The Relationships between Retinopathy and Other Vascular Complications in Adults with Long-Standing Diabetes—Results from the Canadian Study of Longevity in Type 1 Diabetes (T1D)
Bibliographic record
Abstract
We aimed to measure the prevalence of retinopathy in a T1D cohort of 75 adults with T1D duration of ≥50 years, and to determine association with other vascular complications. Participants underwent ultra-widefield retinal imaging and optimal coherence tomography. Neuropathy was characterized by electrophysiology and corneal confocal microscopy. Intrarenal hemodynamic function was determined by inulin and para-aminohippurate clearance, and arterial stiffness was measured by applanation tonometry, both at baseline and in responses to intravenous angiotensin II (ANGII). Participants were classified as having no diabetic retinopathy (ⱷDR), non-proliferative (NPDR), or proliferative (PDR), and associations were determined using multivariable linear regression adjusting for age, sex, and HbA1c. Thirty-nine (52%) participants had PDR, 24 (32%) had NPDR, and 12 (16%) had ⱷDR. Those without retinopathy had lower HbA1c vs. those with NDPR and PDR (6.7±0.6% vs. 7.4±0.7% and 7.5±0.9%, p=0.019). PDR was associated with lower corneal nerve fibre density, worse electrophysiology, and a greater number of signs and symptoms of neuropathy, but not with intrarenal hemodynamic function. Retinopathy severity was associated with greater response to ANGII for carotid-radial pulse wave velocity (mean change -4.9±11.4% vs. 8.2±18.5% vs. 12.9±20.2% for ⱷDR, NPDR, and PDR respectively, p=0.043). In longstanding T1D, retinopathy associated strongly with neuropathy and arterial stiffening, but not with renal hemodynamic function. Greater understanding of the co-occurrence of microvascular complications in patients with T1D, and relationships with macrovascular abnormalities such as arterial stiffness, may improve early detection and management of diabetes-related diseases. Disclosure J.A. Lovshin: Other Relationship; Self; AstraZeneca. Consultant; Self; Novo Nordisk Inc.. Research Support; Self; Sanofi, Merck Sharp & Dohme Corp.. Other Relationship; Self; Novo Nordisk Inc.. L. Lovblom: None. P. Bjornstad: Consultant; Self; Boehringer Ingelheim GmbH. Y. Lytvyn: None. G. Boulet: Advisory Panel; Self; Medtronic, Sanofi, Novo Nordisk Inc.. Other Relationship; Self; Janssen Global Services, LLC., Abbott. A. Weisman: None. V.S. Lai: None. J.M. Tse: None. L. Cham: None. A. Orszag: None. H.A. Keenan: Research Support; Self; Sanofi. Employee; Self; Sanofi Genzyme. N. Paul: None. V. Bril: Consultant; Self; Alexion Pharmaceuticals, Inc.. Research Support; Self; CSL Behring, Grifols. Advisory Panel; Self; CSL Behring. Consultant; Self; Grifols. Research Support; Self; Shire. Advisory Panel; Self; Pfizer Inc. M.H. Brent: Research Support; Self; Novartis Canada. Advisory Panel; Self; Novartis Canada. Research Support; Self; Bayer Canada. Advisory Panel; Self; Bayer Canada, Allergan Canada. Research Support; Self; Roche Canada. B.A. Perkins: Advisory Panel; Self; Boehringer Ingelheim GmbH. Research Support; Self; Boehringer Ingelheim GmbH, Novo Nordisk Inc.. Advisory Panel; Self; Novo Nordisk Inc., Abbott. Speaker's Bureau; Self; Abbott, Janssen Pharmaceuticals, Inc.. Advisory Panel; Self; Insulet Corporation. Speaker's Bureau; Self; Insulet Corporation, Dexcom, Inc. D. Cherney: Consultant; Self; AbbVie Inc.. Other Relationship; Self; AstraZeneca, Boehringer Ingelheim GmbH, Eli Lilly and Company. Consultant; Self; Sanofi. Other Relationship; Self; Merck & Co., Inc.. Consultant; Self; Mitsubishi Tanabe Pharma Corporation. Other Relationship; Self; Janssen Pharmaceuticals, Inc..
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".