Influence of selected factors on the prevalence of cognitive disorders and depression among patients over 60 years of age
Bibliographic record
Abstract
D -data interpretation, E -Manuscript Preparation, F -Literature search, G -Funds collectionBackground. dementia is defined as a gradual loss of intellectual capabilities and cognitive functions that may impair daily functioning.early diagnosis seems essential for proper treatment and slowdown of disease progression.Multimorbidity leading to polypharmacotherapy need a complex dosage regimen. in patients with dementia, this is a real challenge.Objectives. to determine the incidence and the risk factors of cognitive disorders and depression among patients over 60 years of age.Material and methods.a group of 115 patients over 60 years of age attending primary care and geriatric ward in Lodz were enrolled in this observational study (75 women -65.2%; 40 men -34.8%).the patients underwent MMse, gds and cdt tests and completed a questionnaire concerning age, place of residence, marital status, medical history and family history of dementia.the data collected was statistically analysed using statistica 10.0 (statsoft inc, usa).Results.education level in the group: 20% basic, 51.3% secondary, 28.7% higher education.45.2% were married, 54.6% were single.61.7% had hypertension, 27.0% -diabetes, 9.6% -atherosclerosis, and 9.6% had a stroke in the past.Mean score of gds was 9.2 points; MMse 25.7; cdt 1.9.a higher score in gds correlated with a worse result of MMse (p < 0.05).age was an important factor in the group with basic education; it affected: MMse (lower) and cdt (higher) results.Male patients achieved a higher score in MMse (p = 0.0399) and lower in cdt (p = 0.0345).the MMse result was higher (p = 0.0454) and the cdt result was lower (p = 0.0230) in married individuals.the number of diseases correlated with the gds score (p < 0.05). Conclusions.Patients predisposed to dementia were: older females, patients with basic education, those who were single, mostly widowed.Family physicians should pay special attention to such patients and be aware of early symptoms of dementia.cooperation with the patient's family or caregivers seems crucial to provide proper care and improve patient compliance.
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 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 | 0.002 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".