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PubMed1985

Outline for a comprehensive classification of retinal dystrophy and its consequences.

Classification of all relevant factors is a prerequisite to the formulation of specific objectives to attain goals of prevention of retinal dystrophy (RD) and effective provision of services. National and international agreement on a classification is sought. This outline stresses the importance of a sound conceptual basis. The root meaning of dystrophy (difficult nourishment), and the concepts given in the World Organization's International Classification of Impairments, Disabilities and Handicaps are emphasized. The proposed classification is designed to be statistical as well as assisting diagnosis and case management. The scheme for RD entities takes into account special features, in contrast to most treatable eye diseases. Genetics is stressed because of the importance of genetic counseling and rapid research advances. Three appendices illustrate portions of a comprehensive classification already in operation at the Retinal Dystrophy Service of NSW.

Disability Evaluation↗
PubMed1988

TNM classification of genitourinary tumours 1987--position of the EORTC Genitourinary Group.

This report analyses the changes in the classification of the genitourinary tumours introduced by the 1987 edition of the TNM system. Criticism and suggestions for improvement are given. These are based on the extensive experience of the EORTC GU Group with clinical trial work particularly the identification of prognostic factors, on their success in reaching international consensus on tumour classification, and on information from the literature. Many of the changes introduced in the 1987 system are not considered to be strictly necessary. These include the introduction of the new additional descriptors, including "C" and "R", the changes in the T classification of prostatic and renal cancer, and the introduction of uniform N categories for all tumours and other features. We regret the omission of minimal requirements, the omission of the V classification for macroscopic or microscopic vascular invasion, the changes in the T categories of carcinoma of the bladder and the introduction of stage groupings for all urological tumours. Some of these changes are considered unacceptable. The attitude of the EORTC GU Group toward the use of the new TNM classification is indicated in detail.

Female↗
PubMedDate not supplied

Classifications of epileptic syndromes: advantages and limitations for evaluation of childhood epileptic syndromes in clinical practice.

The advantages and limitations of the two most recent International League Against Epilepsy classifications of the epilepsies and epileptic syndromes have been assessed after examining the clinical records of 645 consecutive outpatients aged 1 month to 15 years followed at the Children's Epilepsy Center of the University of Milan, Italy, from 1977 through 1985. The percentage of cases that could be classified according to the 1970 and 1985 proposals for classification were 94.1 and 98.1%, respectively. According to the 1985 proposal, partial epilepsies (PE) and generalized epilepsies (GE) were almost equally represented (45.0 vs. 47.2%). Among PE, symptomatic epilepsies were the commonest variety. In the group of GE, idiopathic and/or symptomatic epilepsies were most common. Childhood absence epilepsy was the largest subgroup among idiopathic GE. Newly diagnosed patients, a less biased sample of the epileptic population represented 38.9% of the entire sample, and a proper classification was possible in 96% of cases. Idiopathic epilepsies were about twice as frequent and idiopathic and/or symptomatic GE less frequent in newly diagnosed patients when compared with the remainder. Marked differences in the frequency of the epilepsies were found in comparison with other reports in the literature which used the 1970 classification. This finding probably depends on different diagnostic assessment, selection bias, and different geographic and ethnic components, but it can also reflect the variable interpretation of the clinical and EEG features of a patient with epilepsy in the light of the artifactual categories of the classification.

Adolescent↗
PubMed1997

Recognition and classification of seizures in infants.

