Predictive Validity of the Braden Scale for Pressure Ulcer Risk in Elderly Residents of Long-Term Care Facilities

The aim of this study was to evaluate the predictive validity of the Braden Scale for Predicting Pressure Sore Risk in elderly residents of long-term care facilities (LTCFs) in Brazil. The determination of the cutoff score for the Brazilian population is important for the comparison between Brazilian and international studies and establishment of guidelines for prevention of pressure ulcers in our health care facilities. This is the first study of its kind in Brazil. This was a secondary analysis of a prospective cohort study conducted with 233 LTCF residents aged 60 and over who underwent complete skin examination and Braden Scale rating every 2 days for 3 months. Two groups of patients were considered: the total group (N = 233) and risk group (n = 94, total scores <= 18). Data from the first and last assessments were analyzed for sensitivity, specificity, and likelihood ratios. The best results were obtained for the total group, with cutoff scores of 18 and 17, sensitivity of 75.9% and 74.1%, specificity of 70.3% and 75.4%, and area under the receiver operating characteristic curve (AUC-ROC) of 0.79 and 0.81 at the first and last assessments, respectively. For the risk group, the cutoff scores of 16 (first assessment) and 13 (last assessment) were associated with a smaller AUC-ROC and, therefore, lower predictive accuracy. The Braden Scale showed good predictive validity in elderly LTCF residents. (Geriatr Nurs 2010;31:95-104)

Kernel machines for epilepsy diagnosis via EEG signal classification: A comparative study

Objective: We carry out a systematic assessment on a suite of kernel-based learning machines while coping with the task of epilepsy diagnosis through automatic electroencephalogram (EEG) signal classification. Methods and materials: The kernel machines investigated include the standard support vector machine (SVM), the least squares SVM, the Lagrangian SVM, the smooth SVM, the proximal SVM, and the relevance vector machine. An extensive series of experiments was conducted on publicly available data, whose clinical EEG recordings were obtained from five normal subjects and five epileptic patients. The performance levels delivered by the different kernel machines are contrasted in terms of the criteria of predictive accuracy, sensitivity to the kernel function/parameter value, and sensitivity to the type of features extracted from the signal. For this purpose, 26 values for the kernel parameter (radius) of two well-known kernel functions (namely. Gaussian and exponential radial basis functions) were considered as well as 21 types of features extracted from the EEG signal, including statistical values derived from the discrete wavelet transform, Lyapunov exponents, and combinations thereof. Results: We first quantitatively assess the impact of the choice of the wavelet basis on the quality of the features extracted. Four wavelet basis functions were considered in this study. Then, we provide the average accuracy (i.e., cross-validation error) values delivered by 252 kernel machine configurations; in particular, 40%/35% of the best-calibrated models of the standard and least squares SVMs reached 100% accuracy rate for the two kernel functions considered. Moreover, we show the sensitivity profiles exhibited by a large sample of the configurations whereby one can visually inspect their levels of sensitiveness to the type of feature and to the kernel function/parameter value. Conclusions: Overall, the results evidence that all kernel machines are competitive in terms of accuracy, with the standard and least squares SVMs prevailing more consistently. Moreover, the choice of the kernel function and parameter value as well as the choice of the feature extractor are critical decisions to be taken, albeit the choice of the wavelet family seems not to be so relevant. Also, the statistical values calculated over the Lyapunov exponents were good sources of signal representation, but not as informative as their wavelet counterparts. Finally, a typical sensitivity profile has emerged among all types of machines, involving some regions of stability separated by zones of sharp variation, with some kernel parameter values clearly associated with better accuracy rates (zones of optimality). (C) 2011 Elsevier B.V. All rights reserved.

Combination of Multiple Molecular Markers Can Improve Prognostication in Patients With Locally Advanced and Lymph Node Positive Bladder Cancer

