Malnutrition-inflammation is a risk factor for cerebral small vessel diseases and cognitive decline in peritoneal dialysis patients: a cross-sectional observational study
Bibliographic record
Abstract
BACKGROUND: Chronic kidney disease patients have an increased prevalence of subclinical cerebrovascular diseases. Dialysis patients have severe vascular diseases burden. The cerebral small vessel diseases (CSVD) are difficult to find by clinical assessment. The evaluation of CVSD needs MRI. Cognitive impairment is a consequence of CVSD which is diagnosed by cognitive testing. These limited the study of CVSD and cognitive function in dialysis patients. Peritoneal dialysis (PD) patients are minority of dialysis population. We know even fewer about the CVSD in this special population. METHODS: In this cross-sectional study, we enrolled 72 PD patients who received care at the Peking Union Medical College hospital peritoneal dialysis center. CSVD were assessed by brain MR images. Cognitive function was evaluated with the Chinese version of the MMSE and MoCA. RESULTS: In our PD patients, the brain MRI showed the prevalence different signs of CSVD were: lacunar infarcts 38.9%, microbleeds 36.1%, abnormal brain white matter hyperintensities (WMHs) 48.6%, and intracerebral hemorrhage 4.2%. 25% and 86.8%of our patients could be diagnosed as cognitive impairment, according to the MMSE and MoCA test, respectively. nPCR was lower in patients with a lacunar infarct or intracerebral hemorrhage, and relative to the MMSA/MoCA score; hsCRP was higher in patients with lacunar infarct or abnormal WMHs and negative relative to the MMSA/MoCA score. In logistic regression analyses, nPCR was an independent risk factor for lacunar infarcts and impaired cognitive function. The presence of lacunar infarct was an independent risk factor for cognitive function decline. CONCLUSION: We demonstrated a high prevalence of CSVD and cognitive impairment in our PD patients. Lacunar infarct was the main kind of CVSD responsible for PD patients cognitive function decline. Our novel observation also revealed an association between malnutrition-inflammation and CSVD.
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How this classification was reachedexpand
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".