1.Development of Micro-invasive Blood Glucose Detector Based on SPR
Qiubo HAN ; Lixin ZHANG ; Yuzhen CAO ; Kexin XU
Chinese Medical Equipment Journal 2004;0(08):-
Objective To develop a new portable micro-invasive blood glucose detector.Methods With a high-performance MCU C8051F060 as the core,the system is composed of SPR biosensor,step-motor,vacuum pump and a lattice-style liquid crystal module.With multi-task RTOS,RTX51-TINY,the system realizes blood measurement.Results Microinvasive and real-time acquisition and detection for the body's blood glucose can be fulfilled.Conclusion This detector has the characteristics of small size,high-speed and accurate detection,so it has a nice application foreground.
2.Multifactorial analysis and risk prediction model of poor abdominal incision healing in elderly women
Han ZHANG ; Bo ZHANG ; Shuo ZHANG ; Jinbowen YAN ; Qingwei MENG ; Qiubo LYU ; Xunyuan TUO ; Dan ZHOU
Chinese Journal of Geriatrics 2024;43(11):1438-1444
Objective:To investigate the factors influencing the occurrence of poor surgical incision healing after gynecologic open surgery in elderly patients, and to construct a risk prediction model.Methods:A retrospective cohort study was conducted to collect perioperative data from 255 elderly patients(age ≥60 years at the time of surgery)who underwent gynecologic open abdominal surgery in Beijing Hospital from September 2021 to September 2023, and the patients were divided into 204 cases of the well-healed group and 51 cases of the poorly healed group according to the healing of their abdominal incision conditions, and all the included samples were randomly split into the training set of 179 cases and the validation set of 76 cases according to a ratio of 7∶3.Risk factors for poor incision healing were screened using univariate analysis and multifactorial Logistic regression analysis, and a column-line diagram model was constructed.The predictive value of the model was examined using the receiver operating characteristic(ROC)curve, the internal validation of the model was performed using the Bootstrap method, the clinical application value of the model was evaluated by plotting the calibration curve, and the predictive performance of the model was compared by calculating the net reclassification index(NRI)and the integrated discriminant improvement index(IDI).Results:The results of univariate analysis showed that age, body mass index(BMI), preoperative abdominal wall thickness, intraoperative bleeding, preoperative albumin, postoperative minimum albumin, ascites, nature of the disease, and perioperative albumin supplementation were correlated with abdominal incision healing(all P<0.05).Multifactorial Logistic regression analysis showed that perioperative albumin supplementation( OR=0.07, 95% CI: 0.01-0.44, P=0.008), age( OR=1.28, 95% CI: 1.12-1.52, P<0.001), preoperative abdominal wall thickness( OR=5.75, 95% CI: 2.81-15.74, P<0.001), and postoperative minimum albumin( OR=0.82, 95% CI: 0.69-0.97, P=0.017)were the influencing factors of abdominal incision healing.Plotting the ROC curves of the column-line graphical model showed that the area under the curve(AUC)for the training set and the internal validation set were 0.982(95% CI: 0.967-0.997)and 0.961(95% CI: 0.906-1.000), respectively.The model was validated using the Bootstrap self-sampling method, and the calibration curve showed that the model predicted well with good calibration, and NRI and IDI indicated that the predictive value of the four combined was higher than that of a single index for poor incision healing. Conclusions:The prediction model established in this study(including 4 indicators of age, preoperative abdominal wall thickness, perioperative albumin supplementation, and postoperative minimum albumin)has been statistically tested and internally validated to predict the risk of poorly healed abdominal incisions in elderly women in the perioperative period, facilitating timely clinical adjustment of treatment for high-risk patients.