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Record W2137948485 · doi:10.1016/j.jalz.2013.05.1491

P4–101: Establishment of a database on aging and dementia in the Philippines

2013· article· en· W2137948485 on OpenAlexaboutno aff
Jacqueline C. Dominguez, Mary Grace Serranilla, Jeniffer Rose Soriano, Cely D. Magpantay, Wynette Marie Solis, Encarnita Ampil, Ma. Lourdes Corrales‐Joson, Primitivo B. Mactal, Precy S. Cruz, Rolando C. Esteban, Merceditas Dizon, Ma. Luisa Daroy

Bibliographic record

VenueAlzheimer s & Dementia · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicHealth, Environment, Cognitive Aging
Canadian institutionsnot available
Fundersnot available
KeywordsDementiaClinical Dementia RatingWechsler Adult Intelligence ScaleMemory spanMontreal Cognitive AssessmentPsychologyGeriatric Depression ScaleNeuropsychologyGerontologyVerbal fluency testPsychiatryTest (biology)DatabaseDepression (economics)Clinical psychologyCognitionDiseaseMedicineWorking memoryComputer science

Abstract

fetched live from OpenAlex

Databasing is an effective strategy to facilitate the efficient conduct of research and an opportunity to collaborate with other researchers of similar interest. There are multiple databases on aging and dementia around the world but no such database exists in the Philippines. This paper is to describe the creation of the database on aging and dementia in the Philippines and to present its initial results. The St. Luke's Memory Center which was established in 2001 uses standardized data collection methods adapted from the Washington University in Saint Louis Alzheimer's Disease Research Center (ADRC). Its community study site in Marikina Valley uses a shorter method adapted from the Minimum Data Set (MDS) of the National Alzheimer's Coordinating Center (NACC).[i]E ligible subjects from both sources were enrolled in the database. The following were collected: subject demographics, informant demographics, subject family history, medications, health history, physical examination and the Hachinski Ischemic Score, Clinical Dementia Rating and clinician diagnosis, Philippine versions of the Montreal Cognitive Assessment (MoCA), Geriatric Depression Scale (15-item), Neuropsychiatric Inventory short form (NPI-Q), and the Disability Assessment in Dementia (DAD). Neuropsychological tests like Mini Mental State Examination (MMSE), Logical Memory Immediate and Delayed Recall from the WMS-R, short version of Boston Naming Test (BNT), verbal fluency, Digit Span and Digit Symbol subtests of the Wechsler Adult Intelligence Scale (WAIS), and Trail Making Test A and B were collected from Memory Center subjects. Neuroimaging and APOE genotyping were collected on those who agreed. [i] https://www.alz.washington.edu. Table 1. The strength of this database is the collection and measurement of the core set of variables recommended by the Unified Data Set (UDS) which permits collaboration. A website is being developed facilitate collaboration. The team involved is multidisciplinary: Neurology, Geriatrics, Allied Health Professionals like Nurses, Psychologist, Speech and Language Pathologist, Occupational therapist and Medical Anthropologist. Only 18% underwent genotyping and fewer had neuroimaging. Use of biomarkers is limitation due to limited funding. A database on aging and dementia has been established in the Philippines. It integrates memory center and community data using the core variables of the UDS. Initial findings are presented.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.306
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.027
GPT teacher head0.265
Teacher spread0.238 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2013
Admission routes1
Has abstractyes

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