Existing near-infrared non-invasive blood glucose detection modelings mostly detect multi-spectral signals with different wavelength, which is not conducive to the popularization of non-invasive glucose meter at home and does not consider the physiological glucose dynamics of individuals. In order to solve these problems, this study presented a non-invasive blood glucose detection model combining particle swarm optimization (PSO) and artificial neural network (ANN) by using the 1 550 nm near-infrared absorbance as the independent variable and the concentration of blood glucose as the dependent variable, named as PSO-2ANN. The PSO-2ANN model was based on two sub-modules of neural networks with certain structures and arguments, and was built up after optimizing the weight coefficients of the two networks by particle swarm optimization. The results of 10 volunteers were predicted by PSO-2ANN. It was indicated that the relative error of 9 volunteers was less than 20%; 98.28% of the predictions of blood glucose by PSO-2ANN were distributed in the regions A and B of Clarke error grid, which confirmed that PSO-2ANN could offer higher prediction accuracy and better robustness by comparison with ANN. Additionally, even the physiological glucose dynamics of individuals may be different due to the influence of environment, temper, mental state and so on, PSO-2ANN can correct this difference only by adjusting one argument. The PSO-2ANN model provided us a new prospect to overcome individual differences in blood glucose prediction.
ObjectiveTo explore the relationship between blood glucose variability index and persistent organ failure (POF) in acute pancreatitis (AP). MethodsWe prospectively included those patients who were diagnosed with AP with hyperglycemia and were hospitalized in the West China Center of Excellence for Pancreatitis of West China Hospital of Sichuan University from July 2019 to November 2021. The patients were given blood glucose monitoring at least 4 times a day for at least 3 consecutive days. The predictive value of blood glucose variability index for POF in patients with AP was analyzed. ResultsA total of 559 patients with AP were included, including 95 cases of POF. Comparing with those without POF, patients with AP complicated by POF had higher levels of admission glucose (11.0 mmol/L vs. 9.6 mmol/L), minimum blood glucose (6.8 mmol/L vs. 5.8 mmol/L), mean blood glucose (9.6 mmol/L vs. 8.7 mmol/L), and lower level of coefficient of variation of blood glucose (16.6 % vs. 19.0 %), P<0.05. Logistic regression analyses after adjustment for confounding factors showed that the risk of POF increased with the increase of admission glucose [OR=1.11, 95%CI (1.04, 1.19), P=0.002], minimum blood glucose [OR=1.28, 95%CI (1.10, 1.48), P=0.001] and mean blood glucose [OR=1.18, 95%CI (1.04, 1.33), P=0.010]; with the higher level of coefficient of variation of blood glucose [OR=0.95, 95%CI (0.92, 0.99), P=0.021], the risk of POF decreased. The results of area under the curve (AUC) of the receiver operator curves showed that AG [AUC=0.787, 95%CI (0.735, 0.840)] had the highest accuracy in predicting POF, with sensitivities of 60.0% and specificities of 84.7%. ConclusionHigh admission glucose, minimum blood glucose, mean blood glucose, and low coefficient of variation of blood glucose were risk factors for the development of POF in patients with hyperglycemic AP on admission.
Objective To evaluate the accuracy of newer-generation home blood glucose meter (Accu-Check? Integra) in patients with impaired glucose regulation (IGR) and newly-diagnosed type 2 diabetes mellitus. Methods A cross-sectional study was performed on 109 cases with newly-diagnosed type 2 diabetes or IGR who were asked to take oral glucose tolerance test (OGTT), while paired samples, that were Accu-Check? Integra in capillary blood glucose (CBG) and laboratory glucose in venous plasma glucose (VPG ), were taken simultaneously. Taking VPG as the reference value, the accuracy of the home glucose meter was assessed according to the international standardization organization (ISO), including, the accuracy was studied by means of Median absolute difference (Median AD) and Median absolute relative difference (Median RAD), the consistency of CBG and VPG was studied by Clarke Error Grid analysis, the correlation of CBG and VPG was analyzed according to liner regression analysis, and the sensitivity and specificity for hyperglycemia were also calculated. Results There were 292 VPG values paired with CBG values, among which 93.49% of CBG values met ISO home glucose meter criteria, the median AD was 7.2 mg/dL, and the median RAD was 4.76%. Paired glucose measurements from the Accu-Check Integra meter and laboratory glucose measurement demonstrated that 100% of paired points in the overall subject population fell in zones A and B of the Clarke Error Grid. The CBG value was well correlated to VPG value in the overall level, and the sensitivity and specificity were 94.6% and 95.7% respectively for hyperglycemia. Conclusion The newer-generation home blood glucose meter (Accu-Check? Integra) demonstrates a high degree of accuracy, and it can precisely report the real value of blood glucose.
