scholarly journals Parenteral Nutrition-Associated Hyperglycemia in Noncritically Ill Inpatients Is Associated with Higher Mortality

2010 ◽  
Vol 24 (7) ◽  
pp. 453-457 ◽  
Author(s):  
Sofia Sarkisian ◽  
Tanis R Fenton ◽  
Abdel Aziz Shaheen ◽  
Maitreyi Raman
Keyword(s):  
Renal Failure ◽  
Blood Glucose ◽  
Parenteral Nutrition ◽  
Blood Glucose Level ◽  
Glucose Level ◽  
Glucose Monitoring ◽  
Hospital Length ◽  
Hospital Length Of Stay ◽  
Coronary Events ◽  
Mean Blood Glucose

BACKGROUND: Hyperglycemia is a marker of poor clinical outcomes in studies evaluating hospitalized critically ill patients.OBJECTIVES: To identify whether glycemic control is associated with health outcomes including acute coronary events, renal failure, infection, hospital length of stay, intensive care unit (ICU) admission, sepsis and mortality in noncritically ill patients administered parenteral nutrition (PN), and to compare the current standard of care for glucose monitoring at the Foothills Medical Centre (Calgary, Alberta) with the 2009 American Society of Parenteral and Enteral Nutrition guidelines.METHODS: A retrospective chart review of 100 adult (18 years of age or older) non-ICU inpatients who received PN for seven days or longer at the Foothills Medical Centre was conducted.RESULTS: Seventeen patients (17%) had a mean blood glucose level of 10.0 mmol/L or greater. PN patients with a mean blood glucose level of 10 mmol/L or greater had a higher rate of mortality than patients with a mean blood glucose level of less than 10 mmol/L (OR 7.22; 95% CI 1.08 to 48.29; P=0.042). Hyperglycemia was independently and significantly associated with mortality when adjusted for age and sex. Acute coronary events, renal failure, infection, hospital length of stay, ventilator use and ICU admissions were not associated with hyperglycemia. Only one-half of those with hyperglycemia, and none of the patients in the euglycemic group, received adequate glucose monitoring during the first two days of PN.CONCLUSION: Hyperglycemia in noncritically ill inpatients receiving PN was found to be a risk factor for increased mortality.

scholarly journals Association Between Preoperative Blood Glucose Level and Hospital Length of Stay for Patients Undergoing Appendectomy or Laparoscopic Cholecystectomy

Diabetes Care ◽  
2020 ◽  
Vol 44 (1) ◽  
pp. 107-115
Author(s):  
Hsiu-Yin Chiang ◽  
Kuan-Ting Robin Lin ◽  
Ya-Luan Hsiao ◽  
Han-Chun Huang ◽  
Shih-Ni Chang ◽  
...  
Keyword(s):  
Laparoscopic Cholecystectomy ◽  
Blood Glucose ◽  
Length Of Stay ◽  
Blood Glucose Level ◽  
Glucose Level ◽  
Hospital Length ◽  
Hospital Length Of Stay

scholarly journals The Impact of Preoperative Fasting Duration on Blood Glucose and Hemodynamics in Children

2020 ◽  
Vol 2020 ◽  
pp. 1-6
Author(s):  
Pouran Hajian ◽  
Minoo Shabani ◽  
Elham Khanlarzadeh ◽  
Mahshid Nikooseresht
Keyword(s):  
Blood Pressure ◽  
Blood Glucose ◽  
Blood Glucose Level ◽  
Systolic Blood Pressure ◽  
Glucose Level ◽  
Anesthesia Induction ◽  
Preoperative Fasting ◽  
Mean Blood Glucose ◽  
Fasting Duration ◽  
The Impact

Background. Prolonged preoperative fasting is one of the concerns of pediatricians and anesthesiologists in pediatric surgery. The aim of this study was to assess the impact of preoperative fasting duration on blood glucose and hemodynamics in children. Methods. This cross-sectional study was conducted on 50 children who were between the ages of 3 and 12 years in Besat Hospital, Hamedan, Iran. The time of the last solid and liquid meal taken by child were recorded based on interview with the parents. The first blood glucose test was obtained in the operation room, and the second test was performed 20 minutes after induction of anesthesia by glucometer. Systolic blood pressure (SBP), mean arterial pressure (MAP), and heart rate (HR) were recorded before anesthesia induction and in five-minute intervals in the first 20 minutes of surgery. Results. The mean age of the children was 6.63 (SD 1.85) years. Mean blood glucose 20 minutes after surgery was 101.17 (SD 92) mg/dl, which was significantly higher than the baseline values (87.66 (SD 11.84) mg/dl) (P<0.001). The comparison of mean blood glucose level between groups of fasting with different duration for solids (<12 hours and >12 hours) and for liquids (<6 hours and >6 hours) revealed no significant difference in either groups (P>0.05). No significant correlation was observed between blood glucose level at the induction of anesthesia with weight and age (P>0.05). There was a significantly negative correlation between duration of fasting for liquids and SBP (P>0.05). Conclusion. Prolonged preoperative fasting cannot affect blood glucose in children; however, maybe it has impact on systolic blood pressure.

