Prognostic value of preoperatively obtained clinical and laboratory data in predicting survival following orthotopic liver transplantation

Twenty‐seven clinical and laboratory data and the subsequent clinical course of 93 consecutive adult patients who underwent orthotopic liver transplantation for various chronic advanced liver diseases were analyzed retrospectively to assess the risk factors of early major bacterial infection and death after the procedure. Forty‐one patients (44%) had early major bacterial infection during hospitalization for orthotopic liver transplantation. The mortality rate was 70.7% in patients with early major bacterial infection and was 7.7% in patients without early major bacterial infection (p < 0.001). Total serum bilirubin, total white blood cell count and polymorphonuclear cell count, IgG (all p < 0.05) and plasma creatinine level (p < 0.001) were higher in patients that developed early major bacterial infection than in those who did not. By step‐wise discriminant analysis, the strongest risk factor for early major bacterial infection was the serum creatinine level, which achieved an accuracy of 69% for a creatinine level greater than 1.58 mg per dl. Seven variables (ascites, hepatic encephalopathy, elevated white blood and polymorphonuclear cell count, decreased helper to suppressor T cell ratio and elevated plasma creatinine and bilirubin levels) were associated with a significant increased risk for death. A step‐wise discriminant analysis of these seven factors resulted in the demonstration of serum creatinine as the greatest risk factor for mortality. A preoperative serum creatinine either less than or greater than 1.72 mg per dl accurately predicts survival or death, respectively, in 79% of cases. These data suggest that the baseline preoperative serum creatinine level provides the best indication of the short‐term prognosis after liver transplantation than does any other preoperatively obtained index of the patient's status. Copyright © 1986 American Association for the Study of Liver Disease

Towards Robotic Laboratory Automation Plug & Play: Survey and Concept Proposal on Teaching-free Robot Integration with the LAPP Digital Twin

The Laboratory Automation Plug & Play (LAPP) framework is an over-arching reference architecture concept for the integration of robots in life science laboratories. The plug & play nature lies in the fact that manual configuration is not required, including the teaching of the robots. In this paper a digital twin (DT) based concept is proposed that outlines the types of information that have to be provided for each relevant component of the system. In particular, for the devices interfacing with the robot, the robot positions have to be defined beforehand in a device-attached coordinate system (CS) by the vendor. This CS has to be detectable by the vision system of the robot by means of optical markers placed on the front side of the device. With that, the robot is capable of tending the machine by performing the pick-and-place type transportation of standard sample carriers. This basic use case is the primary scope of the LAPP-DT framework. The hardware scope is limited to simple benchtop and mobile manipulators with parallel grippers at this stage. This paper first provides an overview of relevant literature and state-of-the-art solutions, after which it outlines the framework on the conceptual level, followed by the specification of the relevant DT parameters for the robot, for the devices and for the facility. Finally, appropriate technologies and strategies are identified for the implementation

Establishing a highly automated and digitalized end-to-end bioprocess

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Years of life lost (YLL) from cancer is an important measure of population burden – and should be considered when allocating research funds

Recently, cancer mortality has been compared to research spending by the National Cancer Research Institute (NCRI), whose research budget is approximately £250 million. The analysis shows a mis-match between mortality and research spending. As well as crude mortality rates, other measures of cancer burden should be considered because they contribute additional information. ‘Years of life lost' (YLL) summed over each individual dying after a diagnosis of cancer represents a population-based mortality indicator of the impact of that disease on society. Years of life lost divided by the number of deaths for each cancer site produces an additional statistic, the average years of life lost (AYLL), which is a measure of the burden of cancer to the individual patient. For 17 cancer sites where data are available, four tumour sites have a rather large difference in mortality, comparing YLL to crude mortality. Years of life lost shows the population burden from cancers of the ovary, cervix, and CNS to be rather larger than suggested by crude mortality, despite screening programmes for cervix cancer. Using YLL, the underprovision of funding for lung cancer research is similar to that reported using percentage mortality. Breast cancer and leukaemia receive a relatively higher research spend than the population burden of these cancers, and the spending on leukaemia is quite extreme. Prostate cancer has a low per cent YLL but attracts a moderate amount of research spending. The use of AYLL as an indicator of individual cancer burden considerably changes the ranking of the mortality from different tumours. The mean AYLL is 12.5 years. Prostate cancer has the lowest AYLL, only 6.1 years; brain tumour patients have the highest, at just over 20 years. Comparing AYLL to research spending suggests four ‘Cinderella' cancer sites with high individual cancer burden but low research spending: CNS tumours, cervix and kidney cancers, and melanoma. Breast cancer and leukaemia have roughly average AYLL but a considerable excess of research spending. YLL emphasises the discrepancy between research spending and mortality, and may be helpful for decisions concerning research support. Avearage years of life lost measures the burden to individual patients and may be helpful where individuals' needs are relevant, such as palliative care. As well as crude mortality, more subtle and comprehensive calculations of mortality statistics would be useful in debates on research funding and public health issues

Towards Robotic Laboratory Automation Plug & Play: The "LAPP" Framework

Increasing the level of automation in pharmaceutical laboratories and production facilities plays a crucial role in delivering medicine to patients. However, the particular requirements of this field make it challenging to adapt cutting-edge technologies present in other industries. This article provides an overview of relevant approaches and how they can be utilized in the pharmaceutical industry, especially in development laboratories. Recent advancements include the application of flexible mobile manipulators capable of handling complex tasks. However, integrating devices from many different vendors into an end-to-end automation system is complicated due to the diversity of interfaces. Therefore, various approaches for standardization are considered in this article, and a concept is proposed for taking them a step further. This concept enables a mobile manipulator with a vision system to "learn" the pose of each device and - utilizing a barcode - fetch interface information from a universal cloud database. This information includes control and communication protocol definitions and a representation of robot actions needed to operate the device. In order to define the movements in relation to the device, devices have to feature - besides the barcode - a fiducial marker as standard. The concept will be elaborated following appropriate research activities in follow-up papers