dementia, any stage CKD, home SSRI/SRNI prescription, any spine injury and cerebrovascular disease, or injury. DISCUSSION: Comorbidities of CAD, CHF, CKD, and depression, and these medications: home lorazepam and ICU epinephrine/norepinephrine statistically are more common in patients developing delirium. Dementia, CKD, home SSRI/SRNI and stroke/cerebrovascular disease/injury, and spine injuries are independent predictors by BLR.

Development and Usability Testing of a Mobile App-Based Clinical Decision Support System for Delirium: Randomized Crossover Trial.

Background: The 3-Minute Diagnostic Interview for Confusion Assessment Method-Defined Delirium (3D-CAM) is an instrument specially developed for the assessment of delirium in general wards, with high reported sensitivity and specificity. However, the use of the 3D-CAM by bedside nurses in routine practice showed relatively poor usability, with multiple human errors during assessment. Objective: This study aimed to develop a mobile app-based delirium assessment tool based on the 3D-CAM and evaluate its usability among older patients by bedside nurses. Methods: The Delirium Assessment Tool With Decision Support Based on the 3D-CAM (3D-DST) was developed to address existing issues of the 3D-CAM and optimize the assessment process. Following a randomized crossover design, questionnaires were used to evaluate the usability of the 3D-DST among older adults by bedside nurses. Meanwhile, the performances of both the 3D-DST and the 3D-CAM paper version, including the assessment completion rate, time required for completing the assessment, and the number of human errors made by nurses during assessment, were recorded, and their differences were compared. Results: The 3D-DST included 3 assessment modules, 9 evaluation interfaces, and 16 results interfaces, with built-in reminders to guide nurses in completing the delirium assessment. In the usability testing, a total of 432 delirium assessments (216 pairs) on 148 older adults were performed by 72 bedside nurses with the 3D-CAM paper version and the 3D-DST. Compared to the 3D-CAM paper version, the mean usability score was significantly higher when using the 3D-DST (4.35 vs 3.40; P<.001). The median scores of the 6 domains of the satisfactory evaluation questionnaire for nurses using the 3D-CAM paper version and the 3D-DST were above 2.83 and 4.33 points, respectively (P<.001). The average time for completing the assessment reduced by 2.1 minutes (4.4 vs 2.3 min; P<.001) when the 3D-DST was used. Conclusions: This study demonstrated that the 3D-DST significantly improved the efficiency of delirium assessment and was considered highly acceptable by bedside nurses.

Reliability and Validity of the Spanish Adaptation of the Stanford Proxy Test for Delirium in Two Clinical Spanish-Speaking Communities.

BACKGROUND: Delirium is the most prevalent neuropsychiatric syndrome experienced by patients admitted to inpatient clinical units, occurring in at least 20% of medically hospitalized patients and up to 85% of those admitted to critical care units. Although current guidelines recommend the implementation of universal prevention strategies, the use of management strategies largely depends on constant surveillance and screening. This allows for the timely diagnosis and correction of its underlying causes and implementation of management strategies. OBJECTIVE: It was to adapt and analyze the Spanish adaptation of the Stanford Proxy Test for Delirium (S-PTDsv) instrument for its use among Spanish-speaking populations. The S-PTD is an instrument consisting of 13 observational items to be completed by a clinician observer, usually the patient's nurse. The completion of the questionnaire takes about 1 minute and does not require the active participation of the person evaluated, which has important clinical advantages compared to other available instruments (e.g., the Confusion Assessment Method). METHODS: The psychometric properties of the S-PTDsv were evaluated in a population of 123 patients using a quantitative, cross-sectional design. All subjects were over 18 years of age and hospitalized in various inpatient medico-surgical and intensive care unit services, either at the Barcelona Clinical Hospital (Barcelona, Spain) or the UC-Christus Health Network Clinical Hospital (Santiago, Chile, S.A.). The ultimate diagnosis of delirium was made by a member of the Psychiatry Consult Service by means of an independent neuropsychiatric evaluation based on the Fifth Edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) criteria, published in 2013, which is the latest version of the diagnostic manual. All study tests were performed by study personnel who were blinded to each other's test results within an hour of each other. RESULTS: In the receiver operator characteristic (ROC) curve analysis, the S-PTDsv demonstrated excellent classification qualities when compared with the DSM-5 as the classification reference standard. Using a cutoff point of ≥3, the S-PTDsv had a sensitivity of 94% and a specificity of 97%. The area under the curve indicator was equal to 0.95, suggesting the S-PTDsv has an excellent overall performance in accurately identifying cases of delirium. Accordingly, the S-PTDsv's positive predictive value = 0.93, and the negative predictive value = 0.97. The internal reliability measured with Cronbach's alpha was 0.96. Confirmatory factor analysis revealed a 1-dimensional structure with high loadings (>0.72), demonstrating that all items similarly contribute to the total diagnostic dimension, suggesting adequate construct validity. This provided evidence of convergent validity. CONCLUSIONS: The performance of the S-PTDsv, as compared to a blinded neuropsychiatric assessment based on DSM-5, indicates that it is an effective instrument for the detection of delirium, in the Spanish-speaking populations. These results are comparable and consistent with previously published studies in the English language version.

