We used 3-d food-record-keeping techniques to examine nutritional factors in diabetic patients with and without retinopathy. Patients without retinopathy had significantly higher daily intakes of total carbohydrate, water-soluble dietary fibers, insoluble dietary fibers, and glucose than did patients with retinopathy. Also, patients without retinopathy took a significantly lower proportion of their total daily calories as protein.

Biological fluid collection to identify and analyze different disease markers is a routine and normal procedure in health care settings. Body fluids are as varied as urine, blood, mucus, cerebrospinal fluid (CSF), tears, semen, etc. The volumes of the collected fluids range from micro liters (e.g., tears, CSF) to tens and hundreds of milliliters (blood, urine, etc.). In some manifestations, a disease marker (particularly protein markers) can occur in trace amounts, yet the fluids collected are in large volumes. To identify these trace markers, cumbersome methods, expensive instruments, and trained personnel are required. We developed an easy method to rapidly capture, concentrate, and identify protein markers in large volumes of test fluids. This method involves the utilization of two antibodies recognizing two different epitopes of the protein biomarker. Antibody-1 helps to capture and concentrate the biomarker and Antibody-2 adsorbed or conjugated to nanogold beads will detect the biomarker. This method was validated in capturing and detecting lipocalin type prostaglandin-D2 synthase, a marker in urine that implicates diabetic nephropathy. A one-step collection, concentration, and detection device was designed based on this method. This device can replace many of the normal body fluid collection devices such as tubes and containers. A one-step fluid collection and biomarker capture and concentration device for rapid diagnosis of diseases has tremendous advantage in terms of cost and providing timely results.

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Background: It is common for patients with type 2 diabetes mellitus (T2DM) to have vitamin D deficiency. Aim of the study is to determine the metabolic effects of oral vitamin D supplementation in a cohort of T2DM subjects.Methods: Subjects with T2DM were divided into two groups. Group A (Control) included subjects who received the standard treatment (conventional antidiabetic drugs). Group B (Intervention), apart from the standard treatment (conventional antidiabetic drugs), was also supplemented with Vitamin D3. All the patients were followed up at baseline, 6 months, 12 months and 18 months.Results: Vitamin D deficiency was noted down in all the study subjects. Even after 18 months of supplementation, all subjects remained vitamin D deficient. There was a significant improvement in the circulating levels of 25-hydroxyvitamin D. Improvement in the lipid profile of subjects was observed as evidenced by a decrease in total cholesterol (5.0±0.92 mmol/l) as compared to baseline (5.5±1.6 mmol/l). HOMA-IR changed significantly after 18 months of supplementation from baseline (7.0±1.06 vs 10.8±1.96 nmol/l).Conclusions: Supplementation to achieve higher levels of vitamin D remains a promising adjuvant therapy for T2DM patients. Additionally, the intervention brought out a favourable change in HDL/LDL ratio among study subjects.

