Biomedical subjects

U Ludwigs

Publications and source records attributed to U Ludwigs.

7 recordsLinked to original sources

PubMed1991

Multivariable optimization of mechanical ventilation. A linear programming approach.

The proposed method aims at improved ventilatory care with reduced morbidity. It combines two important aspects of mechanical ventilation: gas exchange and lung mechanics. A single criterion was selected as optimization index of lung trauma: peak respiratory power (PRP) defined as the maximum product of pressure times flow during inspiration. Arterial blood gases reflect gas exchange and constitute the constraints of the problem. The constraints as well as the optimization index are expressed as linear functions of the input variables (frequency of breathing, tidal volume, and positive end expiratory pressure). A linear programming approach can therefore be used to determine the values of input variables that minimize PRP and at the same time keep arterial blood gases within the prescribed limits. The coefficients of the constraints and the optimization index equation are found by manipulating input variables in order to obtain four different values of PaO2, PaCO2 and PRP (there are four coefficients in each equation). The coefficients can then be calculated and the optimization procedure run. In a pilot study 5 patients suffering from diseases of varying pulmonary pathology were investigated with this method. In 4 out of 5 the ventilator treatment improved in terms of blood gas values (mean increase in PaO2 was 4.7%) and reduction of mechanical load on the lungs (mean PRP reduction was 20%). Lower PRP is accompanied by lower mean power and pressure values, which results in increased cardiac output. Presently, the main problem is the time it takes to determine the patient coefficients (approx one hour), a procedure that needs to be simplified.

Acute Disease↗

PubMed1991

Medical logic module (MLM) representation of knowledge in a ventilator treatment advisory system.

In any medical expert system it is the inherent knowledge that is the power of the system and not the particulars of its implementation. Therefore it would be valuable to use a representation that would allow: knowledge transfer between different systems, users, experts and 'importers' to be able to evaluate the logic, experts to easily input their knowledge and be guided how to use the syntax. Adren Syntax of Medical Logic Module is a proposed knowledge representation, fulfilling these criteria. The Arden Syntax has been used to represent rules and logic in a decision support system for ventilator therapy in patients with acute respiratory failure (ARF) that is under development. The medical experts involved in the project have used the Arden Syntax as a convenient way for transfer and storage of medical knowledge. The syntax is easy to learn and may be used with a minimum of training. In the present system, Medical Logical Modules have been used to represent knowledge pertinent to the initiation and maintenance phases of ventilator therapy.

Acute Disease↗

PubMed1990

Integrating knowledge-based technology into computer aided ventilation systems.

A knowledge-based decision support system for respirator treatment, the KUSIVAR system, has been designed in cooperation between hospital, university and industry. Changes in patient data from respirator and monitoring equipment trigger a computer program that generates advice to the staff concerning e.g. therapy modes and respirator settings using expert systems and process control technology. A prototype has been built on an advanced development workstation, the Unisys Explorer, using the software Knowledge Engineering Environment (KEE). The clinical version is implemented on an Intel 80396-based microcomputer connected on-line via a data-acquisition processor to the respirator. The decision support software is implemented as a module under the Microsoft Windows multitasking environment and communicates with modules for data acquisition, database handling and data presentation by means of message passing using the Windows Dynamic Data Exchange protocol. The modules present coherent user interfaces by conforming to Microsoft Windows standards. The knowledge base is being extensively validated by an expert group in the ICU and the system will be evaluated through animal experiments and clinical studies.

Computer Systems↗

PubMed1989

A microcomputer system for on-line monitoring of pulmonary function during artificial ventilation.

Standard monitoring of the artificially ventilated patient in the intensive care unit (ICU) and during anaesthesia includes repeated determinations of arterial blood gases, airway pressure and expired volume. However, there is a need for more extensive monitoring of the critically ill ventilator treated patient, and this is possible by better utilization of modern technology. Information on a variety of variables related to both pulmonary mechanics and gas exchange has long been accessible in the lung-function laboratory. Small, inexpensive microcomputers (PCs), accurate and fast bedside monitors and modern ventilators have also made this information directly available to the ICU staff. This paper describes a microcomputer (PC-XT) system for on-line bedside monitoring of pulmonary function. The microcomputer receives airway pressure, gas-flow and timing signals from the ventilator and signals for carbon dioxide concentration from an infrared analyzer. Data related to pulmonary mechanics and gas exchange are derived and displayed on the computer screen, both numerically and as graphs. In studies of ten artificially ventilated patients the coefficients of variation (CV) were below 10% for directly obtained variables (tidal volume, airway pressure, end-tidal and mixed expired carbon dioxide, carbon dioxide production, airway dead space), whereas the derived variables (compliance, phase III carbon dioxide slope) were associated with greater variability, with CVs ranging from 1.3 to 24% (median 6.25% and 8.65% respectively). The accuracy in estimating dead space variations was checked in two ventilator-treated patients by adding known dead space volumes. Simple regression analysis yielded an r value of 0.98 indicating adequate correctness of measurements and calculations.