Postoperative delirium in 47 379 individuals undergoing transcatheter aortic valve replacement: a systematic review and meta-analysis.

Objective: The study aims to discuss the assessment methods used for the incidence of in-hospital postoperative delirium (IHPOD) in transcatheter aortic valve replacement (TAVR) patients and explore possible strategies for preventing and reducing postoperative complications in the geriatric population. Methodology: An electronic search of PubMed, Embase, BioMedCentral, Google Scholar, and the Cochrane Central Register of Controlled Trials was conducted up to August 2021, to identify studies on the IHPOD following TAVR in patients above 70 years. The primary objective of the study was to determine the incidence of delirium following TAVR and procedures like transfemoral (TF) and non-TF approaches. The secondary objectives were to determine the incidence of stroke and incidence according to the confusion assessment method (CAM) diagnostic tool. The authors only included studies published in English and excluded patients with comorbidities and studies with inaccessible full-text. Results: Among the selected 42 studies with 47 379 patients, the incidence of IHPOD following TAVR was 10.5% (95% CI: 9.2-11.9%, I2=95.82%, P<0.001). Incidence based on CAM was 15.6% (95% CI: 10.5-20.7%, I2=95.36%, P<0.001). The incidence of IHPOD after TF-TAVR was 9.3% (95% CI: 7.6-11.0%, I2=94.52%, P<0.001), and after non-TF TAVI was 25.3% (95% CI: 15.4-35.1%, I2=92.45%, P<0.001). The incidence of stroke was 3.7% (95% CI: 2.9-4.5%, I2=89.76%, P<0.001). Meta-regression analyses between mean age (P=0.146), logistic EuroSCORE (P=0.099), or percentage of participants treated using the TF approach (P=0.276) were nonsignificant while stroke (P=0.010) was significant. When considering these variables, the residual heterogeneity remained high indicating that other variables influence the heterogeneity. Conclusion: IHPOD following TAVR was observed in 10.5% of individuals and in 15.6% using CAM. Its incidence was found to be three times higher after non-TF TAVR (25.3%) compared to TF TAVR (9.3%). Stroke showed an incidence of 3.7% after TAVR and was found to be significantly associated with the risk of developing delirium following TAVR. Further studies are needed to evaluate possible causes and risk factors responsible for delirium and to assess the role of anesthesia and cerebral embolic protection in preventing delirium after TAVR.

Delirium assessment tools among hospitalized older adults: A systematic review and metaanalysis of diagnostic accuracy.

