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Background & aims: Continuous glucose monitoring (CGM) provides data on short-term glycemic variability (GV). GV is associated with adverse outcomes in individuals with diabetes. Whether GV is associated with cardiometabolic risk in individuals without diabetes is unclear. We systematically reviewed the literature to assess whether GV is associated with cardiometabolic risk markers or outcomes in individuals without diabetes. Methods: Searches were performed in PubMed/Medline, Embase and Cochrane from inception through April 2022. Two researchers were involved in study selection, data extraction and quality assessment. Studies evaluating GV using CGM for >= 24 h were included. Studies in populations with acute and/or critical illness were excluded. Both narrative synthesis and meta -analyzes were performed, depending on outcome. Results: Seventy-one studies were included; the majority were cross-sectional. Multiple measures of GV are higher in individuals with compared to without prediabetes and GV appears to be inversely associated with beta cell function. In contrast, GV is not clearly associated with insulin sensitivity, fatty liver disease, adiposity, blood lipids, blood pressure or oxidative stress. However, GV may be positively associated with the degree of atherosclerosis and cardiovascular events in individuals with coronary disease. Conclusion: GV is elevated in prediabetes, potentially related to beta cell dysfunction, but less clearly associated with obesity or traditional risk factors. GV is associated with coronary atherosclerosis development and may predict cardiovascular events and type 2 diabetes. Prospective studies are warranted, investigating the predictive power of GV in relation to incident disease. GV may be an important risk measure also in individuals without diabetes. (c) 2024 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

Background & aims: Continuous glucose monitoring (CGM) provides data on short-term glycemic variability (GV). GV is associated with adverse outcomes in individuals with diabetes. Whether GV is associated with cardiometabolic risk in individuals without diabetes is unclear. We systematically reviewed the literature to assess whether GV is associated with cardiometabolic risk markers or outcomes in individuals without diabetes. Methods: Searches were performed in PubMed/Medline, Embase and Cochrane from inception through April 2022. Two researchers were involved in study selection, data extraction and quality assessment. Studies evaluating GV using CGM for >= 24 h were included. Studies in populations with acute and/or critical illness were excluded. Both narrative synthesis and meta -analyzes were performed, depending on outcome. Results: Seventy-one studies were included; the majority were cross-sectional. Multiple measures of GV are higher in individuals with compared to without prediabetes and GV appears to be inversely associated with beta cell function. In contrast, GV is not clearly associated with insulin sensitivity, fatty liver disease, adiposity, blood lipids, blood pressure or oxidative stress. However, GV may be positively associated with the degree of atherosclerosis and cardiovascular events in individuals with coronary disease. Conclusion: GV is elevated in prediabetes, potentially related to beta cell dysfunction, but less clearly associated with obesity or traditional risk factors. GV is associated with coronary atherosclerosis development and may predict cardiovascular events and type 2 diabetes. Prospective studies are warranted, investigating the predictive power of GV in relation to incident disease. GV may be an important risk measure also in individuals without diabetes. (c) 2024 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

Background & aims: Continuous glucose monitoring (CGM) provides data on short-term glycemic variability (GV). GV is associated with adverse outcomes in individuals with diabetes. Whether GV is associated with cardiometabolic risk in individuals without diabetes is unclear. We systematically reviewed the literature to assess whether GV is associated with cardiometabolic risk markers or outcomes in individuals without diabetes. Methods: Searches were performed in PubMed/Medline, Embase and Cochrane from inception through April 2022. Two researchers were involved in study selection, data extraction and quality assessment. Studies evaluating GV using CGM for >= 24 h were included. Studies in populations with acute and/or critical illness were excluded. Both narrative synthesis and meta -analyzes were performed, depending on outcome. Results: Seventy-one studies were included; the majority were cross-sectional. Multiple measures of GV are higher in individuals with compared to without prediabetes and GV appears to be inversely associated with beta cell function. In contrast, GV is not clearly associated with insulin sensitivity, fatty liver disease, adiposity, blood lipids, blood pressure or oxidative stress. However, GV may be positively associated with the degree of atherosclerosis and cardiovascular events in individuals with coronary disease. Conclusion: GV is elevated in prediabetes, potentially related to beta cell dysfunction, but less clearly associated with obesity or traditional risk factors. GV is associated with coronary atherosclerosis development and may predict cardiovascular events and type 2 diabetes. Prospective studies are warranted, investigating the predictive power of GV in relation to incident disease. GV may be an important risk measure also in individuals without diabetes. (c) 2024 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

BACKGROUND: Roux-en-Y gastric bypass (RYGB) and sleeve gastrectomy (SG) lead to lower fasting glucose concentrations, but might cause higher glycemic variability (GV) and increased risk of hypoglycemia. However, it has been sparsely studied in patients without preoperative diabetes under normal living conditions. OBJECTIVES: To study 24-hour interstitial glucose (IG) concentrations, GV, the occurrence of hypoglycemia and dietary intake before and after laparoscopic RYGB and SG in females without diabetes. SETTING: Outpatient bariatric units at a community and a university hospital. METHODS: Continuous glucose monitoring and open-ended food recording over 4 days in 4 study periods: at baseline, during the preoperative low-energy diet (LED) regimen, and at 6 and 12 months postoperatively. RESULTS: Of 47 patients included at baseline, 83%, 81%, and 79% completed the remaining 3 study periods. The mean 24-hour IG concentration was similar during the preoperative LED regimen and after surgery and significantly lower compared to baseline in both surgical groups. GV was significantly increased 6 and 12 months after surgery compared to baseline. The self-reported carbohydrate intake was positively associated with GV after surgery. IG concentrations below 3.9 mmol/L were observed in 14/25 (56%) of RYGB- and 9/12 (75%) of SG-treated patients 12 months after surgery. About 70% of patients with low IG concentrations also reported hypoglycemic symptoms. CONCLUSIONS: The lower IG concentration in combination with the higher GV after surgery, might create a lower margin to hypoglycemia. This could help explain the increased occurrence of hypoglycemic episodes after RYGB and SG.

Background & aims: Continuous glucose monitoring (CGM) provides data on short-term glycemic variability (GV). GV is associated with adverse outcomes in individuals with diabetes. Whether GV is associated with cardiometabolic risk in individuals without diabetes is unclear. We systematically reviewed the literature to assess whether GV is associated with cardiometabolic risk markers or outcomes in individuals without diabetes. Methods: Searches were performed in PubMed/Medline, Embase and Cochrane from inception through April 2022. Two researchers were involved in study selection, data extraction and quality assessment. Studies evaluating GV using CGM for >= 24 h were included. Studies in populations with acute and/or critical illness were excluded. Both narrative synthesis and meta -analyzes were performed, depending on outcome. Results: Seventy-one studies were included; the majority were cross-sectional. Multiple measures of GV are higher in individuals with compared to without prediabetes and GV appears to be inversely associated with beta cell function. In contrast, GV is not clearly associated with insulin sensitivity, fatty liver disease, adiposity, blood lipids, blood pressure or oxidative stress. However, GV may be positively associated with the degree of atherosclerosis and cardiovascular events in individuals with coronary disease. Conclusion: GV is elevated in prediabetes, potentially related to beta cell dysfunction, but less clearly associated with obesity or traditional risk factors. GV is associated with coronary atherosclerosis development and may predict cardiovascular events and type 2 diabetes. Prospective studies are warranted, investigating the predictive power of GV in relation to incident disease. GV may be an important risk measure also in individuals without diabetes. (c) 2024 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

Background & aims: Continuous glucose monitoring (CGM) provides data on short-term glycemic variability (GV). GV is associated with adverse outcomes in individuals with diabetes. Whether GV is associated with cardiometabolic risk in individuals without diabetes is unclear. We systematically reviewed the literature to assess whether GV is associated with cardiometabolic risk markers or outcomes in individuals without diabetes. Methods: Searches were performed in PubMed/Medline, Embase and Cochrane from inception through April 2022. Two researchers were involved in study selection, data extraction and quality assessment. Studies evaluating GV using CGM for >= 24 h were included. Studies in populations with acute and/or critical illness were excluded. Both narrative synthesis and meta -analyzes were performed, depending on outcome. Results: Seventy-one studies were included; the majority were cross-sectional. Multiple measures of GV are higher in individuals with compared to without prediabetes and GV appears to be inversely associated with beta cell function. In contrast, GV is not clearly associated with insulin sensitivity, fatty liver disease, adiposity, blood lipids, blood pressure or oxidative stress. However, GV may be positively associated with the degree of atherosclerosis and cardiovascular events in individuals with coronary disease. Conclusion: GV is elevated in prediabetes, potentially related to beta cell dysfunction, but less clearly associated with obesity or traditional risk factors. GV is associated with coronary atherosclerosis development and may predict cardiovascular events and type 2 diabetes. Prospective studies are warranted, investigating the predictive power of GV in relation to incident disease. GV may be an important risk measure also in individuals without diabetes. (c) 2024 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

Glucocorticoids, which are administered with chemotherapy, cause hyperglycemia. Glycemic variability among breast cancer patients without diabetes is not well known. A retrospective cohort study was conducted involving early-stage breast cancer patients without diabetes who received dexamethasone prior to neoadjuvant or adjuvant taxane chemotherapy between August 2017-December 2019. Random blood glucose levels were analyzed, and steroid-induced hyperglycemia (SIH) was defined as a random glucose level of >140 mg/dL. A multivariate proportional hazards model was used to identify the risk factors of SIH. Out of 100 patients, the median age was 53 years (IQR: 45-63.5). A total of 45% of patients were non-Hispanic White, 28% Hispanic, 19% Asian, and 5% African American. The incidence of SIH was 67%, and glycemic fluctuations were highest in those with glucose levels of >200 mg/dL. Non-Hispanic White patients represented a significant predictor for time to SIH, with a hazard ratio of 2.5 (95% CI: 1.04, 5.95, p = 0.039). SIH was transient in over 90% of the patients, and only seven patients remained hyperglycemic after glucocorticoid and chemotherapy completion. Pretaxane dexamethasone-induced hyperglycemia was observed in 67% of the patients, with the greatest glycemic lability in those patients with blood glucose levels of >200 mg/dL. The non-Hispanic White patients had a higher risk of developing SIH.

