Erratum. Predictive Low-Glucose Insulin Suspension Reduces Duration of Nocturnal Hypoglycemia in Children Without Increasing Ketosis. Diabetes Care 2015;38:1197-1204.
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SUBMITTER: Buckingham BA
PROVIDER: S-EPMC5321240 | biostudies-literature | 2015 Sep
REPOSITORIES: biostudies-literature
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Erratum. Predictive Low-Glucose Insulin Suspension Reduces Duration of Nocturnal Hypoglycemia in Children Without Increasing Ketosis. Diabetes Care 2015;38:1197-1204.
Buckingham Bruce A BA Raghinaru Dan D Cameron Fraser F Bequette B Wayne BW Chase H Peter HP Maahs David M DM Slover Robert R Wadwa R Paul RP Wilson Darrell M DM Ly Trang T Aye Tandy T Hramiak Irene I Clarson Cheril C Stein Robert R Gallego Patricia H PH Lum John J Sibayan Judy J Kollman Craig C Beck Roy W RW
Diabetes care 20150901 9
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Project description:ObjectiveNocturnal hypoglycemia can cause seizures and is a major impediment to tight glycemic control, especially in young children with type 1 diabetes. We conducted an in-home randomized trial to assess the efficacy and safety of a continuous glucose monitor-based overnight predictive low-glucose suspend (PLGS) system.Research design and methodsIn two age-groups of children with type 1 diabetes (11-14 and 4-10 years of age), a 42-night trial for each child was conducted wherein each night was assigned randomly to either having the PLGS system active (intervention night) or inactive (control night). The primary outcome was percent time <70 mg/dL overnight.ResultsMedian time at <70 mg/dL was reduced by 54% from 10.1% on control nights to 4.6% on intervention nights (P < 0.001) in 11-14-year-olds (n = 45) and by 50% from 6.2% to 3.1% (P < 0.001) in 4-10-year-olds (n = 36). Mean overnight glucose was lower on control versus intervention nights in both age-groups (144 ± 18 vs. 152 ± 19 mg/dL [P < 0.001] and 153 ± 14 vs. 160 ± 16 mg/dL [P = 0.004], respectively). Mean morning blood glucose was 159 ± 29 vs. 176 ± 28 mg/dL (P < 0.001) in the 11-14-year-olds and 154 ± 25 vs. 158 ± 22 mg/dL (P = 0.11) in the 4-10-year-olds, respectively. No differences were found between intervention and control in either age-group in morning blood ketosis.ConclusionsIn 4-14-year-olds, use of a nocturnal PLGS system can substantially reduce overnight hypoglycemia without an increase in morning ketosis, although overnight mean glucose is slightly higher.
| S-EPMC4477332 | biostudies-literature
Project description:ObjectiveTo assess the effect of overnight insulin pump suspension in an automated predictive low glucose suspend system on morning blood glucose and ketone levels in an attempt to determine whether routine measurement of ketone levels is useful when a closed-loop system that suspends insulin delivery overnight is being used.Research design and methodsData from an in-home randomized trial of 45 individuals with type 1 diabetes (age range 15-45 years) were analyzed, evaluating an automated predictive low glucose pump suspension system in which blood glucose, blood ketone, and urine ketone levels were measured on 1,954 mornings.ResultsOne or more pump suspensions occurred during 744 of the 977 intervention nights (76%). The morning blood ketone level was ≥0.6 mmol/L after 11 of the 744 nights (1.5%) during which a pump suspension occurred and 2 of the 233 nights (0.9%) during which there was no suspension compared with 11 of 977 control nights (1.1%). The morning blood ketone level was ≥0.6 mmol/L after only 2 of 159 nights (1.3%) with a pump suspension exceeding 2 h. Morning fasting blood glucose level was not a good predictor of the presence of blood ketones.ConclusionsRoutine measurement of blood or urine ketones during use of an automated pump suspension system using continuous glucose monitoring, whether threshold based or predictive, is not necessary. Recommendations for checking ketone levels should be no different when a patient is using a system with automated insulin suspension than it is for conventional diabetes self-management.