Delirium is a common neuropsychiatric syndrome that is often overlooked in clinical settings. The most accurate instrument for screening delirium has not been established. This study aimed to compare the diagnostic accuracy of the 4 'A's Test (4AT), Nursing Delirium Screening Scale (Nu-DESC), and Confusion Assessment Method (CAM) in detecting delirium among older adults in clinical settings. These assessment tools feature concise item sets and straightforward administration procedures. Five electronic databases were systematically searched from their inception to September 7, 2022. Studies evaluating the sensitivity and specificity of the 4AT, Nu-DESC, and CAM against the Diagnostic and Statistical Manual of Mental Disorders or International Classification of Diseases as the reference standard were included. Bivariate random effects model was used to summarize the sensitivity and specificity results. A total of 38 studies involving 7378 patients were included. The 4AT, Nu-DESC, and CAM had comparable sensitivity in detecting delirium (0.76, 0.78, and 0.80, respectively). However, the specificity of the CAM was higher than that of the 4AT (0.98 vs 0.89, P = .01) and Nu-DESC 0.99 vs 0.90, P = .003). Diagnostic accuracy was moderated by the percentage of women, acute care setting, sample size, and assessors. The three tools exhibit comparable sensitivity, and the CAM has the highest specificity. Based on the feasibility of the tools, nurses and clinical staffs could employ the Nu-DESC and the 4AT on screening out positive delirium cases and integrate these tools into daily practice. Further investigations are warranted to verify our findings.

Optimal strategy for delirium detection in older patients admitted to intensive care unit after non-cardiac surgery.

Background: Delirium detection is challenging due to the fluctuating nature and frequent hypoactive presentation. This study aimed to determine an optimal strategy that detects delirium with higher sensitivity but lower effort in older patients admitted to the intensive care unit (ICU) after surgery. Methods: This was a secondary analysis of the database from a randomized trial. Seven hundred older patients (aged ≥65 years) who were admitted to the ICU after elective noncardiac surgery were enrolled. Delirium was assessed with the Confusion Assessment Method for the ICU (CAM-ICU) twice daily during the first 7 days postoperatively. The sensitivity of different strategies in detecting delirium were analyzed and compared. Results: Of all enrolled patients, 111 (15.9%; 95% CI: 13.3% to 18.8%) developed at least one episode of delirium during the first 7 postoperative days. Among patients who developed delirium, 60.4% (67/111) had their first delirium onset on postoperative day 1, 84.7% (94/111) by the end of day 2, 91.9% (102/111) by the end of day 3, and 99.1% (110/111) by the end of day 4. Compared with delirium assessment twice daily for 7 days, twice-daily measurements for 5 days detected 100% of delirium patients with 71% efforts; twice-daily measurements for 4 days detected 99% (95% CI: 94% to 100%) of delirium patients with 57% efforts; twice-daily assessment for 3 days detected 92% (95% CI: 85% to 96%) of delirium patients with only 43% efforts. Conclusions: For older patients admitted to the ICU after elective noncardiac surgery, it is reasonable to detect delirium with the CAM-ICU twice daily for no more than 5 days, and if the personnel and funds are insufficient, 4 days could be sufficient.

The effects of a sensory stimulation intervention for preventing delirium in a surgical intensive care unit: A randomized controlled trial.

BACKGROUND: Despite extensive efforts and advances in developing and fostering evidence-based delirium prevention interventions, the incidence of delirium remains high in hospitalized patients. Evidence suggests that sensory stimulation is a core component in interventions to prevent delirium among critically ill patients. However, its impact on the occurrence and outcomes of delirium is poorly understood. AIM: To evaluate the effects of a sensory stimulation intervention on preventing delirium in a surgical intensive care unit (ICU). STUDY DESIGN: A prospective, assessor-blind, parallel-group randomized controlled trial. Adult patients were recruited from a surgical ICU of one tertiary hospital in Guangzhou, China. Participants in the intervention group received a daily 30-min auditory and visual stimulation session for a week, taking into consideration the participants' predefined condition and intervention protocol. The primary outcomes were delirium incidence and delirium-free days, and the secondary outcomes were delirium duration, severity and the first occurrence of delirium. Demographic and clinical data were collected at recruitment, and delirium was assessed three times a day for seven consecutive days using Confusion Assessment-ICU. RESULTS: One hundred and fifty-two participants were randomly assigned to intervention or control groups. For primary outcomes, there were fewer patients with delirium in the intervention group than in the control group (10 vs. 19, risk ratio = 0.53), although statistical significance was not reached. The result showed that there were longer delirium-free days among participants in the intervention group than in the control group (3.66 vs. 2.84, p = .019). For secondary outcomes, the intervention could significantly reduce delirium duration (1.70 ± 0.82 vs. 4.53 ± 2.74 days, p = .004) and delirium severity (3.70 ± 1.25 vs. 5.68 ± 1.57, p = .002). The Kaplan-Meier curve showed the intervention group had a significantly delayed first occurrence of delirium compared with the control group (p = .043). CONCLUSIONS: The study did not provide significant evidence to support that sensory stimulation could reduce the incidence of delirium, but significant difference on delirium-free days. RELEVANCE TO CLINICAL PRACTICE: This study provides evidence-based practice for clinical healthcare providers to adopt the sensory stimulation protocol to prevent delirium, significantly reducing delirium duration and severity.

