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A unified nursing diagnostic model.

The diagnostic model proposed in this article seeks to connect the taxonomic systems of the North American Diagnosis Association (NANDA) and the American Nurses Association (ANA). Pictured as an actual tree, the NANDA taxonomic labels are the roots; the ANA psychiatricmental health taxa, the supporting branches; the fruit, the NANDA diagnostic labels. A patient case vignette illustrates how the paradigm may be used as a clinical and research tool to validate each taxonomy, with the goal of creating a unified classification system for nursing phenomena.

American Nurses' Association

A diagnostic model and a test to assess word-finding skills in children.

There has been a diagnostic gap in the assessment of word-finding disorders in children. Although research in this area has continued to document strong correlations between word-finding skills and low reading achievement, dyslexia, language disorders, learning disabilities, and stuttering there have been no formal standardised measures for the assessment of word-finding skills in children. The purpose of this paper is to present: (1) a diagnostic model for the assessment of word finding; (2) a literature review that supports this model; (3) a formalised measure, the Test of Word Finding (TWF), which executes this diagnostic model for children. The assessment model includes variation in stimulus context (multiple naming sections); incorporates indices traditionally used to define word-finding problems in adults and children (accuracy, response time, response analysis and secondary characteristics); and provides for a comprehension assessment of naming errors. Components of this model are discussed with respect to stimulus context, target word frequency, nature of the target word and facilitating cues.

Child

A clinical diagnostic model for the assessment of asbestosis: a new algorithmic approach.

Asbestosis, one of the pneumoconioses that is defined by a set of clinical, radiographic, and pathologic findings, occurs as a result of exposure to asbestos fibers. Several approaches have attempted to describe the presence, progression, or extent of asbestosis. However, these approaches have attempted to describe the presence, progression, or extent of asbestosis. However, these approaches have limitations or lack correlations with other diagnostic modalities. We propose a comprehensive clinical diagnostic model that uses the sensitivities and specificities of the various clinical, radiographic, and pathologic findings to generate a set of "likelihood numbers." These likelihood numbers, contribute to the calculation of a value that can indicate the probability of asbestosis. The clinical diagnostic model is heuristic in that a specific feature supportive of the diagnosis of asbestosis may be tested as to its sensitivity and specificity, and new features may be added to the model. The model also indicates how probabilistic a given set of findings is in the diagnosis of asbestosis and suggests what additional data may make the diagnosis more or less statistically probable. Regarding the radiologic considerations of asbestosis, the strength of the clinical diagnostic model is that it is capable of supporting a diagnosis of asbestosis in the presence of a normal chest radiograph and, conversely, may reject the diagnosis of asbestosis despite the radiographic finding of pulmonary fibrosis.

Algorithms

Mathematical analysis of the API enteric 20 profile register using a computer diagnostic model.

Results for 21 biochemical tests using the API-20 Enteric kit were obtained from the manufacturer's files for 27,820 bacterial isolates. These isolates were identified by the API Profile Register and also by a computer diagnostic model which estimates the relative likelihoods of various identifications. The computer confirmed the identification in the API Profile Register for 99.36% of the isolates. The manufacturer has reviewed areas of the API Profile Register questioned by the computer analysis; a number of resulting modifications to the API Profile Register have been incorporated in an update letter. This computer model provides a convenient and powerful way to interpret a large number of test results for bacterial identification. This study also demonstrates the use of a large collection of isolates to refine the data matrix used by the diagnostic model.

Bacteriological Techniques

Acoustic neurinoma diagnostic model evaluation using decision support systems.

Three acoustic neurinoma (hereafter called acoustic neuroma) diagnostic models (Jenkins, Le Liever, Kaseff) were implemented as rule-based decision support systems and evaluated from the perspective of sensitivity, specificity, and US dollar cost, using a data base of 95 case histories suggestive of acoustic neuroma. The specificities of the models were equivalent (.97). The Jenkins model had the highest sensitivity (.96) and the highest average cost ($1470.99). The sensitivities and average costs of the Le Liever and Kaseff models were comparable (.84 vs. .82, and $1092.38 vs $1114.17, respectively). We observed that omitting brain-stem evoked response and electronystagmography testing from the Le Liever model subjected four (4.2%) more patients without acoustic neuroma to air contrast computed tomography, increased sensitivity to .89, and decreased the average cost to $774.75, without affecting specificity. We discuss the reasons for the slightly improved sensitivity and the impact of decision support systems on the clinician.

Decision Making

Diagnostic model for local temporal thermal change at the skin of the breast during extended application of diagnostic ultrasound.

