Manabu Nii

BACKGROUND/AIM: Patients diagnosed with cancer are expected to choose one or more treatment modalities after receiving corresponding explanations of the options. When making these choices, patients consider the effects of treatment and aspects related to their quality of life. These concerns can cause confusion and conflict owing to the complicated information provided by medical caregivers. The objective of the study was to identify perceptions of cancer treatment in patients with cancer and the decision-making factors affecting their treatment choices. PATIENTS AND METHODS: In this observational (cross-sectional) study, an online questionnaire survey was administered to 194 Japanese cancer patients with treatment experience. Patient information, perceptions of explanations provided by healthcare professionals, treatment views, and reasons for treatment decisions were subjected to a simple tabulation. Content and factor analysis was conducted to determine important treatment selection elements. RESULTS: Regarding treatment perception, 60.3% of respondents (n=117) considered treatment a financial and family burden, 47.4% (n=92) had concerns about physical pain, and 40.2% (n=78) were worried about increased stress. Regarding decision-making quality, 95.9% determined their preferred treatment within one week, 49.0% reported difficulties in making their decisions, and 83.0% chose their treatment themselves. Major decisive factors were prolonging life, opinions of medical staff, and accepting treatment risks (68.0%, 68.6%, and 60.3% of patients, respectively). The main attitudes toward treatment were anxiety, expectations of benefit, and expectations of support and care. CONCLUSION: SDM should enable patients to visualize the changes that their bodies will experience and include discussions on prognosis. Psychological care should be prioritized to alleviate anxiety and improve readiness for decision-making; attention should be paid to the extent and timing of information provision.

Introduction: The purpose of this study was to clarify the relationship between the available service information on small-scale multifunctional in-home nursing care (KANTAKI) and its operational status via text mining. Methods: We obtained nationwide textual information on KANTAKI from the Nursing Care Service Information Disclosure System and the Ministry of Health, Labour, and Welfare, and analyzed the characteristics of the word usage using KH Coder. The number of users and employees and the implementation of services were compared among the facilities that used terms relating to medical dependency and end-of-life care, which are KANTAKI characteristics, and with other facilities. Results: The facilities that used terms relating to medical dependency and end-of-life care showed significantly more users requiring nursing care level 5 and more full-time nursing staff than those not using such terms. Moreover, regarding service provision, the rate of procedures was significantly higher in 11 of 12 items, except for stoma. Conclusion: The facilities that use terms relating to medical dependency and end-of-life care in their information have more users and provide a greater variety of services. In the future, educational support is required to enable facility managers to understand the services and translate them into their work.

Background: We investigated factors involved in decision-making support provided by physicians, nurses, pharmacists and medical and psychiatric social workers involved in cancer care. Materials & methods: A questionnaire survey on decision-making support was conducted. The level of clinician support was classified as 'supporting patients' 'decision-making process regarding cancer treatment', 'no support for patients' 'decision-making process regarding cancer treatment' or 'team-based support for patients' 'decision-making process regarding cancer treatment'. Results: Physicians estimated that 83.7% of patients made a cancer treatment decision within 1 week, but 45.4% of patients had difficulty making a decision. Conclusion: Medical personnel should support patients who have difficulty making decisions, establish a screening method to identify those needing support and develop a system providing decision-making support through interprofessional work.

Background Japan is a superaging society unparalleled in the world. Elderly people who need medical care do not receive adequate support in the community. As a new service to address this issue, a small-scale multifunctional in-home care nursing service called Kantaki was created in 2012. Kantaki, in collaboration with a primary physician, operates 24 hours a day and provides various nursing services (home visits, home care, day care, and overnight stays) to older people living in the community. The Japanese Nursing Association is working hard to promote this system; however, its low utilization rate is an issue. Objective This study aimed to determine factors influencing the utilization rate of Kantaki facilities. Methods This was a cross-sectional study. A questionnaire on the operation of Kantaki was sent to all administrators of Kantaki facilities operating in Japan from October 1 to December 31, 2020. A multiple regression analysis was used to determine factors associated with a high utilization rate. Results Responses from 154 of the 593 facilities were analyzed. The average utilization rate for all valid responding facilities was 79.4%. The average number of actual users and the break-even point were almost equal, resulting in little surplus profit from facility operations. A multiple regression analysis showed that factors that had a significant impact on the utilization rate included the break-even point, a surplus of users relative to the break-even point (ie, the margin of revenues), the number of months in office of the administrator, the type of corporation (ie, nonprofit), and Kantaki’s profit from operating home-visit nursing offices. The break-even point, a surplus of users relative to the break-even point, and the number of months in office of the administrator were robust. In addition, support for reducing the burden on family helpers, a service sought by the system, significantly and negatively affected the utilization rate. In the analysis that removed the most influential factors, the cooperation of the home-visit nursing office, Kantaki’s profit from operating the home-visit nursing office, and the number of full-time care workers were significantly related. Conclusions To improve the utilization rate, managers need to stabilize their organization and increase profitability. However, a positive relationship was found between the break-even point and utilization rate, suggesting that simply increasing users did not contribute to cost reduction. Moreover, providing services that meet the needs of individual clients may result in lower utilization rates. These results, which are inconsistent with common sense, reflect the divergence between the assumptions underlying the system’s design and actual conditions. To solve these issues, institutional reforms, such as an increase in nursing care fee points, may be necessary.

