Association of Visceral Obesity Indices With Incident Diabetic Retinopathy in Patients With Diabetes: Prospective Cohort Study
Notice bibliographique
Résumé
BACKGROUND: Visceral adipose tissue plays an active role in the pathogenesis of type 2 diabetes and vascular dysfunction. The lipid accumulation product (LAP), visceral adiposity index (VAI), and Chinese VAI (CVAI) have been proposed as simple and validated surrogate indices for measuring visceral adipose tissue. However, the evidence from prospective studies on the associations between these novel indices of visceral obesity and diabetic retinopathy (DR) remains scant. OBJECTIVE: This study aimed to investigate the longitudinal associations of LAP, VAI, and CVAI with incident DR in Chinese patients with diabetes. METHODS: This was a prospective cohort study conducted in Guangzhou in southern China. We collected baseline data between November 2017 and July 2020, while on-site follow-up visits were conducted annually until January 2022. The study participants consisted of 1403 patients with a clinical diagnosis of diabetes, referred from primary care, who were free of DR at baseline. The LAP, VAI, and CVAI levels were calculated by sex-specific equations based on anthropometric and biochemical parameters. DR was assessed using 7-field color stereoscopic fundus photographs and graded according to the modified Airlie House Classification scheme. Time-dependent Cox proportional hazard models were constructed to estimate the hazard ratios with 95% CIs. Restricted cubic spline curves were fitted to examine the dose-response relationship between the 3 indices of visceral obesity and new-onset DR. Subgroup analyses were performed to investigate the potential effect modifiers. RESULTS: The mean age of study participants was 64.5 (SD 7.6) years, and over half (816/1403, 58.2%) were female. During a median follow-up of 2.13 years, 406 DR events were observed. A 1-SD increment in LAP, VAI, or CVAI was consistently associated with increased risk for new-onset DR, with a multivariable‑adjusted hazard ratio of 1.24 (95% CI 1.09-1.41; P=.001), 1.22 (95% CI 1.09-1.36; P<.001), and 1.48 (95% CI 1.19-1.85; P=.001), respectively. Similar patterns were observed across tertiles in LAP (P for trend=.001), VAI (P for trend<.001), and CVAI (P for trend=.009). Patients in the highest tertile of LAP, VAI, and CVAI had an 84%, 86%, and 82% higher hazard of DR, respectively, compared to those in the lowest tertile. A nonlinear dose-response relationship with incident DR was noted for LAP and VAI (both P for nonlinearity<.05), but not for CVAI (P for nonlinearity=.51). We did not detect the presence of effect modification by age, sex, duration of diabetes, BMI, or comorbidity (all P for interaction>.10). CONCLUSIONS: Visceral obesity, as measured by LAP, VAI, or CVAI, is independently associated with increased risk for new-onset DR in Chinese patients with diabetes. Our findings may suggest the necessity of incorporating regular monitoring of visceral obesity indices into routine clinical practice to enhance population-based prevention for DR.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».