PURPOSE: We wished to assess the reliability of the International League Against Epilepsy (ILAE) seizure classification system applied to infantile seizures and to test a proposed new classification. METHODS: We first analyzed 39 seizures in 20 infants (aged 1-26 months) recorded with simultaneous closed-circuit television and EEG (CCTV/EEG). EEGs and videotapes of all seizures were independently analyzed by two epileptologists blinded to clinical histories. Videotapes of each seizure were reviewed without simultaneous EEG (phase 1), and printouts of ictal EEGs were assessed without behavioral correlates (phase II). The observers classified seizures according to ILAE criteria. Interrater agreement was assessed by the kappa statistic. RESULTS: Agreement on EEG features (phase II) was moderate (= 0.54) in identifying focal ictal onsets and substantial (= 0.79) in identifying generalized onsets. In contrast, analysis of videotapes showed substantial disagreement between observers in terms of classifying seizures as partial or generalized. Therefore, agreement between observers for partial was slight (= 0.14) and fair for generalized seizures (= 0.26). Similarly, conclusions of the observers as compared with those of a consensus panel were divergent for both partial (= 0.18) and generalized seizures (= 0.30). We therefore developed an alternative classification scheme and retested interrater agreement in a review of 50 seizures in 25 other infants. With this classification scheme, there was substantial agreement between observers (= 0.72). CONCLUSIONS: With clinical observations and interictal EEGs, seizures in infants cannot be reliably classified by current ILAE criteria. In contrast, a proposed new classification scheme based solely on semiology showed substantial reliability.

Age Factors↗
PubMed2000

Classification of psychiatric symptoms in patients with epilepsy.

Epilepsy is a neurological disorder, but many patients with epilepsy also have psychiatric symptoms. These symptoms and the underlying psychopathology vary considerably among patients, and the classification of these symptoms is disputed. Some classifications are based on the psychiatric symptomatology, the presence or absence of disturbance of consciousness, the EEG abnormalities, or the temporal relation between the symptoms and the seizures. The International Classification of Mental and Behavioral Disorders: Clinical Description and Diagnostic Guidelines (ICD-10) is accepted worldwide in psychiatry. The feasibility of classifying the psychiatric symptoms associated with the epilepsy according to the ICD-10 classification was studied. It was concluded that only symptoms in cases of epilepsy where there is a clear sensorium might be appropriately classified by the ICD-10. The classification of psychiatric symptoms in epilepsy needs further investigation.

Adult↗
PubMed1996

Limitations of tachycardia confirmation and rate classification algorithms in a third-generation implantable cardioverter defibrillator.

Newer ICDs provide antitachycardia (ATP) and bradycardia pacing and cardioversion and defibrillation shocks based on sensed interval criteria. The objectives of this investigation were to determine the algorithm related errors in tachycardia confirmation and rate classification that occurred in patients with a third-generation, noncommitted, tiered ICD therapy. Forty-three consecutive patients with the Guardian ATP 4210 ICD, which uses an X out of Y sensed interval counting algorithm for tachycardia detection, confirmation, and classification were studied. Surface ECGs, intracardiac electrograms, stored data logs, and sense histories were reviewed to diagnose errors due to these algorithms that resulted in delivery of inappropriate therapy or inhibition of appropriate therapy. Sixty-eight classification or confirmation algorithm errors from 7,610 tachycardia detections (< 1%) were diagnosed in 23 (53%) of 43 patients. Three types of errors not related to device or sensing lead malfunction or programming mistakes were seen. In 26 episodes, the confirmation algorithm failed to detect late tachycardia reversion of nonsustained tachyarrhythmias, on the last or next to last sensed interval, and did not inhibit ATP (n = 17) or shocks (n = 9). In 28 episodes, inaccurate classification of tachycardia rate resulted in inappropriate ATP (n = 23) or shock (n = 5) therapy. In 14 episodes, the posttherapy reconformation algorithm produced inhibition of VVI pacing and prolonged asystole following shock therapy. These errors in tachycardia confirmation and rate classification were due to the inherent limitations of the X out of Y counting algorithm.

Adult↗
PubMed2000

Automated classification of human atrial fibrillation from intraatrial electrograms.