A biophysical model is derived to account for the temporal thermal change at the skin of the breast as a result of ultrasound stimulation at the suspect lesion for seven minutes, with responses recorded using an infrared camera. Twenty-two patients were studied. The observed temporal responses for malignant cases have a different pattern from those of the benign cases studied and a mathematical model is used to investigate the controlling parameters. A new method is used to estimate the coefficients of the resulting difference equation which allows more useful diagnostic parameters to be computed than the corresponding continuous bioheat equation. The model is used to fit the experimental data. The results suggest that this method might be a rapid and noninvasive aid for distinguishing between benign and malignant breast tumours.

Biophysical Phenomena

Modeling diagnostic reasoning: a summary of parsimonious covering theory.

Parsimonious covering theory is a formal model of diagnostic reasoning. Diagnostic knowledge is represented in the theory as a network of causal associations, and problem-solving is represented in algorithms that support a hypothesize-and-test inference process. This paper summarizes in informal terms the basic ideas in parsimonious covering theory.

Algorithms

[Diagnostic models. 2. Fabrication].

After describing in Part I the preparation of diagnostic cast, the authors describe the Wax Up preparation. Most of the definition of centric relation agree that the position of the mandible is slightly behind its position in centric occlusion. The Hinge axis position is used for mounting the cast on articulator. The final restauration must reconstruct both position and the occlusion should be established in front the centric occlusion. After equilibration anterior guidance is studied and restaured if necessary. After creating the different curve of occlusion, the final Wax Up is settled. The use of the diagnostic cast so obtained will be presented in Part III.

Dental Articulators

[The use of rating scales for the study of diagnostic models: recognition of the uncertainties in classification principles].

In a cross cultural comparison of diagnostic concepts, we obtained from 45 expert italian psychiatrits symptom rating profiles, in terms of B.P.R.S., of the 12 most used diagnostic categories. While for 11 diagnostic concepts agreement was reasonably good, for cycloïd psychosis the variability of results supported the conclusion that this diagnostic concept is rather non specific among italian psychiatrists.

Cross-Cultural Comparison

Test selection in jaundice: a comparison between physician behavior and a diagnostic model.

The results of an observational study aimed at a formal assessment of clinicians' test-selection behavior are presented. We first make a proposal for diagnostic test usage in the latter phases of jaundice diagnosis. Next we compute a probabilistic estimate of the patient diagnosis, based on the COMIK algorithm. From the proposal and the probabilistic estimate we can predict the "test-selection behavior" of clinicians. The assessment follows from a tabulation of the predicted behavior against the tests selected by clinicians. It is shown that for most tests, the predictions are consistent with the observed test-selection behavior at a statistically significant level. Discussions of discrepancies between prediction and observation, and reasons for deviations from general guidelines, provide new dimensions for medical education. The methodology applied is a useful tool to improve medical care for the jaundiced patient.

Algorithms

Non-Newtonian rheology of leukemic blood and plasma: are n and k parameters of power law model diagnostic?

When discussing the rheological properties of normal and leukemic blood it must be considered that blood is a suspension of cells in aqueous solution which is also known as plasma. Whole blood viscosity and plasma viscosity were determined by Rheometer LS30 which allows measuring whole blood and plasma viscosity in the middle and low shear rate ranges. The measurements of the viscosity showed that whole blood and plasma behave as non-Newtonian power law fluid. The values of n (non-Newtonian index) and k (consistency index) of power law fluid were calculated for both leukemic blood and plasma samples. The importance of this phenomenon for the micro-circulation is discussed.

Adolescent

Derivation and validation of a clinical diagnostic model for chlamydial cervical infection in university women.

We developed and prospectively tested a logistic regression model for chlamydial cervical infection. Study subjects included 2271 women receiving gynecologic care in our student health clinic. Clinical data were collected in a standardized fashion. We identified cell culture--isolated Chlamydia trachomatis from 133 (9%) of 1458 subjects in the derivation set and 73 (10%) of 729 subjects in the validation set. Model variables included a new sexual partner within 2 months or more than one sexual partner within 6 months; cervical ectopy; cervical friability; at least 20 polymorphonuclear leukocytes per high-power field in cervical secretions; white blood cells in vaginal secretions; and use of an antibiotic active against C trachomatis within a month. This model can distinguish women with low, medium, and high risks of chlamydial infection (on derivation set: receiver operating characteristic curve area, 0.710; SE, 0.026; on validation set: area, 0.698; SE, 0.035) using simple clinical information obtained in the office.

Adolescent