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- Thoma, B, et al.
(author)
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An international, interprofessional investigation of the self-reported podcast listening habits of emergency clinicians: A METRIQ Study
- 2020
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In: CJEM. - : Springer Science and Business Media LLC. - 1481-8043 .- 1481-8035. ; 22:1, s. 112-117
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Journal article (peer-reviewed)abstract
- ObjectivesPodcasts are increasingly being used for medical education. A deeper understanding of usage patterns would inform both producers and researchers of medical podcasts. We aimed to determine how and why podcasts are used by emergency medicine and critical care clinicians.MethodsAn international interprofessional sample (medical students, residents, physicians, nurses, physician assistants, and paramedics) was recruited through direct contact and a multimodal social media (Twitter and Facebook) campaign. Each participant completed a survey outlining how and why they utilize medical podcasts. Recruitment materials included an infographic and study website.Results390 participants from 33 countries and 4 professions (medicine, nursing, paramedicine, physician assistant) completed the survey. Participants most frequently listened to medical podcasts to review new literature (75.8%), learn core material (75.1%), and refresh memory (71.8%). The majority (62.6%) were aware of the ability to listen at increased speeds, but most (76.9%) listened at 1.0 x (normal) speed. All but 25 (6.4%) participants concurrently performed other tasks while listening. Driving (72.3%), exercising (39.7%), and completing chores (39.2%) were the most common. A minority of participants used active learning techniques such as pausing, rewinding, and replaying segments of the podcast. Very few listened to podcasts multiple times.ConclusionsAn international cohort of emergency clinicians use medical podcasts predominantly for learning. Their listening habits (rarely employing active learning strategies and frequently performing concurrent tasks) may not support this goal. Further exploration of the impact of these activities on learning from podcasts is warranted.
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- De Kort, A. M., et al.
(author)
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Decreased Cerebrospinal Fluid Amyloid beta 38, 40, 42, and 43 Levels in Sporadic and Hereditary Cerebral Amyloid Angiopathy
- 2023
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In: Annals of neurology. - : Wiley. - 0364-5134 .- 1531-8249. ; 93:6, s. 1173-86
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Journal article (peer-reviewed)abstract
- Objective: Vascular amyloid beta (A beta) accumulation is the hallmark of cerebral amyloid angiopathy (CAA). The composition of cerebrospinal fluid (CSF) of CAA patients may serve as a diagnostic biomarker of CAA. We studied the diagnostic potential of the peptides A beta 38, A beta 40, A beta 42, and A beta 43 in patients with sporadic CAA (sCAA), hereditary Dutch-type CAA (D-CAA), and Alzheimer disease (AD).Methods: A beta peptides were quantified by immunoassays in a discovery group (26 patients with sCAA and 40 controls), a validation group (40 patients with sCAA, 40 patients with AD, and 37 controls), and a group of 22 patients with D-CAA and 54 controls. To determine the diagnostic accuracy, the area under the curve (AUC) was calculated using a receiver operating characteristic curve with 95% confidence interval (CI).Results: We found decreased levels of all A beta peptides in sCAA patients and D-CAA patients compared to controls. The difference was most prominent for A beta 42 (AUC of sCAA vs controls for discovery: 0.90, 95% CI = 0.82-0.99; for validation: 0.94, 95% CI = 0.89-0.99) and A beta 43 (AUC of sCAA vs controls for discovery: 0.95, 95% CI = 0.88-1.00; for validation: 0.91, 95% CI = 0.83-1.0). All A beta peptides except A beta 43 were also decreased in sCAA compared to AD (CSF A beta 38: AUC = 0.82, 95% CI = 0.71-0.93; CSF A beta 40: AUC = 0.88, 95% CI = 0.80-0.96; CSF A beta 42: AUC = 0.79, 95% CI = 0.66-0.92).Interpretation: A combined biomarker panel of CSF A beta 38, A beta 40, A beta 42, and A beta 43 has potential to differentiate sCAA from AD and controls, and D-CAA from controls. ANN NEUROL 2023
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- Jansen, Willemijn J, et al.
(author)
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Prevalence Estimates of Amyloid Abnormality Across the Alzheimer Disease Clinical Spectrum.
- 2022
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In: JAMA neurology. - : American Medical Association (AMA). - 2168-6157 .- 2168-6149. ; 79:3, s. 228-243
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Journal article (peer-reviewed)abstract
- One characteristic histopathological event in Alzheimer disease (AD) is cerebral amyloid aggregation, which can be detected by biomarkers in cerebrospinal fluid (CSF) and on positron emission tomography (PET) scans. Prevalence estimates of amyloid pathology are important for health care planning and clinical trial design.To estimate the prevalence of amyloid abnormality in persons with normal cognition, subjective cognitive decline, mild cognitive impairment, or clinical AD dementia and to examine the potential implications of cutoff methods, biomarker modality (CSF or PET), age, sex, APOE genotype, educational level, geographical region, and dementia severity for these estimates.This cross-sectional, individual-participant pooled study included participants from 85 Amyloid Biomarker Study cohorts. Data collection was performed from January 1, 2013, to December 31, 2020. Participants had normal cognition, subjective cognitive decline, mild cognitive impairment, or clinical AD dementia. Normal cognition and subjective cognitive decline were defined by normal scores on cognitive tests, with the presence of cognitive complaints defining subjective cognitive decline. Mild cognitive impairment and clinical AD dementia were diagnosed according to published criteria.Alzheimer disease biomarkers detected on PET or in CSF.Amyloid measurements were dichotomized as normal or abnormal using cohort-provided cutoffs for CSF or PET or by visual reading for PET. Adjusted data-driven cutoffs for abnormal amyloid were calculated using gaussian mixture modeling. Prevalence of amyloid abnormality was estimated according to age, sex, cognitive status, biomarker modality, APOE carrier status, educational level, geographical location, and dementia severity using generalized estimating equations.Among the 19097 participants (mean [SD] age, 69.1 [9.8] years; 10148 women [53.1%]) included, 10139 (53.1%) underwent an amyloid PET scan and 8958 (46.9%) had an amyloid CSF measurement. Using cohort-provided cutoffs, amyloid abnormality prevalences were similar to 2015 estimates for individuals without dementia and were similar across PET- and CSF-based estimates (24%; 95% CI, 21%-28%) in participants with normal cognition, 27% (95% CI, 21%-33%) in participants with subjective cognitive decline, and 51% (95% CI, 46%-56%) in participants with mild cognitive impairment, whereas for clinical AD dementia the estimates were higher for PET than CSF (87% vs 79%; mean difference, 8%; 95% CI, 0%-16%; P=.04). Gaussian mixture modeling-based cutoffs for amyloid measures on PET scans were similar to cohort-provided cutoffs and were not adjusted. Adjusted CSF cutoffs resulted in a 10% higher amyloid abnormality prevalence than PET-based estimates in persons with normal cognition (mean difference, 9%; 95% CI, 3%-15%; P=.004), subjective cognitive decline (9%; 95% CI, 3%-15%; P=.005), and mild cognitive impairment (10%; 95% CI, 3%-17%; P=.004), whereas the estimates were comparable in persons with clinical AD dementia (mean difference, 4%; 95% CI, -2% to 9%; P=.18).This study found that CSF-based estimates using adjusted data-driven cutoffs were up to 10% higher than PET-based estimates in people without dementia, whereas the results were similar among people with dementia. This finding suggests that preclinical and prodromal AD may be more prevalent than previously estimated, which has important implications for clinical trial recruitment strategies and health care planning policies.
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