The assessment of the degree of organization and the classification of atrial fibrillation (AF) according to the types defined by Wells usually resorts to the visual inspection of bipolar intraatrial electrograms. The focus of this study was to test seven parameters aimed to quantify the degree of organization of the electrograms, and then to design a final classification scheme based on a multidimensional, minimum-distance analysis. The following parameters were tested: mean atrial period (AP) and its coefficient of variation (CV); number of points lying at the baseline (NO) and the Shannon entropy (EN) of the amplitude probability density function (APDF); depolarization width (F-WIDTH); and correlation waveform analysis (CWA) and electrogram bandwidth (BW). The signal database consisted in a set of 160 AF strips of Type I, II, and III AF, scored by an expert cardiologist (60 Type I, 40 Type II, 60 Type III) and further divided in a training set (60) and a test set (100). Strips were 6 seconds long and were recorded with 5-mm interspace bipolar catheters from electrically induced (n = 13) and chronic (n = 10) patients. A classification algorithm based on a minimum-distance (Mahalanobis distance) discriminant analysis was tested. Using a single parameter, the best discriminations were provided by NO, F-WIDTH, and CV. F-WIDTH was found strongly inversely correlated to NO (r = -0.90). Of all the two-parameter combinations, CV-NO provided the best classification: 92 of 100 segments were correctly classified with sensitivity > 90% and specificity > 92%. A further improvement was obtained by including BW as a third parameter (93/100 correctly classified). The use of more than three parameters not only failed to improve, but even degraded the classification.

Algorithms↗
PubMed1995

Paroxysmal atrial fibrillation: a need for classification.

UNLABELLED: Classification of Atrial Fibrillation. INTRODUCTION: Clinical aspects of paroxysmal atrial fibrillation are heterogeneous. The attacks of atrial fibrillation may differ in their duration frequency and presence and severity of symptoms. Therefore, a proposal for a clinical classification of paroxysmal atrial fibrillation may be helpful. We tested a new classification system in a cohort of 51 consecutive hospitalized patients with paroxysmal atrial fibrillation. METHODS AND RESULTS: Paroxysmal atrial fibrillation was subdivided into three classes. Class I included a first attack of symptomatic atrial fibrillation either with spontaneous termination (IA) or requiring cardioversion because of poor tolerance (IB). Class II included recurrent attacks in untreated patients within three subgroups: IIA with no symptoms, IIB with < 1 symptomatic attack per 3-month period, and IIC > with 1 symptomatic attack per 3-month period. Class III included recurrent atrial fibrillation unresponsive to one or more antiarrhythmic agents for prevention of recurrences. Class III also consisted of three subgroups: IIIA with no or mild symptoms, IIIB with < 1 symptomatic attack per 3-month period, and IIIC with > 1 symptomatic attack per 3-month period. The criteria for paroxysmal atrial fibrillation (episode > 2 minutes and < 7 days in duration) were fulfilled by 51 patients (29 men, 22 women; mean age 61 +/- 14 years). Structural heart disease was present in 31 patients; the atrial fibrillation was idiopathic in 18 (35%). All 51 patients could be classified within the three classes and their subgroups: 14 patients (27%) in Class I, 13 (25%) in Class II, and 24 (47%) in Class III. The incidences of idiopathic atrial fibrillation were 21%, 30%, and 45% of the patients in Classes I, II, and III, respectively. CONCLUSIONS: Based on this new classification system, all hospitalized patients with paroxysmal atrial fibrillation could be classified. This classification may be useful to delineate better the clinical subgroups of patients with paroxysmal atrial fibrillation, to characterize better the patient population in future studies, and to improve treatment strategies.

Aged↗
PubMed2006

Potential advantages and limitations of applying the chronic kidney disease classification to kidney transplant recipients.

The National Kidney Foundation (NKF) Kidney Disease Outcomes Quality Initiative (K/DOQI) classification of Chronic Kidney Disease (CKD) characterizes patients by their level of kidney function and includes kidney transplant recipients (KTRs). Most KTRs have stage > or = 3 CKD (estimated glomerular filtration rate < 60 mL/min/1.73 m2) and may benefit from aggressive CKD care. Recent modifications to the K/DOQI CKD classification reflect the recognition of KTRs as a unique subset of CKD patients in whom the presentation, progression and implications of CKD may vary from those in nontransplant CKD populations. Currently, there is limited information about how adopting the CKD classification in KTRs will influence clinical management and outcomes. Appropriately designed studies are needed to develop transplant-specific CKD treatment recommendations, and to ensure patient, health provider and payer acceptance of the continued need for aggressive CKD care after transplantation. Education and implementation strategies will be required to ensure appropriate integration of the CKD classification and treatment guidelines into existing posttransplant care programs. The CKD classification thus represents an exciting potential strategy to improve clinical outcomes that should be adopted, further studied and modified to incorporate considerations unique to KTRs.

