A Diagnostic System Using Broad Categories With Clinicaly Relevant Specifiers: Lessons for ICD-10

A diagnostic system for ICD-11 is proposed which commences with broad reorganization and simplification of the current categories and the use of clinically relevant specifiers. Such changes have implications for the positioning of diagnostic groups and lead to a range of possibilities for improving terminology and the juxtaposition of individual conditions. The development of ICD-11 provides the first opportunity in almost two decades to improve the validity and reliability of the international classification system. Widespread change in broad categories and criteria cannot be justified by research that has emerged since the last revision. It would also be disruptive to clinical practice and might devalue past research work. However, the case for reorganization of the categories is stronger and has recently been made by an eminent international group of researchers (Andrews et al., 2009). A simpler, interlinked diagnostic system is proposed here which is likely to have fewer categories than its predecessor. There are major advantages of such a system for clinical practice and research and it could also produce much needed simplification for primary care (Gask et al., 2008) and the developing world (Wig, 1990; Kohn et al., 2004).

The validity of the MacNew Quality of Life Questionnaire in heart disease.

Background A previous review suggested that the MacNew Quality of Life Questionnaire was the most appropriate disease-specific measure of health-related quality of life among people with ischaemic heart disease. However, there is ambiguity about the allocation of items to the three factors underlying the MacNew and the factor structure has not been confirmed previously among the people in the UK. Methods The MacNew Questionnaire and the SF-36 were administered to 117 newly admitted patients to a tertiary referral centre in Northern Ireland. All patients had been diagnosed with ischaemic heart disease. Results A confirmatory factor analysis was conducted on the factor structure of the MacNew and the model was found to be an inadequate fit of the data. A quantitative and qualitative analysis of the items suggested that a five factor solution was more appropriate and this was validated by confirmatory factor analysis. This new structure also displayed strong evidence of concurrent validity when compared to the SF-36. Conclusion We recommend that researchers should submit scores obtained from items on the MacNew to secondary analyses after being grouped according to the factor structure proposed in this paper, in order to explore further the most appropriate grouping of items.

Can diagnostic triage by general practitioners or rheumatology nurses improve the positive predictive value of referrals to early arthritis clinics?

Objectives: To determine whether diagnostic triage by general practitioners (GPs) or rheumatology nurses (RNs) can improve the positive predictive value of referrals to early arthritis clinics (EACs).

Methods: Four GPs and two RNs were trained in the assessment of early in?ammatory arthritis (IA) by four visits to an EAC supervised by hospital rheumatologists. Patients referred to one of three EACs were recruited for study and assessed independently by a GP, an RN and one of six rheumatologists. Each assessor was asked to record their clinical ?ndings and whether they considered the patient to have IA. Each was then asked to judge the appropriateness of the referral according to predetermined guidelines. The rheumatologists had been shown previously to have a satisfactory level of agreement in the assessment of IA.

Results: Ninety-six patients were approached and all consented to take part in the study. In 49 cases (51%), the rheumatologist judged that the patient had IA and that the referral was appropriate. The assessments of GPs and RNs were compared with those of the rheumatologists. Levels of agreement were measured using the kappa value, where 1.0 represents total unanimity. The kappa value was
0.77 for the GPs when compared with the rheumatologists and 0.79 for the RNs. Signi?cant stiffness in the morning or after rest and objective joint swelling were the most important clinical features enabling the GPs and RNs to discriminate between IA and non-IA conditions.

Conclusion: Diagnostic triage by GPs or RNs improved the positive predictive value of referrals to an EAC with a degree of accuracy approaching that of a group of experienced rheumatologists.

The use of morphological characteristics and texture analysis in the identification of tissue composition in prostatic neoplasia

Quantitative examination of prostate histology offers clues in the diagnostic classification of lesions and in the prediction of response to treatment and prognosis. To facilitate the collection of quantitative data, the development of machine vision systems is necessary. This study explored the use of imaging for identifying tissue abnormalities in prostate histology. Medium-power histological scenes were recorded from whole-mount radical prostatectomy sections at × 40 objective magnification and assessed by a pathologist as exhibiting stroma, normal tissue (nonneoplastic epithelial component), or prostatic carcinoma (PCa). A machine vision system was developed that divided the scenes into subregions of 100 × 100 pixels and subjected each to image-processing techniques. Analysis of morphological characteristics allowed the identification of normal tissue. Analysis of image texture demonstrated that Haralick feature 4 was the most suitable for discriminating stroma from PCa. Using these morphological and texture measurements, it was possible to define a classification scheme for each subregion. The machine vision system is designed to integrate these classification rules and generate digital maps of tissue composition from the classification of subregions; 79.3% of subregions were correctly classified. Established classification rates have demonstrated the validity of the methodology on small scenes; a logical extension was to apply the methodology to whole slide images via scanning technology. The machine vision system is capable of classifying these images. The machine vision system developed in this project facilitates the exploration of morphological and texture characteristics in quantifying tissue composition. It also illustrates the potential of quantitative methods to provide highly discriminatory information in the automated identification of prostatic lesions using computer vision.

A novel diagnostic test detects a low frequency of the hemicentin Gln5345Arg variant among Northern Irish age related macular degeneration patients.

