Epidemiology of Motoric Cognitive Risk Syndrome in the Kerala Einstein Study: Protocol for a Prospective Cohort Study
Bibliographic record
Abstract
BACKGROUND: The southern India state of Kerala has among the highest proportion of older adults in its population in the country. An increase in chronic age-related diseases such as dementia is expected in the older Kerala population. Identifying older individuals early in the course of cognitive decline offers the best hope of introducing preventive measures early and planning management. However, the epidemiology and pathogenesis of predementia syndromes at the early stages of cognitive decline in older adults are not well established in India. OBJECTIVE: The Kerala Einstein Study (KES) is a community-based cohort study that was established in 2008 and is based in the Kozhikode district in Kerala state. KES aims to establish risk factors and brain substrates of motoric cognitive risk syndrome (MCR), a predementia syndrome characterized by the presence of slow gait and subjective cognitive concerns in individuals without dementia or disability. This protocol describes the study design and procedures for this KES project. METHODS: KES is proposing to enroll a sample of 1000 adults ≥60 years old from urban and rural areas in the Kozhikode district of Kerala state: 200 recruited in the previous phase of KES and 800 new participants to be recruited in this project. MCR is the cognitive phenotype of primary interest. The associations between previously established risk factors for dementia as well as novel risk factors (apathy and traumatic brain injury) and MCR will be examined in KES. Risk factor profiles for MCR will be compared between urban and rural residents as well as with individuals who meet the criteria for mild cognitive impairment (MCI). Cognitive and physical function, medical history and medications, sociodemographic characteristics, lifestyle patterns, and activities of daily living will be evaluated. Participants will also undergo magnetic resonance imaging and electrocardiogram investigations. Longitudinal follow-up is planned in a subset of participants as a prelude to future longitudinal studies. RESULTS: KES (2R01AG039330-07) was funded by the US National Institutes of Health in September 2019 and received approval from the Indian Medical Council of Research to start the study in June 2021. We had recruited 433 new participants from urban and rural sites in Kozhikode as of May 2023: 41.1% (178/433) women, 67.7% (293/433) rural residents, and 13.4% (58/433) MCR cases. Enrollment is actively ongoing at all the KES recruitment sites. CONCLUSIONS: KES will provide new insights into risk factors and brain substrates associated with MCR in India and will help guide future development of regionally specific preventive interventions for dementia. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/49933.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.017 | 0.015 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.026 | 0.007 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".