Research on innovative design of community mutual aid elderly care service platform based on Kano model.

The mutual aid elderly care model is important to solve the world population's current aging problem. However, although mutual aid elderly care has been developing in China for more than 20 years, there is still a lack of a systematic way to participate in mutual aid elderly care services, which has led to a slow development of mutual aid elderly care. Therefore, in order to promote the development of mutual aid elderly care and the transition of social elderly care towards sustainability, this study analyzes the actual elderly care service needs and proposes new design strategies for mutual aid elderly care service platforms. In this study, first, the actual elderly care needs were obtained through interview methods and offline questionnaire surveys. The results showed that the elderly have a high demand for health, daily life, entertainment, and spiritual needs, which can be used to establish a comprehensive Kano model. Based on the priority of the needs hierarchy, mutual aid elderly care resources can be allocated rationally. For example, when applying the research results to the design of mutual aid elderly care service platforms, the "Must-be quality" is first satisfied, followed by the "One-dimensional quality" and the "Attractive quality" according to the actual situation. Furthermore, the mutual aid elderly care service platform is divided into a basic version and a professional version to promote the actual needs of different groups of elderly people. In conclusion, the study aims to promote the development of mutual aid elderly care and the transition of social elderly care towards sustainability. The research value of this study lies in its potential to alleviate the slow development of the current mutual aid elderly care model in China and provide a reference for solving the problem of global aging population.

A Bayesian platform trial design to simultaneously evaluate multiple drugs in multiple indications with mixed endpoints.

In the era of targeted therapies and immunotherapies, the traditional drug development paradigm of testing one drug at a time in one indication has become increasingly inefficient. Motivated by a real-world application, we propose a master-protocol-based Bayesian platform trial design with mixed endpoints (PDME) to simultaneously evaluate multiple drugs in multiple indications, where different subsets of efficacy measures (eg, objective response and landmark progression-free survival) may be used by different indications as single or multiple endpoints. We propose a Bayesian hierarchical model to accommodate mixed endpoints and reflect the trial structure of indications that are nested within treatments. We develop a two-stage approach that first clusters the indications into homogeneous subgroups and then applies the Bayesian hierarchical model to each subgroup to achieve precision information borrowing. Patients are enrolled in a group-sequential way and adaptively assigned to treatments according to their efficacy estimates. At each interim analysis, the posterior probabilities that the treatment effect exceeds prespecified clinically relevant thresholds are used to drop ineffective treatments and "graduate" effective treatments. Simulations show that the PDME design has desirable operating characteristics compared to existing method.

PMED: Optimal Bayesian Platform Trial Design with Multiple Endpoints.

In oncology drug development, indication selection and optimal dose identification are the primary objectives for the early phase of clinical trials and could significantly impact the probability of success. Master protocols, e.g., basket trial, umbrella trial, and platform trial, have become popular in practice considering the connection of trial designs with multiple indications and treatment candidates. They also enable the optimization of operational resources and maximize the capability of data-driven decision-making. However, most of the available designs are developed with the efficacy endpoint only for treatment effect estimation and testing, without consideration of the safety end point. Thus, it often lacks a comprehensive quantitative framework to allow optimal treatment selection, which could put future development at risk. We propose an optimal Bayesian platform trial design with multiple end points (PMED) to characterize the overall benefit-risk profile. The design is further extended to allow treatment and indication selection within and across arms, with continuous monitoring on multiple interim analyses for futility. In addition, we propose dynamic borrowing across arms to increase the efficiency and accuracy of estimation given the level of similarity across arms. A hierarchical hypothesis structure is utilized to achieve optimal indication and treatment combination selection by controlling family-wise error. Through simulation studies, we show that PMED is a robust design under the studied scenarios with superb power and controlled family-wise error rate.

A 3-Year Prospective Clinical Study to Evaluate the Outcome of Single-Piece Implant-Prosthetic Complex after Immediate NonFunctional Loading in the Maxillary Anterior and Mandibular Posterior Areas in Varied Bone Densities.

