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PubMed2026

Discrepancies in CPAK classification between CT and long-leg radiography: a systematic review and meta-analysis.

OBJECTIVE: To determine whether substantial differences in coronal plane alignment of the knee phenotype distribution, as well as systematic angular measurement discrepancies, exist between CT and long-leg radiography. MATERIALS AND METHODS: From February 2021 to April 2025, we searched PubMed, Embase, and the Cochrane Central Register of Controlled Trials for studies comparing CT- and long-leg radiography-derived coronal plane alignment classifications of the knee in patients with osteoarthritis. The primary outcome was distribution of coronal plane alignment phenotypes. Secondary outcomes included differences in medial proximal tibial angle, lateral distal femoral angle, arithmetic hip-knee-ankle angle, and joint line obliquity. RESULTS: Four studies (1,134 knees) were included. Compared with long-leg radiography-derived classification, CT-derived classification increased type I phenotypes (risk difference: 0.10; 95% confidence interval: 0.01-0.20; P = 0.040) and decreased type III (risk difference: -0.04; 95% confidence interval: -0.07 to -0.01; P = 0.020) and type V phenotypes (risk difference: -0.04; 95% confidence interval: -0.07 to -0.01; P = 0.004). CT yielded significantly lower medial proximal tibial angle (weighted mean difference: - 1.18°; P < 0.001), arithmetic hip-knee-ankle angle (weighted mean difference: - 0.95°; P < 0.001), and joint line obliquity (weighted mean difference: - 1.40°; P < 0.001) than long-leg radiography. Heterogeneity was high for type I phenotype (I2 = 81%), lateral distal femoral angle (I2 = 70%), and joint line obliquity (I2 = 69%). CONCLUSION: Discrepancies between CT-based software-generated and long-leg radiography-derived measurements substantially affect coronal plane alignment classification and angular parameters. Surgeons should consider these modality-specific variations and employ compensatory verification strategies to ensure optimal alignment.

Humans↗

PubMed2000

Intracranial pressure processing with artificial neural networks: classification of signal properties.

Intracranial pressure (ICP) is commonly used by neurosurgeons as a source of valuable information about the current condition of the neurosurgical patient. Nevertheless, despite years of effort, extracting clinically valuable information from the ICP signal is still problematical. Approaches, using current values of ICP, may fail to disclose imminent risk, because unpredictable factors can rapidly change the properties of the signal. An alternative approach is to determine some global characteristics of the signal within a longer time interval and such statistical analyses have been proposed by several authors. A further, rarely considered, problem is assessment of the results obtained from the point of view of their practical utility and/or such classification of the obtained properties of the signal that they correspond to certain clinical states of the patient. While this might be a typical task for discriminant analysis, we approached the analysis using an alternative methodology, that of computational intelligence, implemented in artificial neural networks (ANN). We tested two variants of the ANN algorithms for classification and discrimination of global properties of the ICP signal. In a "dynamic pattern classification" the network was presented with several sections of ICP records together with information from the expert-neurosurgeon, classifying 4 risk groups. In this mode no data pre-processing was carried out, in contrast to our second approach, in which the signal had been pre-processed using published statistical analyses and only these intermediate coefficients were fed into the ANN classifier. The results obtained with both classification methods at their current stage of training were similar and approximated to a 70% rate of judgements consistent with the expert scoring. Nevertheless, the method based on the assessment of global parameters from the ICP record looks more promising, because it leaves the possibility for modification of the set of parameters analysed. The new parameters may include information extracted not only from the ICP signal, but also from other diagnostic modalities, like colour coded Doppler ultrasonography. The ultimate goal of this work is to build up a pseudo-intelligent computer expert system, which would be able to reason from a reduced set of input information, available from a standard monitoring modality, because it had been taught salient links between these data and higher-order data, upon which expert scoring was based.

Cerebral Hemorrhage↗

PubMed2003

International Headache Society classification: new proposals about chronic headache.

In the International Headache Society (IHS) classification of 1988, chronic daily headache (CDH) forms are not exhaustively categorized. The forthcoming revision of the classification will include a number of CDH forms that had been reported prior to 1988 or have been identified after that date. In particular, chronic migraine will be added to the classification as a complication of migraine, provided that use of symptomatic drugs does not exceed 10 days per month. In addition to chronic cluster headache and chronic paroxysmal hemicrania, short-lasting unilateral neuralgiform headache with conjunctival injection and tearing (SUNCT) and hemicrania continua will be comprised among CDH forms with short-lived attacks. Hypnic headache will be included in Group 4 ("Other primary headaches"). No additions will be made to the new IHS classification for forms such as new daily persistent headache (NDPH) and cervicogenic headache as proposed by Sjaastad.