Background: Gestational diabetes mellitus (GDM) is a pregnancy complication associated with short- and long-term health consequences for mother and child. First line treatment is diet and exercise but there is a recognized knowledge gap as to what diet treatment is optimal. A healthy Nordic diet has been associated with improved health but no studies in women with GDM exist. The New Nordic Diet (NND) is an initiative with the purpose to develop a healthy Nordic diet including foods with the potential to grow in Nordic countries; including fruit, berries, vegetables, whole-grain cereal products, nuts, fish, and rapeseed oil. The purpose of the intervention with new Nordic DIet in women with GestatiOnal diabetes mellitus (iNDIGO) is to test if the NND compared with usual care improves glucose control in women with GDM. Methods: The iNDIGO study is a randomized parallel controlled trial where 50 women with GDM will be randomized to either an NND or usual care for 14 days (30–32 weeks of gestation). Participants in the NND group will receive menus and food bags containing foods to be consumed. Primary outcome is glycemic control (time in target) measured using continuous glucose monitoring. Compliance to the dietary intervention will be tested using dietary biomarkers and adherence questionnaires. Conclusion: Diet treatment represents first line treatment in GDM but it remains unclear what type of diets are effective. iNDIGO is an efficacy study and will provide evidence as to whether a healthy Nordic diet can improve glucose control in women with GDM.

Background: Gestational diabetes mellitus (GDM) is a pregnancy complication associated with short- and long-term health consequences for mother and child. First line treatment is diet and exercise but there is a recognized knowledge gap as to what diet treatment is optimal. A healthy Nordic diet has been associated with improved health but no studies in women with GDM exist. The New Nordic Diet (NND) is an initiative with the purpose to develop a healthy Nordic diet including foods with the potential to grow in Nordic countries; including fruit, berries, vegetables, whole-grain cereal products, nuts, fish, and rapeseed oil. The purpose of the intervention with new Nordic DIet in women with GestatiOnal diabetes mellitus (iNDIGO) is to test if the NND compared with usual care improves glucose control in women with GDM. Methods: The iNDIGO study is a randomized parallel controlled trial where 50 women with GDM will be randomized to either an NND or usual care for 14 days (30–32 weeks of gestation). Participants in the NND group will receive menus and food bags containing foods to be consumed. Primary outcome is glycemic control (time in target) measured using continuous glucose monitoring. Compliance to the dietary intervention will be tested using dietary biomarkers and adherence questionnaires. Conclusion: Diet treatment represents first line treatment in GDM but it remains unclear what type of diets are effective. iNDIGO is an efficacy study and will provide evidence as to whether a healthy Nordic diet can improve glucose control in women with GDM.

Background: Gestational diabetes mellitus (GDM) is a pregnancy complication associated with short- and long-term health consequences for mother and child. First line treatment is diet and exercise but there is a recognized knowledge gap as to what diet treatment is optimal. A healthy Nordic diet has been associated with improved health but no studies in women with GDM exist. The New Nordic Diet (NND) is an initiative with the purpose to develop a healthy Nordic diet including foods with the potential to grow in Nordic countries; including fruit, berries, vegetables, whole-grain cereal products, nuts, fish, and rapeseed oil. The purpose of the intervention with new Nordic DIet in women with GestatiOnal diabetes mellitus (iNDIGO) is to test if the NND compared with usual care improves glucose control in women with GDM. Methods: The iNDIGO study is a randomized parallel controlled trial where 50 women with GDM will be randomized to either an NND or usual care for 14 days (30–32 weeks of gestation). Participants in the NND group will receive menus and food bags containing foods to be consumed. Primary outcome is glycemic control (time in target) measured using continuous glucose monitoring. Compliance to the dietary intervention will be tested using dietary biomarkers and adherence questionnaires. Conclusion: Diet treatment represents first line treatment in GDM but it remains unclear what type of diets are effective. iNDIGO is an efficacy study and will provide evidence as to whether a healthy Nordic diet can improve glucose control in women with GDM.

Introdución: A Diabetes Mellitus (DM) é unha enfermidade metabólica caracterizada pola presenza de elevados niveis de glicosa en sangue. Un axeitado control metabólico asóciase coa diminución no desenvolvemento e progresión da enfermidade. Son varios os factores que poden contribuír á presenza de oscilacións nos niveis de glicosa ao longo do día, sendo a influencia das emocións un deles. Obxectivos: Explorar como as diferentes emocións poden influír nos niveis de glicosa en persoas con diagnóstico de DM, así como determinar como outras variables, como o tipo de emoción, a idade e o sexo, poden interferir nesta relación. Metodoloxía: Realizouse unha busca sistemática nas bases de datos Medline/Pubmed e Google Académico a partir dos seguintes termos: Glucose, Mood e Diabetes. O cribado dos artigos realizouse tendo en conta os seguintes criterios de inclusión: a) traballos científicos en formato artigo, b) publicacións posteriores ao ano 2000, c) estudos realizados en humanos, d) en idioma inglés ou castelán. Resultados: A partir da busca realizada obtívose un total de 14 traballos que permitiron recompilar información sobre o tema a tratar. Analizouse cada traballo tendo en conta: as características da mostra, os instrumentos empregados para a medición das emocións, os métodos usados para a medición da glicosa e os resultados obtidos. Atopouse relación entre as emocións e os niveis de glicosa pero só para as emoción negativas, non atopando relación significativa coas emocións positivas. Conclusións: As emocións negativas relaciónanse co incremento dos niveis de glicosa, mentres que a relación entre as emocións positivas e a glicosa parece non estar clara, atopándose resultados dispares. Por outro lado, non se atopou información de como a idade e o sexo poden interferir na relación entre as emocións e os niveis de glicosa., Introducción: La Diabetes Mellitus (DM) es una enfermedad metabólica caracterizada por la presencia de niveles elevados de glucosa en sangre. Un control metabólico adecuado se asocia con un menor desarrollo y progresión de la enfermedad. Son varios los factores que pueden contribuir a la presencia de fluctuaciones en los niveles de glucosa a lo largo del día, siendo la influencia de las emociones uno de ellos. Objetivos: Explorar cómo las diferentes emociones pueden influir en los niveles de glucosa en personas diagnosticadas con DM, así como determinar cómo otras variables, como el tipo de emoción, la edad y el sexo, pueden interferir en esta relación. Metodología: Se realizó una búsqueda sistemática en las bases de datos Medline/Pubmed y Google Scholar a partir de los siguientes términos: Glucose, Mood y Diabetes. La selección de los artículos se realizó teniendo en cuenta los siguientes criterios de inclusión: a) trabajos científicos en formato artículo, b) publicaciones posteriores al año 2000, c) estudios realizados en humanos, d) en inglés o español. Resultados: De la búsqueda realizada se obtuvo un total de 14 trabajos que permitieron recopilar información sobre el tema a tratar. Cada trabajo se analizó teniendo en cuenta: las características de la muestra, los instrumentos utilizados para medir las emociones, los métodos usados para medir la glucosa y los resultados obtenidos. Se encontró relación entre las emociones y los niveles de glucosa pero solo para las emociones negativas, no encontrando relación significativa con las emociones positivas. Conclusiones: Las emociones negativas se relacionan con el aumento de los niveles de glucosa, mientras que la relación entre las emociones positivas y la glucosa no parece estar clara, encontrándose resultados dispares. Por otro lado, no se encontró información sobre cómo la edad o el sexo pueden interferir en la relación entre las emociones y los niveles de glucosa., Introduction: Diabetes Mellitus (DM) is a metabolic disease characterized by the presence of high blood glucose levels. Adequate metabolic control is associated with less development and progression of the disease. There are several factors that can contribute to the presence of fluctuations in glucose levels throughout the day, with the influence of emotions being one of them. Objectives: To explore how different emotions can affect glucose levels in people diagnosed with DM, as well as determining how other variables, such as emotion type, age and gender, may interfere with this relationship. Methodology: A systematic search was performed on the Medline/Pubmed and Google Scholar databases, based on the following terms: Glucose, Mood, and Diabetes. The selection of articles was made considering the following inclusion criteria: a) scientific papers in article format, b) publications after the year 2000, c) studies conducted in humans, d) in English or in Spanish. Results: A total of fourteen papers were obtained from the search, which allowed us to collect information on the topic to be addressed. Each work was analyzed considering: the characteristics of the sample, the instruments used to measure emotions, the methods used for measuring glucose and the results obtained. A relationship was found between emotions and glucose levels but only for negative emotions, not finding a significant relationship with positive emotions. Conclusions: Negative emotions are related to increased glucose levels, while the relationship between positive emotions and glucose does not seem to be clear, with different results. On the other hand, no information was found on how age or sex may interfere with the relationship between emotions and glucose levels.

