Type 1 diabetes remains an important cause of end-stage kidney disease. In this report, we describe the use of automated insulin delivery technology to assist a person living with Type 1 diabetes to manage their glucose pre-, peri- and post-renal transplantation. In addition, we review the potential options available for managing such patients, including closed-loop technology, pancreatic and islet cell transplantation.

The aims of this study were to assess cognitions relating to hypoglycaemia in adults with type 1 diabetes and impaired awareness of hypoglycaemia before and after the multimodal HypoCOMPaSS intervention, and to determine cognitive predictors of incomplete response (one or more severe hypoglycaemic episodes over 24 months).This analysis included 91 adults with type 1 diabetes and impaired awareness of hypoglycaemia who completed the Attitudes to Awareness of Hypoglycaemia (A2A) questionnaire before, 24 weeks and 24 months after the intervention, which comprised a short psycho-educational programme with optimisation of insulin therapy and glucose monitoring.The age and diabetes duration of the participants were 48±12 and 29±12 years, respectively (mean±SD). At baseline, 91% reported one or more severe hypoglycaemic episodes over the preceding 12 months; this decreased to <20% at 24 weeks and after 24 months (p=0.001). The attitudinal barrier 'hyperglycaemia avoidance prioritised' (η2p=0.250, p=0.001) decreased from baseline to 24 weeks, and this decrease was maintained at 24 months (mean±SD=5.3±0.3 vs 4.3±0.3 vs 4.0±0.3). The decrease in 'asymptomatic hypoglycaemia normalised' from baseline (η2p=0.113, p=0.045) was significant at 24 weeks (1.5±0.3 vs 0.8±0.2). Predictors of incomplete hypoglycaemia response (one or more further episodes of severe hypoglycaemia) were higher baseline rates of severe hypoglycaemia, higher baseline scores for 'asymptomatic hypoglycaemia normalised', reduced change in 'asymptomatic hypoglycaemia normalised' scores at 24 weeks, and lower baseline 'hypoglycaemia concern minimised' scores (all p<0.05).Participation in the HypoCOMPaSS RCT was associated with improvements in hypoglycaemia-associated cognitions, with 'hyperglycaemia avoidance prioritised' most prevalent. Incomplete prevention of subsequent severe hypoglycaemia episodes was associated with persistence of the cognition 'asymptomatic hypoglycaemia normalised'. Understanding and addressing cognitive barriers to hypoglycaemia avoidance is important in individuals prone to severe hypoglycaemia episodes.www.isrctn.org : ISRCTN52164803 and https://eudract.ema.europa.eu : EudraCT2009-015396-27.

OBJECTIVE:The Hypoglycemia Fear Survey-II (HFS-II) is a well-validated measure of fear of hypoglycemia in people with type 1 diabetes. The aim of this study was to explore the relationships between hypoglycemia worries, behaviors, and cognitive barriers to hypoglycemia avoidance and hypoglycemia awareness status, severe hypoglycemia, and HbA1c. RESEARCH DESIGN AND METHODS:Participants with type 1 diabetes (n = 178), with the study population enriched for people at risk for severe hypoglycemia (49%), completed questionnaires for assessing hypoglycemia fear (HFS-II), hyperglycemia avoidance (Hyperglycemia Avoidance Scale [HAS]), diabetes distress (Problem Areas In Diabetes [PAID]), and cognitive barriers to hypoglycemia avoidance (Attitudes to Awareness of Hypoglycemia [A2A]). Exploratory factor analysis was applied to the HFS-II. We sought to establish clusters based on HFS-II, A2A, Gold, HAS, and PAID using k-means clustering. RESULTS:Four HFS-II factors were identified: Sought Safety, Restricted Activity, Ran High, and Worry. While Sought Safety, Restricted Activity, and Worry increased with progressively impaired awareness and recurrent severe hypoglycemia, Ran High did not. With cluster analysis we outlined four clusters: two clusters with preserved hypoglycemia awareness were differentiated by low fear/low cognitive barriers to hypoglycemia avoidance (cluster 1) versus high fear and distress and increased Ran High behaviors (cluster 2). Two clusters with impaired hypoglycemia awareness were differentiated by low fear/high cognitive barriers (cluster 3) as well as high fear/low cognitive barriers (cluster 4). CONCLUSIONS:This is the first study to define clusters of hypoglycemia experience by worry, behaviors, and cognitive barriers to hypoglycemia avoidance. The resulting subtypes may be important in understanding and treating problematic hypoglycemia.

