To Screen for Obstructive Sleep Apnoea in Type 2 Diabetes and its Correlation with Hscrp Levels and Microvascular Complications.
Bibliographic record
Abstract
The prevalence of OSA is estimated to be 2-4% in the general population but high among diabetics. Since intermittent hypoxia has shown to exert adverse effects on glucose metabolism, OSA increases the risk of developing T2DM and contributes to poor glycemic control. Studies show that people with diabetes with severe OSA had higher HbA1c levels compared to non-apneic people. and implicated that OSA is a pro-inflammatory state wherein inflammatory markers like hsCRP are elevated. This study aims to study the correlation between OSA, hsCRP levels,glycemic control and presence of microvascular complications in diabetics. Material: This cross-sectional study was conducted in the hospitals attached to BMCRI. 100 patients with T2DM fitting the ADA criteria were screened by the STOP-BANG questionnair and were divided into OSA risk groups based on STOP-BANG score: 0-2, 3-4 and 5-8 indicated low, intermediate and high risk respectively. hsCRP levels were estimated. To assess microvascular complications, patients were subjected to Toronto clinical neuropathy score for diabetic neuropathy, fundoscopy for diabetic retinopathy and urine microalbumin creatinine ratio for nephropathy. Observation: Out of the 100 patients, 16 were in high risk, 68 in intermediate risk and 16 in low risk group.
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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 | 0.000 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".