Background Glycemic variability (GV) has only been sparsely studied in patients with community-acquired pneumonia (CAP). This study aimed to quantify in-hospital GV in CAP patients, including determining the impact of type 2 diabetes mellitus (T2DM) and glucocorticoid (GC) treatment on GV. Methods This is a prospective cohort study of CAP patients (N = 40) with or without T2DM and treated or not with GCs. The primary endpoint was GV measured as glucose standard deviation (SD), coefficient of variation (CV), and postprandial glucose excursions (PPGE) based on continuous glucose monitoring (CGM). Analysis of glucose data was split into daytime and nighttime when possible. Results Patients included had a mean age of 74 (range 55 to 91) years. SD (95%CI) increased by a factor of 1.93 (1.40 to 2.66) and 2.29 (1.38 to 3.81) in patients with T2DM and not treated with GCs during the daytime and the nighttime, respectively (both P < 0.01), and by a factor of 1.42 (1.04 to 1.97) in patients treated with GCs but without T2DM during the daytime (P = 0.031) compared to patients without T2DM and not treated with GCs. CV (95%CI) increased by 5.1 (0.0 to 10.1) and 8.1 (1.0 to 15.2) percentage points during the daytime and the nighttime, respectively, in patients with T2DM and not treated with GCs compared to patients without T2DM and not treated with GCs (P = 0.046 and P = 0.026, respectively). PPGE (95% CI) increased during lunch by 2.5 (0.7 to 4.3) mmol/L (45 (13 to 77) mg/dL) in patients with T2DM and treated with GCs compared to patients without T2DM and not treated with GCs (P = 0.018). Conclusions CAP patients receiving GCs, especially those with T2DM, are at great risk of developing high GV and therefore require clinical attention to mitigate GV. This applies particularly during the daytime. Results support the 1 to 2-h post-lunch screening procedure for glucocorticoid-induced hyperglycemia in patients without diabetes. SD was positively correlated with hospital length

Background Glycemic variability (GV) has only been sparsely studied in patients with community-acquired pneumonia (CAP). This study aimed to quantify in-hospital GV in CAP patients, including determining the impact of type 2 diabetes mellitus (T2DM) and glucocorticoid (GC) treatment on GV. Methods This is a prospective cohort study of CAP patients (N = 40) with or without T2DM and treated or not with GCs. The primary endpoint was GV measured as glucose standard deviation (SD), coefficient of variation (CV), and postprandial glucose excursions (PPGE) based on continuous glucose monitoring (CGM). Analysis of glucose data was split into daytime and nighttime when possible. Results Patients included had a mean age of 74 (range 55 to 91) years. SD (95%CI) increased by a factor of 1.93 (1.40 to 2.66) and 2.29 (1.38 to 3.81) in patients with T2DM and not treated with GCs during the daytime and the nighttime, respectively (both P < 0.01), and by a factor of 1.42 (1.04 to 1.97) in patients treated with GCs but without T2DM during the daytime (P = 0.031) compared to patients without T2DM and not treated with GCs. CV (95%CI) increased by 5.1 (0.0 to 10.1) and 8.1 (1.0 to 15.2) percentage points during the daytime and the nighttime, respectively, in patients with T2DM and not treated with GCs compared to patients without T2DM and not treated with GCs (P = 0.046 and P = 0.026, respectively). PPGE (95% CI) increased during lunch by 2.5 (0.7 to 4.3) mmol/L (45 (13 to 77) mg/dL) in patients with T2DM and treated with GCs compared to patients without T2DM and not treated with GCs (P = 0.018). Conclusions CAP patients receiving GCs, especially those with T2DM, are at great risk of developing high GV and therefore require clinical attention to mitigate GV. This applies particularly during the daytime. Results support the 1 to 2-h post-lunch screening procedure for glucocorticoid-induced hyperglycemia in patients without diabetes. SD was positively correlated with hospital length

Background: Gestational diabetes mellitus (GDM) is a pregnancy complication associated with short- and long-term health consequences for mother and child. First line treatment is diet and exercise but there is a recognized knowledge gap as to what diet treatment is optimal. A healthy Nordic diet has been associated with improved health but no studies in women with GDM exist. The New Nordic Diet (NND) is an initiative with the purpose to develop a healthy Nordic diet including foods with the potential to grow in Nordic countries; including fruit, berries, vegetables, whole-grain cereal products, nuts, fish, and rapeseed oil. The purpose of the intervention with new Nordic DIet in women with GestatiOnal diabetes mellitus (iNDIGO) is to test if the NND compared with usual care improves glucose control in women with GDM. Methods: The iNDIGO study is a randomized parallel controlled trial where 50 women with GDM will be randomized to either an NND or usual care for 14 days (30–32 weeks of gestation). Participants in the NND group will receive menus and food bags containing foods to be consumed. Primary outcome is glycemic control (time in target) measured using continuous glucose monitoring. Compliance to the dietary intervention will be tested using dietary biomarkers and adherence questionnaires. Conclusion: Diet treatment represents first line treatment in GDM but it remains unclear what type of diets are effective. iNDIGO is an efficacy study and will provide evidence as to whether a healthy Nordic diet can improve glucose control in women with GDM.

Background: Gestational diabetes mellitus (GDM) is a pregnancy complication associated with short- and long-term health consequences for mother and child. First line treatment is diet and exercise but there is a recognized knowledge gap as to what diet treatment is optimal. A healthy Nordic diet has been associated with improved health but no studies in women with GDM exist. The New Nordic Diet (NND) is an initiative with the purpose to develop a healthy Nordic diet including foods with the potential to grow in Nordic countries; including fruit, berries, vegetables, whole-grain cereal products, nuts, fish, and rapeseed oil. The purpose of the intervention with new Nordic DIet in women with GestatiOnal diabetes mellitus (iNDIGO) is to test if the NND compared with usual care improves glucose control in women with GDM. Methods: The iNDIGO study is a randomized parallel controlled trial where 50 women with GDM will be randomized to either an NND or usual care for 14 days (30–32 weeks of gestation). Participants in the NND group will receive menus and food bags containing foods to be consumed. Primary outcome is glycemic control (time in target) measured using continuous glucose monitoring. Compliance to the dietary intervention will be tested using dietary biomarkers and adherence questionnaires. Conclusion: Diet treatment represents first line treatment in GDM but it remains unclear what type of diets are effective. iNDIGO is an efficacy study and will provide evidence as to whether a healthy Nordic diet can improve glucose control in women with GDM.

Background: Emerging evidence indicates a relationship between glycemic variability during intensive care unit (ICU) admission and death. We assessed whether mean glucose, hypoglycemia occurrence, or premorbid glycemic control modified this relationship. Methods: In this retrospective, multicenter cohort study, we included adult patients admitted to five ICUs in Australia and Sweden with available preadmission glycated hemoglobin A1c (HbA1c) and three or more glucose readings. We calculated the glycemic lability index (GLI), a measure of glycemic variability, and the time-weighted average blood glucose (TWA-BG) from all glucose readings. We used logistic regression analysis with adjustment for hypoglycemia and admission characteristics to assess the independent association of GLI (above vs. below cohort median) and TWA-BG (above vs. below cohort median) with hospital mortality. Results: Among 2305 patients, 859 (37%) had diabetes, median GLI was 40 [mmol/L]2 /h/week, median TWA-BG was 8.2 mmol/L, 171 (7%) developed hypoglycemia, and 371 (16%) died. The adjusted odds ratio for death was 1.61 (95% CI, 1.19-2.15; P = .002) for GLI above versus below median and 1.06 (95% CI, 0.80-1.41; P = .67) for TWA-BG above versus below median. The relationship between GLI and mortality was not modified by TWA-BG (P [interaction] = 0.66), a history of diabetes (P [interaction] = 0.89) or by HbA1c ≥52 mmol/mol (vs. <52 mmol/mol) (P [interaction] = 0.29). Conclusion: In adult patients admitted to an ICU in Sweden and Australia, a high GLI was associated with increased hospital mortality irrespective of the level of mean glycemia, hypoglycemia occurrence, or premorbid glycemic control. These findings support the assessment of interventions to reduce glycemic variability during critical illness.

Background: Emerging evidence indicates a relationship between glycemic variability during intensive care unit (ICU) admission and death. We assessed whether mean glucose, hypoglycemia occurrence, or premorbid glycemic control modified this relationship. Methods: In this retrospective, multicenter cohort study, we included adult patients admitted to five ICUs in Australia and Sweden with available preadmission glycated hemoglobin A1c (HbA1c) and three or more glucose readings. We calculated the glycemic lability index (GLI), a measure of glycemic variability, and the time-weighted average blood glucose (TWA-BG) from all glucose readings. We used logistic regression analysis with adjustment for hypoglycemia and admission characteristics to assess the independent association of GLI (above vs. below cohort median) and TWA-BG (above vs. below cohort median) with hospital mortality. Results: Among 2305 patients, 859 (37%) had diabetes, median GLI was 40 [mmol/L]2 /h/week, median TWA-BG was 8.2 mmol/L, 171 (7%) developed hypoglycemia, and 371 (16%) died. The adjusted odds ratio for death was 1.61 (95% CI, 1.19-2.15; P = .002) for GLI above versus below median and 1.06 (95% CI, 0.80-1.41; P = .67) for TWA-BG above versus below median. The relationship between GLI and mortality was not modified by TWA-BG (P [interaction] = 0.66), a history of diabetes (P [interaction] = 0.89) or by HbA1c ≥52 mmol/mol (vs. <52 mmol/mol) (P [interaction] = 0.29). Conclusion: In adult patients admitted to an ICU in Sweden and Australia, a high GLI was associated with increased hospital mortality irrespective of the level of mean glycemia, hypoglycemia occurrence, or premorbid glycemic control. These findings support the assessment of interventions to reduce glycemic variability during critical illness.