Purpose: Age related macular degeneration (AMD) is a common cause of severe vision loss. Identification of genes involved in AMD will facilitate early detection and ultimately help to identify pathways for treatment for this disorder. The A16,263G mutation in the HEMICENTIN-1 gene produces a non-conservative substitution of arginine for glutamine at codon 5345 which has been implicated in familial AMD. The aim of this study is to develop a rapid diagnostic assay for the detection of this mutation and to evaluate its frequency in a sample of AMD patients. Methods: A primer probe set was designed from exon 104 of the HEMICENTIN-1 gene to differentiate between mutant and wild type alleles. A region spanning the mutation was amplified by PCR using a LightCycler (Roche Diagnostic). The mutation was then detected by melt curve analysis of the hybrid formed between the PCR product and a specific fluorescent probe. The frequency of the mutation within the Northern Ireland population was evaluated by assaying 508 affected AMD patients, 25 possibly affected and 163 controls. Results: This assay clearly discriminates between the A16,263G mutant and wild type HEMICENTIN-1 alleles. The wild type sequence has a single base mismatch with the probe which decreases the stability of the hybrid, resulting in a lower TM (TM=51.27 °C) than that observed for the perfectly matched mutant allele (TM=59.9 °C). The mutant allele was detected in only one of the 696 subjects, an affected AMD patient. Conclusions: We describe a rapid assay for the genotyping of the Gln5345Arg mutation using real-time fluorescence PCR to facilitate rapid processing of samples through combined amplification and detection steps. These characteristics are suitable for a clinical setting where high throughput diagnostic procedures are required. The frequency of this mutation within the Northern Ireland population has been estimated at 0.2%, concurring with previous findings that this mutation is a rare variant associated with AMD. A rapid diagnostic assay will facilitate a reliable and convenient evaluation of the frequency of the Gln5345Arg mutation and its association with AMD within other populations.

Computer usage and the validity of self-assessed computer competence among first-year business students

Abstract This study evaluates the reliability of self-assessment as a measure of computer competence. This evaluation is carried out in response to recent research which has employed self-reported ratings as the sole indicator of students’ computer competence. To evaluate the reliability of self-assessed computer competence, the scores achieved by students in self-assessed computer competence tests are compared with scores achieved in objective tests. The results reveal a statistically significantly over-estimation of computer competence among the students surveyed. Furthermore, reported pre-university computer experience in terms of home and school use and formal IT education does not affect this result. The findings call into question the validity of using self-assessment as a measure of computer competence. More generally, the study also provides an up-to-date picture of self-reported computer usage and IT experience among pre-university students from New Zealand and South-east Asia and contrasts these findings with those from previous research.

Computerised Diagnostic Decision Support System for the Classification of Pre-Invasive Cervical Squamous Lesions.

Previous studies have revealed considerable interobserver and intraobserver variation in the histological classification of preinvasive cervical squamous lesions. The aim of the present study was to develop a decision support system (DSS) for the histological interpretation of these lesions. Knowledge and uncertainty were represented in the form of a Bayesian belief network that permitted the storage of diagnostic knowledge and, for a given case, the collection of evidence in a cumulative manner that provided a final probability for the possible diagnostic outcomes. The network comprised 8 diagnostic histological features (evidence nodes) that were each independently linked to the diagnosis (decision node) by a conditional probability matrix. Diagnostic outcomes comprised normal; koilocytosis; and cervical intraepithelial neoplasia (CIN) 1, CIN II, and CIN M. For each evidence feature, a set of images was recorded that represented the full spectrum of change for that feature. The system was designed to be interactive in that the histopathologist was prompted to enter evidence into the network via a specifically designed graphical user interface (i-Path Diagnostics, Belfast, Northern Ireland). Membership functions were used to derive the relative likelihoods for the alternative feature outcomes, the likelihood vector was entered into the network, and the updated diagnostic belief was computed for the diagnostic outcomes and displayed. A cumulative probability graph was generated throughout the diagnostic process and presented on screen. The network was tested on 50 cervical colposcopic biopsy specimens, comprising 10 cases each of normal, koilocytosis, CIN 1, CIN H, and CIN III. These had been preselected by a consultant gynecological pathologist. Using conventional morphological assessment, the cases were classified on 2 separate occasions by 2 consultant and 2 junior pathologists. The cases were also then classified using the DSS on 2 occasions by the 4 pathologists and by 2 medical students with no experience in cervical histology. Interobserver and intraobserver agreement using morphology and using the DSS was calculated with K statistics. Intraobserver reproducibility using conventional unaided diagnosis was reasonably good (kappa range, 0.688 to 0.861), but interobserver agreement was poor (kappa range, 0.347 to 0.747). Using the DSS improved overall reproducibility between individuals. Using the DSS, however, did not enhance the diagnostic performance of junior pathologists when comparing their DSS-based diagnosis against an experienced consultant. However, the generation of a cumulative probability graph also allowed a comparison of individual performance, how individual features were assessed in the same case, and how this contributed to diagnostic disagreement between individuals. Diagnostic features such as nuclear pleomorphism were shown to be particularly problematic and poorly reproducible. DSSs such as this therefore not only have a role to play in enhancing decision making but also in the study of diagnostic protocol, education, self-assessment, and quality control. (C) 2003 Elsevier Inc. All rights reserved.