Study on the relationship between hypoglycemia and cognitive function in type 2 diabetes cases
Bibliographic record
Abstract
Objective To explore the relationship between hypoglycemia,especially recurrent hypoglycemia and cognitive function in type 2 diabetes cases and analyze the influencing factors.Methods Totally 133 the cases were evaluated with Montreal Cognitive Assessments(MOCA)and divided into two groups,normal cognition group(A,31 cases,score≥26)and impaired cognitive function group(B,102 cases,score26).The indexes including age,education level,progress of the diabetes,hypoglycemia,hypertension,body mass index(BMI),the complication,level of cholesterols and triglycerides were analyzed with single factor,and influencing factors were analyzed by logistic regression method.Results Compared with group B,younger age,lower frequency of hypoglycemia,shorter course of diabetes,less complication,lower hyperlipidemia and BMI and higher education level were in group A.Conclusion The frequency of hypoglycemia,the complication and progress of diabetes,age,BMI,cholesterols and triglycerides are risk factors for cognitive disorder,and education level is protective factor.Frequency of hypoglycemia and diabetic complication play key role for cognitive disorder.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 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".