Problematic hypoglycaemia still complicates insulin therapy for some with type 1 diabetes. This study describes baseline emotional, cognitive and behavioural characteristics in participants in the HARPdoc trial, which evaluates a novel intervention for treatment-resistant problematic hypoglycaemia. We documented a cross-sectional baseline description of 99 adults with type 1 diabetes and problematic hypoglycaemia despite structured education in flexible insulin therapy. The following measures were included: Hypoglycaemia Fear Survey II (HFS-II); Attitudes to Awareness of Hypoglycaemia questionnaire (A2A); Hospital Anxiety and Depression Index; and Problem Areas In Diabetes. k-mean cluster analysis was applied to HFS-II and A2A factors. Data were compared with a peer group without problematic hypoglycaemia, propensity-matched for age, sex and diabetes duration (n = 81). The HARPdoc cohort had long-duration diabetes (mean ± SD 35.8 ± 15.4 years), mean ± SD Gold score 5.3 ± 1.2 and a median (IQR) of 5.0 (2.0–12.0) severe hypoglycaemia episodes in the previous year. Most individuals had been offered technology and 49.5% screened positive for anxiety (35.0% for depression and 31.3% for high diabetes distress). The cohort segregated into two clusters: in one (n = 68), people endorsed A2A cognitive barriers to hypoglycaemia avoidance, with low fear on HFS-II factors; in the other (n = 29), A2A factor scores were low and HFS-II high. Anxiety and depression scores were significantly lower in the comparator group. The HARPdoc protocol successfully recruited people with treatment-resistant problematic hypoglycaemia. The participants had high anxiety and depression. Most of the cohort endorsed unhelpful health beliefs around hypoglycaemia, with low fear of hypoglycaemia, a combination that may contribute to persistence of problematic hypoglycaemia and may be a target for adjunctive psychological therapies.

Behavioural responses to hypoglycaemia require coordinated recruitment of broadly distributed networks of interacting brain regions. We investigated hypoglycaemia-related changes in brain connectivity in people without diabetes (ND) and with type 1 diabetes with normal (NAH) or impaired (IAH) hypoglycaemia awareness. Two-step hyperinsulinaemic hypoglycaemic clamps were performed in 14 ND, 15 NAH and 22 IAH participants. BOLD timeseries were acquired at euglycaemia (5.0 mmol/L) and hypoglycaemia (2.6 mmol/L), with symptom and counter-regulatory hormone measurements. We investigated hypoglycaemia-related connectivity changes using established seed regions for the default mode (DMN), salience (SN) and central executive (CEN) networks and regions whose activity is modulated by hypoglycaemia: the thalamus and right inferior frontal gyrus (RIFG). Hypoglycaemia-induced changes in the DMN, SN and CEN were evident in NAH (all p < 0.05), with no changes in ND or IAH. However, in IAH there was a reduction in connectivity between regions within the RIFG (p = 0.001), not evident in the ND or NAH groups. We conclude that hypoglycaemia induces coordinated recruitment of the DMN and SN in diabetes with preserved hypoglycaemia awareness which is absent in IAH and ND. Changes in connectivity in the RIFG, a region associated with attentional modulation, may be key in impaired hypoglycaemia awareness.

