Does Diabetes Alter CSF Total Protein Levels? A Retrospective Cohort Study
Bibliographic record
Abstract
Background and Purpose: Elevation of total protein level in cerebrospinal fluid (CSF-TP) in diabetic patients is often disregarded by clinicians. However, existing studies on the topic have significant limitations, and therefore we aimed to explore the relationship between diabetes and CSF-TP in a large database of CSF samples. Methods: Retrospective review of all diagnostic lumbar punctures at the Ottawa Hospital between 1996-2016. Patients were excluded if they had elevated CSF cell counts, or a condition known to elevate CSF-TP. Multivariate linear regression modeling considered the effects of age, sex, and diabetes. Results: Among 6124 patients (746 with diabetes, 5378 without), mean CSF-TP did not differ significantly between groups (0.39 and 0.35 mmol/L, p = 0.2). When controlled for age and sex, there was no significant effect of diabetes on CSF-TP and no significant correlation between mean serum glucose and CSF-TP (R 2 = 0.12). Conclusions: CSF-TP did not differ significantly between diabetic and non-diabetic groups, once the influence of age and sex was controlled. Elevated CSF-TP should be regarded as pathologic, even in the setting of diabetes.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".