This is an observational study of interstitial glucose (IG) concentrations, IG variability and dietary intake under free-living conditions in 46 females with obesity but without diabetes. We used continuous glucose monitoring, open-ended food recording and step monitoring during regular dietary intake followed by a low-energy diet (LED). Thirty-nine participants completed both study periods. The mean BMI at baseline was 43.6 ± 6.2 kg/m2. Three weeks of LED resulted in a mean weight loss of 5.2% with a significant reduction in diurnal IG concentration but with greater glycemic variability observed during LED. The mean 24 h IG concentration decreased from 5.8 ± 0.5 mmol/L during the regular diet period to 5.4 ± 0.5 mmol/L (p < 0.001) during LED, while the mean amplitude of glycemic excursion increased from 1.5 ± 0.7 to 1.7 ± 0.7 mmol/L (p = 0.031). The positive incremental area under the curve at breakfast was significantly larger for LED compared to regular diet. The daily fiber intake and the glycemic index of breakfast meals were significantly associated with the glycemic variability during regular dietary intake. In conclusion, the 24 h mean IG concentration was lower but with more pronounced glycemic variability during LED compared to a regular diet.

Background: Emerging evidence indicates a relationship between glycemic variability during intensive care unit (ICU) admission and death. We assessed whether mean glucose, hypoglycemia occurrence, or premorbid glycemic control modified this relationship. Methods: In this retrospective, multicenter cohort study, we included adult patients admitted to five ICUs in Australia and Sweden with available preadmission glycated hemoglobin A1c (HbA1c) and three or more glucose readings. We calculated the glycemic lability index (GLI), a measure of glycemic variability, and the time-weighted average blood glucose (TWA-BG) from all glucose readings. We used logistic regression analysis with adjustment for hypoglycemia and admission characteristics to assess the independent association of GLI (above vs. below cohort median) and TWA-BG (above vs. below cohort median) with hospital mortality. Results: Among 2305 patients, 859 (37%) had diabetes, median GLI was 40 [mmol/L]2 /h/week, median TWA-BG was 8.2 mmol/L, 171 (7%) developed hypoglycemia, and 371 (16%) died. The adjusted odds ratio for death was 1.61 (95% CI, 1.19-2.15; P = .002) for GLI above versus below median and 1.06 (95% CI, 0.80-1.41; P = .67) for TWA-BG above versus below median. The relationship between GLI and mortality was not modified by TWA-BG (P [interaction] = 0.66), a history of diabetes (P [interaction] = 0.89) or by HbA1c ≥52 mmol/mol (vs. <52 mmol/mol) (P [interaction] = 0.29). Conclusion: In adult patients admitted to an ICU in Sweden and Australia, a high GLI was associated with increased hospital mortality irrespective of the level of mean glycemia, hypoglycemia occurrence, or premorbid glycemic control. These findings support the assessment of interventions to reduce glycemic variability during critical illness.

This is an observational study of interstitial glucose (IG) concentrations, IG variability and dietary intake under free-living conditions in 46 females with obesity but without diabetes. We used continuous glucose monitoring, open-ended food recording and step monitoring during regular dietary intake followed by a low-energy diet (LED). Thirty-nine participants completed both study periods. The mean BMI at baseline was 43.6 ± 6.2 kg/m2. Three weeks of LED resulted in a mean weight loss of 5.2% with a significant reduction in diurnal IG concentration but with greater glycemic variability observed during LED. The mean 24 h IG concentration decreased from 5.8 ± 0.5 mmol/L during the regular diet period to 5.4 ± 0.5 mmol/L (p < 0.001) during LED, while the mean amplitude of glycemic excursion increased from 1.5 ± 0.7 to 1.7 ± 0.7 mmol/L (p = 0.031). The positive incremental area under the curve at breakfast was significantly larger for LED compared to regular diet. The daily fiber intake and the glycemic index of breakfast meals were significantly associated with the glycemic variability during regular dietary intake. In conclusion, the 24 h mean IG concentration was lower but with more pronounced glycemic variability during LED compared to a regular diet.

This is an observational study of interstitial glucose (IG) concentrations, IG variability and dietary intake under free-living conditions in 46 females with obesity but without diabetes. We used continuous glucose monitoring, open-ended food recording and step monitoring during regular dietary intake followed by a low-energy diet (LED). Thirty-nine participants completed both study periods. The mean BMI at baseline was 43.6 ± 6.2 kg/m2. Three weeks of LED resulted in a mean weight loss of 5.2% with a significant reduction in diurnal IG concentration but with greater glycemic variability observed during LED. The mean 24 h IG concentration decreased from 5.8 ± 0.5 mmol/L during the regular diet period to 5.4 ± 0.5 mmol/L (p < 0.001) during LED, while the mean amplitude of glycemic excursion increased from 1.5 ± 0.7 to 1.7 ± 0.7 mmol/L (p = 0.031). The positive incremental area under the curve at breakfast was significantly larger for LED compared to regular diet. The daily fiber intake and the glycemic index of breakfast meals were significantly associated with the glycemic variability during regular dietary intake. In conclusion, the 24 h mean IG concentration was lower but with more pronounced glycemic variability during LED compared to a regular diet.

Background: Emerging evidence indicates a relationship between glycemic variability during intensive care unit (ICU) admission and death. We assessed whether mean glucose, hypoglycemia occurrence, or premorbid glycemic control modified this relationship. Methods: In this retrospective, multicenter cohort study, we included adult patients admitted to five ICUs in Australia and Sweden with available preadmission glycated hemoglobin A1c (HbA1c) and three or more glucose readings. We calculated the glycemic lability index (GLI), a measure of glycemic variability, and the time-weighted average blood glucose (TWA-BG) from all glucose readings. We used logistic regression analysis with adjustment for hypoglycemia and admission characteristics to assess the independent association of GLI (above vs. below cohort median) and TWA-BG (above vs. below cohort median) with hospital mortality. Results: Among 2305 patients, 859 (37%) had diabetes, median GLI was 40 [mmol/L]2 /h/week, median TWA-BG was 8.2 mmol/L, 171 (7%) developed hypoglycemia, and 371 (16%) died. The adjusted odds ratio for death was 1.61 (95% CI, 1.19-2.15; P = .002) for GLI above versus below median and 1.06 (95% CI, 0.80-1.41; P = .67) for TWA-BG above versus below median. The relationship between GLI and mortality was not modified by TWA-BG (P [interaction] = 0.66), a history of diabetes (P [interaction] = 0.89) or by HbA1c ≥52 mmol/mol (vs. <52 mmol/mol) (P [interaction] = 0.29). Conclusion: In adult patients admitted to an ICU in Sweden and Australia, a high GLI was associated with increased hospital mortality irrespective of the level of mean glycemia, hypoglycemia occurrence, or premorbid glycemic control. These findings support the assessment of interventions to reduce glycemic variability during critical illness.

The optimal dietary pattern to improve metabolic function remains elusive. In a 21-day randomized controlled inpatient crossover feeding trial of 20 insulin-resistant obese women, we assessed the extent to which two isocaloric dietary interventions—Mediterranean (M) and high protein (HP)—improved metabolic parameters. Obese women were assigned to one of the following dietary sequences: M–HP or HP–M. Cardiometabolic parameters, body weight, glucose monitoring and gut microbiome composition were assessed. Sixteen women completed the study. Compared to the M diet, the HP diet was more effective in (i) reducing insulin resistance (insulin: Beta (95% CI) = −6.98 (−12.30, −1.65) µIU/mL, p = 0.01; HOMA-IR: −1.78 (95% CI: −3.03, −0.52), p = 9 × 10−3 ); and (ii) improving glycemic variability (−3.13 (−4.60, −1.67) mg/dL, p = 4 × 10−4 ), a risk factor for T2D development. We then identified a panel of 10 microbial genera predictive of the difference in glycemic variability between the two diets. These include the genera Coprococcus and Lachnoclostridium, previously associated with glucose homeostasis and insulin resistance. Our results suggest that morbidly obese women with insulin resistance can achieve better control of insulin resistance and glycemic variability on a high HP diet compared to an M diet.

This is an observational study of interstitial glucose (IG) concentrations, IG variability and dietary intake under free-living conditions in 46 females with obesity but without diabetes. We used continuous glucose monitoring, open-ended food recording and step monitoring during regular dietary intake followed by a low-energy diet (LED). Thirty-nine participants completed both study periods. The mean BMI at baseline was 43.6 ± 6.2 kg/m2. Three weeks of LED resulted in a mean weight loss of 5.2% with a significant reduction in diurnal IG concentration but with greater glycemic variability observed during LED. The mean 24 h IG concentration decreased from 5.8 ± 0.5 mmol/L during the regular diet period to 5.4 ± 0.5 mmol/L (p < 0.001) during LED, while the mean amplitude of glycemic excursion increased from 1.5 ± 0.7 to 1.7 ± 0.7 mmol/L (p = 0.031). The positive incremental area under the curve at breakfast was significantly larger for LED compared to regular diet. The daily fiber intake and the glycemic index of breakfast meals were significantly associated with the glycemic variability during regular dietary intake. In conclusion, the 24 h mean IG concentration was lower but with more pronounced glycemic variability during LED compared to a regular diet.

