Computerized decision support is an effective approach to select memory clinic patients for amyloid-PET.

BACKGROUND: The use of amyloid-PET in dementia workup is upcoming. At the same time, amyloid-PET is costly and limitedly available. While the appropriate use criteria (AUC) aim for optimal use of amyloid-PET, their limited sensitivity hinders the translation to clinical practice. Therefore, there is a need for tools that guide selection of patients for whom amyloid-PET has the most clinical utility. We aimed to develop a computerized decision support approach to select patients for amyloid-PET. METHODS: We included 286 subjects (135 controls, 108 Alzheimer's disease dementia, 33 frontotemporal lobe dementia, and 10 vascular dementia) from the Amsterdam Dementia Cohort, with available neuropsychology, APOE, MRI and [18F]florbetaben amyloid-PET. In our computerized decision support approach, using supervised machine learning based on the DSI classifier, we first classified the subjects using only neuropsychology, APOE, and quantified MRI. Then, for subjects with uncertain classification (probability of correct class (PCC) < 0.75) we enriched classification by adding (hypothetical) amyloid positive (AD-like) and negative (normal) PET visual read results and assessed whether the diagnosis became more certain in at least one scenario (PPC≥0.75). If this was the case, the actual visual read result was used in the final classification. We compared the proportion of PET scans and patients diagnosed with sufficient certainty in the computerized approach with three scenarios: 1) without amyloid-PET, 2) amyloid-PET according to the AUC, and 3) amyloid-PET for all patients. RESULTS: The computerized approach advised PET in n = 60(21%) patients, leading to a diagnosis with sufficient certainty in n = 188(66%) patients. This approach was more efficient than the other three scenarios: 1) without amyloid-PET, diagnostic classification was obtained in n = 155(54%), 2) applying the AUC resulted in amyloid-PET in n = 113(40%) and diagnostic classification in n = 156(55%), and 3) performing amyloid-PET in all resulted in diagnostic classification in n = 154(54%). CONCLUSION: Our computerized data-driven approach selected 21% of memory clinic patients for amyloid-PET, without compromising diagnostic performance. Our work contributes to a cost-effective implementation and could support clinicians in making a balanced decision in ordering additional amyloid PET during the dementia workup.

Impact of COVID-19 pandemic on mortality rate in memory clinic patients.

INTRODUCTION: We investigated whether mortality in memory clinic patients changed due to coronavirus disease 2019 (COVID-19) pandemic. METHODS: We included patients from the Amsterdam Dementia Cohort: (1) n = 923 pandemic patients (baseline visit: 2017-2018, follow-up: until 2021), and (2) n = 830 historical control patients (baseline visit: 2015-2016, follow-up: until 2019). Groups were well-balanced. We compared mortality during pandemic with historical control patients using Cox regression. Differences in cause of death between groups were explored using Fisher's exact test. RESULTS: Pandemic patients had a higher risk of mortality than historical control patients (hazard ratio [HR] [95% confidence interval {CI}] = 1.34 [1.05-1.70]). Stratified for syndrome diagnosis, the effect remained significant in dementia patients (HR [95% CI] = 1.35 [1.03-1.78]). Excluding patients who died of COVID-19-infection, the higher mortality risk in pandemic patients attenuated (HR [95% CI] = 1.24 [0.97-1.58]). Only the difference in cause of death between pandemic patients and historical control patients for death to COVID-19-infection (p = 0.001) was observed. CONCLUSION: Memory clinic patients had increased mortality risk during COVID-19 compared to historical control patients, attributable to dementia patients. Highlights: We investigated if mortality rates in memory clinic patients changed due to COVID-19 pandemic.We included patients along the cognitive continuum, including SCD, MCI, and dementia.We used a well-balanced historical control group.Memory clinic patients had higher risk for mortality during COVID-19 lockdown.Our results indicate that excess mortality is mainly caused by death to COVID-19 infection.