Context: There is limited evidence on the outcome of single-piece implant-prosthetic complex after immediate nonfunctional loading in varied bone densities. Aim: The aim of this study was to report the outcome of single-piece implant-prosthetic complex with a novel cervical platform design in the anterior and posterior jaws 3 years after loading. Setting and Design: Prospective clinical study. Materials and Methods: The present study included placement of 90 single-piece implants in the anterior and the posterior jaws in varied bone densities. After immediate loading, survival and marginal bone loss was recorded at regular intervals. Statistical Analysis: Independent sample t-test and paired t-test were done (P = 0.05). Results: Group I, annual marginal bone loss at the end of one, 2 and 3 years was 0.21, respectively, in both bone densities. Group II, annual marginal bone loss in D2 regions was 0.75,0.38 and 0.18; 0.64, 0.28 and 0.18 in D3 regions at the end of 1, 2, and 3 years, respectively. Group I showed no statistically significant difference in marginal bone loss between D2 and D3 bone annually in contrast to Group II. Intragroup comparisons of mean between baseline and various time intervals showed statistically significant bone loss in both bone densities. Conclusion: Three years after loading, single-piece implants with the novel cervical platform design provided survival rates of 93% in the maxillary anteriors and 91% in the mandibular posteriors. D3 bone showed more marginal bone loss than D2 bone.

Challenges and potential strategies utilizing external data for efficacy evaluation in small-sized clinical trials.

In clinical trials for diseases with very small patient populations, trial investigators may encounter recruitment difficulties. It can be challenging to conduct clinical trials with enough power to detect a treatment effect, and randomization may not be feasible due to timeline, budget, and ethical concerns. To bring breakthrough therapies to the market quickly, it is important to come up with efficient approaches to utilizing individual patient data through improved study design and sound statistical methods. Emerging topics in this area include the use of Bayesian approaches to flexibly incorporate prior information into the current clinical trials, the use of historical controls to efficiently conduct trials that will reduce the number of subjects recruited and ease ethical considerations, and the use of innovative study designs, such as a platform design, to improve the efficiency and speed of the medical therapy development progress. In this paper, we describe three scenarios which highlight some of the challenges encountered in small-sized clinical trial development and provide potential statistical approaches to overcome the aforementioned challenges.

Single-Walled Carbon Nanotube Sensor Platform for the Study of Extracellular Analytes.

Single-walled carbon nanotubes (SWNT) are attractive targets for the formation of high-density sensor arrays. Their small size and high reactivity could allow for the spatial and temporal study of extracellular products to a degree which greatly surpasses contemporary sensors. However, current methods of SWNT immobilization produce a low fluorescence yield that requires a combination of high magnification, exposure time, and laser intensity to combat, thus limiting the sensor's applications. In this work, a platform for the immobilization of SWNT sensors with increased fluorescence yield, longevity, fluorescence distribution, and fast reaction times is developed.

A Bayesian adaptive phase I/II platform trial design for pediatric immunotherapy trials.

Immunotherapy is the most promising new cancer treatment for various pediatric tumors and has resulted in an unprecedented surge in the number of novel immunotherapeutic treatments that need to be evaluated in clinical trials. Most phase I/II trial designs have been developed for evaluating only one candidate treatment at a time, and are thus not optimal for this task. To address these issues, we propose a Bayesian phase I/II platform trial design, which accounts for the unique features of immunotherapy, thereby allowing investigators to continuously screen a large number of immunotherapeutic treatments in an efficient and seamless manner. The elicited numerical utility is adopted to account for the risk-benefit trade-off and to quantify the desirability of the dose. During the trial, inefficacious or overly toxic treatments are adaptively dropped from the trial and the promising treatments are graduated from the trial to the next stage of development. Once an experimental treatment is dropped or graduated, the next available new treatment can be immediately added and tested. Extensive simulation studies have demonstrated the desirable operating characteristics of the proposed design.

Master protocols: New directions in drug discovery.

A master protocol is a unifying study construct that includes multiple subgroups and substudies, with patients having same or different diseases and that employ one or multiple drugs to treat it. Initially designed for oncology, master protocol trials are intended to simultaneously evaluate more than one investigational drug and/or more than one cancer type within the same overall trial structure. The ability to use a single infrastructure, trial design, and protocol to simultaneously evaluate multiple drugs and/or disease populations in multiple substudies, speeds up drug development and makes it more efficient. Thus, it is important for the clinical trial professionals to understand both the basic principles of master protocol trials and the way innovative trial designs are starting to change the landscape of clinical research.

ComPAS: A Bayesian drug combination platform trial design with adaptive shrinkage.

