“Z” Chest Drainage and Modified Incision and Closure Techniques for Uniportal VATS

Abstract

BACKGROUND: To research the application of “Z” chest drainage and modified incision and closure techniques for uniportal VATS.METHODS: The 422 patients by uniportal VATS were divided into three groups:282 in experimental group(“Z” Chest drainage with two 16 F chest tube),male 156,female 126, medianage is 55 years old;100 in control group1(traditional Chest drainage with two 16 F chest tube) , male 58,female 42, medianage is 53 years old;;40 in control group2(traditional Chest drainage with two 34 F chest tube), male 24,female 16, medianage is 52 years old. The age,sex and surgical method of the three groups has no statistical significance. To compare the incidence rate of Incision exudating、Poor healing of incision and debridement between the 3 groups.RESULTS: Incidence rate of Incision exudating of experimental group, control group1 and control group2: 5（1.8%,5/282），5（5%,5.0/100） and 6（15.0%，6/40）; Poor healing of incision of the three groups: 0，1（1%,1/100） and 3（7.5%,3/40）; debridement of the three groups: 0，0 and 3（7.5%,3/40）. For the healing of incision, control group1was better than control group2;and experimental group was better than control group1.CONCLUSIONS: “Z” Chest drainage and Modified Incision and Closure Techniques decreased the incidence rate of Incision exudating、Poor healing of incision and debridement,which would be useful to obtain a better cosmetic effect after uniportal VATS .

Online insulator defects detection and application based on YOLOv7-tiny algorithm

“…The research is primarily categorized into classical feature extraction and artificial intelligence methods (Antwi-Bekoe et al, 2022;Pan et al, 2022). Classical feature extraction techniques include binarization, binary support vector machines (Zhou et al, 2020), edge detection algorithms based on Canny (Cao et al, 2020), and multiscale feature extraction (Zhang et al, 2020;Siu et al, 2022). After the feature extraction process, fault areas are identified using either a threshold method or classical machine learning approaches.…”