Introduction Severe hypoglycaemia (SH), when blood glucose falls too low to support brain function, is the most feared acute complication of insulin therapy for type 1 diabetes mellitus (T1DM). 10% of people with T1DM contribute nearly 70% of all episodes, with impaired awareness of hypoglycaemia (IAH) a major risk factor. People with IAH may be refractory to conventional approaches to reduce SH, with evidence for cognitive barriers to hypoglycaemia avoidance. This paper describes the protocol for the Hypoglycaemia Awareness Restoration Programme for People with Type 1 Diabetes and Problematic Hypoglycaemia Persisting Despite Optimised Self-care (HARPdoc) study, a trial to assess the impact on hypoglycaemia experience of a novel intervention that addresses cognitive barriers to hypoglycaemia avoidance, compared with an existing control intervention, recommended by the National Institute of Health and Care Excellence. Methods and analysis A randomised parallel two-arm trial of two group therapies: HARPdoc versus Blood Glucose Awareness Training, among 96 adults with T1DM and problematic hypoglycaemia, despite attendance at education with or without technology use, in four centres providing specialist T1DM services. The primary outcome will be the SH rate at 12 and/or 24 months after randomisation to either course. Secondary outcomes include rates of SH requiring parenteral therapy, involving unconsciousness or needing emergency services; hypoglycaemia awareness status, overall diabetes control and quality of life measures. An implementation study to evaluate how the interventions are delivered and how implementation impacts on clinical effectiveness is planned as a parallel study, with its own protocol. Ethics and dissemination The protocol was approved by the London Dulwich Research Ethics Committee, the Health Research Authority, National Health Service R&D and the Institutional Review Board of the Joslin Diabetes Center in the USA. Study findings will be disseminated to study participants and through peer-reviewed publications and conference presentations, including user groups. Trial registration number NCY02940873; Pre-results.

Insulin is the life-saving treatment in type 1 diabetes, and increasingly used to treat advanced type 2 diabetes. Over the years there have been improvements and alterations in insulin treatment, moving from animal-derived insulin, through recombinant human insulin to genetically modified analogue insulins to help support people with diabetes to achieve better glucose control. Improved insulin delivery through insulin pens and more complex devices such as insulin pumps have helped improve quality of life and biomedical outcomes such as lower HbA1c and reduced hypoglycaemia. In this chapter we will describe currently available insulins with a focus on clinical trials that demonstrate differences relevant to individual users. We go on to discuss the wide variety of devices used to administer these insulins together with a discussion of their relative advantages and disadvantages.

Background: Restoration of symptoms in response to hypogycemia has been seen in people with type 1 diabetes (T1D) and impaired awareness of hypoglycaemia (IAH) using an education and diabetes technology approach (HypoAware Study) and a psycho-educational approach addressing cognitions (HARPdoc Trial) . We investigated regional brain responses to hypoglycemia following restoration of IAH between the interventions. Methods: Twelve people with T1D and IAH from HypoAware and from HARPdoc underwent two-step hyperinsulinemic hypoglycemic clamps before and after their intervention. pCASL fMRI brain blood flow images were acquired. A 2x2 study by timepoint ANOVA interaction design was conducted to compare the effect of each intervention on hypoglycemia-euglycemia difference brain blood flow maps. Within group analysis of the difference maps was conducted using paired t-tests. Results: HARPdoc participants were older, mean±SD age 54.1±12.3 vs. 34.7±9.0 yrs (p<0.001) with similar HbA1c, 7.8±0.9 vs. 7.8±0.7%, Gold score, 6.0±1.0 vs. 6.0±1.0, BMI 24.6±4.6 vs. 24.4±3.6 and diabetes duration 22.2±7.2 vs. 23.6±7.7 yrs (all p>0.05) . Each intervention was associated with enhanced activation in the anterior cingulate cortex (ACC) in within group studies (HARPdoc FWEp=0.048, HypoAware FWEp=0.011) . In the between group analysis, a superior frontal gyrus (SFG) region was more activated at hypoglycemia following HARPdoc than HypoAware (FWEp=0.044) . Conclusion: We have shown different brain responses to hypoglycemia in treated IAH depending on the therapeutic approach. Enhanced ACC responses were expected following recovery of symptoms. However, the cognitive approach of HARPdoc enhances the hypoglycemia response in the SFG, known to be involved in self-awareness and appreciation of symptoms, is unique to HARPdoc and is consistent with its psychological and cognitive nature. This may increase the potential for lasting effect. Disclosure P.Jacob: None. S.A.Amiel: Advisory Panel; Medtronic, Novo Nordisk, Other Relationship; Sanofi. M.Nwokolo: None. P.Choudhary: Advisory Panel; Abbott Diabetes, Lilly Diabetes, Medtronic, Research Support; Novo Nordisk, Speaker's Bureau; Dexcom, Inc., Glooko, Inc., Insulet Corporation, Sanofi. Funding Juvenile Diabetes Research Foundation (3-SRA-2017-484-S-B)