Multiple accelerometers (chest and wrist) and physiological sensors (electrocardiogram (ECG) and electrodermal activity (EDA)) based activity classification systems have been proposed to classify those activities which are too abstruse to classify with the accelerometer-based system only. “ActiGraph” count value as well as several features of ECG and EDA were extracted from 14 persons with an open-source dataset named “PPG Field Study Dataset”. The activities were considered as different types (type A, type B, type C) based on the movement intensity of the wrist and the chest. The features were fitted to machine learning (ML) algorithms with accelerometer features only and both (count and physiological feature). In the case of type A activities (no chest and wrist movement), classification with accelerometers only and both, the accuracy was 89.3% with weighted K-NN and 100% with linear regression, respectively. In the case of classification between type B (hand soccer, cycling, driving, lunch) activities with accelerometers only and both, the accuracy was 66.1% and 89.3% with linear and quadratic support vector machine (SVM) respectively. In the case of classification between type C activities (stair and walk) with accelerometers only and both, the accuracy was 64.3% and 82.1% with linear discrimination and SVM (linear) classifier respectively. All the results for type A and type C activities classification were generated with leave one out cross-validation, and classification between type B activities was classified with 50-fold cross-validation to avoid overfitting where Bayesian optimizer tuned the hyperparameters of the ML classifiers.

Objectives: In order to cope with a rapidly aging national population, the Japanese government promotes the use of a comprehensive community care system known as Kantaki, which was established in 2012. Aimed at older populations, Kantaki offers a variety of services, including home-visit nursing care, day care, and overnight care. This study clarified the factors that affect the estimated revenue of Kantaki services through a secondary analysis of detailed information released by the Ministry of Health, Labour and Welfare (MHLW). Our goal was to provide information that may facilitate the stable management of Kantaki operations across Japan. Methods: We conducted a secondary analysis of official statistics data and detailed information released by the MHLW in April 2020. As such, we calculated the estimated revenue for Kantaki services. We then conducted a logistic regression analysis with estimated revenue set as the dependent variable in order to assess the magnitude of each influencing factor. Results: A total of 594 multifunctional in-home long-term care services were established. Of these, 506 met the requirements for Kantaki set in this study’s analysis. The logistic regression analysis showed that items with large odds ratios included tube feeding (2.59), enhanced working conditions for care workers (I) (2.58), and colostomy/ileostomy care (1.76). Conclusion: To achieve stable management practices for Kantaki, it is important to handle at-home medical needs through the use of skilled care workers, who must be properly trained and ensured stable employment.

<sec> <title>Background:</title> Anterior cruciate ligament (ACL) injury causes knee instability which affects sports activity involving cutting and twisting motions. The ACL reconstruction surgery replaces the damaged ACL with artificial one which is fixed to the bone tunnels opened by the surgeon. The outcome of the ACL reconstruction is strongly related to the placement of the bone tunnels, therefore, the optimization of tunnel drilling technique is an important factor to obtain satisfactory surgical results. </sec> <sec> <title>Aims:</title> The quadrant method is used for the post-operative evaluation of the ACL reconstruction surgery, which evaluates the bone tunnel opening sites on the lateral 2D X-ray radiograph. </sec> <sec> <title>Methods:</title> For the purpose of applying the quadrant method to the pre-operative knee MRI, we have synthesized the pseudo lateral 2D X-ray radiograph from the patients' knee MRI. This paper proposes a computer-aided surgical planning system for the ACL reconstruction. The proposed system estimates appropriate bone tunnel opening sites on the pseudo lateral 2D X-ray radiograph synthesized from the pre-operative knee MRI. </sec> <sec> <title>Results:</title> In the experiment, the proposed method was applied to 98 subjects including subjects with osteoarthritis. The experimental results showed that the proposed method can estimate the bone tunnel opening sites accurately. The other experiment using 36 healthy patients showed that the proposed method is robust to the knee shape deformation caused by disease. </sec> <sec> <title>Conclusion:</title> It is verified that the proposed method can be applied to subjects with osteoarthritis. </sec>