| S-EPMC3994933 | biostudies-literature
Project description:To evaluate a sensor-augmented insulin pump with a low glucose suspend (LGS) feature that automatically suspends basal insulin delivery for up to 2 h in response to sensor-detected hypoglycemia.The LGS feature of the Paradigm Veo insulin pump (Medtronic, Inc., Northridge, CA) was tested for 3 weeks in 31 adults with type 1 diabetes.There were 166 episodes of LGS: 66% of daytime LGS episodes were terminated within 10 min, and 20 episodes lasted the maximum 2 h. LGS use was associated with reduced nocturnal duration ?2.2 mmol/L in those in the highest quartile of nocturnal hypoglycemia at baseline (median 46.2 vs. 1.8 min/day, P = 0.02 [LGS-OFF vs. LGS-ON]). Median sensor glucose was 3.9 mmol/L after 2-h LGS and 8.2 mmol/L at 2 h after basal restart.Use of an insulin pump with LGS was associated with reduced nocturnal hypoglycemia in those at greatest risk and was well accepted by patients.
| S-EPMC3161284 | biostudies-literature
Project description:Background: This analysis from the SMILE randomized study was performed to identify predictive factors associated with the greatest reductions in hypoglycemia with the Medtronic MiniMed™ 640G Suspend before low feature in adults with type 1 diabetes at high risk of severe hypoglycemia. Methods: Clinical and treatment-related factors associated with decreased sensor hypoglycemia (SH) were identified in participants from the intervention arm by univariate and multivariate analyses. Results: The reduction in SH events <54 mg/dL (<3.0 mmol/L) in the intervention group was significantly (P < 0.0001) associated with the baseline mean number of sensor hypoglycemic events (MNSHE) <54 mg/dL. When excluding continuous glucose monitoring (CGM) factors not readily available (MNSHE, duration of SH events, area under the curve, mean amplitude of glycemic excursions), only the baseline mean time spent <54 mg/dL was found to be a significant independent predictor factor (P < 0.0001). Baseline HbA1c, mean self-monitoring of blood glucose (SMBG), and coefficient of variation of SMBG were significant, although weak, predictors in the absence of any CGM data. Conclusions: The greatest reductions in SH events achieved with the MiniMed 640G system with the Suspend before low feature were seen in participants with higher baseline MNSHE. Measuring these (usually uncollected) events can be a useful tool to predict hypoglycemia reduction. ClinicalTrials.gov Registration Identifier NCT02733991.
| S-EPMC7478192 | biostudies-literature
Project description:ObjectiveNocturnal hypoglycemia is a common problem with type 1 diabetes. In the home setting, we conducted a pilot study to evaluate the safety of a system consisting of an insulin pump and continuous glucose monitor communicating wirelessly with a bedside computer running an algorithm that temporarily suspends insulin delivery when hypoglycemia is predicted.Research design and methodsAfter the run-in phase, a 21-night randomized trial was conducted in which each night was randomly assigned 2:1 to have either the predictive low-glucose suspend (PLGS) system active (intervention night) or inactive (control night). Three predictive algorithm versions were studied sequentially during the study for a total of 252 intervention and 123 control nights. The trial included 19 participants 18-56 years old with type 1 diabetes (hemoglobin A1c level of 6.0-7.7%) who were current users of the MiniMed Paradigm® REAL-Time Revel™ System and Sof-sensor® glucose sensor (Medtronic Diabetes, Northridge, CA).ResultsWith the final algorithm, pump suspension occurred on 53% of 77 intervention nights. Mean morning glucose level was 144±48 mg/dL on the 77 intervention nights versus 133±57 mg/dL on the 37 control nights, with morning blood ketones >0.6 mmol/L following one intervention night. Overnight hypoglycemia was lower on intervention than control nights, with at least one value ≤70 mg/dL occurring on 16% versus 30% of nights, respectively, with the final algorithm.ConclusionsThis study demonstrated that the PLGS system in the home setting is safe and feasible. The preliminary efficacy data appear promising with the final algorithm reducing nocturnal hypoglycemia by almost 50%.