Chronic Disease↗

PubMed1989

Classifications of subjects with the language PROLOG.

The logical language PROLOG is used for the definition and characterization of groups of subjects. The groups are firstly defined by sets of variables with comparable scales. Secondly, the single members of the groups are characterized by logically structured combinations of variables which do not necessarily have comparable scales. The performance of the characterizations is estimated by determining the rates sensitivity and specificity. The new classification method is applied in a follow-up study including the assessment of the activity of 76 healthy subjects during two controlled experiments. The classification with PROLOG is then compared with the methods of logistic regression and with discriminant analysis. The comparisons demonstrate that, under similar conditions, the results of a classification with PROLOG parallel the results of statistically based classification procedures. In addition, PROLOG permits characterizations of single subjects based on variables from different scientific disciplines.

Cardiovascular Physiological Phenomena↗

PubMed2004

International Classification of Diseases-9th revision coding for preeclampsia: how accurate is it?

OBJECTIVE: The purpose of this study was to evaluate the accuracy of the International Classification of Diseases-9th revision codes for preeclampsia and eclampsia. STUDY DESIGN: The University of Illinois Medical Center at Chicago discharge database was used to identify 135 women from 1999 through 2001 whose disease was coded as having preeclampsia or eclampsia. With American College of Obstetrics and Gynecology criteria as the gold standard, the diagnosis that was determined through chart review was compared with the International Classification of Diseases-9th revision code that was present in the discharge database. Patients were classified as true cases if the International Classification of Diseases-9th revision code matched the American College of Obstetricians and Gynecologists diagnosis; the positive predictive value of the code was then calculated. RESULTS: The overall positive predictive value for the complete sample was only 54%, but the positive predictive value for severe preeclampsia was 84.8%, which was high compared with mild preeclampsia (45.3%) and eclampsia (41.7%). Diagnostic (clinician) error was the most common reason for miscoding error. CONCLUSION: The findings suggest that International Classification of Diseases-9th revision codes for preeclampsia/eclampsia vary greatly in their accuracy of diagnosis. Therefore, a review of medical records is required when data are being gathered on the incidence of preeclampsia and eclampsia.

Adolescent↗

PubMed2004

Results of a questionnaire regarding improvement of 'C' in the CEAP classification.

BACKGROUND: One of the shortcomings of the CEAP classification is that some of the clinical conditions in the original version were not defined and, therefore, were used in different ways by those who work with CEAP. AIM: To clarify the definitions of the seven clinical classes in the CEAP classification and to improve universal understanding of these in phlebology. METHODS: The authors prepared a short questionnaire regarding the 'C' part of CEAP with five main questions, dealing with definitions of clinical items: telangiectases, corona phlebectatica, reticular veins, varicose veins and the use of CEAP. The questionnaire was translated into 11 different languages and sent around the world by means of International Venous Digest by fax. Two hundred and six answers were received from 67 countries out of 3681 faxes sent (5.6%). RESULTS: There were a wide variety of opinions returned thus demonstrating that the same term is used with various meanings by different physicians. All physicians classify telangiectases of thigh and foot as class C1, but discrepant answers were obtained concerning the differences between reticular veins and reticular varicose veins as well as the diameter of small and large varicose veins. Sixty per cent of physicians answering this survey use the CEAP classification. CONCLUSION: Further clarification and refinement of the CEAP classification are necessary. The authors hope that this will result in broader acceptance of CEAP.

Humans↗

PubMed2006

Developing a saltmarsh classification tool for the European water framework directive.

The Water Framework Directive (WFD) identifies marine angiosperms (seagrasses and saltmarshes) as one of the biological elements used to classify water body status. This paper concentrates on the saltmarsh classification tools currently under development in the UK and RoI by the Marine Plants Task Team (MPTT) of the UK Technical Advisory Group (UK TAG). Saltmarsh classification is presently focusing on habitat extent, zonation and species diversity in order to fulfil the requirements of the WFD normative definitions. One of the many issues is that the natural rates of erosion and/or accretion differ between locations - this spatial and temporal natural variation is difficult to quantify; the tools and reference conditions developed will need to take this into consideration. To accurately quantify the classification boundaries and natural variability has posed a number of challenges; possible solutions are identified in this paper. Novel future classifications may also include saltmarsh ecosystem functioning (e.g., as a marine fish nursery) which may be further developed in an integrated saltmarsh tool.