Background: Insulin-treated patients with type 2 diabetes (T2D) are at risk of hypoglycemia, which is associated with an increased risk of cardiovascular disease and mortality. Using a long-term monitoring approach, we investigated the association between episodes of hypoglycemia, glycemic variability and cardiac arrhythmias in a real-life setting. Methods: Insulin-treated patients with T2D (N = 21, [mean ± SD] age 66.8 ± 9.6 years, BMI 30.1 ± 4.5 kg/m2, HbA1c 6.8 ± 0.4% [51.0 ± 4.8 mmol/mol]) were included for a one-year observational study. Patients were monitored with continuous glucose monitoring ([mean ± SD] 118 ± 6 days) and an implantable cardiac monitor (ICM) during the study period. Results: Time spend in hypoglycemia was higher during nighttime than during daytime ([median and interquartile range] 0.7% [0.7–2.7] vs. 0.4% [0.2–0.8]). The ICMs detected 724 episodes of potentially clinically significant arrhythmias in 12 (57%) participants, with atrial fibrillation and pauses accounting for 99% of the episodes. No association between hypoglycemia and cardiac arrhythmia was found during daytime. During nighttime, subject-specific hourly incidence of cardiac arrhythmias tended to increase with the occurrence of hypoglycemia (incident rate ratio [IRR] 1.70 [95% CI 0.36–8.01]) but only slightly with increasing time in hypoglycemia (IRR 1.04 [95% CI 0.89–1.22] per 5 min). Subject-specific incidence of cardiac arrhythmias during nighttime increased with increasing glycemic variability as estimated by coefficient of variation whereas it decreased during daytime (IRR 1.33 [95% CI 1.05–1.67] and IRR 0.77 [95% CI 0.59–0.99] per 5% absolute increase, respectively). Conclusions: Cardiac arrhythmias were common in insulin-treated patients with T2D and were associated with glycemic variability, whereas arrhythmias were not strongly associated with hypoglycemia. Trial registration: NCT03150030, ClinicalTrials.gov, registered May 11, 2017. https://clinicaltrial

Background: Carbohydrate counting and use of automated bolus calculators (ABCs) can help reduce HbA1c in type 1 diabetes but only limited evidence exists in type 2 diabetes. We evaluated the efficacy of advanced carbohydrate counting (ACC) and use of an ABC compared with manual insulin bolus calculation (MC) in persons with type 2 diabetes. Materials and Methods: A 24-week open-label, randomized clinical study was conducted in 79 persons with type 2 diabetes treated with basal-bolus insulin (mean age 62.5 ± 9.6 years, HbA1c 8.7% ± 1.0% [72 ± 11 mmol/mol], diabetes duration 18.7 ± 7.6 years). Participants were randomized 1:1 into two groups: ABC group received training in ACC and use of an ABC; MC group received training in ACC and manual calculation of insulin bolus. Participants wore blinded continuous glucose monitors for 6 days at baseline and at study end. Primary endpoint was change in HbA1c. Results: After 24 weeks, HbA1c decreased 0.8% (8.8 mmol/mol) in ABC group and 0.8% (9.0 mmol/mol) in MC group with no between-group difference (P = 0.96) and without increase in time in hypoglycemic range (sensor glucose <3.9 mmol/L). Glycemic variability decreased significantly in both groups, whereas the total insulin dose and body mass index (BMI) remained unchanged during the study. Treatment satisfaction increased significantly in both groups after 24 weeks. Conclusion: ACC is an effective, low-cost tool to reduce HbA1c and glycemic variability in persons with basal-bolus insulin-treated type 2 diabetes without increase in hypoglycemia or BMI. Similar effects were seen with use of an ABC and with use of manual bolus calculation.

CONTEXT: The extent of the glycemic variability in diabetes secondary to total pancreatectomy is not fully understood. OBJECTIVE: To evaluate glycemic variability in totally pancreatectomized (PX) patients and compare it to glycemic variability in hemoglobin A1c (HbA1c)-matched patients with long-standing type 1 diabetes (T1D). DESIGN: A case-control study was performed. SETTING: Center for Clinical Metabolic Research, Gentofte Hospital, University of Copenhagen, Hellerup, Denmark. PATIENTS OR OTHER PARTICIPANTS: Ten PX patients (mean [SEM]: age 64.3 [9.8] years; body mass index (BMI) 34.4 [5.0] kg/m2; duration of diabetes 3 [2.8] years), 10 HbA1c-matched patients with T1D (63.9 [8.6] years; 24.6 [3.1] kg/m2; 22 [4] years), and 10 gender-, age-, and BMI-matched healthy controls. All patients were managed on multiple daily injections of insulin. INTERVENTION: Continuous glucose monitoring (CGM) (Medtronic MiniMed iPro 2) during 12 consecutive days. MAIN OUTCOME MEASURES: Glycemic variability. RESULTS: HbA1c levels were similar in the PX group and the T1D group. The PX group had greater continuous overall net glycemic action per 60 minutes (CONGA60 min) compared with the T1D group (mean [SEM]: 9.5 [0.3] vs 8.3 [0.2] mmol/L, P < 0.003) and mean plasma glucose values were higher in the PX group (10.6 [0.9] vs 9.0 [0.9] mmol/L, P < 0.001), whereas coefficient of variation for plasma glucose and standard deviation of mean plasma glucose, respectively, were similar in the 2 groups. Time spent below range was not different between the PX and the T1D group (2.3 [0.8] vs 4.5 [0.8]%, P = 0.065), whereas time spent above range was higher in the PX group (51.4 [3.3] vs 37.6 [1.9]%, P < 0.001). CONCLUSIONS: CGM-assessed glycemic variability showed higher CONGA60 min and time spent above range in our PX patients compared with HbA1c-matched T1D patients. This study is registered at www.ClinicalTrials.gov (NCT02944110).

Background: Insulin-treated patients with type 2 diabetes (T2D) are at risk of hypoglycemia, which is associated with an increased risk of cardiovascular disease and mortality. Using a long-term monitoring approach, we investigated the association between episodes of hypoglycemia, glycemic variability and cardiac arrhythmias in a real-life setting. Methods: Insulin-treated patients with T2D (N = 21, [mean ± SD] age 66.8 ± 9.6 years, BMI 30.1 ± 4.5 kg/m2, HbA1c 6.8 ± 0.4% [51.0 ± 4.8 mmol/mol]) were included for a one-year observational study. Patients were monitored with continuous glucose monitoring ([mean ± SD] 118 ± 6 days) and an implantable cardiac monitor (ICM) during the study period. Results: Time spend in hypoglycemia was higher during nighttime than during daytime ([median and interquartile range] 0.7% [0.7–2.7] vs. 0.4% [0.2–0.8]). The ICMs detected 724 episodes of potentially clinically significant arrhythmias in 12 (57%) participants, with atrial fibrillation and pauses accounting for 99% of the episodes. No association between hypoglycemia and cardiac arrhythmia was found during daytime. During nighttime, subject-specific hourly incidence of cardiac arrhythmias tended to increase with the occurrence of hypoglycemia (incident rate ratio [IRR] 1.70 [95% CI 0.36–8.01]) but only slightly with increasing time in hypoglycemia (IRR 1.04 [95% CI 0.89–1.22] per 5 min). Subject-specific incidence of cardiac arrhythmias during nighttime increased with increasing glycemic variability as estimated by coefficient of variation whereas it decreased during daytime (IRR 1.33 [95% CI 1.05–1.67] and IRR 0.77 [95% CI 0.59–0.99] per 5% absolute increase, respectively). Conclusions: Cardiac arrhythmias were common in insulin-treated patients with T2D and were associated with glycemic variability, whereas arrhythmias were not strongly associated with hypoglycemia. Trial registration: NCT03150030, ClinicalTrials.gov, registered May 11, 2017. https://clinicaltrial

Background: Emerging evidence indicates a relationship between glycemic variability during intensive care unit (ICU) admission and death. We assessed whether mean glucose, hypoglycemia occurrence, or premorbid glycemic control modified this relationship. Methods: In this retrospective, multicenter cohort study, we included adult patients admitted to five ICUs in Australia and Sweden with available preadmission glycated hemoglobin A1c (HbA1c) and three or more glucose readings. We calculated the glycemic lability index (GLI), a measure of glycemic variability, and the time-weighted average blood glucose (TWA-BG) from all glucose readings. We used logistic regression analysis with adjustment for hypoglycemia and admission characteristics to assess the independent association of GLI (above vs. below cohort median) and TWA-BG (above vs. below cohort median) with hospital mortality. Results: Among 2305 patients, 859 (37%) had diabetes, median GLI was 40 [mmol/L]2 /h/week, median TWA-BG was 8.2 mmol/L, 171 (7%) developed hypoglycemia, and 371 (16%) died. The adjusted odds ratio for death was 1.61 (95% CI, 1.19-2.15; P = .002) for GLI above versus below median and 1.06 (95% CI, 0.80-1.41; P = .67) for TWA-BG above versus below median. The relationship between GLI and mortality was not modified by TWA-BG (P [interaction] = 0.66), a history of diabetes (P [interaction] = 0.89) or by HbA1c ≥52 mmol/mol (vs. <52 mmol/mol) (P [interaction] = 0.29). Conclusion: In adult patients admitted to an ICU in Sweden and Australia, a high GLI was associated with increased hospital mortality irrespective of the level of mean glycemia, hypoglycemia occurrence, or premorbid glycemic control. These findings support the assessment of interventions to reduce glycemic variability during critical illness.

