Cognitive Dysfunction Screening in Peritoneal Dialysis Patients: A Cross-Sectional Study
Why this work is in the frame
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Bibliographic record
Abstract
Background: Mild cognitive impairment (MCI) in peritoneal dialysis (PD) patients has been described as a risk factor for worse outcomes such as peritonitis, technique failure, and mortality. In this study, we aimed to determine the prevalence of MCI in a population of PD patients and identify the possible risk factors associated with MCI. Materials and Methods: We performed an observational, cross-sectional study to evaluate cognitive function using the Montreal Cognitive Assessment (MOCA) test and the Mini Mental State Examination (MMSE) test in PD patients. Patients with diagnosis of dementia or severe neurologic impairment, active cancer, or infection were excluded. Results: We evaluated 66 patients (mean age 60 years); 53% were male. Prevalence of MCI assessed by MOCA test and MMSE test was 65% and 33%, respectively. Predictors of MCI with MOCA test were higher age ( P = 0.0001), lower education level ( P = 0.005), need of a helper ( P = 0.009), and continuous ambulatory PD modality ( P = 0.019). Higher Charlson comorbidity index ( P = 0.002), coronary artery disease ( P = 0.006), and peripheral artery disease ( P = 0.033) were also associated with MCI. Lower Kt/V ( P = 0.012) and lower levels of normalized protein catabolic rate (nPCR; P < 0.000) were related to MCI. MCI patients had more episodes of peritonitis ( P = 0.047). Multivariable analysis showed that lower education, Kt/V, and nPCR were the most relevant factors connected to MCI ( P = 0.029, P = 0.037, and P = 0.019, respectively). Conclusion: In our PD population, MCI was detected in more than half of the patients. Patients with MCI were older, had lower education level, more disease burden, and higher risk for developing peritonitis. Lower Kt/V and nPCR levels were associated with MCI.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it