Diabetes care最新文献

Objective: We investigated the association between historic redlining and risk of gestational diabetes mellitus (GDM), and whether this relationship is mediated by maternal obesity and area-level deprivation.

Research design and methods: This retrospective study included 86,834 singleton pregnancies from Kaiser Permanente Southern California's health records (2008-2018). Redlining was assessed using digitized Home Owners' Loan Corporation (HOLC) maps, with patients' residential addresses geocoded and assigned HOLC grades (A, B, C, or D) based on their geographic location within HOLC-graded zones. For GDM case patients, exposure was assigned based on address at diagnosis date; for noncase patients, it was assigned based on address during the 24th to 28th gestational week. Health records were combined with area deprivation index (ADI) from 2011 to 2015 census data. Mixed-effect logistic regression models assessed associations between redlining and GDM, with mediation by BMI and ADI evaluated using inverse odds ratio weighting. Models were adjusted for maternal age, education, race and ethnicity, neighborhood-level income, and smoking status.

Results: Among the 10,134 (11.67%) GDM case patients, we found increased risk of GDM in B ("still desirable," adjusted odds ratio [aOR] 1.20, 95% CI 0.99-1.44), C-graded ("definitely declining," aOR 1.22, 95% CI 1.02-1.47), and D-graded ("hazardous," i.e., redlined, aOR 1.30, 95% CI 1.08-1.57) neighborhoods compared with the "best"-graded zone. Prepregnancy BMI and ADI mediated 44.2% and 64.5% of the increased GDM risk among mothers in redlined areas.

Conclusions: Historic redlining is associated with an increased risk of GDM, mediated by maternal obesity and neighborhood deprivation. Future research is needed to explore the complex pathways linking redlining to pregnancy outcomes.

Objective: Diabetic peripheral neuropathy (DPN) and neuropathic pain impacts quality of life (QoL) and mental health negatively. This cross-sectional survey study aimed to 1) elucidate the associations between painful and painless DPN and QoL, mental health, and socioeconomic factors, 2) assess the prevalence of sensory pain descriptors, and 3) evaluate the association between descriptors and the above factors.

Research design and methods: Participants were grouped into people with (n = 1,601) and without (n = 5,359) DPN based on the Michigan Neuropathy Screening Instrument questionnaire. Participants with DPN were subsequently divided into people with (n = 1,085) and without (n = 516) concomitant neuropathic pain based on the modified Douleur Neuropathique en 4 Questions-interview.

Results: The study showed diminished QoL (36-item Short Form Health Survey [SF-36]: 55.1 [interquartile range {IQR}36.7, 73.6], 82.2 [63.6, 90.9]) and poorer mental health (Hospital Anxiety and Depression Scale, subscale for anxiety: [HADS-A]: 5.00 [2, 9], 2.00 [1, 5]; HADS-subscale for depression [HADS-D]: 4.00 [1, 8], 1.00 [0, 3]) in participants with DPN compared with participants without DPN. The addition of pain diminished QoL (SF-36: 50.7 [34.8, 69.8]) and mental health (HADS-A: 6 [3, 10], HADS-D: 4 [1, 8]) further. The most prevalent pain descriptor in participants with painful DPN were burning pain (73%), while the most prevalent sensory descriptor was pins-and-needles (93%). An interesting finding is the high prevalence of itch (44%). Weak associations with mental health and QoL were present for cold pain, electric pain, and itch.

Conclusions: An increased focus on differences in QoL, mental health, and pain phenotypes is of importance to move the field forward toward more interdisciplinary, personalized treatment.

Objective: We examined sex differences in longitudinal blood pressure (BP) and 32-year cardiovascular disease (CVD) incidence in the Pittsburgh Epidemiology of Diabetes Complications type 1 diabetes cohort.

Research design and methods: BP was measured up to nine (median six) times between 1986-1988 baseline and 2016-2018; n = 300 women and 304 men without CVD at baseline were followed until December 2020 for incidence of total CVD, major adverse cardiovascular events (MACE) (CVD death, myocardial infarction [MI], or stroke), and hard coronary artery disease (hCAD) (CAD death, MI, or coronary revascularization/blockage ≥ 50%). We estimated associations between time to event and longitudinal systolic BP (SBP) and diastolic BP (DBP) by sex using joint models adjusted for time-varying longitudinal antihypertensive (AH) medication use, HbA1c, and overt nephropathy, baseline age, and other CVD risk factors.

Results: Longitudinal SBP was 5.8 mmHg lower (P < 0.0001) and DBP 6.2 mmHg lower (P < 0.0001) in women versus men. Women had -0.3 mmHg/year faster DBP decline (P < 0.0001) despite similar AH rates by sex. Incidence of CVD was similar by sex. Each 5-mmHg increment in longitudinal SBP (hazard ratio [HR] = 1.23; 95% CI 1.04, 1.45) and DBP (HR = 1.56; 95% CI 1.20, 2.04) was associated with MACE in men only; DBP (HR = 1.28; 95% CI 1.05, 1.56) was associated with hCAD in women only.