This is an observational study of interstitial glucose (IG) concentrations, IG variability and dietary intake under free-living conditions in 46 females with obesity but without diabetes. We used continuous glucose monitoring, open-ended food recording and step monitoring during regular dietary intake followed by a low-energy diet (LED). Thirty-nine participants completed both study periods. The mean BMI at baseline was 43.6 ± 6.2 kg/m2. Three weeks of LED resulted in a mean weight loss of 5.2% with a significant reduction in diurnal IG concentration but with greater glycemic variability observed during LED. The mean 24 h IG concentration decreased from 5.8 ± 0.5 mmol/L during the regular diet period to 5.4 ± 0.5 mmol/L (p < 0.001) during LED, while the mean amplitude of glycemic excursion increased from 1.5 ± 0.7 to 1.7 ± 0.7 mmol/L (p = 0.031). The positive incremental area under the curve at breakfast was significantly larger for LED compared to regular diet. The daily fiber intake and the glycemic index of breakfast meals were significantly associated with the glycemic variability during regular dietary intake. In conclusion, the 24 h mean IG concentration was lower but with more pronounced glycemic variability during LED compared to a regular diet.

Glycemic variability (GV) represents the amplitude of oscillations in glucose levels over time and is associated with higher mortality in critically ill patients. Our aim is to evaluate the impact of GV on acute ischemic stroke (IS) outcomes in humans and explore the impact of two different insulin administration routes on GV in an animal model. This translational study consists of two studies conducted in parallel: The first study is an observational, multicenter, prospective clinical study in which 340 patients with acute IS will be subcutaneously implanted a sensor to continuously monitor blood glucose levels for 96 h. The second study is a basic experimental study using an animal model (rats) with permanent occlusion of the middle cerebral artery and induced hyperglycemia (through an intraperitoneal injection of nicotinamide and streptozotocin). The animal study will include the following 6 groups (10 animals per group): sham; hyperglycemia without IS; IS without hyperglycemia; IS and hyperglycemia without treatment; IS and hyperglycemia and intravenous insulin; and IS and hyperglycemia and subcutaneous insulin. The endpoint for the first study is mortality at 3 months, while the endpoints for the animal model study are GV, functional recovery and biomarkers. The GLIAS-III study will be the first translational approach analyzing the prognostic influence of GV, evaluated by the use of subcutaneous glucose monitors, in acute stroke. Trial registration (NCT04001049)

Prediabetes (intermediate hyperglycemia) consists of two abnormalities, impaired fasting glucose (IFG) and impaired glucose tolerance (IGT) detected by a standardized 75-gram oral glucose tolerance test (OGTT). Individuals with isolated IGT or combined IFG and IGT have increased risk for developing type 2 diabetes (T2D) and cardiovascular disease (CVD). Diagnosing prediabetes early and accurately is critical in order to refer high-risk individuals for intensive lifestyle modification. However, there is currently no international consensus for diagnosing prediabetes with HbA1c or glucose measurements based upon American Diabetes Association (ADA) and the World Health Organization (WHO) criteria that identify different populations at risk for progressing to diabetes. Various caveats affecting the accuracy of interpreting the HbA1c including genetics complicate this further. This review describes established methods for detecting glucose disorders based upon glucose and HbA1c parameters as well as novel approaches including the 1-hour plasma glucose (1-h PG), glucose challenge test (GCT), shape of the glucose curve, genetics, continuous glucose monitoring (CGM), measures of insulin secretion and sensitivity, metabolomics, and ancillary tools such as fructosamine, glycated albumin (GA), 1,5- anhydroglucitol (1,5-AG). Of the approaches considered, the 1-h PG has considerable potential as a biomarker for detecting glucose disorders if confirmed by additional data including health economic analysis. Whether the 1-h OGTT is superior to genetics and omics in providing greater precision for individualized treatment requires further investigation. These methods will need to demonstrate substantially superiority to simpler tools for detecting glucose disorders to justify their cost and complexity.

Carbohydrate is the macronutrient that has the greatest impact on blood glucose response. Limited data are available on how carbohydrate distribution throughout the day affects blood glucose in women with gestational diabetes mellitus (GDM). We aimed to assess how a high-carbohydrate morning-intake (HCM) versus a low-carbohydrate-morning-intake (LCM), affect glycemic variability and glucose control. In this randomized crossover study continuous glucose monitoring (CGM) was performed in 12 women with diet treated GDM (75 g, 2-h OGTT ≥ 8.5 mmol/L), who went through 2 × 3 days of HCM and LCM. A within-subject-analysis showed a significantly higher mean amplitude of glucose excursions (MAGE) (0.7 mmol/L, p = 0.004) and coefficient of variation (CV) (5.1%, p = 0.01) when comparing HCM with LCM, whereas a significantly lower mean glucose (MG) (-0.3 mmol/L, p = 0.002) and fasting blood glucose (FBG) were found (-0.4 mmol/L, p = 0.01) on the HCM diet compared to the LCM diet. In addition, insulin resistance, expressed as Homeostatic Model Assessment for Insulin Resistance (HOMA-IR), decreased significantly during HCM. Results indicate that a carbohydrate distribution of 50% in the morning favors lower blood glucose and improvement in insulin sensitivity in women with GDM, but in contrary gives a higher glycemic variability.

Carbohydrate is the macronutrient that has the greatest impact on blood glucose response. Limited data are available on how carbohydrate distribution throughout the day affects blood glucose in women with gestational diabetes mellitus (GDM). We aimed to assess how a high-carbohydrate morning-intake (HCM) versus a low-carbohydrate-morning-intake (LCM), affect glycemic variability and glucose control. In this randomized crossover study continuous glucose monitoring (CGM) was performed in 12 women with diet treated GDM (75 g, 2-h OGTT ≥ 8.5 mmol/L), who went through 2 × 3 days of HCM and LCM. A within-subject-analysis showed a significantly higher mean amplitude of glucose excursions (MAGE) (0.7 mmol/L, p = 0.004) and coefficient of variation (CV) (5.1%, p = 0.01) when comparing HCM with LCM, whereas a significantly lower mean glucose (MG) (-0.3 mmol/L, p = 0.002) and fasting blood glucose (FBG) were found (-0.4 mmol/L, p = 0.01) on the HCM diet compared to the LCM diet. In addition, insulin resistance, expressed as Homeostatic Model Assessment for Insulin Resistance (HOMA-IR), decreased significantly during HCM. Results indicate that a carbohydrate distribution of 50% in the morning favors lower blood glucose and improvement in insulin sensitivity in women with GDM, but in contrary gives a higher glycemic variability.

Background: Bariatric surgery improves glucose homeostasis; however, side effects such as hypoglycemia can occur. We investigated the effects of meals on interstitial glucose (IG) response in biliopancreatic diversion with duodenal switch (BPD-DS) and Roux-en-Y gastric bypass (RYGBP)-operated patients at least 1 year after surgery. Methods: Thirty patients treated with BPD-DS or RYGBP were recruited at the outpatient Obesity Unit, Uppsala University Hospital. IG was measured by continuous glucose monitoring (CGM) for 3 consecutive days, and postprandial IG levels from 5 to 120 min were analyzed for 2 of these days. All intake of food and beverages was simultaneously registered in a food diary, which was processed using The Meal Pattern Questionnaire. Results: Postprandial IG levels were significantly lower in BPD-DS (n = 14) compared to RYGBP (n = 15)-treated patients, with mean concentrations of 5.0 (+/- 1.0) and 6.3 (+/- 1.8) mmol/L respectively (p < 0.001). The mean postprandial IG increment was lower in BPD-DS than in RYGBP patients, 0.2 (+/- 0.6) vs. 0.4 (+/- 1.4) mmol/L (p < 0.001). Furthermore, the postprandial IG variability was less pronounced in BPD-DS than in RYGBP patients. The mean number of daily meals did not differ between the two groups, 7.8 (+/- 2.6) in BPD-DS and 7.2 (+/- 1.7) in the RYGBP (p = 0.56). Conclusion: BPD-DS patients demonstrated lower postprandial IG concentrations, with smaller postprandial IG increments and less pronounced postprandial IG variability compared to RYGBP patients. The two groups had similar meal pattern and the postprandial IG responses is probably associated with differences in postoperative physiology.

