Supplementary Material for: The Incidence Prognosis and Risk Factors of Cognitive Impairment in Maintenance Haemodialysis Patients
Bibliographic record
Abstract
Objective: To investigate the incidence and the prognosis of cognitive impairment (CI) and to find out the risk factors associated with the outcome in maintenance haemodialysis (MHD) patients. Methods: Enrolled the patients who met the criteria as below: MHD (≥3 months) patients before July 2014, ≥18 years old and could carry on the cognitive function test (Montreal Cognitive Assessment [MoCA]). All enrolled patients were divided into 2 groups: CI group (MoCA < 26) and non-CI group (MoCA ≥26). All patients were followed up for 36 months. The incidence, demography data, medical history, haemodialysis data, laboratory examination and prognosis of CI in haemodialysis patients were prospectively compared and analyzed. Multivariate logistic regression analysis was used to investigate the risk factors of CI. Kaplan-Meier survival curve was used for survival analysis. Results: In the present study, 219 patients were enrolled. The ratio of male to female was 1.46: 1. Age was 60.07 ± 12.44 and dialysis vintage was 100.79 ± 70.23 months. One hundred thirteen patients’ MoCA scores were lower than 26 were divided into CI group. Education status (OR 3.428), post-dialysis diastolic pressure (OR 2.234) and spKt/V (OR 1.982) were independent risk factors for CI in MHD patients. During the follow-up period, 15 patients died (13.2%) in the CI group and 5 died (4.72%) in the non-CI group (p < 0.05). The Kaplan-Meier survival curve analysis showed that the survival rate of patients with CI was lower than that of non-CI group in MHD patients during 3 years follow-up (p = 0.046). Conclusion: CI is one of the most common complications in MHD patients. The mortality is high in patients who had CI. Education status, post-dialysis diastolic pressure and spKt/V are independent risk factors for CI in MHD 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 | 0.001 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.734 | 0.126 |
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".