Background:Limited information is available on the impact of target disease-modifying anti-rheumatic drugs (tDMARD) on patients with rheumatoid arthritis (RA) and type 2 diabetes mellitus (T2DM).Objectives:The objective was to compare T2DM-related healthcare resource utilization (HCRU) and cost for TNF inhibitors (TNFi)-naive patients pooled from two commercial databases with RA and T2DM receiving abatacept, other non-TNFi, or TNFi.Methods:A retrospective, observational study was conducted with MarketScan and PharMetrics (January 2008-September 2018). The study population included TNFi-naïve adult patients with RA and T2DM newly initiating abatacept, TNFi (adalimumab, certolizumab pegol, etanercept, golimumab, infliximab) or other non-TNFi (tocilizumab, anakinra, sarilumab, rituximab, tofacitinib). Date of tDMARD initiation was the index date. Patients had ≥2 RA diagnoses separated by ≥7 days, ≥1 T2DM diagnosis, and had ≥12 months of pre-index continuous enrollment. Follow-up ended at the end of patient insurance enrollment, study period or index treatment. T2DM-related HCRU and costs including inpatient stay, outpatient visits, ER visits, and pharmacy use were measured on a per-patient-per-month (PPPM) basis (2018 USD). Patients treated with abatacept were matched to TNFi and non-TNFi cohorts separately by propensity score adjusted with patients baseline comorbidities, HCRU, and costs.Results:A total of 16,236 patients meeting criteria were identified. Most patients were female (74.3%), and the overall average age of 55.4 years (Table 1). After matching, 850 pairs of abatacept vs non-TNFi patients, and 1,096 pairs of abatacept vs TNFi patients were included in the adjusted results. Patients initiating abatacept had $144 lower adjusted T2DM-related costs as compared to non-TNFi and $79 lower costs than TNFi cohorts (Table 2).Table 1.Patient CharacteristicsAbataceptn=1,134Non-TNFin=1,353TNFin=13,749TotalN=16,236Age, mean years (SD)58.5 (11.3)57.7 (11.2)54.9 (10.6)55.41 (10.7)Gender, female, n (%)936 (82.5)993 (73.4)10,142 (73.8)12,071 (74.3)CCI, mean (SD)2.2 (1.4)2.3 (1.4)1.8 (1.1)1.89 (1.14)DCSI, n (%) Cardiovascular361 (31.8)406 (30.0)2,500 (18.2)3,267 (20.1) Neuropathy294 (25.9)374 (27.6)3,161 (23.0)3,829 (23.6) Nephropathy146 (12.9)193 (14.3)1,151 (8.4)1,490 (9.2) PVD131 (11.6)155 (11.5)874 (6.4)1,160 (7.1) Retinopathy103 (9.1)119 (8.8)922 (6.7)1,144 (7.0) Cerebrovascular74 (6.5)102 (7.5)620 (4.5)796 (4.9) Metabolic9 (0.8)20 (1.5)141 (1.0)170 (1.0)CCI: Charlson comorbidity index; DCSI: diabetes complications severity index; PVD: peripheral vascular disease.Table 2.Adjusted T2DM-related HCRU and Costs after Propensity Score MatchingAbataceptn=850Non-TNFin=850Diff (ABA- Non-TNF)Abataceptn=1,096TNFin=1,096Diff (ABA- TNF)T2DM-related HCRU (per 1000 Patients per Month)Number of Hospitalizations13.920.4-6.5*12.614.9-2.3*Number ofER Visits22.016.15.9*18.416.32.0*Number ofOutpatient Visits311334.8-23.7*299.3286.912.4T2DM-related Costs (PPPM $)Inpatient Costs507535-28413475-62ER Costs271710*2225-3Outpatient Costs190323-13318617016*Pharmacy Costs1071007*97128-31Total Costs831975-144719798-79**P<0.05Conclusion:TNFi-naive RA patients with T2DM newly initiating abatacept had lower adjusted rates of T2DM-related hospitalizations compared to patients who initiated a non-TNFi or a TNFi. Total costs were lower among patients initiating abatacept vs. patients who initiated a non-TNFi or a TNFi. Findings suggest that initial abatacept among TNFi-naïve patients may be able to reduce healthcare utilization arising from T2DM complications and reduce T2DM-related costs in RA patients.Disclosure of Interests:Xue Han Employee of: BMS, Qian Xia Shareholder of: I own shares of Bristol-Myers Squibb Company, Employee of: I am a paid employee of Bristol-Myers Squibb Company, Ying Bao Shareholder of: Bristol-Myers Squibb, Employee of: Bristol-Myers Squibb, Vardhaman PATEL Employee of: Bristol Myers Squibb, Amrina Roy Employee of: Mu-Sigma, Varshini Rajagopalan Employee of: Mu-Sigma, Francis Lobo Shareholder of: Bristol-Myers Squibb (US), Employee of: Bristol-Myers Squibb (US)