Determinación precoz del deterioro cognitivo mínimo (MCI) con la montreal cognitive assessment (Moca) como riesgo para desarrollar enfermedad de Alzheimer, en adultos mayores de 65 años que acuden al servicio de cirugía del Hospital Regional Isidro Ayora en el periodo febrero-agosto 2014.
Bibliographic record
Abstract
Keywords; minimal cognitive impairment, Alzheimer's Disease, Test MOCA \n \nThis research work was conducted at the Department of Surgery at the Provincial Hospital Isidro Ayora Cave, during the period February 2014 - August 2014, and was raised as specific objectives; Identify according to MONTREAL COGNITIVE ASSESSMENT (MOCA), if any Minimum cognitive impairment in patients older than 65 years attending the Department of Surgery. Correlate in patients over 65 years with predisposing factors to determine whether they develop cognitive impairment as least risk to Alzheimer submit. Develop a proposal for intervention in patients with Minimum determined cognitive impairment. \n \n \nThe research is descriptive. The sample was constituted by 91 patients who met the inclusion criteria, the data collection sheet which includes general patient data was used as clinical history, patient name, age, gender, years of schooling, if you live alone, with some family in a house or home, your personal medical history: if you have Hypertension or Diabetes Mellitus is how long evolution and the present value of pressure and blood sugar, your height, weight, body mass index, personal habits such as snuff, alcohol, exercise, after learning that the MOCA test was applied. \n \nIn the present investigation minimal cognitive impairment predominates in males with 54% in those aged between 66 and 75 years concludes. These patients have a basic education have completed only primary. Within the cardiovascular risk their incidence is low, it’s determined by Body Mass Index weight is within normal limits, in history of Hypertension and Diabetes Mellitus its frequency is lower than 20% and 12% respectively. \nAlso within the personal habits of these patients consumption of snuff and alcohol is low, but in relation to sport these patients do not engage in any physical activity. \n \nWhat determines these are predisposing factors to developing Alzheimer's disease but may or may not modify its evolution? \n \nAlso a proposal for intervention where it could establish a policy of integration with a team of specialists in Internal Medicine, Neurology, Geriatrics, Radiology, Psychology and Social Work, where patients would come forwarded multidisciplinary team was introduced. We may establish our practice, measures to keep out the questions about forgetfulness of our patients and see if they apply them to the test MOCA and knowing the result guide both the patient and their family to perform memory exercises and submit if any Neurologist or a Geriatrician.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".