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Health-related issues and occurrences with regard to a particular population are the subject of an epidemiology study. This paper presents the results of a retrospective epidemiological investigation on 15922 hospitalized hand trauma patients from Central China between 2011 and 2020. Gender, age, onset season, injury mechanism, injury environment, injury location, and clinical characteristics are among the characteristics of the data gathered. The study is using computational analysis to draw inferences from the case studies collected in the databases of the hospitals. The types and characteristics of occupational injuries at home and outdoor are compared and analyzed. The purpose of the study is to present the findings from recent case studies for future reference and to recommend useful roles for the industrial sector in the care of patients with hand trauma in order to lower occupational harm. The injuries of preschool children are also analyzed. The incidence rate of hand injuries in infants has been increasing year by year which is directly related to the inefficient growth of children in rural areas. The data are collected from hospitals, then the data analytical tools are applied to draw conclusions. The suggested model is intelligently learned through the application of computational techniques, which are also used to suggest treatments to trauma victims. According to this study, males are more likely than females to sustain hand trauma; occupational injuries are more common than living injuries; males between the ages of 20 and 50 are at an increased risk of suffering an occupational injury. This study showed that the proportion of hand trauma in preschool children was higher (12.27%), and the 2-3-year-old group was the main injury target of preschool children (45.70%). The accidental injuries of newborns and young children can be reduced by government assistance, social support, and tighter monitoring.

BackgroundExcessive BMI was associated with lower mortality after stroke. However, some believed that excessive BMI can lead to a poor prognosis because of some physiological mechanism, such as glucose metabolism disorder. Therefore, this study aims to discuss the association between mortality, BMI, and blood glucose.Materials and methodsThis was a retrospective observational study and all data were extracted from the Medical Information Mart for Intensive Care III database. The exposure was BMI classified into the normal weight group and the excessive weight group. The outcome concluded 30-day, 90-day, and 1-year mortality. The association between two groups and mortality was elucidated by Cox regression models, propensity score matching (PSM) and inverse probability of treatment weighting (IPTW). The underlying effect of blood glucose on the “obesity paradox” was analyzed by causal mediation analysis.ResultsAccording to Cox regression models, a significant beneficial effect of excessive BMI in terms of mortality was observed: 30-day mortality (HR 0.57, 95% CI 0.35–0.90, P = 0.017), 90-day mortality (HR 0.53, 95% CI 0.36–0.78, P = 0.001), and 1-year mortality (HR 0.65, 95% CI 0.46–0.91, P = 0.013). After PSM and IPTW, we got a similar conclusion. The causal mediation analysis showed that the protective effect of excessive BMI on 30-day mortality reduced with the increase of blood glucose.ConclusionFor ischemic stroke patients in the Intensive Care Unit, those with excessive BMI are associated with both lower short-term mortality and lower long-term mortality, while the protective effect on 30-day mortality weakened accompanied by the increase of blood glucose.

Background: On the one hand, according to the obesity paradox, patients with excessive BMI will have lower mortality after onset. On the other hand, due to higher levels of glucose induced by excessive BMI, they will suffer a worse prognosis. This is contradictory. In the present study, we aim to prove the obesity paradox in critically ill stroke patients and find out the potential role of increased glucose.Methods: This was a retrospective observational study about patients with acute stroke in the intensive care unit (ICU) and all data were extracted from the Medical Information Mart for Intensive Care III (MIMIC-III) database. The main exposure was BMI classified into normal group (18.5≤ BMI＜25), excessive group (BMI≥ 25). The outcome concluded 30-day, 90-day and 1-year mortality. The association between two BMI groups and mortality was elucidated by Cox regression models, propensity score matching (PSM) and inverse probability of treatment weighting (IPTW). The underlying effect of blood glucose on the “obesity paradox” was analyzed by causal mediation analysis. Results: A total of 522 patients were included in our study, of which 177 were the normal group and 345 were the excessive group. According to Cox regression models, a significant beneficial effect of excessive BMI in terms of mortality was observed: 30-day mortality (HR 0.57, 95%CI 0.35-0.90, p = 0.017), 90-day mortality (HR 0.53, 95%CI 0.36-0.78, p = 0.001) and 1-year mortality (HR 0.65, 95%CI 0.46-0.91, p = 0.013). The conclusions were stable after propensity score matching and inverse probability of treatment weighting. There were no interactions between BMI, gender, age, and diabetes. The causal mediation analysis showed that the increased glucose level would reduce the protective effect of excessive BMI on 30-day mortality.Conclusions: In severe stroke patients, those with excessive BMI are linked to lower mortality, while the protective effect on 30-day mortality weakened accompanied by the acute increase of glucose level.