[Background] To promote an integrated community care system, the Japanese government created a multifunctional long-term care service model called Kantaki in 2012, aiming to provide a combination of services such as short-stay, day-care, and home visit by aides and/or nurses to meet various client needs. However, it is unclear how well this model has been utilized and accessed throughout Japan.[Objective] This study aimed to understand the distribution status of Kantaki through a secondary analysis of information on its operations and population trends released by public institutions.[Methods] The study determined the number of Kantaki, Shotaki (a service that is similar to the Kantaki model except it does not provide home visit service by nurses), and visiting nurse stations from the Ministry of Health, Labour and Welfare website registry. Population trend information was collected from the national census. Statistical processing included a correlation analysis using descriptive analysis and Spearman's correlation coefficient.[Results] As of December 31, 2018, there were 479 Kantaki operations throughout Japan. The mean number of Kantaki operations by prefecture was 10.19 ± 10.51. Of the municipalities, 233 (13.5%) out of 1,724 had Kantaki operations available. The number of Shotaki (.765), number of visiting nurse stations (.747), population (.703), population density (.513), and the rate of aging (-.442) were found to have a significant correlation with the number of Kantaki operations present.[Discussion] The number of Kantaki operations showed a large variation across regions, with a higher prevalence in population-dense urban areas, and lower prevalence in regions with a high aging rate. This reveals the distribution model is unrelated to the elderly population, who can be potential clients, and must be affected by other reasons such as staffing issues and operating costs. To promote Kantaki throughout Japan, such operational issues should be analyzed further.

BACKGROUND: This study presents a novel method of constructing a spatiotemporal statistical shape model (st-SSM) for adult brain. St-SSM is an extension of statistical shape model (SSM) in the temporal domain which will represent the statistical variability of shape as well as the temporal change of statistical variance with respect to time. AIMS: Expectation-Maximization (EM) based weighted principal component analysis (WPCA) using a temporal weight function is applied where the eigenvalues of each data are estimated by Estep using temporal eigenvectors, and M-step updates Eigenvectors in order to maximize the variance. Both E and M-step are iterated until updating vectors reaches the convergence point. A weight parameter for each subject is allocated in accordance with the subject's age to calculate the weighted variance. A Gaussian function is utilized to define the weight function. The center of the function is a time point while the variance is a predefined parameter. METHODS: The proposed method constructs adult brain st-SSM by changing the time point between minimum to maximum age range with a small interval. Here, the eigenvectors changes with aging. The feature vector of representing adult brain shape is extracted through a level set algorithm. To validate the method, this study employed 103 adult subjects (age: 22 to 93 y.o. with Mean ± SD = 59.32±16.89) from OASIS database. st-SSM was constructed for time point 40 to 90 with a step of 2. RESULTS: We calculated the temporal deformation change between two-time points and evaluated the corresponding difference to investigate the influence of analysis parameter. An application of the proposed model is also introduced which involves Alzheimer's disease (AD) identification utilizing support vector machine. CONCLUSION: In this study, st-SSM based adult brain shape feature extraction and classification techniques are introduced to classify between normal and AD subject as an application.

先行研究でGyftopoulosらは腱板断裂患者の2次元MR画像から腱板3次元形状の再構築を行う方法を報告しているが、論文中に例示された腱板3次元形状は滑らかではないため、腱板の形状を忠実に再現できたとは言い難い。一方、Turkらは複数枚の断面図から物体3次元形状を再構築する方法を報告している。同手法の概要は、3次元形状を陰関数で表現し、断面間の陰関数値を放射基底関数で補間することで滑らかな3次元形状を生成するというものであり、本法を肝臓などの医用画像に応用した報告はあるが、腱板に応用した報告はみられない。そこで今回、腱板断裂例に応用し、本法によって再構築された3次元形状と実際の術中所見を比較した。結果、再構築された3次元形状は滑らか且つ自然であり、術中所見と一致した。