Objective:To explore the precise layered and tension-reducing sutures for skin pigmented mole surgery to promote tissue healing and reduce scar hyperplasia.Methods:From January 2019 to December 2021, the First Department of Surgery of the Civil Aviation General Hospital and Tenth Department of the Plastic Surgery Hospital of the Chinese Academy of Medical Sciences treated 56 patients with skin pigmented moles aged 18-52 years, with an average age of 26 years, including 30 males and 26 females. All patients in this group underwent surgical resection of skin pigmented moles, which reached the subcutaneous fat layer. The dermis and subcutaneous tissue under the skin incision were precisely buried and guided suture by using the middle common hole equal-chord and equal-arc buried guide suture with scale marks on both ends of the needle tip.Results:The incision width of skin tissue defect in this group of patients was less than 30 mm. After the suturing was completed, the tension between the tissues on both sides of the incision and the close-fitting of each layer of tissue on both sides of the incision without dead space were realized immediately. 55 cases achieved primary incision healing. After two years of follow-up observation, there was no scar hyperplasia, and the effect was satisfactory. In only one case, local incision was red and swollen due to suture reaction, and a small amount of scar hyperplasia appeared later.Conclusions:This submerged guided suture method is an effective surgical technique for reducing skin incision scars, and it is more suitable for small incisions with a skin incision length of less than 10 mm, which is difficult to achieve layered suture of the deep tissue of the incision with ordinary suture needles.

Objective To predict the burden caused by fatal road traffic injuries from 2015 to 2030. Methods We searched the websites of United Nations Population Division,United States Department of Agriculture,World Health Organization,China Energy Research Foundation and other agencies to obtain the predictive values of gross domestic product(GDP)per capita,urbanization, motorization and education from 2015 to 2030 in China. Predicted values were then applied to log-linear models to estimate the numbers and years of life lost due to road traffic injuries from 2015 to 2030. Results The mortality rate caused by road traffic injury decreased slightly,from 13.7/100 000 in 2015 to 11.8/100 000 in 2030. 191,189,183,169 thousand persons were estimated to die from road traffic crashes in 2015,2020,2025 and 2030,respectively,showing a declining trend. Years of Life Lost(YLLs)caused by road traffic deaths were predicted to be 6 918,6 634,6 189,5 513 thousand years in 2015,2020,2025 and 2030,respectively,also showing a gradual downward trend. But the YLLs displayed an increase among people at 55 years of age or older,between 2015 and 2030. Results from the sensitivity analysis showed a stable forecasting result. Conclusion Mortality, number of deaths and YLLs from road traffic crashes were predicted to decrease slightly,between 2015 and 2030 but the number of deaths and YLLs due to road traffic injuries will continue to increase from 2015 to 2030.

OBJECTIVETo develop the forecasting models for fatal road traffic injuries and to provide evidence for predicting the future trends on road traffic injuries.

METHODSData on the mortality of road traffic injury including factors as gender and age in different countries, were obtained from the World Health Organization Mortality Database. Other information on GDP per capita, urbanization, motorization and education were collected from online resources of World Bank, WHO, the United Nations Population Division and other agencies. We fitted logarithmic models of road traffic injury mortality by gender and age group, including predictors of GDP per capita, urbanization, motorization and education. Sex- and age-specific forecasting models developed by WHO that including GDP per capita, education and time etc. were also fitted. Coefficient of determination(R(2)) was used to compare the performance between our modes and WHO models.

RESULTS2 626 sets of data were collected from 153 countries/regions for both genders, between 1965 and 2010. The forecasting models of road traffic injury mortality based on GDP per capita, motorization, urbanization and education appeared to be statistically significant(P < 0.001), and the coefficients of determination for males at the age groups of 0-4, 5-14, 15-24, 25-34, 35-44, 45-54, 55-64, 65+ were 22.7% , 31.1%, 51.8%, 52.3%, 44.9%, 41.8%, 40.1%, 25.5%, respectively while the coefficients for these age groups in women were 22.9%, 32.6%, 51.1%, 49.3%, 41.3%, 35.9%, 30.7%, 20.1%, respectively. The WHO models that were based on the GDP per capita, education and time variables were statistically significant (P < 0.001)and the coefficients of determination were 14.9% , 22.0%, 31.5%, 33.1% , 30.7%, 28.5%, 27.7% and 17.8% for males, but 14.1%, 20.6%, 30.4%, 31.8%, 26.7%, 24.3%, 17.3% and 8.8% for females, respectively.

CONCLUSIONThe forecasting models that we developed seemed to be better than those developed by WHO.

Accidents, Traffic ; mortality ; prevention & control ; trends ; Adolescent ; Adult ; Aged ; Child ; Child, Preschool ; Female ; Forecasting ; Humans ; Infant ; Infant, Newborn ; Male ; Middle Aged ; Models, Statistical

OBJECTIVETo predict the burden caused by fatal road traffic injuries from 2015 to 2030.

METHODSWe searched the websites of United Nations Population Division,United States Department of Agriculture, World Health Organization, China Energy Research Foundation and other agencies to obtain the predictive values of gross domestic product (GDP) per capita, urbanization, motorization and education from 2015 to 2030 in China. Predicted values were then applied to log-linear models to estimate the numbers and years of life lost due to road traffic injuries from 2015 to 2030.

RESULTSThe mortality rate caused by road traffic injury decreased slightly, from 13.7/100 000 in 2015 to 11.8/100 000 in 2030. 191, 189, 183, 169 thousand persons were estimated to die from road traffic crashes in 2015, 2020, 2025 and 2030, respectively, showing a declining trend. Years of Life Lost (YLLs) caused by road traffic deaths were predicted to be 6 918, 6 634, 6 189, 5 513 thousand years in 2015, 2020, 2025 and 2030, respectively, also showing a gradual downward trend. But the YLLs displayed an increase among people at 55 years of age or older, between 2015 and 2030. Results from the sensitivity analysis showed a stable forecasting result.

CONCLUSIONMortality, number of deaths and YLLs from road traffic crashes were predicted to decrease slightly, between 2015 and 2030 but the number of deaths and YLLs due to road traffic injuries will continue to increase from 2015 to 2030.

Accidents, Traffic ; mortality ; Adolescent ; Adult ; Aged ; Child ; Child, Preschool ; China ; epidemiology ; Cost of Illness ; Female ; Humans ; Infant ; Infant, Newborn ; Male ; Middle Aged ; Young Adult