Do you really think your competent? doctor will use this to start dementia prevention protocols on you? I don't! You will likely need them, so ask your incompetent doctor why they don't exist!
Check out how many years your doctor has had to prepare dementia prevention protocols! Incompetence in inaction! No excuses allowed!
1. A documented 33% dementia chance post-stroke from an Australian study? May 2012.
2. Then this study came out and seems to have a range from 17-66%. December 2013.`
3. A 20% chance in this research. July 2013.
4. Dementia Risk Doubled in Patients Following Stroke September 2018
The latest here:
New model may reliably predict mild cognitive impairment, dementia onset
Key takeaways:
- Predicted ages for the onset of mild cognitive impairment and Alzheimer’s dementia were close for the model and clinical observance.
- Margins of error were low for the model in a simulated study.
A novel statistical model may be a reliable method to predict the age of onset for both mild cognitive impairment and Alzheimer’s disease-related dementia, according to research published in JAMA Network Open.
“Currently, no tools are available for clinicians to predict the age at [mild cognitive impairment (MCI)] or AD onset,” Chenyin Chu, MSci, MPhil,
of the Florey Institute of Neuroscience and Mental Health at the
University of Melbourne, Australia, and colleagues wrote. “A tool that
accurately predicts age at onset could enable older adults to plan their
dementia care while they are still capable of doing so, and it could
also guide clinicians in the use of monoclonal antibody drugs by
prioritizing patients with risk of more rapid cognitive decline for
treatment.”
Clinicians require valid tools to accurately predict the onset of MCI or AD-related dementia, so that patients and their providers can make the most informed decisions regarding dementia care, Chu and colleagues wrote.
The researchers sought to assess whether a statistical model could predict the age at onset of both MCI and Alzheimer’s dementia.
Their undertaking utilized data from a pair of aging and dementia cohort studies — the Australian Imaging, Biomarker and Lifestyle (AIBL) study and the Alzheimer’s Disease Neuroimaging Initiative (ADNI) — to develop and validate the Florey Dementia Index (FDI), a novel method for prediction of MCI and AD onset age in older adults. FDI input includes both age of the participant as well as the Clinical Dementia Rating Sum of Boxes (CDR-SB) score.
Concurrently, the researchers employed data from the Anti-Amyloid Treatment in Asymptomatic Alzheimer (A4) study to simulate results.
The full analysis set included 3,787 participants, including 1,665 from the AIBL (44.5% women; mean age at first evaluation, 71.8 years), 2,029 from ADNI (45.6% women; mean age at first evaluation, 74.5 years) and 93 from A4 (51.6% women; mean age at first evaluation, 73.4 years).
The main outcome of interest was the comparison of predicted age of MCI or AD onset with the model vs. clinically observed age. The mean CDR-SB trajectory was calculated by averaging the scores of all AIBL participants aged 60 to 100 years, with mean CDR-SB values plotted against chronological age and disease trajectories converted from chronological age.
According to the results, the predicted mean age within the model at MCI onset was 76.3 years and 76.7 years for AD, respectively, aligning closely with clinically observed predicted ages of 75.7 years for MCI and 76.8 years for AD.
Data show that FDI achieved mean absolute errors of 2.78 (95% CI, 2.63-2.93) years for MCI onset and 1.48 (95% CI, 1.32-1.65) years for AD onset.
The researchers additionally reported, regarding the simulated A4 trial, the FDI achieved mean absolute errors of 1.57 (95% CI, 1.41-1.71) years for MCI onset and 0.70 (95% CI, 0.53-0.88) years for Alzheimer’s dementia onset.
“The promising results achieved in the present study support the potential clinical use of the FDI model so that timely diagnostics, treatment and care plans for individuals at risk can be arranged,” Chu and colleagues wrote. “Our developed prototype application for the FDI, once validated, can be readily used by clinicians without any prior knowledge in statistics.”
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