Predicting hospital mortality and length of stay: A prospective cohort study comparing the Intensive Care Delirium Screening Checklist versus Confusion Assessment Method for the Intensive Care Unit.

OBJECTIVE: The objective of this study was to compare two tools, the Intensive Care Delirium Screening Checklist (ICDSC) and Confusion Assessment Method for the intensive care unit (ICU) (CAM-ICU), for their predictive validity for outcomes related to delirium, hospital mortality, and length of stay (LOS). METHODS: The prospective study conducted in six medical ICUs at a tertiary care hospital in Taiwan enrolled consecutive patients (≥20 years) without delirium at ICU admission. Delirium was screened daily using the ICDSC and CAM-ICU in random order. Arousal was assessed by the Richmond Agitation-Sedation Scale (RASS). Participants with any one positive result were classified as ICDSC- or CAM-ICU-delirium groups. RESULTS: Delirium incidence evaluated by the ICDSC and CAM-ICU were 69.1% (67/97) and 50.5% (49/97), respectively. Although the ICDSC identified 18 more cases as delirious, substantial concordance (κ = 0.63; p < 0.001) was found between tools. Independent of age, Acute Physiology and Chronic Health Evaluation II score, and Charlson Comorbidity Index, both ICDSC- and CAM-ICU-rated delirium significantly predicted hospital mortality (adjusted odds ratio: 4.93; 95% confidence interval [CI]:1.56 to 15.63 vs. 2.79; 95% CI: 1.12 to 6.97, respectively), and only the ICDSC significantly predicted hospital LOS with a mean of 17.59 additional days compared with the no-delirium group. Irrespective of delirium status, a sensitivity analysis of normal-to-increased arousal (RASS≥0) test results did not alter the predictive ability of ICDSC- or CAM-ICU-delirium for hospital mortality (adjusted odds ratio: 2.97; 95% CI: 1.06 to 8.37 vs. 3.82; 95% CI: 1.35 to 10.82, respectively). With reduced arousal (RASS<0), neither tool significantly predicted mortality or LOS. CONCLUSIONS: The ICDSC identified more delirium cases and may have higher predictive validity for mortality and LOS than the CAM-ICU. However, arousal substantially affected performance. Future studies may want to consider patients' arousal when deciding which tool to use to maximise the effects of delirium identification on patient mortality.

Dexmedetomidine administration during brain tumour resection for prevention of postoperative delirium: a randomised trial.