| S-EPMC3746249 | biostudies-literature
Project description:ObjectiveTo determine the effects of reducing overnight basal insulin or a bedtime dose of terbutaline on nocturnal blood glucose (BG) nadir and hypoglycemia after exercise in children with type 1 diabetes mellitus.Study designSixteen youth (mean age 13.3 years) on insulin pumps were studied overnight on 3 occasions after a 60-minute exercise session with BG measurements every 30 minutes. Admissions were randomized to bedtime treatment with oral terbutaline 2.5 mg, 20% basal rate insulin reduction for 6 hours, or no treatment.ResultsMean overnight nadir BG was 188 mg/dL after terbutaline and 172 mg/dL with basal rate reduction compared with 127 mg/dL on the control night (P = .002 and .042, respectively). Terbutaline eliminated nocturnal hypoglycemia but resulted in significantly more hyperglycemia (?250 mg/dL) when compared with the control visit (P < .0001). The basal rate reduction resulted in fewer BG readings <80 and <70 mg/dL but more readings ?250 mg/dL when compared with the control visit.ConclusionsA basal insulin rate reduction was safe and effective in raising post-exercise nocturnal BG nadir and in reducing hypoglycemia in children with type 1 diabetes mellitus. Although effective at preventing hypoglycemia, a 2.5-mg dose of terbutaline was associated with hyperglycemia.
| S-EPMC2957531 | biostudies-literature
Project description:ObjectivesHypoglycemia is frequent in very low birth weight (VLBW) neonates and compromises their neurological outcome. The aim of this study was to compare real-time continuous glucose monitoring system (RT-CGMS) to standard methods by intermittent capillary blood glucose testing in detecting and managing hypoglycemia.Study designForty-eight VLBW neonates were enrolled in this prospective study. During their 3 first days of life, their glucose level was monitored either by RT-CGMS (CGM-group), or by intermittent capillary glucose testing (IGM-group) associated with a blind-CGMS to detect retrospectively missed hypoglycemia. Outcomes were the number and duration of hypoglycemic (≤ 50 mg/dl) episodes per patient detected by CGMS.ResultsForty-three monitorings were analyzed (IGM n = 21, CGM n = 22), with a median recording time of 72 hours. In the IGM group, blind-CGMS revealed a significantly higher number of hypoglycemia episodes than capillary blood glucose testing (1.2 ± 0.4 vs 0.4 ± 0.2 episode/patient, p<0.01). In the CGM-group, the use of RT-CGMS made it possible (i) to detect the same number of hypoglycemia episodes as blind-CGMS (1.2 ± 0.4 episode/patient), (ii) to adapt the glucose supply in neonates with hypoglycemia (increased supply during days 1 and 2), and (iii) to significantly reduce the duration of hypoglycemia episodes per patient (CGM 44[10-140] min versus IGM 95[15-520] min, p<0.05). Furthermore, it reduced the number of blood samples (CGM 16.9 ± 1.0 vs IGM 21.9 ± 1.0 blood sample/patient, p<0.001).ConclusionRT-CGMS played a beneficial role in managing hypoglycemia in VLBW neonates by adjusting the carbohydrate supply to the individual needs and by reducing the duration of hypoglycemia episodes. The clinical significance of the biological differences observed in our study need to be explored.