Background: Bariatric surgery improves glucose homeostasis; however, side effects such as hypoglycemia can occur. We investigated the effects of meals on interstitial glucose (IG) response in biliopancreatic diversion with duodenal switch (BPD-DS) and Roux-en-Y gastric bypass (RYGBP)-operated patients at least 1 year after surgery. Methods: Thirty patients treated with BPD-DS or RYGBP were recruited at the outpatient Obesity Unit, Uppsala University Hospital. IG was measured by continuous glucose monitoring (CGM) for 3 consecutive days, and postprandial IG levels from 5 to 120 min were analyzed for 2 of these days. All intake of food and beverages was simultaneously registered in a food diary, which was processed using The Meal Pattern Questionnaire. Results: Postprandial IG levels were significantly lower in BPD-DS (n = 14) compared to RYGBP (n = 15)-treated patients, with mean concentrations of 5.0 (+/- 1.0) and 6.3 (+/- 1.8) mmol/L respectively (p < 0.001). The mean postprandial IG increment was lower in BPD-DS than in RYGBP patients, 0.2 (+/- 0.6) vs. 0.4 (+/- 1.4) mmol/L (p < 0.001). Furthermore, the postprandial IG variability was less pronounced in BPD-DS than in RYGBP patients. The mean number of daily meals did not differ between the two groups, 7.8 (+/- 2.6) in BPD-DS and 7.2 (+/- 1.7) in the RYGBP (p = 0.56). Conclusion: BPD-DS patients demonstrated lower postprandial IG concentrations, with smaller postprandial IG increments and less pronounced postprandial IG variability compared to RYGBP patients. The two groups had similar meal pattern and the postprandial IG responses is probably associated with differences in postoperative physiology.

Background: Bariatric surgery improves glucose homeostasis; however, side effects such as hypoglycemia can occur. We investigated the effects of meals on interstitial glucose (IG) response in biliopancreatic diversion with duodenal switch (BPD-DS) and Roux-en-Y gastric bypass (RYGBP)-operated patients at least 1 year after surgery. Methods: Thirty patients treated with BPD-DS or RYGBP were recruited at the outpatient Obesity Unit, Uppsala University Hospital. IG was measured by continuous glucose monitoring (CGM) for 3 consecutive days, and postprandial IG levels from 5 to 120 min were analyzed for 2 of these days. All intake of food and beverages was simultaneously registered in a food diary, which was processed using The Meal Pattern Questionnaire. Results: Postprandial IG levels were significantly lower in BPD-DS (n = 14) compared to RYGBP (n = 15)-treated patients, with mean concentrations of 5.0 (+/- 1.0) and 6.3 (+/- 1.8) mmol/L respectively (p < 0.001). The mean postprandial IG increment was lower in BPD-DS than in RYGBP patients, 0.2 (+/- 0.6) vs. 0.4 (+/- 1.4) mmol/L (p < 0.001). Furthermore, the postprandial IG variability was less pronounced in BPD-DS than in RYGBP patients. The mean number of daily meals did not differ between the two groups, 7.8 (+/- 2.6) in BPD-DS and 7.2 (+/- 1.7) in the RYGBP (p = 0.56). Conclusion: BPD-DS patients demonstrated lower postprandial IG concentrations, with smaller postprandial IG increments and less pronounced postprandial IG variability compared to RYGBP patients. The two groups had similar meal pattern and the postprandial IG responses is probably associated with differences in postoperative physiology.

Background: Bariatric surgery improves glucose homeostasis; however, side effects such as hypoglycemia can occur. We investigated the effects of meals on interstitial glucose (IG) response in biliopancreatic diversion with duodenal switch (BPD-DS) and Roux-en-Y gastric bypass (RYGBP)-operated patients at least 1 year after surgery. Methods: Thirty patients treated with BPD-DS or RYGBP were recruited at the outpatient Obesity Unit, Uppsala University Hospital. IG was measured by continuous glucose monitoring (CGM) for 3 consecutive days, and postprandial IG levels from 5 to 120 min were analyzed for 2 of these days. All intake of food and beverages was simultaneously registered in a food diary, which was processed using The Meal Pattern Questionnaire. Results: Postprandial IG levels were significantly lower in BPD-DS (n = 14) compared to RYGBP (n = 15)-treated patients, with mean concentrations of 5.0 (+/- 1.0) and 6.3 (+/- 1.8) mmol/L respectively (p < 0.001). The mean postprandial IG increment was lower in BPD-DS than in RYGBP patients, 0.2 (+/- 0.6) vs. 0.4 (+/- 1.4) mmol/L (p < 0.001). Furthermore, the postprandial IG variability was less pronounced in BPD-DS than in RYGBP patients. The mean number of daily meals did not differ between the two groups, 7.8 (+/- 2.6) in BPD-DS and 7.2 (+/- 1.7) in the RYGBP (p = 0.56). Conclusion: BPD-DS patients demonstrated lower postprandial IG concentrations, with smaller postprandial IG increments and less pronounced postprandial IG variability compared to RYGBP patients. The two groups had similar meal pattern and the postprandial IG responses is probably associated with differences in postoperative physiology.

Stress hyperglycemia occurs frequently during critical illness due to the increased resistance to insulin. The three domains of dysglycemia, that is, stress hyperglycemia, hypoglycemia, and high glycemic variability, are associated with a poor outcome. The risk-to-benefit ratio of intensive insulin therapy aiming at a blood glucose target ranging from 80 to 110 mg/dL has not been found beneficial in most interventional studies. Glycemic control titrated to reach liberal glycemic ranges of blood glucose and personalized targets are currently investigated in clinical trials., SCOPUS: ch.b, info:eu-repo/semantics/published

Background: Bariatric surgery improves glucose homeostasis; however, side effects such as hypoglycemia can occur. We investigated the effects of meals on interstitial glucose (IG) response in biliopancreatic diversion with duodenal switch (BPD-DS) and Roux-en-Y gastric bypass (RYGBP)-operated patients at least 1 year after surgery. Methods: Thirty patients treated with BPD-DS or RYGBP were recruited at the outpatient Obesity Unit, Uppsala University Hospital. IG was measured by continuous glucose monitoring (CGM) for 3 consecutive days, and postprandial IG levels from 5 to 120 min were analyzed for 2 of these days. All intake of food and beverages was simultaneously registered in a food diary, which was processed using The Meal Pattern Questionnaire. Results: Postprandial IG levels were significantly lower in BPD-DS (n = 14) compared to RYGBP (n = 15)-treated patients, with mean concentrations of 5.0 (+/- 1.0) and 6.3 (+/- 1.8) mmol/L respectively (p < 0.001). The mean postprandial IG increment was lower in BPD-DS than in RYGBP patients, 0.2 (+/- 0.6) vs. 0.4 (+/- 1.4) mmol/L (p < 0.001). Furthermore, the postprandial IG variability was less pronounced in BPD-DS than in RYGBP patients. The mean number of daily meals did not differ between the two groups, 7.8 (+/- 2.6) in BPD-DS and 7.2 (+/- 1.7) in the RYGBP (p = 0.56). Conclusion: BPD-DS patients demonstrated lower postprandial IG concentrations, with smaller postprandial IG increments and less pronounced postprandial IG variability compared to RYGBP patients. The two groups had similar meal pattern and the postprandial IG responses is probably associated with differences in postoperative physiology.

У лекції розглядаються актуальні питання лікування хворих на цукровий діабет (ЦД) похилого й старечого віку. Чисельність таких людей із ЦД 2-го типу неухильно збільшується. Тактика ведення цієї категорії пацієнтів має бути індивідуальною й включати адекватну корекцію гіперглікемії для запобігання мікросудинним ускладненням і гіпоглікемічним станам, зниження серцево-судинної смертності й збереження якості життя. Викладені основні відомості про клінічні особливості ЦД і застосування антигіперглікемізуючих препаратів у пацієнтів похилого й старечого віку. Особлива увага звертається на цільові рівні глікемічного контролю., В лекции рассматриваются актуальные вопросы лечения больных сахарным диабетом (СД) пожилого и старческого возраста. Численность людей с СД 2-го типа неуклонно увеличивается. Тактика ведения этой категории пациентов должна быть индивидуальной и включать адекватную коррекцию гипергликемии для предотвращения микрососудистых осложнений и гипогликемических состояний, снижения сердечно-сосудистой смертности и сохранения качества жизни. Изложены основные сведения о клинических особенностях СД и применении антигипергликемизирующих препаратов у пациентов пожилого и старческого возраста. Особое внимание обращается на целевые уровни гликемического контроля., The lecture deals with the topical issues of treating elderly and senile patients with diabetes mellitus (DM). The number of such people with type 2 DM is steadily increasing. The management of this category of patients should be individual and include adequate correction of hyperglycemia to prevent microvascular complications, as well as hypoglycemic episodes, to reduce cardiovascular mortality and to maintain the quality of life. The basic data about clinical features of DM and application of antihyperglycemic preparations in elderly and senile patients are presented. Special attention is paid to the target levels of glycemic control.

Background: It is well known that adiposity is a risk factor for insulin resistance and type 2 diabetes mellitus. In the present study, we aimed to investigate the associations of measures of adiposity with indices of glycemia and of glycemic variability over a 72-h period in non-diabetic older adults. Methods: This cross-sectional study was conducted in non-diabetic individuals from the Active and Healthy Aging Study (N = 228), Switchbox (N = 116), and the Growing Old Together Study (N = 94). Body mass index (BMI) and waist circumference were measured, and indices of glycemia and glycemic variability were derived from continuous glucose monitoring (CGM) using the Mini-Med® CGM system. Associations between adiposity and CGM were studied separately for the three cohorts, and derived estimates were subsequently meta-analyzed. Results: After meta-analyzing the results from the separate cohorts, individuals with a higher BMI had higher levels of glycemia. Individuals with BMI between 30 and 35 kg/m2 had 0.28 mmol/L [95% confidence interval (CI): 0.12-0.44] higher 72 h-mean glucose concentration, 0.26 mmol/L (0.10-0.42) higher diurnal glucose (6:00 a.m. to 0:00 a.m.), and 0.39 mmol/L (0.19; 0.59) higher nocturnal glucose (3:00 a.m. to 6:00 a.m.) than participants with a normal weight (BMI 18.5-25 kg/m2). However, no associations were observed between higher BMI and glycemic variability. Results for glycemia and glycemic variability were similarly observed for a high waist circumference. Conclusion: High adiposity associates with constant higher mean glucose levels over the day in non-diabetic older adults.

