Several risk stratification instruments for postoperative delirium in older people have been developed because early interventions may prevent delirium. We investigated the performance and agreement of nine commonly used risk stratification instruments in an independent validation cohort of consecutive elective and emergency surgical patients aged ≥50 years with ≥1 risk factor for postoperative delirium. Data was collected prospectively. Delirium was diagnosed according to DSM-IV-TR criteria. The observed incidence of postoperative delirium was calculated per risk score per risk stratification instrument. In addition, the risk stratification instruments were compared in terms of area under the receiver operating characteristic (ROC) curve (AUC), and positive and negative predictive value. Finally, the positive agreement between the risk stratification instruments was calculated. When data required for an exact implementation of the original risk stratification instruments was not available, we used alternative data that was comparable. The study population included 292 patients: 60% men; mean age (SD), 66 (8) years; 90% elective surgery. The incidence of postoperative delirium was 9%. The maximum observed incidence per risk score was 50% (95%CI, 15–85%); for eight risk stratification instruments, the maximum observed incidence per risk score was ≤25%. The AUC (95%CI) for the risk stratification instruments varied between 0.50 (0.36–0.64) and 0.66 (0.48–0.83). No AUC was statistically significant from 0.50 (p≥0.11). Positive predictive values of the risk stratification instruments varied between 0–25%, negative predictive values between 89–95%. Positive agreement varied between 0–66%. No risk stratification instrument showed clearly superior performance. In conclusion, in this independent validation cohort, the performance and agreement of commonly used risk stratification instruments for postoperative delirium was poor. Although some caution is needed because the risk stratification instruments were not implemented exactly as described in the original studies, we think that their usefulness in clinical practice can be questioned.

BackgroundAdequate delirium recognition and management are important to reduce the incidence and severity of delirium. To improve delirium recognition and management, training of medical staff and students is needed.ObjectiveIn this study, we aimed to gain insight into whether the serious game, Delirium Experience, is suited as an educational intervention.MethodsWe conducted a three-arm randomized controlled trial. We enrolled 156 students in the third year of their Bachelor of Medical Sciences degree at the University Medical Centre Groningen. The Game group of this study played Delirium Experience. The Control D group watched a video with explanations on delirium and a patient’s experience of delirious episodes. The Control A group watched a video on healthy aging. To investigate students’ skills, we used a video of a delirious patient for which students had to give care recommendations and complete the Delirium Observations Screening Scale and Delirium Rating Scale R-98. Furthermore, students completed the Delirium Attitude Scale, the Learning Motivation and Engagement Questionnaire, and self-reported knowledge on delirium.ResultsIn total, 156 students participated in this study (Game group, n=51; Control D group, n=51; Control A group, n=55). The Game group scored higher with a median (interquartile range) of 6 (4-8) for given recommendations and learning motivation and engagement compared with the Control D (1, 1-4) and A (0, 0-3) groups (P<.001). Furthermore, the Game group scored higher (7, 6-8) on self-reported knowledge compared with the Control A group (6, 5-6; P<.001). We did not find differences between the groups regarding delirium screening (P=.07) and rating (P=.45) skills or attitude toward delirious patients (P=.55).ConclusionsThe serious game, Delirium Experience, is suitable as an educational intervention to teach delirium care to medical students and has added value in addition to a lecture.

Background There is growing interest for interventions aiming at preventing frailty progression or even to reverse frailty in older people, yet it is still unclear which frailty instrument is most appropriate for measuring change scores over time to determine the effectiveness of interventions. The aim of this prospective cohort study was to determine reproducibility and responsiveness properties of the Frailty Index (FI) and Frailty Phenotype (FP) in acutely hospitalized medical patients aged 70 years and older. Methods Reproducibility was assessed by Intra-Class Correlation Coefficients (ICC), standard error of measurement (SEM) and smallest detectable change (SDC); Responsiveness was assessed by the standardized response mean (SRM), and area under the receiver operating characteristic curve (AUC). Results At baseline, 243 patients were included with a median age of 76 years (range 70–98). The analytic samples included 192 and 187 patients in the three and twelve months follow-up analyses, respectively. ICC of the FI were 0.85 (95 % confidence interval [CI]: 0.76; 0.91) and 0.84 (95% CI: 0.77; 0.90), and 0.65 (95% CI: 0.49; 0.77) and 0.77 (95% CI: 0.65; 0.84) for the FP. SEM ranged from 5 to 13 %; SDC from 13 to 37 %. SRMs were good in patients with unchanged frailty status (< 0.50), and doubtful to good for deteriorated and improved patients (0.43–1.00). AUC’s over three months were 0.77 (95% CI: 0.69; 0.86) and 0.71 (95% CI: 0.62; 0.79) for the FI, and 0.68 (95% CI: 0.58; 0.77) and 0.65 (95% CI: 0.55; 0.74) for the FP. Over twelve months, AUCs were 0.78 (95% CI: 0.69; 0.87) and 0.82 (95% CI: 0.73; 0.90) for the FI, and 0.78 (95% CI: 0.69; 0.87) and 0.75 (95% CI: 0.67; 0.84) for the FP. Conclusions The Frailty Index showed better reproducibility and responsiveness properties compared to the Frailty Phenotype among acutely hospitalized older patients.