Diabetes mellitus: association of cystatin C- versus creatinine-based estimated glomerular filtration rate with mortality and cardiovascular events.

BACKGROUND: To explore the association between the differences between cystatin C- and creatinine-based estimated glomerular filtration rate (eGFRdiff), and the risk of mortality and cardiovascular (CV) events in individuals with diabetes. METHODS: Three prospective cohorts analyzed data from adults with diabetes from the Incident, Development, and Prognosis of Diabetic Kidney Disease (INDEED) study (2016-17 to 2020) in China, the National Health Nutrition Examination Survey (NHANES, 1999-2004 to 2019) in the USA and UK Biobank (UKB, 2006-10 to 2022) in the UK. Baseline eGFRdiff was calculated using both absolute difference between cystatin C- and creatinine-based calculations (eGFRabdiff), and the ratio between them (eGFRrediff). Cox proportional hazards regression models were used to investigate the association between eGFRdiff and outcomes including all-cause mortality and incident CV events. RESULTS: A total of 8129 individuals from INDEED (aged 60.7 ± 10.0 years), 1634 from NHANES (aged 62.5 ± 14.4 years) and 29 358 from UKB (aged 59.4 ± 7.3 years) were included. At baseline, 43.6%, 32.4% and 42.1% of participants in INDEED, NHANES and UKB, respectively, had an eGFRabdiff value ≥15 mL/min/1.73 m2. During a median follow-up of 3.8 years for INDEED, 15.2 years for NHANES and 13.5 years for UKB, a total of 430, 936 and 6143 deaths and a total of 481, 183 and 5583 CV events occurred, respectively. Each 1-standard deviation higher baseline eGFRabdiff was independently associated with a lower risk of all-cause mortality and CV events, with hazard ratios of 0.77 and 0.82 in INDEED, 0.70 and 0.68 in NHANES, and 0.66 and 0.78 in UKB. Similar results were observed for eGFRrediff. CONCLUSIONS: eGFRdiff represents a marker of adverse events for diabetes among general population. Monitoring both eGFRcys and eGFRcr yields additional prognostic information and has clinical utility in identifying high-risk individuals for mortality and CV events.

Goal selection and feedback for solving math word problems.

Solving Math Word Problems (MWPs) automatically is a challenging task for AI-tutoring in online education. Most of the existing State-Of-The-Art (SOTA) neural models for solving MWPs use Goal-driven Tree-structured Solver (GTS) as their decoders. However, owing to the defects of the tree-structured recurrent neural networks, GTS can not obtain the information of all generated nodes in each decoding time step. Therefore, the performance for long math expressions is not satisfactory enough. To address such limitations, we propose a Goal Selection and Feedback (GSF) decoding module. In each time step of GSF, we firstly feed the latest result back to all goal vectors through goal feedback operation, and then the goal selection operation based on attention mechanism is designed for generate the new goal vector. Not only can the decoder collect the historical information from all generated nodes through goal selection operation, but also these generated nodes are always updated timely by goal feedback operation. In addition, a Multilayer Fusion Network (MFN) is proposed to provide a better representation of each hidden state during decoding. Combining the ELECTRA language model with our novel decoder, experiments on the Math23k, Ape-clean, and MAWPS datasets show that our model outperforms the SOTA baselines, especially on the MWPs of complex samples with long math expressions. The ablation study and case study further verify that our model can better solve the samples with long expressions, and the proposed components are indeed able to help enhance the performance of the model.

Daytime Napping, Incident Atrial Fibrillation, and Dynamic Transitions With Dementia.

Background: Associations between napping and incident atrial fibrillation (AF) remain unknown, and few studies have accounted for dynamic transitions between AF and dementia. Objectives: The purpose of this study was to evaluate associations between napping with incident AF and the dynamic transitions of AF and dementia, as well as the mediation pathway of left ventricular (LV) size and function. Methods: A total of 476,588 participants from UK Biobank were included. Napping frequency and other sleep behaviors were evaluated. Incident AF, dementia, and mortality were ascertained via linkage to external registry databases. LV size and function indices were obtained from cardiovascular magnetic resonance imaging phenotypes. A multistate survival analysis was conducted to examine daytime napping in relation to dynamic transitions. Weighed AF genetic risk score was calculated. Results: Frequent daytime napping, compared to never/rarely napping, was associated with a 1.17-fold AF risk (HR: 1.17; 95% CI: 1.12-1.22), which persisted after controlling for other sleep behaviors. Genetic predisposition significantly modified associations between napping and AF (P for interaction <0.001), with stronger associations observed in those of low and moderate genetic risk. LV ejection fraction significantly mediated 26.2% (95% CI: 4.2%-74.1%) of associations between napping and AF. Frequent napping was also associated with a 1.27-fold risk of transition from AF to comorbidity of AF and dementia. Conclusions: Our findings highlight the potential importance of screening for napping in view of the association with incident AF and dementia. Routine evaluations of the LV ejection fraction could be warranted to timely identify early indications of AF onset among habitual nappers.

The Difference Between Cystatin C- and Creatinine-Based Estimated Glomerular Filtration Rate and Risk of Diabetic Microvascular Complications Among Adults With Diabetes: A Population-Based Cohort Study.

OBJECTIVE: The impact of the difference between cystatin C- and creatinine-based estimated glomerular filtration rate (eGFRdiff) on diabetic microvascular complications (DMCs) remains unknown. We investigated the associations of eGFRdiff with overall DMCs and subtypes, including diabetic retinopathy (DR), diabetic kidney disease (DKD), and diabetic neuropathy (DN). RESEARCH DESIGN AND METHODS: This prospective cohort study included 25,825 participants with diabetes free of DMCs at baseline (2006 to 2010) from the UK Biobank. eGFRdiff was calculated using both absolute difference (eGFRabdiff) and the ratio (eGFRrediff) between cystatin C- and creatinine-based calculations. Incidence of DMCs was ascertained using electronic health records. Cox proportional hazards regression models were used to evaluate the associations of eGFRdiff with overall DMCs and subtypes. RESULTS: During a median follow-up of 13.6 years, DMCs developed in 5,753 participants, including 2,752 cases of DR, 3,203 of DKD, and 1,149 of DN. Each SD decrease of eGFRabdiff was associated with a 28% higher risk of overall DMCs, 14% higher risk of DR, 56% higher risk of DKD, and 29% higher risk of DN. For each 10% decrease in eGFRrediff, the corresponding hazard ratios (95% CIs) were 1.16 (1.14, 1.18) for overall DMCs, 1.08 (1.05, 1.11) for DR, 1.29 (1.26, 1.33) for DKD, and 1.17 (1.12, 1.22) for DN. The magnitude of associations was not materially altered in any of the sensitivity analyses. CONCLUSIONS: Large eGFRdiff was independently associated with risk of DMCs and its subtypes. Our findings suggested monitoring eGFRdiff in the diabetes population has potential benefit for identification of high-risk patients.