Leg Swelling during Continuous Standing and Sitting Work without Restricting Leg Movement: Akihiko Seo, et al. Department of Public Health, Hiroshima University School of Medicine—To clarify the dynamics of leg swelling during standing and sitting work without restricting leg movement, lower leg swelling and subjective complaints were measured during work under three working conditions: Straight standing, buttock chair sitting and ordinary chair sitting. Twelve subjects (eight males and four females) were assigned jigsaw puzzles as a task for an hour. The lower leg swelling and subjective complaints were recorded every two minutes. The lower leg swelling was measured by the bioelectrical impedance method. The results were as follows: (1) The lower leg swelling increased during the work under all working conditions. The swelling was least for straight standing and greatest for ordinary chair sitting. The mean and standard deviations for leg swelling after one hour's work were 5.8±3.9% for straight standing, 8.2±4.7% for buttock chair sitting and 9.7 + 7.5% for ordinary chair sitting. (2) The subjective complaints also increased during work. Complaining of lower leg dullness was least for ordinary chair sitting and greatest for straight standing. The relation to the leg swelling was reversed. Complaining of low back pain was more common for buttock chair sitting than for other working postures. It is reasonable that prolonged standing is more likely to cause leg swelling than sitting because of high hydrostatic pressure. This theory has been supported by studies on motionless standing and sitting. Our results obtained without restricting leg movement, however, showed a reversed relation. It was considered that leg swelling factors such as low muscle activity and lymph pumps, low interstitial pressure brought on by low muscle activity, and the seat pressure during prolonged sitting may be dominant in the sitting posture although the hydrostatic pressure was low compared with the standing posture.
Introduction: Late-onset lower limb lymphedema (LLL) is a significant clinical challenge for physicians dealing with patients that undergo treatment involving the pelvic cavity. We aimed to clarify the prevalence of and risk factors for late-onset LLL after treatment for gynecological cancer. Methods: We conducted a multicenter retrospective study using records of cases in which LLL diagnosed by physical findings and measurement of limbs girths. Patients with LLL after treatment for uterine cervical, endometrial, and ovarian cancer were sequentially enrolled. We examined the timing of LLL onset and the associations between the time to onset and clinical characteristics, including age, type of cancer, lymphadenectomy sites, and performance of radiotherapy. We also investigated the risk factors for late-onset LLL and their effects on the cumulative incidence of late-onset LLL. Results: In total, 711 patients fulfilled the required criteria. Mean age of was 50.2 years old and median follow-up period was 5.05 years. More than half of them (50.5%) presented with LLL 5 years after undergoing treatment for gynecological cancer. A substantial number of patients (29.4%) developed LLL 10 years after undergoing treatment for gynecological cancer. Being aged <50 years [(odds ratio (OR): 1.919, P ¼ 0.001), cervical cancer (OR: 1.912, P ¼ 0.001), and radiotherapy (OR: 1.664, P ¼ 0.017) were identified as significant risk factors for late-onset LLL in multivariate logistic regression analysis. Conclusions: A substantial number of patients present with LLL 5 years after receiving treatment for gynecological malignancies. Clinicians are required to identify high-risk patients and inform them of the risk of late-onset LLL.
We proposed a prediction methodology for the incidence of infectious diseases using incidence data on measles and influenza for forty years in Japan. We also proposed a diagram that makes it possible to convey information on infectious disease incidence more attractively to a wider audience. This can be a useful tool for health promotion in the community. The obtained results are as follows:1. It was advantageous to use data transformed by logarithm in statistical analysis of infectious disease incidence.2. The incidences of measles and influenza exhibited strong seasonality.Measles was most frequent in June and influenza in February.3. Long-term trends were extracted from the derived data obtained by eliminating seasonal effects from the original data. For measles, a decline was accelerated by the introduction of vaccination program in 1978. Influenza also showed a decline for these thirty years.4. The observed incidence data were quite well predicted by only the trend and the seasonality. The squares of multiple regression coefficients of measles and influenza were 0.84 and 0.58, respectively. The analysis of the residuals suggested there was a possibility of improvement in prediction. The improvement in prediction was attained by incorporating an autoregressive component of the residuals.As a result, the squares of multiple correlation coefficients of measles and influenza increased to 0.97 and to 0.79, respectively. 6. We finally proposed the TS-decomposition diagram to facilitate practical use of incidence data. In this diagram, current incidence data and predicted values for the near future are plotted on the plane where the trend and the seasonality are superimposed.We also discussed the application of our method to the entire range of infectious disease surveillance data.
Abstract:ioelectrical Impedance Measuring
Half of nurses’ overtime hours are due to records. Nursing records, which are mainly narrative records, cost a large amount of money. However, it has been pointed out that there are problems with their quality and post-use. In this study, we analyzed the value of nursing records for physicians. As a result, we found that the use of standard observation terms in nursing records can create an environment in which patients’ conditions can be shared. To create this environment, the physicians of the clinical path committee classified hospitalized patients in terms of disease, treatment, and examination, and created a list of 778 process paths. Physicians, nurses, and researchers collaborated to develop digital contents with high-priority observation items and care actions adapted to patient conditions for each path. We developed a clinical support system equipped with these digital contents. In May 2019, we installed the system in a 900-bed university hospital. Then, in October 2020, we installed the system in a 400-bed general hospital. We used “nurses’ overtime hours for recording” and “reduction rate” as indicators of the usefulness of this system. In the 900-bed university hospital, we compared the previous year’s results for March, the end of the fiscal year. This overtime hours were 2,944 hours 00 minutes in March 2019 and 2,141 hours 55 minutes in March 2020. 27% reduction was indicated. The respective bed occupancy rates were 90.80 percent and 90.60 percent, with no difference. In the 400-bed general hospital, This overtime hours were compared to the previous year, covering November and December after one month of implementation. 386 hours in November 2019 and 204.5 hours in November 2020. 47% reduction indicated. 366 hours in December 2019 and 214.5 hours in December 2020. A reduction of 41% was shown. These results suggest that the implementation of this system can both improve the quality of team care and reduce overtime.
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