Biodiversity↗

PubMed2005

Classification of bathing water quality based on the parametric calculation of percentiles is unsound.

Analyses of Irish bathing water quality data sets are reported to investigate whether the parametric calculations proposed in the draft Bathing Water Directive are valid. Faecal coliforms (assumed to be Escherichia coli) and faecal streptococci (assumed to be intestinal enterococci) have been analysed separately. It was noted that classifications based on the parametric 95th percentile calculations disagreed with those based on percentage compliance with the standards on 13.8% of occasions. When these disagreements were studied, it was found that the datasets frequently contained many censored data points (Result < 1). Also, the datasets were not log normally distributed on at least 85% of occasions. Both these findings fatally undermine the validity of using a parametric method for calculating 95th percentiles to classify bathing water quality. By contrast the non-parametric Hazen method is a better estimate of true population 95th percentiles, but essentially gives very similar classifications to the percentage compliance approach, fully agreeing on over 95% of occasions. The same is also true when considering 90th percentiles. A series of Monte Carlo studies were also conducted to determine the impact of small numbers. It was ascertained that small sample sizes are very undependable in determining bathing water classification and the parametric method in particular is particularly unreliable. In conclusion, the parametric method for calculating bathing water compliance is so severely and fatally flawed statistically that it should not form the basis of any legislation. The Hazen method gives a better estimate of true 90th or 95th percentiles, though as the resultant classifications agree with percentage compliance so closely it is doubtful that there is any statistical value in using a percentile approach over the long established and well understood percentage compliance approach.

Bathing Beaches↗

PubMed1997

A pattern classification procedure integrating the multivariate statistical analysis with neural networks.

A new procedure integrating multivariate statistical analysis with artificial neural networks (ANN) for complex pattern classification is proposed. Firstly, a specially designed statistical analysis algorithm called correlative component analysis (CCA) was used to identify the classification characteristics (CC) from original high-dimensional pattern information. These CC were then used as input data to the ANN for pattern classification. The proposed new procedure not only effectively decreased the dimensionality of original patterns, but also took advantage of the self-learning power of the ANN. Further, a typical example of classifying natural spearmint essence was employed to verify the effectiveness of the new pattern classification method. The study showed that this novel integrated procedure provides better results than those obtained using individual methods separately.

Algorithms↗

PubMed1995

A mathematically based classification of root canal curvatures on natural human teeth.

Testing of root canal-shaping instruments on natural human teeth has many difficulties, because of the different anatomical forms of root canals. There is a lack of an internationally accepted and mathematically based classification of root canal morphology. The aim of this study was to give a mathematical description of root canal forms with the help of differentiated geometrical pattern analysis and computer graphics. The measurements of 433 roots were conducted on isometric radiographs taken from the clinical view. Measured points of the same radiographs were approximated using fourth degree polynomial functions describing the imaginary axis of canals. The classification of root canal morphology on the basis of Schneider's angle differs from the classification of geometrical pattern analysis. Fourth-degree function approximation as a new method for the description of the shape of root canal curvatures seems to be exact and reliably repeatable. This type of classification of root canals is suitable for standardizing test specimens, including natural human teeth used for testing root forms: I (straight), J (apical curve), C (entirely curved), or S (multicurved).

Chi-Square Distribution↗

PubMed2001

ECG beat classification by a novel hybrid neural network.

This paper presents a novel hybrid neural network structure for the classification of the electrocardiogram (ECG) beats. Two feature extraction methods: Fourier and wavelet analyses for ECG beat classification are comparatively investigated in eight-dimensional feature space. ECG features are determined by dynamic programming according to the divergence value. Classification performance, training time and the number of nodes of the multi-layer perceptron (MLP), restricted Coulomb energy (RCE) and a novel hybrid neural network are comparatively presented. In order to increase the classification performance and to decrease the number of nodes, the novel hybrid structure is trained by the genetic algorithms (GAs). Ten types of ECG beats obtained from the MIT-BIH database and from a real-time ECG measurement system are classified with a success of 96% by using the hybrid structure.

Algorithms↗

PubMed2004

Automated linking of free-text complaints to reason-for-visit categories and International Classification of Diseases diagnoses in emergency department patient record databases.