Background and Objective: As continuous glucose monitoring (CGM) becomes common in research and clinical practice, there is a need to understand how CGM-based hypoglycemia relates to hypoglycemia episodes defined conventionally as patient reported hypoglycemia (PRH). Data show that CGM identify many episodes of low interstitial glucose (LIG) that are not experienced by patients, and so the aim of this study is to use different PRH simulations to optimize CGM parameters of threshold (h) and duration (d) to provide the best PRH detection performance. Methods: The algorithm uses particle Markov chain Monte Carlo optimization to identify the optimal h and d which maximize an objective function for detecting PRH. We tested our algorithm by creating three different cases of PRH simulations. Results: We added three types of simulated PRH events to 10 weeks of anonymized CGM data from 96 type 1 diabetes people to see if the algorithm can detect the optimal parameters set out in the simulations. In simulation 1, we changed the locations of PRHs with respect to LIG episodes in the CGM signal to simulate random optimal LIG parameters for every individual. In simulation 2, the PRHs are CGM glucose <3.9 mmol/L followed by at least 20 min of rise > 0.11 mmol/L/min. Simulation 3 is like simulation 2 but with glucose threshold of 3.0 mmol/L. The median [interquartile range] of deviation between the optimized (found by the algorithm) and the optimal (known) h and d are -0.07% [-0.4, 1.9] and -1.3% [-5.9, 6.8], respectively across the subjects for simulation 1. The mean [min max] of the optimized LIG parameters are h = 3.8 [3.7, 3.8] mmol/L and d = 12 [10, 14] min for simulation 2 and they are h = 3.0 [2.9, 3] mmol/L and d = 10 [8, 14] min for simulation 3 across a 10-fold cross validation. Conclusions: This work demonstrates the feasibility of the algorithm to find the best-fit definition of CGM-based hypoglycemia for PRH detection. In a prospective clinical study collecting CGM and PRH, the current algorithm will be used to optimize the definition of hypoglycemia with respect to PRH with the ambition of using the resulted definition as a surrogate for PRH in clinical practice. (C) 2021 The Authors. Published by Elsevier B.V.

