ObjectiveTo investigate the incidence and trends of cervical (C53), endometrial (C54.1), and ovarian cancer (C56) among Korean females between 1999 and 2015.MethodsThe incidence of the three major gynecological cancers between 1999 and 2015 was analyzed based on the data from the Korea Central Cancer Registry. The age-standardized rates (ASRs) and the annual percent changes (APCs) for each site were calculated.ResultsThe absolute incidence rates of the three major gynecological cancers increased from 6,394 in 1999 to 8,288 in 2015. ASR for gynecologic cancer decreased from 23.7 per 100,000 in 1999 to 21.1 in 2015. This was mainly due to a definitive decrease in the incidence of cervical cancer, which recorded an APC of −3.7%. The trends of APC for gynecologic cancer were variable, being −1.36% between 1999 and 2006 and −0.11% between 2006 and 2015. A definitive but variable increase was noted for endometrial cancer, and the APC for this cancer was 7.4% between 1999 and 2009 and 3.5% between 2009 and 2015. The incidence of ovarian cancer gradually increased, with an APC of 1.8% between 1999 and 2015.ConclusionOverall, ASRs and APCs for the three major gynecological cancers are decreasing, with a recent reduction in the width of the change. However, there has been a progressive increase in the incidence of endometrial and ovarian cancers.

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The aim of this paper is to introduce basic concepts and methods for calculating sample size in animal studies. At the planning stage of clinical studies, the determination of the sample size is a very important process to show the validity, accuracy, and reliability of the study. However, not all studies require a sample size to be calculated. Before conducting the study, it is essential to determine whether the study objectives suggest a pilot and exploratory study, as well as the purpose of testing the hypothesis of interest. Since most animal experiments are pilot and exploratory studies, it would be more appropriate to review other considerations for conducting an experiment while maintaining scientific and qualitative levels rather than sample size estimation. Sample size is calculated in various situations in animal studies. Therefore, it can be estimated according to the situations and objectives through the methods of precision analysis, power analysis, and so on. In some cases, nonparametric methods can be employed if the assumptions of normality is not met or a small sample is available for the study.

Background Physical activity (PA) is an important risk factor associated with health outcomes. However, the relationship between PA and kidney function decline in older adults remains unclear. We examined the influence of PA on kidney function decline and mortality in community-dwelling older adults. Methods Adults aged ≥ 65 years with an estimated glomerular filtration rate (eGFR) > 60 mL/min/1.73 m2 who had available health checkup data from 2009 to 2010 were included. The cohort was followed annually through December 2015 for anthropometric, sociodemographic, and medical information including outcomes and biennially for laboratory information from the health checkup. We divided these patients into three groups according to self-reported PA (Inactive group: no leisure-time PA, Active group: vigorous activity for at least 80 min/week or a sum of moderate-intensity activity and walking for at least 300 min/week, Low-active group: level of PA between the definitions of the other two groups). Associations between the intensity of PA and death, cardiovascular death, and ≥ 50% eGFR decline were investigated. Results Among 102,353 subjects, 32,984 (32.23%), 54,267 (53.02%), and 15,102 (14.75%) were classified into the inactive, low-active, and active groups, respectively. The active group was younger, contained a higher proportion of men, and had higher frequencies of hypertension, diabetes mellitus, drinking, and smoking than the other groups. The active group had significantly lower incidence rates of mortality, cardiovascular mortality, and kidney function decline than the other groups (all p < 0.001). The active group also showed lower all-cause (hazard ratio [HR], 0.76; 95% confidence interval [CI], 0.70–0.82) and cardiovascular mortality (HR, 0.64; 95% CI, 0.53–0.78) and protection against ≥ 50% eGFR decline (HR, 0.81; 95% CI, 0.68–0.97) compared with the inactive group in the fully adjusted Cox proportional hazards regression model. Conclusions High PA was an independent modifiable lifestyle factor for reducing mortality and protecting against declines in kidney function in older adults.

Electromechanical-assisted gait training may be an effective intervention to promote motor recovery after brain injury. However, many studies still have difficulties in clarifying the difference between electromechanical-assisted gait training and conventional gait training. To evaluate the effectiveness of electromechanical-assisted gait training compared to that of conventional gait training on clinical walking function and gait symmetry of stroke patients. We randomly assigned patients with stroke (n = 144) to a control group (physical therapist-assisted gait training) and an experimental group (electromechanical gait training). Both types of gait training were done for 30 min each day, 5 days a week for 4 weeks. The primary endpoint was the change in functional ambulatory category (FAC). Secondary endpoints were clinical walking functions and gait symmetries of swing time and step length. All outcomes were measured at baseline (pre-intervention) and at 4 weeks after the baseline (post-intervention). FAC showed significant improvement after the intervention, as did clinical walking functions, in both groups. The step-length asymmetry improved in the control group, but that in the experimental group and the swing-time asymmetry in both groups did not show significant improvement. In the subgroup analysis of stroke duration of 90 days, FAC and clinical walking functions showed more significant improvement in the subacute group than in the chronic group. However, gait symmetries did not show any significant changes in either the subacute or the chronic group. Electromechanically assisted gait training by EXOWALK was as effective as conventional gait training with a physiotherapist. Although clinical walking function in the subacute group improved more than in the chronic group, gait asymmetry did not improve for either group after gait training.Trial registration: KCT0003411 Clinical Research Information Service (CRIS), Republic of Korea.