Mid-term changes in cognitive functions in patients with atrial fibrillation: a longitudinal analysis of the Swiss-AF cohort.

Background: Longitudinal association studies of atrial fibrillation (AF) and cognitive functions have shown an unclear role of AF-type and often differ in methodological aspects. We therefore aim to investigate longitudinal changes in cognitive functions in association with AF-type (non-paroxysmal vs. paroxysmal) and comorbidities in the Swiss-AF cohort. Methods: Seven cognitive measures were administered up to five times between 2014 and 2022. Age-education standardized scores were calculated and association between longitudinal change in scores and baseline AF-type investigated using linear mixed-effects models. Associations between AF-type and time to cognitive drop, an observed score of at least one standard deviation below individual's age-education standardized cognitive scores at baseline, were studied using Cox proportional hazard models of each cognitive test, censoring patients at their last measurement. Models were adjusted for baseline covariates. Results: 2,415 AF patients (mean age 73.2 years; 1,080 paroxysmal, 1,335 non-paroxysmal AF) participated in this Swiss multicenter prospective cohort study. Mean cognitive scores increased longitudinally (median follow-up 3.97 years). Non-paroxysmal AF patients showed smaller longitudinal increases in Digit Symbol Substitution Test (DSST), Cognitive Construct Score (CoCo)and Trail Making Test part B (TMT-B) scores vs. paroxysmal AF patients. Diabetes, history of stroke/TIA and depression were associated with worse performance on all cognitive tests. No differences in time to cognitive drop were observed between AF-types in any cognitive test. Conclusion: This study indicated preserved cognitive functioning in AF patients, best explained by practice effects. Smaller practice effects were found in non-paroxysmal AF patients in the DSST, TMT-B and the CoCo and could indicate a marker of subtle cognitive decline. As diabetes, history of stroke/TIA and depression-but not AF-type-were associated with cognitive drop, more attention should be given to risk factors and underlying mechanisms of AF.

Diagnosing delirium in perioperative and intensive care medicine.

PURPOSE OF REVIEW: This article reviews the current literature on instruments used for screening and diagnosing delirium in perioperative and intensive care medicine. It summarizes recent findings to guide clinicians and researchers in choosing the most appropriate tools. RECENT FINDINGS: The incidence of delirium in hospitalized patients ranges from 5% to over 50%, depending on the population of patients studied. Failure to diagnose delirium in a timely manner is associated with serious adverse outcomes, including death and institutionalization. Valid assessment tests are needed for delirium detection, as early identification and treatment of delirium may help to prevent complications. Currently, there are more than 30 available instruments, which have been developed to assist with the screening and diagnosis of delirium. However, these tools vary greatly in sensitivity, specificity, and administration time, and their overabundance challenges the selection of specific tool as well as direct comparisons and interpretation of results across studies. SUMMARY: Overlooking or misdiagnosing delirium may result in poor patient outcomes. Familiarizing healthcare workers with the variety of delirium assessments and selecting the most appropriate tool to their needs is an important step toward improving awareness and recognition of delirium.

Independent External Validation of a Preoperative Prediction Model for Delirium After Cardiac Surgery: A Prospective Observational Cohort Study.

OBJECTIVE: This investigation provided independent external validation of an existing preoperative risk prediction model. DESIGN: A prospective observational cohort study of patients undergoing cardiac surgery covering the period between April 16, 2018 and January 18, 2022. SETTING: Two academic hospitals in Switzerland. PARTICIPANTS: Adult patients (≥60 years of age) who underwent elective cardiac surgery, including coronary artery bypass graft, mitral or aortic valve replacement or repair, and combined procedures. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: The primary outcome measure was the incidence of postoperative delirium (POD) in the intensive or intermediate care unit, diagnosed using the Intensive Care Delirium Screening Checklist. The prediction model contained 4 preoperative risk factors to which the following points were assigned: Mini-Mental State Examination (MMSE) score ≤23 received 2 points; MMSE 24-27, Geriatric Depression Scale (GDS) >4, prior stroke and/or transient ischemic attack (TIA), and abnormal serum albumin (≤3.5 or ≥4.5 g/dL) received 1 point each. The missing data were handled using multiple imputation. In total, 348 patients were included in the study. Sixty patients (17.4%) developed POD. For point levels in the prediction model of 0, 1, 2, and ≥3, the cumulative incidence of POD was 12.6%, 22.8%, 25.8%, and 35%, respectively. The validation resulted in a pooled area under the receiver operating characteristics curve of 0.60 (median CI, 0.525-0.679). CONCLUSIONS: The evaluated predictive model for delirium after cardiac surgery in this patient cohort showed only poor discriminative capacity but fair calibration.

Conversion between the Montreal Cognitive Assessment and the Mini-Mental Status Examination.

BACKGROUND: Early and accurate detection of cognitive changes using simple tools is essential for an appropriate referral to a more detailed neurocognitive assessment and for the implementation of therapeutic strategies. The Mini-Mental Status Examination (MMSE) and the Montreal Cognitive Assessment (MoCA) are two commonly used psychometric tests for cognitive screening. Both tests have different strengths and weaknesses. Preferences regarding test selection may therefore differ among clinicians. The aim of this retrospective observational cohort study was to define corresponding scores for the MMSE and the MoCA. METHODS: We examined the relationship between the cognitive screening tests in 803 German-speaking Memory Clinic outpatients, encompassing a wide range of neurocognitive disorders. We produced a conversion table using the equipercentile equating method with log-linear smoothing. In addition, we conducted a systematic review of existing MMSE-MoCA conversions to create a table allowing for the conversion of MoCA scores into MMSE scores and vice versa using the weighted mean method. RESULTS: The Memory Clinic sample showed that the prediction of MMSE to MoCA was overall less accurate compared to the conversion from MoCA to MMSE. The 19 studies included after thorough literature search showed that MoCA scores were consistently lower than MMSE scores. Eleven of 19 conversion studies had addressed the conversion of the MoCA to the MMSE, while two studies converted MMSE to MoCA scores. Another six studies applied bi-directional conversions. We provide an easy-to-use table covering the entire range of scores and taking into account all currently existing conversion formulas. CONCLUSION: The comprehensive MMSE-MoCA conversion table enables a direct comparison of cognitive test scores at screening examinations and over the course of disease in patients with neurocognitive disorders.