Objective To investigate the correlation between stress hyperglycemia ratio (SHR) and acute ischemic stroke (AIS) 1-year prognosis, to provide more clinical basis to improve the prognosis of AIS patients and to target and control the influencing factors. MethodsThe patients with AIS diagnosed for the first time and received treatment at the Shijiazhuang Fifth Hospital between May 2019 and January 2022 were retrospectively and continuously included. According to the Modified Rankin Scale score 1-year after the onset of the disease, the patients were divided into a good prognosis group and a poor prognosis group. Also the patients were divided into 2 groups based on the median of SHR. The correlation between SHR and stress blood glucose was analyzed, and the factors affecting the prognosis of AIS patients were identified. The predictive value of SHR and stress blood glucose on the prognosis of AIS patients was compared using receiver operating characteristic. Results A total of 206 patients were included. Among them, there were 125 cases (60.7%) in the good prognosis group and 81 cases (39.3%) in the poor prognosis group. The median SHR (lower quartile, upper quartile) is 1.20 (1.08, 1.33). There were statistically significant differences between the two groups in the scores of the National Institutes of Health Stroke Scale, diabetes history, hypertension history, low-density lipoprotein cholesterol, stress blood glucose, age, SHR and SHR classification (P<0.05). There was no statistically significant difference in the other indicators compared between the two groups (P＞0.05). Stress blood glucose was positively correlated with SHR (7.95±1.78 vs. 1.21±0.19; r=0.294, P<0.001). Multivariate logistic analysis showed that stress blood glucose and SHR were independent factors influencing the 1-year prognosis of AIS patients (P<0.05), and the interaction between SHR and diabetes was not significant (P>0.05) After adjusting for confounding factors, the area under the receiver operating characteristic curve of SHR for the prognosis of AIS patients was higher than that of stress blood glucose [0.682 (0.614, 0.745) vs .0.585 (0.515, 0.653); Z=2.042, P=0.041]. Conclusions SHR and stress blood glucose are independent risk factors for 1-year prognosis in AIS patients. However, SHR has a better predictive value for 1-year prognosis in AIS patients than stress blood glucose. Whether the patient has diabetes or not, the impact of SHR on the prognosis of AIS patients is consistent.
Most of the existing near-infrared noninvasive blood glucose detection models focus on the relationship between near-infrared absorbance and blood glucose concentration, but do not consider the impact of human physiological state on blood glucose concentration. In order to improve the performance of prediction model, particle swarm optimization (PSO) algorithm was used to train the structure paramters of back propagation (BP) neural network. Moreover, systolic blood pressure, pulse rate, body temperature and 1 550 nm absorbance were introduced as input variables of blood glucose concentration prediction model, and BP neural network was used as prediction model. In order to solve the problem that traditional BP neural network is easy to fall into local optimization, a hybrid model based on PSO-BP was introduced in this paper. The results showed that the prediction effect of PSO-BP model was better than that of traditional BP neural network. The prediction root mean square error and correlation coefficient of ten-fold cross-validation were 0.95 mmol/L and 0.74, respectively. The Clarke error grid analysis results showed that the proportion of model prediction results falling into region A was 84.39%, and the proportion falling into region B was 15.61%, which met the clinical requirements. The model can quickly measure the blood glucose concentration of the subject, and has relatively high accuracy.
摘要:目的:探討經尿道前列腺電切術中糖尿病患者血糖變化以及處理對策。方法:2006年7月~ 2009年1月共對80例患有前列腺增生合并糖尿病患者行TURP,同期對80例單純性前列腺增生患者進行相同手術,回顧分析其術前、術中30 min、60 min、90 min 指尖血糖變化及干預情況。結果:治療組80例患者,51例術中血糖值明顯低于術前,分別為1.8～3 mmol/L;對照組術前與術中血糖值基本一致,血糖波動于4.5～5.6 mmol/L。結論:糖尿病患者糖的儲備能力差,在行經尿道電切術中易發生低血糖綜合征,術中及時的血糖監測及干預對保證患者的安全有重要意義。Abstract: Objective: To study the changes and measures against the glucose in the operation of the Diabetes by TURP. Methods:Eighty patients with prostate combining diabetes operated from July 2006 to Jan. 2009 were reviewed, and 80 prostate treated at the same period with the same operation measure were selected as control. The preoperative glucose, intraoperative glucose (30′, 60′,90′) of fingertip, and countermeasures were studied and compared between the two groups. Results:Fiftyone cases of the experimental group of intraoperative blood glucose was significantly lower than preoperative values, respectively 1.83 mmol/ L; control group preoperative and intraoperative blood glucose values were basically the same, blood glucose fluctuations in the 4.55.6 mmol/L. Conclusion: The capacity in patients with diabetes is poor, easy to hypoglycemia syndrome in the act of TURP surgery, intraoperative blood glucose monitoring and timely intervention to ensure patient safety significance.
