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TRUVACE RECORD VERSION
record: TRV-2026-0936
version: 1
kind: certified
reason: Certified into the record
timestamp: 2026-08-31T06:05:31.671056Z
status: published
lens: g_space
sector: lifestyle
headline: The impact of frailty and its changes on the development of motoric cognitive risk syndrome in middle-aged and older adults
dek: Background Previous research links frailty to cognitive decline, but the relationship between frailty and motoric cognitive risk syndrome (MCR), a dementia precursor, is underexplored. Methods This study used CHARLS data with 3388 participants aged ≥45. Data from 2011 to 2012, 2013, and 2015 were analyzed to examine the relationship between frailty index (FI), total FI, and changes in FI (△FI) with MCR risk. Nine machine learning models were built using baseline FI to predict MCR risk, and changes in frailty sta…
gain_title: Nine machine learning models using baseline frailty index predicted motoric cognitive risk syndrome, with higher frailty linked to increased MCR risk in adults aged 45 and older.
problem_title: (none)
trace_subject: (none)
gain_reading: Nine machine learning models using baseline frailty index predicted motoric cognitive risk syndrome, with higher frailty linked to increased MCR risk in adults aged 45 and older.
gain_evidence: Nine machine learning models were built using baseline FI to predict MCR risk | Early detection and intervention in frailty might be promising targets for mitigating MCR development and potentially linked to dementia prevention
problem_reading: (none)
problem_evidence: (none)
quick_read: Researchers analyzed 3388 CHARLS participants aged 45 and older across 2011 to 2015 to examine frailty and motoric cognitive risk syndrome. They built nine machine learning models using baseline frailty index to predict MCR risk and tracked changes in frailty status. By follow-up end, 127 participants (3.74%) developed MCR, with higher baseline FI, total FI, and change in FI associated with increased risk.

The findings link dynamic frailty changes to a dementia precursor, suggesting early detection and intervention on frailty could help mitigate MCR and potentially dementia. Uncertainty remains because baseline FI alone showed only modest predictive performance around 0.6, and the results are observational from a specific Chinese cohort without demonstrated clinical deployment or intervention efficacy by the publication date of August 29, 2026.
limitation: Predictive utility was limited to modest performance when using baseline frailty index alone, and findings are restricted to CHARLS participants aged 45 and older.
tag: Evidence-backed gain
key_points: Study analyzed CHARLS data with 3388 participants aged 45 from 2011 to 2012, 2013, and 2015. | By follow-up end, 127 participants (3.74%) developed MCR, defined as a dementia precursor. | Participants transitioning from robust to frail/pre-frail showed higher MCR prevalence, while regaining robustness was linked to lower prevalence. | Restricted cubic splines (RCS) showed a linear relationship between FI and MCR risk (p > 0.05).
rundown: The analysis used CHARLS longitudinal data from 2011-2012, 2013, and 2015, examining baseline FI, total FI, and changes in FI (bFI) in relation to MCR risk. Trend regression confirmed a significant upward trend in MCR risk with increasing frailty, and RCS analysis indicated a linear dose-response relationship.

Beyond baseline prediction, the study tracked frailty status transitions over time. Remaining pre-frail or improving to robust status associated with reduced MCR occurrence compared to progressing from pre-frailty to frailty, while regaining robustness from frailty showed lower prevalence than staying frail.
sources:
- peer_reviewed | Journal of the Formosan Medical Association | https://doi.org/10.1016/j.jfma.2026.08.049 | 2026-08-29
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