Relationship between β-amyloid protein 1-42, thyroid hormone levels and the risk of cognitive impairment after ischemic stroke
Bibliographic record
Abstract
BACKGROUND: Post-stroke cognitive impairment (PSCI) is not only a common consequence of stroke but also an important factor for adverse prognosis of patients. Biochemical indicators such as blood lipids and blood pressure are affected by many factors, and the ability of evaluating the progress of patients with PSCI is insufficient. Therefore, it is necessary to find sensitive markers for predicting the progress of patients and avoiding PSCI. Recent studies have shown that β-amyloid protein 1-42 (Aβ1-42) and thyroid hormone levels are closely related to PSCI, which may be the influencing factors of PSCI, but there are few related studies. AIM: To investigate the relationship between serum levels of Aβ and thyroid hormones in acute stage and PSCI and its predicted value. METHODS: A total of 195 patients with acute cerebral infarction confirmed from June 2016 to January 2018 were enrolled in this study. Baseline data and serological indicators were recorded to assess cognitive function of patients. All patients were followed up for 1 year. Their cognitive functions were evaluated within 1 wk, 3 mo, 6 mo and 1 yr after stroke. At the end of follow-up, the patients were divided into PSCI and non-PSCI according to Montreal cognitive assessment score, and the relationship between biochemical indexes and the progression of PSCI was explored. RESULTS: , the higher risk of PSCI in patients who were aged over 70, female and illiterate. CONCLUSION: Aβ1-42 and T3 have the ability to predict the progression of PSCI, which is expected to be applied clinically to reduce the incidence of PSCI and improve the quality of life of patients.
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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 | 0.000 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".