Objectives: Tight glycemic control using intermittent blood glucose measurements is associated with a risk of hypoglycemia. Glucose concentrations can now be measured near continuously (every 5–15min). We assessed the quality and safety of glycemic control guided by a near-continuous glucose monitoring system in ICU patients. Design: Prospective, cluster-randomized, crossover study. Setting: Thirty-five–bed medico-surgical department of intensive care with four separate ICUs. Patients: Adult patients admitted to the department and expected to stay for at least 3 days were considered for inclusion if they had persistent hyperglycemia (blood glucose > 150mg/dL) up to 6 hours after admission and/or were receiving insulin therapy. Interventions: A peripheral venous catheter was inserted in all patients and connected to a continuous glucose monitoring sensor (GlucoClear; Edwards Lifesciences, Irvine, CA). The four ICUs were randomized in pairs in a crossover design to glycemic control using unblinded or blinded continuous glucose monitoring monitors. The insulin infusion rate was adjusted to keep blood glucose between 90 and 150mg/dL using the blood glucose values displayed on the continuous glucose monitor (continuous glucose monitoring group—unblinded units) or according to intermittent blood glucose readings (intermittent glucose monitoring group—blinded units). Measurements and Main Results: The quality and safety of glycemic control were assessed using the proportion of time in range, the frequency of blood glucose less than 70mg/dL, and the time spent with blood glucose less than 70mg/dL (TB70), using blood glucose values measured by the continuous glucose monitoring device. Seventy-seven patients were enrolled: 39 in the continuous glucose monitoring group and 38 in the intermittent glucose monitoring group. A total of 43,107 blood glucose values were recorded. The time in range was similar in the two groups. The incidence of hypoglycemia (8/39 [20.5%] vs 15/38 [3, SCOPUS: ar.j, info:eu-repo/semantics/published

Introduction Premixed insulin analogs represent an alternative to basal or basal–bolus insulin regimens for the treatment of type 2 diabetes (T2D). “Low-mix” formulations with a low rapid-acting to long-acting analog ratio (e.g., 25/75) are commonly used, but 50/50 formulations (Mix50) may be more appropriate for some patients. We conducted a systematic literature review to assess the efficacy and safety of Mix50, compared with low-mix, basal, or basal–bolus therapy, for insulin initiation and intensification. Methods MEDLINE, EMBASE, Cochrane Database of Systematic Reviews, ClinicalTrials.gov, LillyTrials.com, and NovoNordisk-trials.com were searched (11 or 13 Dec 2016) using terms for T2D, premixed insulin analogs, and/or Mix50. Studies (randomized, nonrandomized, or observational; English only) comparing Mix50 with other insulins (except human) and reporting key efficacy [glycated hemoglobin (HbA1c), fasting and postprandial glucose] and/or safety (hypoglycemia, weight gain) outcomes were eligible for inclusion. Narrative reviews, letters, editorials, and conference abstracts were excluded. Risk of bias in randomized trials was assessed using the Cochrane tool. Results MEDLINE and EMBASE searches identified 716 unique studies, of which 32 met inclusion criteria. An additional three studies were identified in the other databases. All 19 randomized trials except one were open label; risk of other biases was generally low. Although not conclusive, the evidence suggests that Mix50 may provide better glycemic control (HbA1c reduction) and, particularly, postprandial glucose reduction in certain patients, such as those with high carbohydrate diets and Asian patients, than low-mix and basal therapy. Based on this evidence and our experience, we provide clinical guidance on factors to consider when deciding whether Mix50 is appropriate for individual patients. Conclusions

type:Departmental Bulletin Paper, [Abstract] Background: The incidence of coronary events is higher in patients with diabetes, even after statin therapy. Recently, glycemic variability assessed by continuous glucose monitoring (CGM)has been suggested to be associated with the progression of coronary atherosclerosis in these patients. Therefore, we prospectively followed patients using serial CGM and coronary angiography(CAG)over 10 months. Methods and Results: This was a prospective observational study of 27 patients with coronary artery disease(CAD)and early stage diabetes (including impaired glucose tolerance). The progression of coronary artery percent stenosis by CAG was observed in 12 patients(the progression group). Assessment of baseline characteristics indicated that a higher mean amplitude of glycemic excursion (MAGE),an index of glycemic variability, was associated with disease progression (P＝0.023). Although low-density lipoprotein cholesterol(LDL-C) levels were significantly decreased during the 10 months, the progression group showed higher LDL-C at follow-up(P＝0.037).In addition, only patients without progression showed increased high-density lipoprotein cholesterol(HDL-C)during the 10 months. Consequently, a high LDL-C/HDLC ratio at follow-up was associated with progression(P＝0.012). However, these were not associated with changes in plaque burden or necrotic core volume on virtual histology-intravascular ultrasound. Conclusions: In Japanese patients with CAD and early stage diabetes receiving statin therapy, both glycemic variability (MAGE) at baseline and a high LDL-C/HDL-C ratio at follow-up were predictors for mid-term progression of coronary atherosclerosis. The strategies for modifying these predictors, and the effects on the progression of coronary atherosclerosis need to be explored further.

Background: Cardiovascular disease is the most common complication of Type 2 Diabetes. While increased physical activity has been shown to improve the glycemic control of Type 2 Diabetics, their risk of cardiovascular disease remains unchanged. This has led to an increased focus on glycemic variability, a component of glycemic control which reflects short-term glucose regulation. Interval training is a novel exercise therapy comprised of alternating bouts of high intensity and low intensity aerobic exercise. It has been proposed that interval training may prove to be a superior exercise protocol over continuous moderate exercise through better regulation of glycemic variability. Objective: The primary objective of this thesis was to determine how interval training affects glycemic variability in adult Type 2 Diabetics compared to continuous aerobic exercise and no training (control). The secondary objective was to investigate the relationships between the individual glycemic variability indices. Methods: Non-insulin dependent Type 2 Diabetics (n=6) were included in a randomized cross-over study consisting of three 2-week interventions: Interval Walking Training (IWT), Continuous Walking Training (CWT), and no training [control (CON)]. During IWT and CWT subjects underwent 10 training sessions consisting of 60 minutes of supervised treadmill walking. Those in the CWT arm walked at a continuous pace for the entire hour while those in IWT walked at 3 minute alternating intervals of low and high intensity. A Continuous Glucose Monitoring (CGM) system was inserted into subjects before and after each intervention to measure glycemic variability. Results: No differences in glycemic variability were found between interventions. Reductions in various glycemic parameters were seen after IWT, although none reached statistical significance. Correlation analysis between the glycemic variability parameters showed a high collinearity between all indices. Conclu

Background: Cardiovascular disease is the most common complication of Type 2 Diabetes. While increased physical activity has been shown to improve the glycemic control of Type 2 Diabetics, their risk of cardiovascular disease remains unchanged. This has led to an increased focus on glycemic variability, a component of glycemic control which reflects short-term glucose regulation. Interval training is a novel exercise therapy comprised of alternating bouts of high intensity and low intensity aerobic exercise. It has been proposed that interval training may prove to be a superior exercise protocol over continuous moderate exercise through better regulation of glycemic variability. Objective: The primary objective of this thesis was to determine how interval training affects glycemic variability in adult Type 2 Diabetics compared to continuous aerobic exercise and no training (control). The secondary objective was to investigate the relationships between the individual glycemic variability indices. Methods: Non-insulin dependent Type 2 Diabetics (n=6) were included in a randomized cross-over study consisting of three 2-week interventions: Interval Walking Training (IWT), Continuous Walking Training (CWT), and no training [control (CON)]. During IWT and CWT subjects underwent 10 training sessions consisting of 60 minutes of supervised treadmill walking. Those in the CWT arm walked at a continuous pace for the entire hour while those in IWT walked at 3 minute alternating intervals of low and high intensity. A Continuous Glucose Monitoring (CGM) system was inserted into subjects before and after each intervention to measure glycemic variability. Results: No differences in glycemic variability were found between interventions. Reductions in various glycemic parameters were seen after IWT, although none reached statistical significance. Correlation analysis between the glycemic variability parameters showed a high collinearity between all indices. Conclu

Chronic hyperglycemia is the main risk factor for the development of diabetes-related complications in both type 1 and type 2 diabetes, but it is thought that frequent or large glucose fluctuations may contribute independently to diabetes-related complications.A systematic literature review was performed using the PubMed, EMBASE and Cochrane Library databases with searches limited to studies published from June 2002 to March 2014, in English and including ≥50 patients. Twenty eight articles were included in the final review.Eighteen studies reported the association between glucose variability and diabetes-related complications exclusively in type 2 diabetes. A positive association between increased variability and microvascular complications and coronary artery disease was consistently reported. Associations between glucose variability and other macrovascular complications were inconsistent in type 2 diabetes.Seven studies examined the association between glucose variability and complications exclusively in type 1 diabetes. Increased glucose variability appears to play a minimal role in the development of micro- and macrovascular complications in type 1 diabetes.Consistent findings suggest that in type 2 diabetes glucose variability is associated with development of microvascular complications. The role of increased glucose variability in terms of microvascular and macrovascular complications in type 1 diabetes is less clear; more data in are needed.