BACKGROUND: Delirium is common, especially after neurosurgery. Dexmedetomidine might reduce delirium by improving postoperative analgesia and sleep quality. We tested the primary hypothesis that dexmedetomidine administration during intracerebral tumour resection reduces the incidence of postoperative delirium. METHODS: This randomised, double-blind, placebo-controlled trial was conducted in two tertiary-care hospitals in Beijing. We randomised 260 qualifying patients to either dexmedetomidine (n=130) or placebo (n=130). Subjects assigned to dexmedetomidine were given a loading dose of 0.6 µg kg-1 followed by continuous infusion at 0.4 µg kg-1 h-1 until dural closure; subjects in the placebo group were given comparable volumes of normal saline. The primary outcome was the incidence of delirium, which was assessed with the Confusion Assessment Method twice daily during the initial 5 postoperative days. RESULTS: The average (standard deviation) age of participating patients was 45 (12) yr, duration of surgery was 4.2 (1.5) h, and patients assigned to dexmedetomidine were given an average of 126 (45) µg of dexmedetomidine. There was less delirium during the initial 5 postoperative days in patients assigned to dexmedetomidine (22%, 28 of 130 patients) than in those given placebo (46%, 60 of 130 patients) with a risk ratio of 0.51 (95% confidence interval: 0.36-0.74, P<0.001). Postoperative pain scores with movement, and recovery and sleep quality were improved by dexmedetomidine (P<0.001). The incidence of safety outcomes was similar in each group. CONCLUSIONS: Prophylactic intraoperative dexmedetomidine infusion reduced by half the incidence of delirium during the initial 5 postoperative days in patients recovering from elective brain tumour resection. CLINICAL TRIAL REGISTRATION: NCT04674241.

Computerized tool and interdisciplinary care for older patients with delirium in the emergency department: a novel model in Taiwan.

AIMS: A computerized tool and interdisciplinary care were implemented to develop a novel model for older patients with delirium in the emergency department (ED). METHODS: We developed a computerized tool using a delirium triage screen and brief confusion assessment in the hospital information system, performed education for the healthcare providers, and developed a continuous care protocol. Comparisons for outcomes between pre- and post-intervention periods were performed. RESULTS: Compared with the pre-intervention period, patients in the post-intervention period had shorter hospitalization stay, lower expenditure of hospitalization, more likely to return home, lower ED revisits of ≤ 3 days, re-hospitalization of ≤ 14 days, and mortality of ≤ 1 month. All mentioned differences were not statistically significant. CONCLUSIONS: A novel model was successfully developed for delirium management in older patients in the ED. Outcome differences were not significant; however, the result is promising, which gives us an important reference in the future.

Delirium Assessment in Intensive Care Unit: A Need for Higher Regard!

How to cite this article: Govil D, Pal D. Delirium Assessment in Intensive Care Unit: A Need for Higher Regard! Indian J Crit Care Med 2022;26(6):661-662.

Assessment of Delirium as an Independent Predictor of Outcome among Critically Ill Patients in Intensive Care Unit: A Prospective Study.

Background: Delirium is frequently observed among critically ill patients in the intensive care unit. Although a preventable and reversible process, it is associated with greater morbidity and mortality. Early recognition and interpreting the predisposing and precipitating risk factors for delirium can improve outcomes among these patients. Objective: A prospective observational study was conducted with the primary objective to evaluate the incidence of delirium in a mixed adult intensive care unit. The secondary objectives were the evaluation of risk factors and outcomes of delirium. Methods: All patients who were more than 18 years of age and with an ICU stay of more than 24 hours were included in the study. Patients with prior history of neurological disorders, psychosis, and who were deaf were excluded. Eligible patients were evaluated by the residents to detect delirium using confusion assessment method for the intensive care unit (CAM-ICU) as a tool. Results: A total of 110 patients were included, and delirium was detected in 41 patients (37.3%). Among the predisposing risk factors, only hypertension was significantly associated with delirium. Among precipitating factors, mechanical ventilation, use of physical restraints and presence of window/natural light exposure, high Acute Physiology and Chronic Health Evaluation II scores, use of opioids, and benzodiazepines were associated with delirium. In multivariate risk regression analysis, presence of window/natural light exposure [odds ratio (OR), 55.52; 95% CI (8.887-346.904)]; (p <0.001) and duration of stay in ICU OR (1.145); 95% CI (1.058-1.238) (p = 0.001) were independent risk factors of delirium. Also, high mortality (53.7%) was observed among the delirious group of patients. Conclusion: Delirium is a common problem in the ICU and is associated with poor outcomes. Various risk factors are linked to ICU environment. How to cite this article: Junior MM, Kumar A, Kumar P, Gupta P. Assessment of Delirium as an Independent Predictor of Outcome among Critically Ill Patients in Intensive Care Unit: A Prospective Study. Indian J Crit Care Med 2022;26(6):676-681.

A machine learning approach to identifying delirium from electronic health records.