Airway Resistance↗

PubMed1989

Knowledge base design for decision support in respirator therapy.

A knowledge base is built for decision support applied to respirator therapy (the KUSIVAR project). The knowledge representation is object-oriented using frames to store multiple forms of knowledge: variable descriptions, transformation tables, rules and mathematical models. The system is data-driven, generating and displaying advice automatically triggered by changes in data from the respirator and the patient. The inferenceing mechanism is forward-chaining i.e. a rule is evaluated as soon as it's condition is satisfied. Temporal aspects of the reasoning are represented by a number of mechanisms, among others limited validity times for data, trend analysis and mathematical models. The knowledge base is organized according to disease groups and decision situation which simplifies knowledge acquisition and improves response times since it enables the system to focus on a limited set of rules in each situation. To test the feasibility of the system design a prototype has been built using Knowledge Engineering Environment (KEE) from Intellicorp on an Explorer workstation from Unisys. The production system, which is interfaced to a Siemens Elema Servo Ventilator 900C, is currently being implemented under the Microsoft Windows multitasking environment on a microcomputer based on an Intel 80386 processor.

Decision Support Techniques↗

PubMed1987

Reaction of unsaturated uronic acid residues with mercuric salts. Cleavage of the hyaluronic acid disaccharide 2-acetamido-2-deoxy-3-O-(beta-D-gluco-4-enepyranosyluronic acid)-D-glucose.

Degradation of connective-tissue polysaccharides with bacterial or fungal eliminases and subsequent characterization of the reaction products are now part of standard methodology for the analysis of these compounds. However, the scope of preparative and analytical work based on the use of eliminases has been limited by the lack of procedures for specific removal of the unsaturated uronic acid residues generated in the eliminase reactions. In the present investigation, we have shown that these residues are cleaved by mercuric salts under mild conditions that are not likely to affect other structures in an oligo- or poly-saccharide molecule. Thus the disaccharide generated from hyaluronic acid by digestion with chondroitinase AC or ABC was cleaved into a keto acid and free N-acetylglucosamine within 10 min at room temperature upon exposure to 14 mM-mercuric acetate at pH 5. The reaction of the disaccharide with mercuric salts was used for ready determination of the distribution of radioactivity between the glucuronic acid and N-acetylglucosamine moieties in radioactive hyaluronic acid that had been synthesized by IMR-90 fibroblasts from 3H-labelled monosaccharides. When the precursor was [3H]galactose, over 95% of the incorporated radioactivity was found in the glucuronic acid moiety. In contrast, cells grown in the presence of [3H]glucosamine synthesized a polysaccharide in which almost all of the label was located in the N-acetylglucosamine units. It is apparent from these experiments that the reaction of unsaturated uronic acid residues with mercuric salts provides a new tool with potential for many applications in the study of the structure and metabolism of connective-tissue polysaccharides.

Cell Line↗

PubMedDate not supplied

Kave: a tool for knowledge acquisition to support artificial ventilation.

A decision support system for artificial ventilation is being developed. One of the fundamental goals for this system is the application of the system when a domain expert is not present. Such a system requires a rich knowledge base. The knowledge acquisition process is often considered to be the bottleneck in acquiring such a complete knowledge base. Since no single available method, for example interviewing domain experts, is sufficient for removing this bottleneck, we have chosen a combination of different methods. The different backgrounds of knowledge engineers and domain experts could cause communication restrictions and difficulties between them, e.g. they might not understand each others knowledge domain and this will affect formulation of the knowledge. To solve this problem we needed a tool which supports both the knowledge engineer and the domain expert already from the initial phase of developing the knowledge base. We have developed a knowledge acquisition system called KAVE to elicit knowledge from domain experts and storing it in the knowledge base. KAVE is based on a domain specific conceptual model which is a result of cooperation between knowledge engineers and domain experts during identification, design and structuring of knowledge for this domain. KAVE includes a patient simulator to help validate knowledge in the knowledge base and a knowledge editor to facilitate refinement and maintenance of the knowledge base.

Artificial Intelligence↗