Cardiovascular Diseases↗
PubMed1995

Amelogenesis imperfecta--towards a new classification.

This editorial reviews the history of the classification of amelogenesis imperfecta (AI). The limitations of the existing classification systems are discussed. An alternative classification is proposed based upon the molecular defect, biochemical result, mode of inheritance and phenotype in the family involved. While not all of the criteria for the proposed classification can yet be addressed, this scheme is proposed for future classification of AI cases and families.

Amelogenesis Imperfecta↗
PubMed2004

Vardenafil improves erectile function in men with erectile dysfunction irrespective of disease severity and disease classification.

BACKGROUND: Vardenafil (Levitra) is a potent and selective phosphodiesterase 5 (PDE5) inhibitor used in the management of erectile dysfunction (ED). This retrospective subgroup analysis assessed the effectiveness of vardenafil treatment in men with ED of different baseline severity and disease classification. METHODS: Data from two pivotal, randomized, double-blind, placebo-controlled clinical trials enrolling men from the general ED population who received placebo or vardenafil 5 mg, 10 mg, or 20 mg during a 12-week treatment period were retrospectively analysed, stratifying by psychogenic, organic, and mixed ED disease classification as determined by the investigator. Efficacy endpoints included the International Index of Erectile Function (IIEF)-Erectile Function (EF) domain score, per-patient diary response rates to questions on penile insertion [Sexual Encounter Profile (SEP-2)] and maintenance of erection (SEP-3) and rates of positive response to the Global Assessment Question (GAQ). RESULTS: Data from 1,385 men who received at least one dose of study medication and had pre- and post-baseline measures of efficacy available (intent-to-treat population) are presented. At baseline 37-41% of patients had severe ED, 30-34% moderate, 22% mild-to-moderate and 6-8% mild ED. At baseline, 46-51% of patients were considered to have an organic cause for ED, 13-16% psychogenic ED, and 36-38% mixed classification of ED. For all classifications and for mild-to-moderate to severe ED, men treated with 10 or 20 mg of vardenafil showed statistically and clinically significant improvements (P < 0.001) in IIEF-EF scores, diary response rates to the SEP-2 and SEP-3 questions, and GAQ as compared with those given placebo. The greatest improvements relative to placebo were noted in patients with more severe ED. The most common treatment-emergent adverse events were headache, flushing, rhinitis, dyspepsia, and were dose-related, mostly mild to moderate in intensity and consistent with the class. CONCLUSIONS: Vardenafil improves EF in men with ED irrespective of investigator-determined classification and baseline ED severity.

3',5'-Cyclic-GMP Phosphodiesterases↗
PubMedDate not supplied

Administrative decision making: staff-patient ratios (a patient classification system for a psychiatric setting).

In this article, we have described a patient classification system in use at the C.F. Menninger Memorial Hospital. It is a type of factor evaluation, in which we use critical indicators or descriptors of care as units of measurement. Each critical indicator represents a grouping of nursing activities rather than concrete time measurement of each activity. The ten critical indicators of patient care needs and nursing activities which were identified were divided into two major categories: routine and extra. Each category was then subdivided to reflect a range or variation of care levels. This type of patient classification appears to have an advantage over other classification systems when applied to psychiatric nursing. The factor evaluations are broad enough in scope to allow inclusion of patient assessment, documentation, and use of the nursing process, while providing a measurement of psychological and psychosocial needs of the patient which are frequently absent in other classification systems that rely on task measurements or acuity levels alone. Because of its practicality it has been readily accepted by nurses working on psychiatric units, and the nurse administrator's effort to put a classification system in place has been made easier.

Activities of Daily Living↗
PubMedDate not supplied

Development and content validity testing of a comprehensive classification of diagnoses for pediatric nurse practitioners.