STUDY OBJECTIVE: The use of the International Classification of Diseases system to describe emergency department (ED) case mix has disadvantages. We therefore developed computer algorithms that recognize a combination of words, word fragments, and word patterns to link free-text complaint fields to 20 reason-for-visit categories. We examine the feasibility and reliability of applying these reason-for-visit categories to ED patient-visit databases. METHODS: We analyzed a database (containing complaints and International Classification of Diseases diagnoses for 1 year's visits to a single ED) using a 3-step process (create initial terms, maximize sensitivity, maximize specificity) to define inclusion and exclusion terms for 20 reason-for-visit categories. To assess the reliability of the reason-for-visit assignment algorithm, we repeated the final 2 steps on a second database, composed of visits sampled from 21 EDs. For each database, we determined the prevalence of complaints that link to each reason-for-visit category and the distributions of International Classification of Diseases, Ninth Revision diagnoses that resulted for all patients and patients stratified by age. RESULTS: The 20 reason-for-visit categories capture 77% of all patients in database 1 (mean age 33.5 years) and 67% of all patients in database 2 (mean age 38.9 years). The percentage of visits captured by the 20 reason-for-visit categories, by age range, for databases 1 and 2 are (respectively) 0 to 2 years (84% and 76%), 3 to 10 years (82% and 74%), 11 to 65 years (76% and 68%), and 66 years or older (69% and 60%). The proportions of all complaints that link to each reason-for-visit category are largely similar between databases. Every complaint field that is linked to each reason-for-visit category includes at least 1 term that relates it to the category title, and the most frequently assigned diagnoses in each reason-for-visit category are those that one would expect to be associated with the reason-for-visit category complaints. CONCLUSION: The method by which free-text complaint fields are parsed into reason-for-visit categories is feasible and reasonably reliable; the finalized database 1 reason-for-visit category inclusion/exclusion terms lists required only modest changes to work well in database 2. The reason-for-visit categories used here are broadly defined to maximize the proportion of visits that they capture; more narrowly defined reason-for-visit categories will require more extensive revision of their inclusion/exclusion terms lists when used in different databases. A prospective, reason-for-visit-based ED classification system could have several useful applications (including syndromic surveillance), although content validity analysis will be necessary to investigate this hypothesis.

Adolescent↗

PubMed1997

Application of autonomous neural network systems to medical pattern classification tasks.

This paper presents a study of the application of autonomously learning multiple neural network systems to medical pattern classification tasks. In our earlier work, a hybrid neural network architecture has been developed for on-line learning and probability estimation tasks. The network has been shown to be capable of asymptotically achieving the Bayes optimal classification rates, on-line, in a number of benchmark classification experiments. In the context of pattern classification, however, the concept of multiple classifier systems has been proposed to improve the performance of a single classifier. Thus, three decision combination algorithms have been implemented to produce a multiple neural network classifier system. Here the applicability of the system is assessed using patient records in two medical domains. The first task is the prognosis of patients admitted to coronary care units; whereas the second is the prediction of survival in trauma patients. The results are compared with those from logistic regression models, and implications of the system as a useful clinical diagnostic tool are discussed.

Artificial Intelligence↗

PubMed2005

Problems associated with the classification and diagnosis of psychiatric disorders.

Several methodological issues of classification of psychiatric disorders are addressed. Beside some historical aspects and basic characteristics of the classification of mental disorders, the advantages and disadvantages of the syndromatological and nosological classifications are broadly described. Finally the current situation of the international standardisation of psychiatric classification and particuarly the improvement of reliability by using operationalised procedures is discussed.

Comorbidity↗

PubMed1998

The immunophenotype of adult acute myeloid leukemia: high frequency of lymphoid antigen expression and comparison of immunophenotype, French-American-British classification, and karyotypic abnormalities.