The identification of delirium in electronic health records (EHRs) remains difficult due to inadequate assessment or under-documentation. The purpose of this research is to present a classification model that identifies delirium using retrospective EHR data. Delirium was confirmed with the Confusion Assessment Method for the Intensive Care Unit. Age, sex, Elixhauser comorbidity index, drug exposures, and diagnoses were used as features. The model was developed based on the Columbia University Irving Medical Center EHR data and further validated with the Medical Information Mart for Intensive Care III dataset. Seventy-six patients from Surgical/Cardiothoracic ICU were included in the model. The logistic regression model achieved the best performance in identifying delirium; mean AUC of 0.874 ± 0.033. The mean positive predictive value of the logistic regression model was 0.80. The model promises to identify delirium cases with EHR data, thereby enable a sustainable infrastructure to build a retrospective cohort of delirium.

Ascertainment of Delirium Status Using Natural Language Processing From Electronic Health Records.

BACKGROUND: Delirium is underdiagnosed in clinical practice and is not routinely coded for billing. Manual chart review can be used to identify the occurrence of delirium; however, it is labor-intensive and impractical for large-scale studies. Natural language processing (NLP) has the capability to process raw text in electronic health records (EHRs) and determine the meaning of the information. We developed and validated NLP algorithms to automatically identify the occurrence of delirium from EHRs. METHODS: This study used a randomly selected cohort from the population-based Mayo Clinic Biobank (N = 300, age ≥65). We adopted the standardized evidence-based framework confusion assessment method (CAM) to develop and evaluate NLP algorithms to identify the occurrence of delirium using clinical notes in EHRs. Two NLP algorithms were developed based on CAM criteria: one based on the original CAM (NLP-CAM; delirium vs no delirium) and another based on our modified CAM (NLP-mCAM; definite, possible, and no delirium). The sensitivity, specificity, and accuracy were used for concordance in delirium status between NLP algorithms and manual chart review as the gold standard. The prevalence of delirium cases was examined using International Classification of Diseases, 9th Revision (ICD-9), NLP-CAM, and NLP-mCAM. RESULTS: NLP-CAM demonstrated a sensitivity, specificity, and accuracy of 0.919, 1.000, and 0.967, respectively. NLP-mCAM demonstrated sensitivity, specificity, and accuracy of 0.827, 0.913, and 0.827, respectively. The prevalence analysis of delirium showed that the NLP-CAM algorithm identified 12 651 (9.4%) delirium patients, the NLP-mCAM algorithm identified 20 611 (15.3%) definite delirium cases, and 10 762 (8.0%) possible cases. CONCLUSIONS: NLP algorithms based on the standardized evidence-based CAM framework demonstrated high performance in delineating delirium status in an expeditious and cost-effective manner.

Influence of perioperative dexmedetomidine on the incidence of postoperative delirium in adult patients undergoing cardiac surgery.

BACKGROUND: Delirium is a common neurocognitive complication after cardiac surgery. The aim of this systematic review was to determine whether the administration of dexmedetomidine in the perioperative period decreases the incidence of postoperative delirium in adult patients undergoing cardiac surgery. METHODS: Central, CINAHL, Ovid Embase, Ovid Medline, and Web of Science databases were searched for RCTs of adult patients undergoing cardiac surgery where participants received i.v. dexmedetomidine or control in the perioperative period. The methods included systematic review, meta-analysis, and trial sequential analysis. The primary outcome was the incidence of postoperative delirium. Dichotomous outcomes were presented as risk ratio (RR) using the Mantel-Haenszel method, and continuous variables were presented as mean difference with the inverse variance method. RESULTS: Thirty trials, comprising 4090 patients, were included. With unselected inclusion of trials, dexmedetomidine vs control was associated with decreased incidence of postoperative delirium (12.4% vs 16.2%; RR=0.62; 95% confidence interval 0.44-0.86; P=0.005; I2=61%). If trials at high risk of bias were excluded, the incidence of postoperative delirium was not significantly different between groups (RR=0.71; 95% confidence interval 0.49-1.03; P=0.070; I2=58%). Postoperative delirium was not a reliably determined outcome across trials because of methodological and reporting limitations, including the heterogeneity of delirium diagnostic approach. Trial sequential analysis revealed that the optimal information size was not reached, and the Z-curve did not cross the trial sequential boundaries for benefit or futility. With respect to safety concerns, dexmedetomidine was not significantly associated with incident bradycardia or hypotension, or with the duration of mechanical ventilation. CONCLUSIONS: When trials at high risk of bias were excluded, the use of perioperative dexmedetomidine was not associated with decreased incidence of postoperative delirium. PROSPERO REGISTRATION NUMBER: CRD 42021252779.