The use of non-invasive blood glucose detection techniques can help diabetic patients to alleviate the pain of intrusive detection, reduce the cost of detection, and achieve real-time monitoring and effective control of blood glucose. Given the existing limitations of the minimally invasive or invasive blood glucose detection methods, such as low detection accuracy, high cost and complex operation, and the laser source's wavelength and cost, this paper, based on the non-invasive blood glucose detector developed by the research group, designs a non-invasive blood glucose detection method. It is founded on dual-wavelength near-infrared light diffuse reflection by using the 1 550 nm near-infrared light as measuring light to collect blood glucose information and the 1 310 nm near-infrared light as reference light to remove the effects of water molecules in the blood. Fourteen volunteers were recruited for in vivo experiments using the instrument to verify the effectiveness of the method. The results indicated that 90.27% of the measured values of non-invasive blood glucose were distributed in the region A of Clarke error grid and 9.73% in the region B of Clarke error grid, all meeting clinical requirements. It is also confirmed that the proposed non-invasive blood glucose detection method realizes relatively ideal measurement accuracy and stability.
ObjectiveTo investigate the change of blood glucose and its clinical significance in patients with acute pancreatitis (AP). MethodsThe regularity of blood glucose change and the relation between the regularity and the prognosis were analyzed in 115 patients with AP and hyperglycemia.ResultsBlood glucose was increased with a median (M) of 8.7 mmol/L，18.45 mmol/L and 27.22 mmol/L, which gradually decreased to normal value within 3-17 days, 7-26 days and 24-46 days after treatment,respectively in patients with mild AP, type Ⅰ of severe acute pancreatitis (SAP) and type Ⅱ of SAP. There was marked statistical difference among the three groups. A smaller dose of regular insulin was used for 36 patients with mild AP; however, a larger dose of regular insulin was used for all 30 patients with SAP.ConclusionThe level of blood glucose, the dose of regular insulin and the duration of hyperglycemia increase with the severity of AP.
摘要:目的:研究高血壓病患者過氧化物酶體增殖物激活受體(PPAR)γ2基因Pro12Ala多態性與血糖水平之間的關系。方法:納入177名原發性高血壓患者,其中空腹血糖(FBG)lt;5.6 mmol/L組65例, FBG≥5.6 mmol/L組112例,收集一般資料;分別測定空腹及餐后2小時血糖、胰島素;對PPARγ2 基因Pro12Ala多態性與各臨床變量的關系進行研究。結果:FBGlt;5.6 mmol/L組和FBG≥5.6 mmol/L組Pro和Ala等位基因頻率分別為0.333,0.034及0.602,0.031;PP和PA基因型頻率分別為0.299,0.068及0.571,0.062;無AA型純合子。以體重指數(BMI)分層后,BMIlt;25組內,FBG與PPARγ2基因型相關（P=0.029)。以基因型分組比較,PA組空腹血糖水平和胰島素抵抗指數都低于PP組(Plt;0.05)。結論:成都地區高血壓患者PPARγ2基因Pro12Ala多態性與空腹血糖水平相關,且攜帶Ala基因者空腹血糖水平較低,胰島素抵抗較輕,推測該突變可能有減輕高血壓病患者胰島素抵抗,改善糖代謝異常的作用。Abstract: Objective:To study the association between the Pro12Ala polymorphism in peroxisome proliferatorsactivated receptorγ2 ( PPARγ2 ) gene and blood glucose levels in patients with primary hypertension. Methods：The Pro12Ala polymorphism in PPARγ2 was determined by polymerase chain reactionrestriction fragment length polymorphism (PCRRELP) in 177 subjects with primary hypertension of the Han people in Chengdu of China, including 65 subjects with fasting blood glucose (FBG)lt;5.6 mmol/L and 112 subjects with FBG≥5.6 mmol/L; the clinical characteristics including height, weight, OGTT(0h and 2h) of the subjects were detected and the realationship between the Pro12Ala polymorphism and the clinical characteristics were analysed. Results: The allele frequencies in the group with FBGlt;5.6 mmol/L and FBG≥5.6 mmol/L were 0.333, 0.602 for Pro and 0.034, 0.031 for Ala. The genotype frequencies were 0.299, 0.571 for PP and 0.068, 0.062 for PA, and there was no AA. In the group with BMIlt;25, the Pro12Ala polymorphism was associated with FBG （P=0.029). the Ala allele had a negative relationship to the FPG and insulin resistance index (IRI) (Plt;0.05).Conclusion: The data showed that the Pro12Ala polymorphism was associated with FBG., and The allele Ala probably had benefits to glycometabolic disturbance in patients with primary hypertension by declining insulin resistance.
For the near-infrared (NIR) spectral analysis of the concentration of blood glucose, the calibration accuracy can be affected because of the existing of outlier samples. In this research, a Monte-Carlo cross validation (MCCV) method is constructed for eliminating outlier samples. The human blood plasma experiment in vitro and the human body experiment in vivo were introduced to evaluate the MCCV method for its application effect in NIR spectral analysis of blood glucose. And the uninformative sample elimination method based on modified uninformative variable elimination (MUVE-USE) was employed in this study for the comparison with MCCV. The results indicated that, like the MUVE-USE method, the outlier samples elimination method based on MCCV could be used to eliminate the outlier samples which came from gross errors (such as bad sample) or system errors (such as baseline drift). In addition, the outlier samples from the random errors of uncertain causes which affect model accuracy can be eliminated simultaneously by MCCV. The elimination of multiple outlier samples is beneficial to the improvement of prediction accuracy of calibration model.