Immunophenotyping has become common in the diagnosis and classification of acute leukemias and is particularly important in the proper identification of cases of minimally differentiated acute myeloid leukemia (AML-M0). To evaluate the immunophenotype of adult AML, 106 cases were studied by cytochemical analysis and by flow cytometry with a panel of 22 antibodies. The results were compared with the French-American-British (FAB) Cooperative Group classification, as well as with available cytogenetic data on each case. CD45, CD33, and CD13 were the most commonly expressed antigens (97.2%, 95.3%, and 94.3%, respectively). Lymphoid-associated antigens were expressed in 48.1% of cases. CD20 was the most commonly expressed lymphoid antigen (17%), although often expressed in only a subpopulation of leukemic cells, followed by CD7 (16%), CD19 (9.8%), CD2 (7.5%), CD3 (6.7%), CD5 (4.8%), and CD10 (2.9%). Some immunophenotypes correlated with FAB type, including increased frequency of CD2 expression in AML-M3; lack of CD4, CD11c, CD36, CD117, and HLA-DR expression in AML-M3; increased frequency of CD20 and CD36 expression and lack of CD34 expression in AML-M5; increased frequency of CD5 expression in AML-M5a; and increased frequency of CD14 expression in AML-M5b, when compared with all other AMLs (P < .05). When compared with AML-M5b, AML-M5a demonstrated a lack of CD4 expression and a high frequency of CD117 expression. Complete morphologic and cytogenetic agreement between AML-M3 and t(15;17) was present, and four of five cases of AML-M4Eo demonstrated inv(16). The remaining case of M4Eo was characterized by a 6;9 translocation, and two other inv(16) cases were not classified as M4Eo. Expression of CD2 was present in two t(15;17) cases and in one inv(16) case, but expression of this antigen was not restricted to AML cases with these karyotypic abnormalities. Similarly, expression of CD19 was not specific for t(8;21) AML. All t(8;21) leukemias demonstrated M2 morphology. With the exception of M3, M4Eo, and a subgroup of M2 leukemias, the FAB classification does not appear to define cytogenetically distinct disease groups in adult AML. Immunophenotypically distinct profiles were identified in the M3 and M5 morphologic groups of the FAB classification. Immunophenotyping studies are helpful in the determination of myeloid lineage. In general, however, they are not sufficiently specific alone to be useful in precisely identifying either FAB or cytogenetically defined disease subtypes.

Acute Disease↗

PubMed2003

On the use of administrative databases to support planning activities: the case of the evaluation of neonatal case-mix in the Emilia-Romagna region using DRG and APR-DRG classification systems.

There are several versions of the Diagnosis Related Group (DRG) classification systems that are used for case-mix analysis, utilization review, prospective payment, and planning applications. The objective of this study was to assess the adequacy of two of these DRG systems--Medicare DRG and All Patient Refined DRG--to classify neonatal patients. The first part of the paper contains a descriptive analysis that outlines the major differences between the two systems in terms of classification logic and variables used in the assignment process. The second part examines the statistical performance of each system on the basis of the administrative data collected in all public hospitals of the Emilia-Romagna region relating to neonates discharged in 1997 and 1998. The Medicare DRG are less developed in terms of classification structure and yield a poorer statistical performance in terms of reduction in variance for length of stay. This is important because, for specific areas, a more refined system can prove useful at regional level to remove systematic biases in the measurement of case-mix due to the structural characteristics of the Medicare DRGs classification system.

Database Management Systems↗

PubMed1984

A lifespan study of classification preference.

Individuals between the ages of 4 and 70 were presented with a revised version of the Conceptual Styles Test. The number of similarity classifications was found to increase from the 4- to the 45- to 50-year-old group and to decrease thereafter; the number of complementary responses was found to decrease and then increase. The 20- to 25-year-old group used more perceptual similarity classifications, whereas the 35- to 40- and 45- to 50-year-old groups used more functional similarity classifications. One purpose of the study was to determine whether, as Kogan has suggested, elderly adults are more creative and free-wheeling in their classification responses than younger individuals. Two measures of creativity were employed; one was based on the experimenter's judgements and one based on the frequency with which the same response was given by other subjects. Neither measure indicated that the elderly individuals were more creative than the other age groups.

Adult↗

PubMed2005

The JCAHO patient safety event taxonomy: a standardized terminology and classification schema for near misses and adverse events.

BACKGROUND: The current US national discussions on patient safety are not based on a common language. This hinders systematic application of data obtained from incident reports, and learning from near misses and adverse events. OBJECTIVE: To develop a common terminology and classification schema (taxonomy) for collecting and organizing patient safety data. METHODS: The project comprised a systematic literature review; evaluation of existing patient safety terminologies and classifications, and identification of those that should be included in the core set of a standardized taxonomy; assessment of the taxonomy's face and content validity; the gathering of input from patient safety stakeholders in multiple disciplines; and a preliminary study of the taxonomy's comparative reliability. RESULTS: Elements (terms) and structures (data fields) from existing classification schemes and reporting systems could be grouped into five complementary root nodes or primary classifications: impact, type, domain, cause, and prevention and mitigation. The root nodes were then divided into 21 subclassifications which in turn are subdivided into more than 200 coded categories and an indefinite number of uncoded text fields to capture narrative information. An earlier version of the taxonomy (n = 111 coded categories) demonstrated acceptable comparability with the categorized data requirements of the ICU safety reporting system. CONCLUSIONS: The results suggest that the Joint Commission on Accreditation of Healthcare Organizations (JCAHO) Patient Safety Event Taxonomy could facilitate a common approach for patient safety information systems. Having access to standardized data would make it easier to file patient safety event reports and to conduct root cause analyses in a consistent fashion.

Causality↗