Detection of delirium by family members in the intensive care unit: Translation, Cross-Cultural adaptation and validation of the Family Confusion Assessment Method for the German-Speaking area.

AIM: The aim of this study was the translation, cross-cultural adaptation and validation of the Family Confusion Assessment Method in critically ill patients. BACKGROUND: Delirium is a frequently unrecognized disorder in critically ill patients. Visiting family members might be the first to notice subtle changes in a patient's cognition and behaviour. The Family Confusion Assessment Method was developed to detect delirium by family members, but has not been available for the German-speaking area yet. DESIGN: A prospective validation study was conducted between January 2020 and October 2020. METHODS: The Family Confusion Assessment Method was translated into German according to the Principles of Good Practice for the Translation and Cultural Adaptation Process for Patient-Reported Outcomes. Subsequently, we compared the Family Confusion Assessment Method with the Confusion Assessment Method for the Intensive Care Unit in critically ill patients and their family members in a medical intensive care unit in Germany. RESULTS: We included 50 dyads of critically ill patients and their family members. The prevalence of delirium measured by Confusion Assessment Method for the Intensive Care Unit was 44%. Cohen's kappa coefficient was 0.84. The German Family Confusion Assessment Method had a high sensitivity of 95.5% and specificity of 89.3%. The positive predictive value and negative predictive value were 87.5% and 96.2% respectively. CONCLUSIONS: These findings suggest that the German Family Confusion Assessment Method is an accurate assessment tool for delirium detection in the intensive care unit by family members. Furthermore, the results indicate that family members may identify delirium by the Family Confusion Assessment Method without prior training. IMPACT: Collaborating medical staff with patients' family members to detect delirium in the intensive care unit may lead to early recognition of delirium.

Delirium detection methodologies: Implications for outcome measurement in clinical trials in postoperative delirium.

OBJECTIVE: Delirium is a common postoperative complication of hip fracture. Various methods exist to detect delirium as a reference standard. The goal of this study was to characterize the properties of the measures obtained in a randomized controlled trial, to document their relationship to the Diagnostic and Statistical Manual of Mental Disorders:Text Revision based diagnosis of postoperative delirium by a consensus panel, and to describe the method in detail to allow replication by others. METHODS: A secondary analysis of the randomized trial STRIDE (A Strategy to Reduce the Incidence of Postoperative Delirium in Elderly Patients) was conducted. Delirium assessments were performed in 200 consecutive hip fracture repair patients ≥65 years old. Assessors underwent extensive training in delirium assessment and the final delirium diagnosis was adjudicated by a consensus panel of three physicians with expertise in delirium assessment. RESULTS: A total of 680 consensus panel delirium diagnoses were completed. There were only 19 (2.8%, 19/678) evaluations where the delirium adjudication by the consensus panel differed from delirium findings by the Confusion Assessment Method (CAM). In 16 (84%, 16/19) of the cases, CAM was negative but the consensus panel diagnosed the patient as having delirium based on all of the available information including the CAM. CONCLUSION: The consensus panel diagnosis was more sensitive compared to CAM alone, however the magnitude of the difference was not large. When assessors are well trained and delirium assessments are closely supervised throughout the study, CAM may be adequate for delirium diagnosis in a clinical trial. Future studies are needed to test this hypothesis.

Comparison of delirium detection tools in acute care : A rapid review.

BACKGROUND: Delirium 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 METHODS: Rapid 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. RESULTS: A 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. CONCLUSION: Besides 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.