Aims/hypothesis The aim of this work was to assess the effectiveness of continuous glucose monitoring (CGM) vs selfmonitoring of blood glucose (SMBG) in maintaining glycaemic control among people with type 1 diabetes mellitus. Methods Cochrane Library, PubMed, Embase, CINAHL, Scopus, trial registries and grey literature were searched from 9 June 2011 until 22 December 2020 for RCTs comparing CGM intervention against SMBG control among the non-pregnant individuals with type 1 diabetes mellitus of all ages and both sexes on multiple daily injections or continuous subcutaneous insulin infusion with HbA 1c levels, severe hypoglycaemia and diabetic ketoacidosis (DKA) as outcomes. Studies also included any individual or caregiver-led CGM systems. Studies involving GlucoWatch were excluded. Risk of bias was appraised with Cochrane risk of bias tool. Metaanalysis and meta-regression were performed using Review Manager software and R software, respectively. Heterogeneity was evaluated using χ 2 and I 2 statistics. Overall effects and certainty of evidence were evaluated using Z statistic and GRADE (Grading of Recommendations, Assessment, Development and Evaluation) software. Results Twenty-two studies, involving 2188 individuals with type 1 diabetes, were identified. Most studies had low risk of bias. Meta-analysis of 21 studies involving 2149 individuals revealed that CGM significantly decreased HbA 1c levels compared with SMBG (mean difference −2.46 mmol/mol [−0.23%] [95% CI −3.83, −1.08], Z = 3.50, p=0.0005), with larger effects experienced among higher baseline HbA 1c >64 mmol/mol (>8%) individuals (mean difference −4.67 mmol/mol [−0.43%] [95% CI −6.04, −3.30], Z = 6.69, p<0.00001). However, CGM had no influence on the number of severe hypoglycaemia (p=0.13) and DKA events (p=0.88). Certainty of evidence was moderate. Conclusions/interpretation CGM is superior to SMBG in improving glycaemic control among individuals with type 1 diabetes in the community, especially in those with uncontrolled glycaemia. Individuals with type 1 diabetes with HbA 1c >64 mmol/mol (>8%) are most likely to benefit from CGM. Current findings could not confer a concrete conclusion on the effectiveness of CGM on DKA outcome as DKA incidences were rare. Current evidence is also limited to outpatient settings. Future research should evaluate the accuracy of CGM and the effectiveness of CGM across different age groups and insulin regimens as these remain unclear in this paper. PROSPERO registration Registration no. CRD42020207042.

No abstract

An adaptive filtering algorithm is proposed in this paper to remove mismatch, dc offsets, flicker noise, and intersymbol interference (ISI) simultaneously in a direct-conversion receiver. mismatch is cancelled by a real valued adaptive mismatch canceller, and dc offsets are removed with one complex tap. In addition, flicker noise is modeled as a complex autoregressive (AR) random process so the system to be identified transforms to an ARX model. After estimating the coefficients in the model during the training period, the desired signal can be estimated using the decision feedback method. To accelerate the convergence of the algorithm and to reduce the estimation variance, an internal iterative algorithm is introduced. The convergence analysis of the proposed algorithm is also given, and the closed form of the minimum mean square error of the proposed algorithm is derived. Simulation results are provided to verify the superior performance of the proposed algorithm.Index Terms-ARX model, convergence, dc offsets, direct-conversion receivers, flicker noise, mismatch, minimum meansquare error (MMSE).