Conclusions: BP was lower in women than men, and the strength of its association with the initial manifestation of CVD differed by sex. Further research into sex-specific BP mechanisms is needed to improve CVD risk reduction in people living with type 1 diabetes.

Objective: Evidence for using continuous glucose monitoring (CGM) as an alternative to oral glucose tolerance tests (OGTTs) in presymptomatic type 1 diabetes is primarily cross-sectional. We used longitudinal data to compare the diagnostic performance of repeated CGM, HbA1c, and OGTT metrics to predict progression to stage 3 type 1 diabetes.

Research design and methods: Thirty-four multiple autoantibody-positive first-degree relatives (FDRs) (BMI SD score [SDS] <2) were followed in a multicenter study with semiannual 5-day CGM recordings, HbA1c, and OGTT for a median of 3.5 (interquartile range [IQR] 2.0-7.5) years. Longitudinal patterns were compared based on progression status. Prediction of rapid (<3 years) and overall progression to stage 3 was assessed using receiver operating characteristic (ROC) areas under the curve (AUCs), Kaplan-Meier method, baseline Cox proportional hazards models (concordance), and extended Cox proportional hazards models with time-varying covariates in multiple record data (n = 197 OGTTs and concomitant CGM recordings), adjusted for intraindividual correlations (corrected Akaike information criterion [AICc]).

Results: After a median of 40 (IQR 20-91) months, 17 of 34 FDRs (baseline median age 16.6 years) developed stage 3 type 1 diabetes. CGM metrics increased close to onset, paralleling changes in OGTT, both with substantial intra- and interindividual variability. Cross-sectionally, the best OGTT and CGM metrics similarly predicted rapid (ROC-AUC = 0.86-0.92) and overall progression (concordance = 0.73-0.78). In longitudinal models, OGTT-derived AUC glucose (AICc = 71) outperformed the best CGM metric (AICc = 75) and HbA1c (AICc = 80) (all P < 0.001). HbA1c complemented repeated CGM metrics (AICc = 68), though OGTT-based multivariable models remained superior (AICc = 59).

Conclusions: In longitudinal models, repeated CGM and HbA1c were nearly as effective as OGTT in predicting stage 3 type 1 diabetes and may be more convenient for long-term clinical monitoring.

Objective: The Metformin and Dietary Restriction to Prevent Age-Related Morbid Events in People With Metabolic Syndrome (MeMeMe) trial tested whether 1,700 mg/day metformin (MET) with or without a Mediterranean diet (MedDiet) intervention could reduce the cumulative incidence of major noncommunicable diseases in people with metabolic syndrome.

Research design and methods: A total of 1,442 participants were randomly assigned to one of four interventions: 1) MET (1,700 mg/day) plus MedDiet intervention (MET+MedDiet); 2) placebo plus MedDiet intervention; 3) MET (1,700 mg/day) alone; and 4) placebo alone. Participants were followed up for 3 years on average. The primary outcome was the cumulative incidence of major noncommunicable diseases (including type 2 diabetes, cardiovascular diseases, and cancer). Secondary outcomes were the incidence of type 2 diabetes and the changing prevalence of metabolic syndrome.

Results: The crude incidence of the major noncommunicable diseases was 6.7 cases per 100 person-years in the MET+MedDiet group, 6.9 in the MET alone group, 13.3 in the placebo plus MedDiet group, and 11.3 in the placebo group. The differences were fully explained by the reduction of type 2 diabetes, which was 80% and 92% lower in the MET and MET+MedDiet groups, respectively, compared with placebo.

Conclusions: The use of 1,700 mg/day MET is effective to prevent diabetes in people selected on the basis of metabolic syndrome.

Objective: To explore how the commercially available large language model (LLM) GPT-4 compares to endocrinologists when addressing medical questions when there is uncertainty regarding the best answer.

Research design and methods: This study compared responses from GPT-4 to responses from 31 endocrinologists using hypothetical clinical vignettes focused on diabetes, specifically examining the prescription of metformin versus alternative treatments. The primary outcome was the choice between metformin and other treatments.

Results: With a simple prompt, GPT-4 chose metformin in 12% (95% CI 7.9-17%) of responses, compared with 31% (95% CI 23-39%) of endocrinologist responses. After modifying the prompt to encourage metformin use, the selection of metformin by GPT-4 increased to 25% (95% CI 22-28%). GPT-4 rarely selected metformin in patients with impaired kidney function, or a history of gastrointestinal distress (2.9% of responses, 95% CI 1.4-5.5%). In contrast, endocrinologists often prescribed metformin even in patients with a history of gastrointestinal distress (21% of responses, 95% CI 12-36%). GPT-4 responses showed low variability on repeated runs except at intermediate levels of kidney function.

Conclusions: In clinical scenarios with no single right answer, GPT-4's responses were reasonable, but differed from endocrinologists' responses in clinically important ways. Value judgments are needed to determine when these differences should be addressed by adjusting the model. We recommend against reliance on LLM output until it is shown to align not just with clinical guidelines but also with patient and clinician preferences, or it demonstrates improvement in clinical outcomes over standard of care.