Combining different treatment regimens provides an effective approach to induce a synergistic treatment effect and overcome resistance to monotherapy. The challenge is that, given the large number of existing monotherapies, the number of possible combinations is huge and new potentially more efficacious compounds may become available any time during drug development. To address this challenge, we propose a flexible Bayesian drug combination platform design with adaptive shrinkage (ComPAS), which allows for dropping futile combinations, graduating effective combinations, and adding new combinations during the course of the trial. A new adaptive shrinkage method is developed to adaptively borrow information across combinations and efficiently identify the efficacious combinations based on Bayesian model selection and hierarchical models. Simulation studies show that ComPAS identifies the effective combinations with higher probability than some existing designs. ComPAS provides an efficient and flexible platform to accelerate drug development in a seamless and timely fashion.

Study on improving the emergency diagnosis and treatment of outpatient and emergency by perfecting the subsystem of patient telephone information management / 中国实用护理杂志

0bjective Exploration of the application effect of a new way of collecting patient′s telephone information to emergency diagnosis and treatment process reengineering in outpatient and emergency department. Methods Relying on the hospital information system platform, design and implement timely collection and validity verification mechanism of mobile phone data in outpatient and emergency department network sub-platform; before and after the implementation of the evaluation of 500 cases of patient registration time, telephone information accuracy. Statistics before and after using the 200 patients with critical value received report (short message, telephone) response time should be again;medical treatment satisfaction. Results The sub-platform realized the timely modification of telephone information through multi-function exchange terminal when patients visited the hospital. There was no statistical significance in the time of registration of patients in the two groups (P>0.05), the registration time was not extended. The accuracy rate of telephone information was 98.4% (492/500) in the experimental group, and 66.6% (333/500) in the control group, there was differences between the two groups (χ2=176.70,P<0.05). After the implementation, the number of the 200 patients who received critical value report (text message, phone call) and answered again within 30 minutes was 189, and there were 132 cases before implementation, there was difference before and after implementation (χ2=69.38, P<0.05). The patients′satisfaction with emergency treatment in the control group and the experimental group was 68.5%(137/200), 95.5%(191/200), there was significant difference (χ2=51.80, P<0.05). The doctors′satisfaction with the system in the experimental group and the control group was 94.0%(188/200), 65.5% (131/200), there was significant difference (χ2=51.25, P<0.05). Conclusions The method of telephone information collection of patients was optimized, and the quality and management level of emergency diagnosis and treatment were improved, and the information construction of door and emergency room was promoted.

A multi-source adaptive platform design for testing sequential combinatorial therapeutic strategies.

Traditional paradigms for clinical translation are challenged in settings where multiple contemporaneous therapeutic strategies have been identified as potentially beneficial. Platform trials have emerged as an approach for sequentially comparing multiple trials using a single protocol. The Ebola virus disease outbreak in West Africa represents one recent example which utilized a platform design. Specifically, the PREVAIL II master protocol sequentially tested new combinations of therapies against the concurrent, optimal standard of care (oSOC) strategy. Once a treatment demonstrated sufficient evidence of benefit, the treatment was added to the oSOC for all future comparisons (denoted as segments throughout the manuscript). In the interest of avoiding bias stemming from population drift, PREVAIL II considered only within-segment comparisons between the oSOC and novel treatments and failed to leverage data from oSOC patients in prior segments. This article describes adaptive design methodology aimed at boosting statistical power through Bayesian modeling and adaptive randomization. Specifically, the design uses multi-source exchangeability models to combine data from multiple segments and adaptive randomization to achieve information balance within a segment. When compared to the PREVAIL II design, we demonstrate that our proposed adaptive platform design improves power by as much as 51% with limited type-I error inflation. Further, the adaptive platform effectuates more balance with respect to the distribution of acquired information among study arms, with more patients randomized to experimental regimens.

Design and application of medical science and technology award system / 中华医学图书情报杂志

The functional module of medical science and technology award system was designed by controlling the RBACI limited inheritance relationship model in the RBAC96 model based on role-based access with Chinese medical science and technology award as an example,which can be used to control the access to data in modules at different levels by different users at different times,to develop the application and management system for Chinese medical science and technology award system,and to implement the information management of Chinese medical science and technology award system.

MIDAS: a practical Bayesian design for platform trials with molecularly targeted agents.