| S-EPMC4295867 | biostudies-literature
Project description:BackgroundHypoglycemia is the most common complication in insulin treated diabetes. Though mostly mild, it can be fatal in rare cases: It is hypothesized that hypoglycemia related QTc prolongation contributes to cardiac arrhythmia.ObjectiveTo evaluate influence of nocturnal hypoglycemia on QTc and heart rate variability (HRV) in children with T1D.MethodsChildren and adolescents with T1D for at least 6 months participated in an observational study using continuous glucose monitoring (CGM) and Holter electrocardiogram for five consecutive nights. Mean QTc was calculated for episodes of nocturnal hypoglycemia (<3.7 mmol/L) and compared to periods of the same duration preceding hypoglycemia. HRV (RMSSD, low and high frequency power LF and HF) was analyzed for different 15 min intervals: before hypoglycemia, onset of hypoglycemia, before/after nadir, end of hypoglycemia and after hypoglycemia.ResultsMean QTc during hypoglycemia was significantly longer compared to euglycemia (412 ± 15 vs. 405 ± 18 ms, p = 0.005). HRV changed significantly: RMSSD (from 88 ± 57 to 73 ± 43 ms) and HF (from 54 ± 17 to 47 ± 17nu) decreased from before hypoglycemia to after nadir, while heart rate (from 69 ± 9 to 72 ± 12 bpm) and LF (from 44 ± 17 to 52 ± 21 nu) increased (p = 0.04).ConclusionA QTc lengthening effect of nocturnal hypoglycemia in children with T1D was documented. HRV changes occurred even before detection of nocturnal hypoglycemia by CGM, which may be useful for hypoglycemia prediction.
| S-EPMC9291884 | biostudies-literature
Project description:BACKGROUND AND OBJECTIVES:In-center, extended duration nocturnal hemodialysis has been associated with variable clinical benefits, but the effect of extended duration hemodialysis on many established uremic solutes and other components of the metabolome is unknown. We determined the magnitude of change in metabolite profiles for patients on extended duration nocturnal hemodialysis. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS:In a 52-week prospective, observational study, we followed 33 patients receiving conventional thrice weekly hemodialysis who converted to nocturnal hemodialysis (7-8 hours per session, three times per week). A separate group of 20 patients who remained on conventional hemodialysis (3-4 hours per session, three times per week) served as a control group. For both groups, we applied liquid chromatography-mass spectrometry-based metabolite profiling on stored plasma samples collected from all participants at baseline and after 1 year. We examined longitudinal changes in 164 metabolites among those who remained on conventional hemodialysis and those who converted to nocturnal hemodialysis using Wilcoxon rank sum tests adjusted for multiple comparisons (false discovery rate <0.05). RESULTS:On average, the nocturnal group had 9.6 hours more dialysis per week than the conventional group. Among 164 metabolites, none changed significantly from baseline to study end in the conventional group. Twenty-nine metabolites changed in the nocturnal group, 21 of which increased from baseline to study end (including all branched-chain amino acids). Eight metabolites decreased after conversion to nocturnal dialysis, including l-carnitine and acetylcarnitine. By contrast, several established uremic retention solutes, including p-cresol sulfate, indoxyl sulfate, and trimethylamine N-oxide, did not change with extended dialysis. CONCLUSIONS:Across a wide array of metabolites examined, extended duration hemodialysis was associated with modest changes in the plasma metabolome, with most differences relating to metabolite increases, despite increased dialysis time. Few metabolites showed reduction with more dialysis, and no change in several established uremic toxins was observed.
| S-EPMC5967674 | biostudies-literature
Project description:Nocturnal hypoglycemia (NH) is a dangerous complication of insulin therapy that often goes undetected. In this study, we aimed to generate machine learning (ML)-based models for short-term NH prediction in hospitalized patients with type 1 diabetes (T1D). The models were trained on continuous glucose monitoring (CGM) data obtained from 406 adult patients admitted to a tertiary referral hospital. Eight CGM-derived metrics of glycemic control and glucose variability were included in the models. Combinations of CGM and clinical data (23 parameters) were also assessed. Random Forest (RF), Logistic Linear Regression with Lasso regularization, and Artificial Neuron Networks algorithms were applied. In our models, RF provided the best prediction accuracy with 15 min and 30 min prediction horizons. The addition of clinical parameters slightly improved the prediction accuracy of most models, whereas oversampling and undersampling procedures did not have significant effects. The areas under the curve of the best models based on CGM and clinical data with 15 min and 30 min prediction horizons were 0.97 and 0.942, respectively. Basal insulin dose, diabetes duration, proteinuria, and HbA1c were the most important clinical predictors of NH assessed by RF. In conclusion, ML is a promising approach to personalized prediction of NH in hospitalized patients with T1D.
| S-EPMC9409948 | biostudies-literature