ABSTRACT
During cross-regional epidemic outbreaks, patients with suspected infection have a high demand for testing resources, while patients with confirmed infection have a high demand for treatment resources. The allocation of testing resources affects the demand for treatment resources in multiple regions and at different periods, which features a time-lag correlation. In this study, we developed a joint allocation model for allocating testing and treatment resources with consideration of their time-lag correlation to minimize the loss of patients and maximum the fairness of allocation in all regions. We devised a sequential solution generation strategy (SSGS) and combined it with the NSGA2 and MOPSO algorithms to solve the proposed joint allocation problem. We demonstrated numerically that NSGA2 coupled with SSGS yields a better solution. Furthermore, we compared the solutions of our joint allocation model with those of an independent allocation model. Our numerical results show that the joint allocation scheme, which considers the time-lag correlation between the two types of resources, has better performance—with a lower loss of patients and higher fairness of allocation. In particular, when the impact of the allocation of testing resources on the demand for treatment resources was increased, the joint allocation scheme performed better in terms of both the objectives.
ABSTRACT
Aim: COVID-19 is a major threat to public health worldwide. A large proportion of COVID-19 patients is proved to develop anemia. Herein, we investigate the association between anemia and severe pneumonia. Materials & methods: 137 of COVID-19-confirmed patients admitted to Wuhan Union Hospital (Wuhan, China) from 13 February to 17 March 2020 were included. Their clinical characteristics and laboratory data were studied, and multivariable logistic regression analyses were performed. Results: The anemic patients were less likely to develop fever in the early stage of COVID-19. Elevated IL-6 levels were found in anemic COVID-19 patients compared with those without anemia. COVID-19 patients with anemia had an 8.2 times greater possibility of developing severe pneumonia compared with their counterparts without anemia. Conclusion: This study comprehensively describes the clinical characteristics of anemic patients with ordinary, severe and critical COVID-19 and demonstrates the close relationship between the anemia and severe COVID-19.
ABSTRACT
PURPOSE: To determine effect of body mass index (BMI) on safety and cancer-related outcomes of thermal ablation for renal cell carcinoma (RRC). MATERIALS AND METHODS: This retrospective study evaluated 427 patients (287 men and 140 women; mean [SD] age, 72 [12] y) who were treated with thermal ablation for RCC between October 2006 and December 2017. Patients were stratified by BMI into 3 categories: normal weight (18.5-24.9 kg/m2), overweight (25-29.9 kg/m2), and obese (≥ 30 kg/m2). Of 427 patients, 71 (16%) were normal weight, 157 (37%) were overweight, and 199 (47%) were obese. Complication rates, local recurrence, and residual disease were compared in the 3 cohorts. RESULTS: No differences in technical success between normal-weight, overweight, and obese patients were identified (P = .72). Primary technique efficacy rates for normal-weight, overweight, and obese patients were 91%, 94%, and 93% (P = .71). There was no significant difference in RCC specific-free survival, disease-free survival, and metastasis-free survival between obese, overweight, and normal-weight groups (P = .72, P = .43, P = .99). Complication rates between the 3 cohorts were similar (normal weight 4%, overweight 2%, obese 3%; P = .71). CONCLUSIONS: CT-guided renal ablation is safe, feasible, and effective regardless of BMI.