Changes in global cerebral blood flow (gCBF) have been suggested as a mechanism for mitigating the functional impact of hypoglycemia on the brain. The impact of type 1 diabetes (T1D) or hypoglycemia awareness status is not clear. We measured gCBF during progressive lowering of plasma glucose in people with and without T1D, and with retained or impaired awareness of hypoglycemia. Methods: Fifty-one participants (15 with no diabetes (ND), 15 with T1D and normal awareness of hypoglycemia (NAH) and 21 with T1D and impaired awareness of hypoglycemia (IAH)) underwent a two-step hyperinsulinemic hypoglycemic clamp. gCBF was estimated using pseudocontinuous arterial spin labelling magnetic resonance imaging at 6 timepoints: 2 euglycemic, two in the descent phase and two hypoglycemic. gCBF was extracted using a global grey matter mask in SPM12. Statistical analysis and thresholded linear models were performed in R. Results: The mean (+ SD) glucose values at the six timepoints were 95.8 (8.0), 95.5 (9.2), 55.0 (8.3), 50.8 (5.3), 45.7 (4.3) and 45.8 (4.0) mg/dL. Symptom responses to hypoglycemia were absent in IAH. There was a significant increase in CBF in response to hypoglycemia (3-way ANOVA p = 0.04). This was driven by responses in NAH (+7.3%, p < 0.05) and IAH (+10.6% p < 0.01) with no response in ND (+3.5% p = 0.16). The response was not linear, with glucose thresholds of 55.8 mg/dL in NAH and 54.0 mg/dL in IAH (pNAH vs IAH = 0.9) with no threshold in ND. Conclusion: In people with T1D, there is a non-linear relationship between falling glucose and rising gCBF which is not related to awareness status and is not seen in health. The threshold glucose between 54 and 56 mg/dL corresponds closely with level 2 hypoglycemia cut-offs used in current clinical practice. We propose that there is a failure of cerebral vascular autoregulation in response to hypoglycemia in T1D. gCBF responses to hypoglycemia in T1D are independent of symptomatic responses and not responsible for lack of hypoglycemia awareness. Disclosure P. Jacob: None. O. Odaly: None. S. A. Amiel: Advisory Panel; Self; Diabetes UK, Medtronic, Other Relationship; Self; Sanofi, Research Support; Self; Diabetes UK, European Union, JDRF. P. Choudhary: Advisory Panel; Self; Abbott Diabetes, Insulet Corporation, Lilly Diabetes, Medtronic, Sanofi-Aventis, Speaker’s Bureau; Self; Dexcom, Inc., Novo Nordisk. Funding JDRF (3-SRA-2017-484-S-B)

Background: The effect of prior hypoglycaemia on cognitive function in type 1 diabetes is an important unresolved clinical question. In this systematic review, we aimed to summarize the studies exploring the impact of prior hypoglycaemia on any aspect of cognitive function in type 1 diabetes. Methods: We used a multidatabase search platform Healthcare Database Advanced Search to search Medline, PubMed, EMBASE, EMCARE, CINAHL, PsycINFO, BNI, HMIC, and AMED from inception until 1 May 2019. We included studies on type 1 diabetes of any age. The outcome measure was any aspect of cognitive function. Results: The 62 studies identified were grouped as severe hypoglycaemia (SH) in childhood (⩽18 years) and adult-onset (>18 years) diabetes, nonsevere hypoglycaemia (NSH) and nocturnal hypoglycaemia (NH). SH in early childhood-onset diabetes, especially seizures and coma, was associated with poorer memory (verbal and visuospatial), as well as verbal intelligence. Among adult-onset diabetes, SH was associated with poorer cognitive performance in the older age (>55 years) group only. Early versus late exposure to SH had a significant association with cognitive dysfunction (CD). NSH and NH did not have any significant association with CD, while impaired awareness of hypoglycaemia was associated with poorer memory and cognitive-processing speeds. Conclusion: The effect of SH on cognitive function is age dependent. Exposure to SH in early childhood (<10 years) and older age groups (>55 years) was associated with a moderate effect on the decrease in cognitive function in type 1 diabetes [PROSPERO ID: CRD42019141321].

Hypoglycemia (low blood glucose) has been recognized as a complication of insulin therapy almost from the time insulin was first used. Almost all patients with type 1 diabetes will experience frequent episodes of hypoglycemia through their life, and for many the fear of hypoglycemia is a significant barrier to achieving or maintaining optimum glycemic targets. The pharmacodynamics and pharmacokinetics of subcutaneously delivered insulin make matching insulin delivery to the actual insulin requirements challenging. This inability to adjust delivered insulin as rapidly or reliably as the changing insulin requirements often results in over-delivery of insulin that can lead to hypoglycemia.

