A polemic about hypotheses: a missing perspective in medical informatics.
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Biomedical subjects
Publications and source records attributed to T L Lincoln.
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This article reviews the issues involved in introducing or upgrading computer automation in the clinical laboratory. The strengths and weaknesses of computers and computer systems are discussed. Information on selecting and educating the laboratory team who will use the computer and analyzing the needs of a particular laboratory is included.
The steps involved in acquiring a computer system, from writing the request for a proposal to signing the contract, are discussed. Guidelines for selecting a system include information on the merits of different hardware and software available for use in the laboratory.
This article focuses on the strengths and shortcomings of application languages as they are used in general purpose computers, on the strategies for their use, and on how they impact laboratory and medical systems. The author describes the reason why we are where we are at the present stage of computer languages and suggests where we might expect to be in the foreseeable future.
The computer is rapidly becoming an interactive workstation for medical research and for clinical decision-making and it has become a preferred instrument for communication and documentation throughout health care. However, when the attempt is made to use the rigid conventions of information processing to impose order on the characteristically volatile and unpredictable phenomena encountered in the clinical setting, deep seated logical issues are uncovered. This challenge has generated the new field of Medical Informatics, one major goal of which is to formulate computer logics that can properly relate the idealized descriptions of disease, the rules for medical practice and the general guidelines for health care to the intricate diversities encountered in the care of individual patients. The Integrated Academic Information Management System (IAIMS) program of the National Library of Medicine provides the most ambitious environment for research in this new endeavor.
We present an overview of our 6-year experience in the design of expert systems for anatomic pathology. Our practical goal is to help practicing pathologists with learning, teaching, and the task of diagnosis by providing them with dynamic expert knowledge by means of a personal computer. This project could only be undertaken by first addressing a scientific goal: to characterize the problem-solving strategies that expert pathologists use in making a diagnosis and to state them in the logical terms of computer science. Our approach has been to build systems first for experimentation and then for use. The result of our work is an integrated computer-based approach that handles expert knowledge as formal relationships and morphologic images and that uses a number of logical strategies to provide multiple perspectives on diagnostic tasks. Configured as a pathologist's workstation, this approach can be expected to enhance the performance of trained general pathologists and pathologists in training. Lymph node pathology has been used as the prototype domain for this research, but care has been taken to seek a generalized authoring and inference structure that can be applied to other areas of pathology by changing the contents but not the structure itself. Excursions into various surgical pathology specialties suggest that the ways the system is constructed and exercised is fundamentally robust. Such computer-based expert systems can be expected to generate a new standard in the practice of pathology--based on the "gold standard" of classical morphology, but including the coordinated use of new methods from immunology and molecular biology in a multidisciplinary approach to diagnosis when these techniques are relevant. The benefits from this technology can be expected to be widespread with the evolution, refinement, and diffusion of these systems.
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We reviewed the clinical records of 33 patients with Immunoblastic Sarcoma in order to further describe this disease clinically. Several common features were found. Thirty percent of the patients had a history of a prior immune disease or lymphoproliferative malignancy. Forty-four percent of the patients tested had a diffuse hypergammaglobulinemia. Lymphopenia (less than 1,000/mm3) was found in 45%, and anemia occurred in 73%. At initial presentation, 30% of the cases were clinically staged as either stage I or II, whereas 70% were found to be stage III or IV. Forty-nine percent of the patients had systemic symptoms at presentation. The median survival was 14 months. Advanced stage of disease, lymphopenia, and presence of systemic symptomatology were associated with significantly decreased survival times (p less than .05). We conclude that IBS is a clinical entity often associated with prior immune disease and/or diffuse hypergammaglobulinemia.
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This study relateds the cytologic types of the classification of malignant lymphoma of Lukes and Collins to the results of immunologic surface marker studies as part of a systematic multiparameter study of 299 cases of non-Hodgkin lymphomas. The results support the hypothesis that malignant lymphomas are neoplasms of the immune system and involve the B- and T-cell systems and, rarely, histiocytes. The morphologic features of the cytologic types of Lukes and Collins are predictive of the subtypes of lymphoma and considerably more effective than the immunologic surface marker techniques in identifying homogeneous groups. There are considerable methodologic and interpretive problems that are evaluated in detail. The verification of the B- and T-cell subtypes of the Lukes and Collins classification indicates that the time has come to change from the terminology and classification of lymphomas of the past to a modern immunologic approach.
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The methotrexate (MTX)-plasma concentrations of 172 high-dose infusions over the range of 50-200 mg/kg were measured over the 72-hour period following the beginning of infusion. Pharmacokinetic analysis shows that a biexponential function adequately describes the plasma decay for all doses. The distribution of plasma clearances over the patient population at a given dose has been characterized by a biexponential clearance function and associated time-dependent variance. It is found that when each of the plasma clearance functions are scaled by their respective dose, the 1 SD bands about the resulting unit dose curves overlap throughout their time ranges and are therefore insignificantly different from one another. Thus, the plasma clearance over the 50-200-mg/kg range may be represented by a single dose-scalable biexponential model with half-lives of 1.8 +/- 0.1 and 8.4 +/- 0.5 hours. For a given maximum allowable plasma-MTX level (eg, 10(-5) M at 24 hours), the variance of the clearance distribution is shown to predict the expected fraction of patients who will require intensified rescue. Urinary clearance has been determined at 104 +/- 8 ml/minute over the dose range of 50-300 mg/kg and only 60% of the MTX was excreted in the urine by 72 hours.
A computer-based model of the pharmacokinetics of cytosine arabinoside (ara-C) and its active metabolite, ara-CTP, has been developed. This model, which is an intracellular extension of the Bischoff-Dedrick model of multi-organ pharmcokinetics gives predictions which are in agreement with the recent measurements of Chou et al on tissue concentrations of ara-CTP and Borsa et al on blood levels of ara-C. It is shown that the ara-CTP halving time in tissue is much greater than the ara-C halving time in blood because of low tissue levels of phosphatase. For a single dose at the LD10 level in mice, significant splenic DNA inhibition is calculated to occur for 26 hours, while the ara-C levels are negligible in 6 hours. The calculated duration of cytostatic effect at lower dosages (2.5 mg/kg) is 10 or 12 hours, while ara-C blood levels are negligible within 3 hours. Implications for cell kinetics and scheduling studies are also briefly described.
The clinical laboratory responds to a request for results by processing a specimen. The output is a report on a priority response. The role of the laboratory computer is that of a work allocation control system, which monitors and directs this intricate piecework activity. The operation is analogous to light industry. Effectiveness depends upon hardware reliability and internal laboratory control of the computer system.