Design of Automatic Insulin Dosage Indicator for Diabetic Patients Using BMI

2020 ◽  
pp. 69-74
Author(s):  
Kanimozhi R ◽  
Saravanakumar S
Keyword(s):  
Blood Glucose ◽  
Blood Glucose Level ◽  
Glucose Level ◽  
Blood Glucose Concentration ◽  
Glucose Monitoring ◽  
Blood Glucose Monitoring ◽  
Insulin Dosage ◽  
Diabetic Patients ◽  
Monitoring Methods ◽  
Invasive Techniques

Diabetes Mellitus is a serious and chronic health disease. It occurs in all age group of people, especially in adults and aged persons. It is important to measure blood glucose level frequently for the diabetes affected persons which in need to determine the appropriate insulin dosage. Along with this, the continuous glucose monitoring is vital to know whether the glucose level is in normal range. The conventional method used to measure the glucose level in blood is invasive which is infectious and a painful process. Nowadays, the non-invasive blood glucose monitoring methods are widely used. In this work, the blood glucose level is measured non-invasively using IR sensor. Besides that, the indication of insulin dosage to be taken is done by determining blood glucose concentration (non- invasively) and comparing it with Body Mass Index (BMI) of the patient. The implementation is based on the variations in the intensity of the IR LED, BMI and blood density. Themethod ismore reliable than the invasive techniques.

scholarly journals Hyperglycemia: A Predictor of Death in Severe Head Injury Patients

2016 ◽  
Vol 9 ◽  
pp. CMED.S40330 ◽  
Author(s):  
Simin Babaie Kafaki ◽  
Kamaledin Alaedini ◽  
Ashkan Qorbani ◽  
Leila Asadian ◽  
Kaveh Haddadi
Keyword(s):  
Blood Glucose ◽  
Head Injury ◽  
Mortality Rate ◽  
Length Of Stay ◽  
Blood Glucose Level ◽  
Prospective Study ◽  
Glucose Level ◽  
Severe Head Injury ◽  
Hospital Length Of Stay ◽  
Comprehensive Treatment

Objectives Management of hyperglycemia during an acute sickness in adults is accompanied by improved outcomes. We have designed a prospective study with meticulous attention to exclude all diabetes patients by checking hemoglobin A1c (HbA1c or glycated hemoglobin) to avoid the ill-effects of hyperglycemia in patients with traumatic head injury admitted to the intensive care unit (ICU). Methods This prospective study included adults with traumatic primary brain injury with a Glasgow coma score of ≥8 necessitating mechanical ventilation treated in the period 2012–2015. After screening 311 patients, 220 were included in the study. Both blood glucose and HbA1c levels of all the patients at admission, as well as blood glucose level after 72 hours, were obtained from the records. The patients were later grouped based on their admission blood glucose levels (<200 mg/dL or ≤200 mg/dL). Injury severity score (ISS) was documented for every patient. As a final point, the outcomes were determined based on the hospital length of stay (HLS) and ICU length of stay (ILS), plusmortality rates. Results About 39% ( n = 85) of patients were admitted with hyperglycemia during the study period. The mortality rate in patients with glucose ≤200 mg/dL was 65.8% ( N = 56), against 23.7% ( N = 32) in the group with glucose <200 mg/dL, with mortality rising as the blood glucose level increased ( P = 0.014). Conclusions We conclude that admission hyperglycemia is related with increased mortality rate in head injury patients, and comprehensive treatment of hyperglycemia can improve the outcome of severe head injury patients.