Problematic hypoglycemia complicates insulin therapy in >25% of adults with type 1 diabetes (T1D). Previous work has identified relationships between cognitive barriers to hypoglycemia avoidance and impaired awareness of hypoglycemia (IAH) with recurrent severe episodes (SH). We investigated fear of hypoglycemia in people with IAH and SH enrolling in a trial of interventions to restore hypoglycemia awareness (“HARPdoc” ClinicalTrials.gov NCT02940873) and compared their data with T1D clinic attenders not enriched for problematic hypoglycemia. Method: Adults with T1D (HARPdoc cohort; n=98, age 54±13 yr, 56% female, T1D duration 40±15 yr) and problematic hypoglycemia (Clarke score 5.5±1.0) completed the Hypoglycemia Fear Survey II (HFS), Hyperglycemia Avoidance Scale (HAS) and anonymous 12 month SH recall forms. The T1D clinic comparator group was n=467, age 46±14 yr, 50% female, T1D duration 30±13 yr. Results: In preliminary analyses, the HARPdoc cohort (n=88) reported higher scores on total HFS (p=0.018) and its worry subscale (p<0.0001) than the comparator. Behavior subscale scores were lower (p<0.0001). In the HARPdoc cohort, 25% (n = 22) reported low worry about hypoglycemia despite high SH risk (vs. 8% in the comparator). People with high worry scored the HAS worry subscale higher (p<0.001). The HARPdoc cohort were grouped by frequency of SH (<2; 2 - 4; 5-12 and >12 SH per yr). Worry scores increased with higher SH rates (p=0.004). Behavior scores increased (p=0.041) but not above the comparator 75th centile. In the ’maintaining high glucose’ subset of HFS behavior items, scores increased between the high SH rate groups (p=0.042) but not the lower rate groups. Conclusion: The majority of people with significant hypoglycemia problems show appropriately increased worry but not corresponding increases in behavior scores. A subgroup show inappropriately low worry. Inability to change behaviors, and worry about hyperglycemia, may be barriers to avoiding SH. Disclosure R.H. Maclean: None. P. Jacob: None. S. Haywood: None. P. Choudhary: Advisory Panel; Self; Abbott, Eli Lilly and Company, Insulet Corporation, Medtronic. Research Support; Self; European Union, JDRF. Speaker’s Bureau; Self; Dexcom, Inc., Novartis AG, Novo Nordisk A/S, Sanofi-Aventis. S.R. Heller: Advisory Panel; Self; Eli Lilly and Company, Novo Nordisk A/S, Zealand Pharma A/S. Speaker’s Bureau; Self; AstraZeneca, Novo Nordisk A/S. Other Relationship; Self; MannKind Corporation. E. Toschi: None. D. Kariyawasam: None. T.C. Anderbro: None. S.A. Amiel: Advisory Panel; Self; Medtronic, Novo Nordisk A/S, Roche Pharma. Other Relationship; Self; Diabetes UK. Funding JDRF (4-SRA-2017-266-M-N)

