Purpose To evaluate the accuracy of various claims‐based definitions of diabetes‐related complications (coronary artery disease [CAD], heart failure, cerebrovascular disease and dialysis). Methods We evaluated data on 1379 inpatients who received care at the Niigata University Medical & Dental Hospital in September 2018. Manual electronic medical chart reviews were conducted for all patients with regard to diabetes‐related complications and were used as the gold standard. Sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of each claims‐based definition associated with diabetes‐related complications based on Diagnosis Procedure Combination (DPC), International Classification of Diseases, Tenth Revision (ICD‐10) codes, procedure codes and medication codes were calculated. Results DPC‐based definitions had higher sensitivity, specificity, and PPV than ICD‐10 code definitions for CAD and cerebrovascular disease, with sensitivity of 0.963–1.000 and 0.905–0.952, specificity of 1.000 and 1.000, and PPV of 1.000 and 1.000, respectively. Sensitivity, specificity, and PPV were high using procedure codes for CAD and dialysis, with sensitivity of 0.963 and 1.000, specificity of 1.000 and 1.000, and PPV of 1.000 and 1.000, respectively. DPC and/or ICD‐10 codes + medication were better for heart failure than the ICD‐10 code definition, with sensitivity of 0.933, specificity of 1.000, and PPV of 1.000. The PPVs were lower than 60% for all diabetes‐related complications using ICD‐10 codes only. Conclusion The DPC‐based definitions for CAD and cerebrovascular disease, procedure codes for CAD and dialysis, and DPC or ICD‐10 codes with medication codes for heart failure could accurately identify these diabetes‐related complications from claims databases.

Background: Bariatric surgery leads to a higher remission rate for type 2 diabetes mellitus than non-surgical treatment. However, it remains unsolved which surgical procedure is the most efficacious. This network meta-analysis aimed to rank surgical procedures in terms of diabetes remission. Methods and findings:We electronically searched for randomized controlled trials in which at least one surgical treatment was included among multiple arms and the diabetes remission rate was included in study outcomes. A random-effects network meta-analysis was performed within a frequentist framework. The hierarchy of treatments was expressed as the surface under the cumulative ranking curve value. Results of the analysis of 25 eligible randomized controlled trials that covered non-surgical treatments and eight surgical procedures (biliopancreatic diversion [BPD], BPD with duodenal switch, Roux-en Y gastric bypass, mini gastric bypass [mini-GBP], laparoscopic adjustable gastric banding, laparoscopic sleeve gastrectomy, greater curvature plication and duodenal-jejunal bypass) showed that BPD and mini-GBP had the highest surface under the cumulative ranking curve values among the eight surgical treatments.Conclusion: Current network meta-analysis indicated that BPD or mini-GBP achieved higher diabetes remission rates than the other procedures. However, the result needs to be interpreted with caution considering that these procedures were in the minority of bariatric surgeries.Data limited to patients with DM. ‡ Patients who dropped out or were excluded from the final analyses were included in baseline data on mean age, proportion of men, mean BMI, mean A1C and mean FPG. § Number of patients who were included in the analysis (not necessarily the number of patients included in the analysis of each study).Network meta-analysis of bariatric surgeries S. Kodama et al. 1623 obesity reviews

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Background Machine learning (ML) algorithms have been widely introduced to diabetes research including those for the identification of hypoglycemia. Objective The objective of this meta-analysis is to assess the current ability of ML algorithms to detect hypoglycemia (ie, alert to hypoglycemia coinciding with its symptoms) or predict hypoglycemia (ie, alert to hypoglycemia before its symptoms have occurred). Methods Electronic literature searches (from January 1, 1950, to September 14, 2020) were conducted using the Dialog platform that covers 96 databases of peer-reviewed literature. Included studies had to train the ML algorithm in order to build a model to detect or predict hypoglycemia and test its performance. The set of 2 × 2 data (ie, number of true positives, false positives, true negatives, and false negatives) was pooled with a hierarchical summary receiver operating characteristic model. Results A total of 33 studies (14 studies for detecting hypoglycemia and 19 studies for predicting hypoglycemia) were eligible. For detection of hypoglycemia, pooled estimates (95% CI) of sensitivity, specificity, positive likelihood ratio (PLR), and negative likelihood ratio (NLR) were 0.79 (0.75-0.83), 0.80 (0.64-0.91), 8.05 (4.79-13.51), and 0.18 (0.12-0.27), respectively. For prediction of hypoglycemia, pooled estimates (95% CI) were 0.80 (0.72-0.86) for sensitivity, 0.92 (0.87-0.96) for specificity, 10.42 (5.82-18.65) for PLR, and 0.22 (0.15-0.31) for NLR. Conclusions Current ML algorithms have insufficient ability to detect ongoing hypoglycemia and considerate ability to predict impeding hypoglycemia in patients with diabetes mellitus using hypoglycemic drugs with regard to diagnostic tests in accordance with the Users’ Guide to Medical Literature (PLR should be ≥5 and NLR should be ≤0.2 for moderate reliability). However, it should be emphasized that the clinical applicability of these ML algorithms should be evaluated according to patients’ risk profiles such as for hypoglycemia and its associated complications (eg, arrhythmia, neuroglycopenia) as well as the average ability of the ML algorithms. Continued research is required to develop more accurate ML algorithms than those that currently exist and to enhance the feasibility of applying ML in clinical settings. Trial Registration PROSPERO International Prospective Register of Systematic Reviews CRD42020163682; http://www.crd.york.ac.uk/PROSPERO/display_record.php?ID=CRD42020163682