Design and Validation of a Low-Cost Non-Invasive Device to Detect Overnight Hypoglycemia

2018 ◽  
Author(s):  
Jonathan Lesko ◽  
Stephen Seibert ◽  
Yong Zhu
Keyword(s):  
Blood Glucose ◽  
Blood Glucose Level ◽  
Glucose Level ◽  
Electrodermal Activity ◽  
Low Cost ◽  
Glucose Monitoring ◽  
Blood Glucose Monitoring ◽  
Life Threatening ◽  
Invasive Device ◽  
The Individual

Research in the field of blood glucose monitoring systems has led to incredible advancements over the past several decades. The blood glucose level of a diabetic patient is vital to monitor since large swings in blood sugar can cause life threatening damage to the individual. The importance of blood glucose monitoring increases when a patient experiences hypoglycemia, which can be very dangerous. The objective of this project is to create a low cost portable device that utilizes the modular bio-signal sensor kit BITalino and Arduino Uno microcontroller to measure and process the electrodermal activity (EDA) and electrocardiography (ECG) signals that can be associated with a drop in the subject’s blood glucose level to detect hypoglycemia in diabetics.

PARAMETRIC AND NON-PARAMETRIC REGRESSION APPROACHES FOR NON-INVASIVE BLOOD GLUCOSE MONITORING

2020 ◽  
Vol 32 (06) ◽  
pp. 2050043
Author(s):  
Keshava N. Acharya ◽  
M. G. Yashwanth Gowda ◽  
M. Vijay ◽  
S. Deepthi ◽  
S. Malathi ◽  
...  
Keyword(s):  
Health Care ◽  
Blood Glucose ◽  
Blood Glucose Level ◽  
Glucose Level ◽  
Glucose Monitoring ◽  
Sensor Data ◽  
Blood Glucose Monitoring ◽  
Self Monitoring ◽  
Non Invasive ◽  
Non Parametric

Blood glucose monitoring systems (BGMSs) play a crucial role in health care applications. Invasive measurements are more accurate while non-invasive BGMS encourage self monitoring and reduce the cost of health care. Though multiple sensor data acquisition and suitable processing improve accuracy, self-monitoring becomes difficult in such non-invasive systems due to multiple signal acquisition. This paper investigates a non-invasive BGMS prototype that renders accurate measurements by statistically processing a single sensor data. The developed prototype is based on near-infrared (NIR) spectroscopy, which provides an electronic voltage that gets mapped to corresponding blood glucose level. This mapping is proposed using two different statistical regression approaches, parametric Bayesian Regression (BR) approach and the non-parametric Gaussian Process Regression (GPR) approach. Dataset is acquired from 33 subjects who visited Ramaiah Medical College Hospital, India. On each subject, voltage from the BGMS prototype and corresponding invasively obtained blood glucose level have been recorded. The BR and GPR approaches are trained with 75% of the data while the remaining 25% is used for testing. Test results show that BR approach renders root mean square error (RMSE) of 3.7[Formula: see text]mg/dL, while the mean absolute percentage error (MAPE) is around 2.5. The GPR with different radial basis function kernels revealed that a multiquadric kernel provides a lowest RMSE of 3.28[Formula: see text]mg/dL and lowest MAPE of 2.2, thus outperforming the parametric BR approach. Investigations also show that for a training data of less than 15 entries, BR renders better accuracy than the GPR approach.

BLOOD GLUCOSE LEVEL NEURAL MODEL FOR TYPE 1 DIABETES MELLITUS PATIENTS

2011 ◽  
Vol 21 (06) ◽  
pp. 491-504 ◽  
Author(s):  
ALMA Y. ALANIS ◽  
BLANCA S. LEON ◽  
EDGAR N. SANCHEZ ◽  
EDUARDO RUIZ-VELAZQUEZ
Keyword(s):  
Diabetes Mellitus ◽  
Type 1 Diabetes ◽  
Blood Glucose ◽  
Blood Glucose Level ◽  
Type 1 Diabetes Mellitus ◽  
Glucose Level ◽  
Glucose Monitoring ◽  
Nonlinear Behavior ◽  
Neural Model

This paper deals with the blood glucose level modeling for Type 1 Diabetes Mellitus (T1DM) patients. The model is developed using a recurrent neural network trained with an extended Kalman filter based algorithm in order to develop an affine model, which captures the nonlinear behavior of the blood glucose metabolism. The goal is to derive a dynamical mathematical model for the T1DM as the response of a patient to meal and subcutaneous insulin infusion. Experimental data given by continuous glucose monitoring system is utilized for identification and for testing the applicability of the proposed scheme to T1DM subjects.

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