Recent success of immunotherapy and other targeted therapies in cancer treatment has led to an unprecedented surge in the number of novel therapeutic agents that need to be evaluated in clinical trials. Traditional phase II clinical trial designs were developed for evaluating one candidate treatment at a time and thus not efficient for this task. We propose a Bayesian phase II platform design, the multi-candidate iterative design with adaptive selection (MIDAS), which allows investigators to continuously screen a large number of candidate agents in an efficient and seamless fashion. MIDAS consists of one control arm, which contains a standard therapy as the control, and several experimental arms, which contain the experimental agents. Patients are adaptively randomized to the control and experimental agents based on their estimated efficacy. During the trial, we adaptively drop inefficacious or overly toxic agents and 'graduate' the promising agents from the trial to the next stage of development. Whenever an experimental agent graduates or is dropped, the corresponding arm opens immediately for testing the next available new agent. Simulation studies show that MIDAS substantially outperforms the conventional approach. The proposed design yields a significantly higher probability for identifying the promising agents and dropping the futile agents. In addition, MIDAS requires only one master protocol, which streamlines trial conduct and substantially decreases the overhead burden. Copyright © 2016 John Wiley & Sons, Ltd.

Study and Compatible Design of Two Types of Liquid Auto Sampler for Gas Chromatographer / 分析化学

We carried out parallel design and development of two differently structured auto sampler based on a multi-axis and multi-mode high-precision closed-loop servo control system. An integrated embedded control drive module was developed based on the idea of compatibility and inter-changeability, so that DC motor and encoder were standardized into uniform models. Meanwhile, electric and mechanical interfaces were uniformed to a same standard. This allows the direct exchange of above-mentioned components between the two models. A 1-μL manual sample injection syringe was installed on both standard 110-sample and platform 40-sample liquid auto sample injectors connected with gas chromatographer. Approximately 0. 5μL of cetane-isooctyl was sampled for 6 consecutive times at six different positions in the sample bottle. The repeatability RSDs of the injection peak areas of the two systems were 1. 1% and 1. 5%, respectively. A linear correlation coefficient (0. 9947) of peak area with injection volume was achieved based on the gradient sampling volume of 0. 1, 0. 3, 0. 5, 0. 7 and 0. 9 μL.

Digitalization of ancient books on traditional Chinese medicine and its platform design and implementation / 中华医学图书情报杂志

After the problems in digitalizing ancient books on traditional Chinese medicine were analyzed, the principles that should be followed in their digitalization were pointed out according to its theories and practice.The platform for digitalizing them was constructed with《Collective Notes to Canon of Materia Medica》as an example, and its design ideas, framework, development model and functional modules were described.

Miniaturised medium pressure capillary liquid chromatography system with flexible open platform design using off-the-shelf microfluidic components.

Trends towards portable analytical instrumentation of the last decades have not been equally reflected in developments of portable liquid chromatography (LC) instrumentation for rapid on-site measurements. A miniaturised medium pressure capillary LC (MPLC) system with gradient elution capability has been designed based on a flexible modular microfluidic system using primarily off-the-shelf low cost components to ensure wide accessibility to other analysts. The microfluidic platform was assembled on a breadboard and contained microsyringe pumps and switch valves, complemented with an injection valve and on-capillary detectors, all controlled by a PC. Four miniaturised microsyringe pumps, with 5, 20 and 100 µL syringe volume options, formed the basis of the pumping system. Two pairs of pumps were used for each mobile phase to create gradient elution capability. The two microsyringe pumps in each pairs were linked by two electrically operated microfluidic switching valves and both pairs of pumps were connected through a zero void volume cross-connector, thus providing a low hold-up volume for gradient formation. Sample was injected by a 20 nL nano-LC sampling valve, directly connected to a 18 cm long 100 µm i.d. Chromolith CapRod RP-18 monolithic capillary column. On-capillary LED-based UV-vis photometric detection was conducted through a piece of equal diameter fused silica capillary connected after the column. The performance of the portable LC system was evaluated theoretically and experimentally, including the maximum operating pressure, gradient mixing performance, and the performance of the detectors. The 5 µL microsyringe pump offered the best performance, with typical maximum operating pressures up to 11.4 ± 0.4 MPa (water) and gradient pumping repeatability of between 4 and 9% for gradients between 0.10% s(-1) and 0.33% s(-1). Test analytes of charged and uncharged dyes and pharmaceuticals of varying hydrophobicity showed typical RSD values of 0.7-1.4% and 3.3-4.8% in isocratic mode and 1.2-4.6% and 3.2-6.4% in gradient mode, respectively for retention time and peak area repeatability.