Neuroimaging studies highlight the importance of thalamic activation in response to hypoglycemia in people with and without type 1 diabetes (T1D). This activation is characteristically attenuated in impaired awareness of hypoglycaemia (IAH), a major risk factor for severe hypoglycemia. We investigated changes in connectivity of the thalamus with other brain regions during hypoglycemia. Methods: Fourteen people without diabetes (no diabetes, ND), 15 with T1D and normal awareness of hypoglycemia (NAH) and 22 with IAH, all right-handed, age, sex and gender matched, underwent a hyperinsulinemic glucose clamp during which we acquired blood oxygen level dependent fMRI at euglycemia (90mg/dL) and at onset of hypoglycemia (48mg/dL). Connectivity was studied using the CONN toolbox in SPM12. A thalamic seed was used in a seed-to-voxel analysis with and without the increase in symptoms at hypoglycemia as an explanatory regressor variable. Results: Symptom scores in response to hypoglycemia rose earliest and to the greatest levels in NAH (11.0 to 18.3, p= 0.029). The rise in symptom scores in ND was not significant at this timepoint (9.2 to 13.8, p= 0.057), whilst IAH showed no symptom change (10.5 to 9.8, p= 0.7). In ND, hypoglycemia increased thalamic connectivity with the right frontal pole (pFDR = 0.018). This did not occur in diabetes, either in NAH or IAH. The NAH group demonstrated a positive relationship between change in symptoms with change in connectivity of the thalamus and a left frontal pole region (pFDR = 0.035), whereas an overlapping area had a negative correlation in ND (pFDR = 0.001). There was no correlation in IAH. Conclusion: During hypoglycemia, those with T1D display aberrantly enhanced thalamic connectivity with brain regions responsible for complex behavior. Disruption of this network occurs in IAH and may be the mechanism for failure of perception of the onset of hypoglycemia and reduced hypoglycemia avoidance behaviors, increasing severe hypoglycemia risk. Disclosure P. Jacob: None. M. Nwokolo: Other Relationship; Self; Sanofi. O. ODaly: None. F.O. Zelaya: None. S.A. Amiel: Advisory Panel; Self; Medtronic, Novo Nordisk A/S, Roche Pharma. Other Relationship; Self; Diabetes UK. P. Choudhary: Advisory Panel; Self; Abbott, Eli Lilly and Company, Insulet Corporation, Medtronic. Research Support; Self; European Union, JDRF. Speaker’s Bureau; Self; Dexcom, Inc., Novartis AG, Novo Nordisk A/S, Sanofi-Aventis. Funding JDRF (3-SRA-2017-484-S-B)

Objectives: To study the effect of baseline glucose variability (GV) on the time to stability and interweek variability (IWV) of continuous glucose monitoring (CGM)-derived glycemic indices. Materials and Methods: Anonymized CGM data (median duration 32 weeks, >= 70% data coverage) of 85 adults with type 1 diabetes; age (41 +/- 12 years), 66.3% women, HbA1c (7.5% +/- 1.2%, 58 mmol/mol) were analyzed. We evaluated the time to stability, that is, the minimum duration of data that provided a close (r(2) >= 0.9) correlation with data taken across the whole sampling period and IWV. We also evaluated the impact of baseline variability on the time to stability. Results: For the whole data set, all indices achieved stability (r(2) >= 0.9) by 9 weeks (range 5-9). Time to stability progressively increased from the lowest quartile to the highest quartile of baseline coefficient of variation (CV). Time above range (TAR) and time below range (TBR) had higher IWV than time in range (TIR) (%CVIWV: TIR-16%, TAR-31%, TBR-62%). Conclusion: Baseline GV and IWV of indices affect the time to stability of glycemic indices. We recommend a minimum of 9 weeks of data to represent long-term CGM data.

### What you need to know Hyponatraemia is the most frequently observed electrolyte abnormality.1 Mild hyponatraemia is associated with cognitive deficits and falls, but in hospitalised patients it is associated with increased mortality.2 In primary care, patients are often found to have hyponatraemia during chronic disease monitoring. This prompts a focused re-evaluation to consider underlying causes such as medication, cancer, or adrenal insufficiency.23 In this article we provide a framework to assess patients with hyponatraemia in primary care. Hyponatraemia is defined as a serum sodium value below the reference range (lower limit is usually 133-135 mmol/L). Hyponatraemia is often subdivided into mild, moderate, severe, and life threatening, using a combination of the presence of associated symptoms and the sodium value.34 There is, however, a poor correlation between symptomatology and serum sodium level, so both must be taken into account when considering urgency of referral and subsequent management. Hyponatraemia may be acute (arbitrarily defined as an onset within 48 hours), chronic (>48 hours), or unknown (where management should be as per chronic). Although it may appear to be asymptomatic, even at modest levels hyponatraemia may predispose to falls and cognitive deficits. In a case-control study of 122 patients with hyponatraemia and 244 matched controls, 21% of patients had been admitted with falls compared with 5% of controls.5 The risk of falls was elevated with any sodium value below 132 mmol/L. Chronic hyponatraemia is a risk factor …