Pediatric nurse practitioners (PNPs) need an integrated, comprehensive classification that includes nursing, disease, and developmental diagnoses to effectively describe their practice. No such classification exists. Further, methodologic studies to help evaluate the content validity of any nursing taxonomy are unavailable. A conceptual framework was derived. Then 178 diagnoses from the North American Nursing Diagnosis Association (NANDA) 1986 list, selected diagnoses from the International Classification of Diseases, the Diagnostic and Statistical Manual, Third Revision, and others were selected. This framework identified and listed, with definitions, three domains of diagnoses: Developmental Problems, Diseases, and Daily Living Problems. The diagnoses were ranked using a 4-point scale (4 = highly related to 1 = not related) and were placed into the three domains. The rating scale was assigned by a panel of eight expert pediatric nurses. Diagnoses that were assigned to the Daily Living Problems domain were then sorted into the 11 Functional Health patterns described by Gordon (1987). Reliability was measured using proportions of agreement and Kappas. Content validity of the groups created was measured using indices of content validity and average congruency percentages. The experts used a new method to sort the diagnoses in a new way that decreased overlaps among the domains. The Developmental and Disease domains were judged reliable and valid. The Daily Living domain of nursing diagnoses showed marginally acceptable validity with acceptable reliability. Six Functional Health Patterns were judged reliable and valid, mixed results were determined for four categories, and the Coping/Stress Tolerance category was judged reliable but not valid using either test. There were considerable differences between the panel's, Gordon's (1987), and NANDA's clustering of NANDA diagnoses. This study defines the diagnostic practice of nurses from a holistic, patient-centered perspective. It is the first study to use quantitative methods to test a diagnostic classification system for nursing. The classification model could also be adapted for other nurse specialties.

Humans↗
PubMed2000

Automatic classification of protein sequences into structure/function groups via parallel cascade identification: a feasibility study.

A recent paper introduced the approach of using nonlinear system identification as a means for automatically classifying protein sequences into their structure/function families. The particular technique utilized, known as parallel cascade identification (PCI), could train classifiers on a very limited set of exemplars from the protein families to be distinguished and still achieve impressively good two-way classifications. For the nonlinear system classifiers to have numerical inputs, each amino acid in the protein was mapped into a corresponding hydrophobicity value, and the resulting hydrophobicity profile was used in place of the primary amino acid sequence. While the ensuing classification accuracy was gratifying, the use of (Rose scale) hydrophobicity values had some disadvantages. These included representing multiple amino acids by the same value, weighting some amino acids more heavily than others, and covering a narrow numerical range, resulting in a poor input for system identification. This paper introduces binary and multilevel sequence codes to represent amino acids, for use in protein classification. The new binary and multilevel sequences, which are still able to encode information such as hydrophobicity, polarity, and charge, avoid the above disadvantages and increase classification accuracy. Indeed, over a much larger test set than in the original study, parallel cascade models using numerical profiles constructed with the new codes achieved slightly higher two-way classification rates than did hidden Markov models (HMMs) using the primary amino acid sequences, and combining PCI and HMM approaches increased accuracy.

Algorithms↗
PubMed2001

Dependence of computer classification of clustered microcalcifications on the correct detection of microcalcifications.

Our purpose was to study the dependence of computer performance in classifying clustered microcalcifications as malignant or benign on the correct detection of microcalcifications. Specifically, we studied the effects of computer-detected true-positive microcalcifications and computer-detected false-positive microcalcifications in true microcalcification clusters. Using a database of 100 mammograms, we compared computer classification performance obtained from computer-detected microcalcifications to (1) computer classification performance obtained from manually identified microcalcifications, and (2) radiologists' performance. When an artificial neural network (ANN) was trained with manually identified microcalcifications, computer classification performance was comparable to or better than radiologists' performance as the number of computer-detected true-positive microcalcifications decreased to 40% and as the number of computer-detected false-positive microcalcifications increased to 50%. Further loss in computer-detected true-positive microcalcifications degraded classification performance substantially. Moreover, training the ANN with computer-detected microcalcifications also degraded computer classification performance. These results show that computer performance in classifying clustered microcalcifications as malignant or benign is insensitive to moderate decreases in computer-detected true-positive microcalcifications and moderate increases in computer-detected false-positive microcalcifications.