Context Although calorie loss from increased urinary glucose excretion continues after long-term treatment with sodium-glucose cotransporter 2 inhibitors (SGLT2is), the mechanisms of the attenuated weight loss due to SGLT2is are not well known. Objective To examine the mechanism of the attenuated weight loss during long-term treatment with an SGLT2i, tofogliflozin, focusing on the antilipolytic effect of insulin on adipose tissue. Design and Participants An integrated analysis was performed using data from two phase 3 studies of 52 weeks of tofogliflozin administration. The antilipolytic effect was evaluated using adipose tissue insulin resistance (Adipo-IR) calculated from the product of the levels of fasting insulin (f-IRI) and fasting free fatty acids (f-FFAs). Results Data from 774 patients with type 2 diabetes (mean age, 58.5 years; glycosylated hemoglobin, 8.1%; body mass index, 25.6 kg/m2; estimated glomerular filtration rate, 83.9 mL/min/1.73m2; 66% men) were analyzed. Weight loss plateaued between weeks 24 and 52 after decreasing significantly. f-IRI levels decreased significantly from baseline to week 24, and the decrease was maintained until Week 52. f-FFA levels significantly increased, peaked at week 24, then declined from weeks 24 to 52. Adipo-IR levels declined progressively throughout the 52 weeks (−3.6 mmol/L·pmol/L and −6.2 mmol/L·pmol/L at weeks 24 and 52, respectively; P < 0.001 baseline vs weeks 24 and 52 and week 24 vs week 52). Higher baseline Adipo-IR levels were independently associated with greater weight loss at week 52. Conclusion The improved antilipolytic effect in adipose tissue may attenuate progressive lipolysis, leading to attenuating future weight loss induced by an SGLT2i in patients with type 2 diabetes.

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Citation: Yamamoto M, Fujihara K, Ishizawa M, et al. Overt proteinuria, moderately reduced eGFR and their combination are predictive of severe diabetic retinopathy or diabetic macular edema in diabetes. Invest Ophthalmol Vis Sci. 2019;60:2685-2689. https://doi.org/10.1167 PURPOSE. Since the combined effects of proteinuria and a moderately decreased eGFR on incident severe eye complications in patients with diabetes are still largely unknown, these associations were determined in a large historical cohort of Japanese patients with diabetes mellitus. METHODS.We evaluated the effects of overt proteinuria (OP) (dipstick 1þ and over) and/or moderately reduced estimated glomerular filtration rate (eGFR) (MG) (baseline eGFR 30.0-54.9 mL/min/1.73 m 2 ) on the incidence of treatment-required diabetic eye diseases (TRDED). We divided 7709 patients into four groups according to the presence or absence of OP and MG: no OP without MG (NP[MGÀ]), OP without MG (OP[MGÀ]), no OP with MG (NP[MGþ]), and OP with MG (OP[MGþ]). Multivariate Cox analyses were performed to calculate hazard ratios (HRs) with 95% confidence intervals for combinations of the presence and/or absence of OP and MG on the risk of developing TRDED. RESULTS.During the median follow-up period of 5.6 years, 168 patients developed TRDED. HRs for OP and MG for incident TRDED were 1.91 (95% confidence interval, 1.27-2.87) and 1.90 (1.11-3.23), respectively. HRs for incident TRDED were 1.73 (1.11-2.69) and 5.57 (2.40-12.94) for OP(MGÀ) and OP(MGþ), respectively, in comparison with NP(MGÀ). CONCLUSIONS.In Japanese patients with diabetes, OP and MG were separately as well as additionally associated with higher risks of TRDED. Results indicate the necessity of the simultaneous assessment of proteinuria and eGFR for appropriate evaluation of risks of severe eye complications in patients with diabetes.