11 May 2019 | the bmj Olfactory loss and higher risk of mortality Older people often say that things don’t smell (or taste) like they used to. Poor olfaction has been linked to higher mortality. You would think that is because people who have lost their sense of smell are already in poor health, with neurodegenerative conditions such as Parkinson’s disease or dementia. But this cohort study finds that the opposite is true—poor olfaction is only an independent predictor of higher mortality among healthy people. Those in poor health are more likely to die overall, but their sense of smell doesn’t help to predict their risk. Liu et al enrolled 2289 older people and used the objective Brief Smell Identification Test. Over half of the participants had died within the 13 years of follow-up; those who had poor olfaction had a 46% higher cumulative risk of dying at year 10, and a 30% higher risk at year 13. But the increased risk was only seen among those who were in good health at enrolment, not among those who were already unwell. The mechanism is still unclear. Olfactory loss in healthy people may prove to be an important predictor of mortality, but I’m not sure what practical benefit there is for patients in knowing that. ̻ Ann Intern Med doi:10.7326/M18-0775

Resting state networks are functionally connected neurons that show similar low-frequency blood oxygen-level dependent (BOLD) signal oscillations. The salience network (SN) is crucial for switching between two other networks: the default mode network (DMN) and the central executive network (CEN). The DMN is active when the brain is not cognitively engaged; the CEN is active when the brain is engaged in a specific task. We hypothesized that impaired awareness of hypoglycemia (IAH) in people with type 1 diabetes (T1D) would be associated with disruption of the integrity of the salience network at hypoglycemia. Methods: Fourteen nondiabetic (ND), 15 T1D with normal awareness of hypoglycemia (NAH) and 22 T1D with IAH participants, matched for age and T1D duration, underwent a two-step hypoglycemic clamp. Resting state BOLD functional magnetic resonance image (fMRI) time series were obtained, one at 90 mg/dL, one at 47 mg/dL. Images were analyzed using the CONN toolbox in SPM12. We used the right anterior insula (AI) as a seed region for the SN in a seed to voxel analysis. Results: The SN was identified in all three groups at euglycemia. At hypoglycemia ND and NAH had brisk symptom response and altered coupling between SN and regions associated with the DMN: precuneus (ND p <0.01) and pregenual anterior cingulate cortex (ACC, NAH p <0.01), IAH had lower symptoms and no change in SN coupling. Mean symptom increase at hypoglycemia was 15.3 (ND and NAH) and 1.5 (IAH, p<0.00001). A 2x2 mixed ANOVA interaction between aware groups (HC and NAH n=29) and IAH (n=22) showed differences in connectivity reduction between the ACC and AI at hypoglycemia (pFEW-Corr=0.04). Conclusions: During hypoglycemia, reduced connectivity between SN and DMN, seen in ND and NAH, may be an important switch for hypoglycemia recognition, facilitating protective behavioral responses. Lack of SN connectivity change may underpin impaired awareness and failure of appropriate responses to hypoglycemia seen in IAH. Disclosure P. Jacob: None. C.E. Osborne: None. F. Zelaya: None. S.A. Amiel: None. P. Choudhary: Advisory Panel; Self; AstraZeneca, Insulet Corporation, Medtronic, Roche Diabetes Care, Sanofi. Speaker's Bureau; Self; Eli Lilly and Company, Novartis AG, Novo Nordisk Inc., WebMD.

Although micro- and macrovascular complications of diabetes are the most important cause of mortality and morbidity in people with diabetes, it is increasingly recognized that diabetes increases the risk of developing cancer. Diabetes and cancer commonly co-exist, and outcomes in people with both conditions are poorer than in those who have cancer but no diabetes. There is no randomized trial evidence that treating hyperglycaemia in people with cancer improves outcomes, but therapeutic nihilism should be avoided, and a personalized approach to managing hyperglycaemia in people with cancer is needed. This review aims to outline the link between diabetes therapies and cancer, and discuss the reasons why glucose should be actively managed people with both. In addition, we discuss clinical challenges in the management of hyperglycaemia in cancer, specifically in relation to glucocorticoids, enteral feeding and end-of-life care.