Breast Neoplasms↗
PubMed2003

Automated lung nodule classification following automated nodule detection on CT: a serial approach.

We have evaluated the performance of an automated classifier applied to the task of differentiating malignant and benign lung nodules in low-dose helical computed tomography (CT) scans acquired as part of a lung cancer screening program. The nodules classified in this manner were initially identified by our automated lung nodule detection method, so that the output of automated lung nodule detection was used as input to automated lung nodule classification. This study begins to narrow the distinction between the "detection task" and the "classification task." Automated lung nodule detection is based on two- and three-dimensional analyses of the CT image data. Gray-level-thresholding techniques are used to identify initial lung nodule candidates, for which morphological and gray-level features are computed. A rule-based approach is applied to reduce the number of nodule candidates that correspond to non-nodules, and the features of remaining candidates are merged through linear discriminant analysis to obtain final detection results. Automated lung nodule classification merges the features of the lung nodule candidates identified by the detection algorithm that correspond to actual nodules through another linear discriminant classifier to distinguish between malignant and benign nodules. The automated classification method was applied to the computerized detection results obtained from a database of 393 low-dose thoracic CT scans containing 470 confirmed lung nodules (69 malignant and 401 benign nodules). Receiver operating characteristic (ROC) analysis was used to evaluate the ability of the classifier to differentiate between nodule candidates that correspond to malignant nodules and nodule candidates that correspond to benign lesions. The area under the ROC curve for this classification task attained a value of 0.79 during a leave-one-out evaluation.

Adult↗
PubMed2004

Automatic detection and classification of hypodense hepatic lesions on contrast-enhanced venous-phase CT.

The objective of this work was to develop and validate algorithms for detection and classification of hypodense hepatic lesions, specifically cysts, hemangiomas, and metastases from CT scans in the portal venous phase of enhancement. Fifty-six CT sections from 51 patients were used as representative of common hypodense liver lesions, including 22 simple cysts, 11 hemangiomas, 22 metastases, and 1 image containing both a cyst and a hemangioma. The detection algorithm uses intensity-based histogram methods to find central lesions, followed by liver contour refinement to identify peripheral lesions. The classification algorithm operates on the focal lesions identified during detection, and includes shape-based segmentation, edge pixel weighting, and lesion texture filtering. Support vector machines are then used to perform a pair-wise lesion classification. For the detection algorithm, 80% lesion sensitivity was achieved at approximately 0.3 false positives (FP) per slice for central lesions, and 0.5 FP per slice for peripheral lesions, giving a total of 0.8 FP per section. For 90% sensitivity, the total number of FP rises to about 2.2 per section. The pair-wise classification yielded good discrimination between cysts and metastases (at 95% sensitivity for detection of metastases, only about 5% of cysts are incorrectly classified as metastases), perfect discrimination between hemangiomas and cysts, and was least accurate in discriminating between hemangiomas and metastases (at 90% sensitivity for detection of hemangiomas, about 28% of metastases were incorrectly classified as hemangiomas). Initial implementations of our algorithms are promising for automating liver lesion detection and classification.

Algorithms↗
PubMed2005

Automatic classification and speaker identification of African elephant (Loxodonta africana) vocalizations.

A hidden Markov model (HMM) system is presented for automatically classifying African elephant vocalizations. The development of the system is motivated by successful models from human speech analysis and recognition. Classification features include frequency-shifted Mel-frequency cepstral coefficients (MFCCs) and log energy, spectrally motivated features which are commonly used in human speech processing. Experiments, including vocalization type classification and speaker identification, are performed on vocalizations collected from captive elephants in a naturalistic environment. The system classified vocalizations with accuracies of 94.3% and 82.5% for type classification and speaker identification classification experiments, respectively. Classification accuracy, statistical significance tests on the model parameters, and qualitative analysis support the effectiveness and robustness of this approach for vocalization analysis in nonhuman species.

Acoustics↗