To screen for obstructive sleep apnea in patients with type 2 diabetes mellitus and its association with microvascular complications
Bibliographic record
Abstract
Objectives: The objectives of this study were to find the association between obstructive sleep apnea (OSA) and microvascualr complications in patients with type 2 diabetes mellitus (T2DM). Material and Methods: This study was conducted at Bangalore Medical College. One hundred patients fulfilling the inclusion criteria were enrolled for the study. The study group included outpatients and inpatients with T2DM in Victoria Hospital and Bowring and Lady Curzon Hospital. The data were collected according to the pro forma in terms of history, clinical examination, and the necessary investigations (HbA1c and urine microalbumincreatinine ratio). To screen for OSA, STOP-BANG questionnaire was used. To assess microvascular complications, patients were subjected to fundoscopy, urine microalbumin-creatinine ratio, and Toronto clinical neuropathy scoring system. Based on STOP-BANG score, patients were divided into three groups: Low risk (0–2), intermediate risk (3–4), and high risk (5–8) for OSA. Mean values for the duration of diabetes, HbA1c, urine microalbumincreatinine ratio, and Toronto neuropathy score were compared in each group using ANOVA variance analysis. To find the association between OSA and diabetic retinopathy, Kruskal–Wallis test was used. Results: Based on STOP-BANG score, 16% of patients were in the low-risk group, 68% in the intermediate-risk group, and 16% in the high-risk group. There was a significant difference in Toronto neuropathy scores, urine microalbumin-creatinine ratio, and diabetic retinopathy between low-, intermediate-, and high-risk OSA groups indicating higher neuropathy scores, higher values of UMCR, and more advanced diabetic retinopathy among the high-risk group as compared to other two groups. The association between STOP-BANG scores and UMCR, Toronto neuropathy score, and diabetic retinopathy was statistically significant with P values of 0.002, 0.029, and 0.03, respectively. Conclusion: All diabetic patients should be screened for OSA which is simple and inexpensive. Those who fall in intermediate-risk and high-risk categories showed more advanced microvascular complications. They should be subjected to polysomnography and treated for OSA for better glycemic control and to delay the progression of microvascular complications.
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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 | 0.001 |
| 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) | 0.002 | 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".