Purpose: We tested whether the combination of 4 established cell cycle regulators (p53, pRB, p21 and p27) could improve the ability to predict clinical outcomes in a large multi-institutional collaboration of patients with pT3-4N0 or pTany Npositive urothelial carcinoma of the bladder. We also assessed whether the combination of molecular markers is superior to any individual biomarker. Materials and Methods: The study comprised 692 patients with pT3-4N0 or pTany Npositive urothelial carcinoma of the bladder treated with radical cystectomy and bilateral lymphadenectomy (median followup 5.3 years). Scoring was performed using advanced cell imaging and color detection software. The base model incorporated patient age, gender, stage, grade, lymphovascular invasion, number of lymph nodes removed, number of positive lymph nodes, concomitant carcinoma in situ and adjuvant chemotherapy. Results: Individual molecular markers did not improve the predictive accuracy for disease recurrence and cancer specific mortality. Combination of all 4 molecular markers into number of altered molecular markers resulted in significantly 1 higher predictive accuracy than any single biomarker (p < 0.001.). Moreover addition of number of altered molecular markers to the base model significantly improved the predictive accuracy for disease recurrence (3.9%, p < 0.001) and cancer specific mortality (4.3%, p < 0.001). Addition of number of altered molecular markers retained statistical significance for improving the prediction of clinical outcomes in the subgroup of patients with pT3N0 (280), pT4N0 (83) and pTany Npositive (329) disease (p < 0.001). Conclusions: While the status of individual molecular markers does not add sufficient value to outcome prediction in patients with advanced urothelial carcinoma of the bladder, combinations of molecular markers may improve molecular staging, prognostication and possibly prediction of response to therapy.

An investigation into feature construction to assist word sense disambiguation

Identifying the correct sense of a word in context is crucial for many tasks in natural language processing (machine translation is an example). State-of-the art methods for Word Sense Disambiguation (WSD) build models using hand-crafted features that usually capturing shallow linguistic information. Complex background knowledge, such as semantic relationships, are typically either not used, or used in specialised manner, due to the limitations of the feature-based modelling techniques used. On the other hand, empirical results from the use of Inductive Logic Programming (ILP) systems have repeatedly shown that they can use diverse sources of background knowledge when constructing models. In this paper, we investigate whether this ability of ILP systems could be used to improve the predictive accuracy of models for WSD. Specifically, we examine the use of a general-purpose ILP system as a method to construct a set of features using semantic, syntactic and lexical information. This feature-set is then used by a common modelling technique in the field (a support vector machine) to construct a classifier for predicting the sense of a word. In our investigation we examine one-shot and incremental approaches to feature-set construction applied to monolingual and bilingual WSD tasks. The monolingual tasks use 32 verbs and 85 verbs and nouns (in English) from the SENSEVAL-3 and SemEval-2007 benchmarks; while the bilingual WSD task consists of 7 highly ambiguous verbs in translating from English to Portuguese. The results are encouraging: the ILP-assisted models show substantial improvements over those that simply use shallow features. In addition, incremental feature-set construction appears to identify smaller and better sets of features. Taken together, the results suggest that the use of ILP with diverse sources of background knowledge provide a way for making substantial progress in the field of WSD.

A hybrid case adaptation approach for case-based reasoning

Case-Based Reasoning is a methodology for problem solving based on past experiences. This methodology tries to solve a new problem by retrieving and adapting previously known solutions of similar problems. However, retrieved solutions, in general, require adaptations in order to be applied to new contexts. One of the major challenges in Case-Based Reasoning is the development of an efficient methodology for case adaptation. The most widely used form of adaptation employs hand coded adaptation rules, which demands a significant knowledge acquisition and engineering effort. An alternative to overcome the difficulties associated with the acquisition of knowledge for case adaptation has been the use of hybrid approaches and automatic learning algorithms for the acquisition of the knowledge used for the adaptation. We investigate the use of hybrid approaches for case adaptation employing Machine Learning algorithms. The approaches investigated how to automatically learn adaptation knowledge from a case base and apply it to adapt retrieved solutions. In order to verify the potential of the proposed approaches, they are experimentally compared with individual Machine Learning techniques. The results obtained indicate the potential of these approaches as an efficient approach for acquiring case adaptation knowledge. They show that the combination of Instance-Based Learning and Inductive Learning paradigms and the use of a data set of adaptation patterns yield adaptations of the retrieved solutions with high predictive accuracy.

Predictive values of aspartate aminotransferase and gamma-glutamyl transferase for the hepatic accumulation of copper in cattle and buffalo

Ten cattle and 10 buffalo were divided into 2 groups (control [n = 8] and experimental [n = 12]) that received daily administration of copper. Three hepatic biopsies and blood samples were performed on days 0, 45, and 105. The concentration of hepatic copper was determined by spectrophotometric atomic absorption, and the activities of aspartate aminotransferase (AST) and gamma-glutamyl transferase (GGT) were analyzed. Regression analyses were done to verify the possible existing relationship between enzymatic activity and concentration of hepatic copper. Sensitivity, specificity, accuracy, and positive and negative predictive values were determined. The serum activities of AST and GGT had coefficients of determination that were excellent predictive indicators of hepatic copper accumulation in cattle, while only GGT serum activity was predictive of hepatic copper accumulation in buffalo. Elevated serum GGT activity may be indicative of increased concentrations of hepatic copper even in cattle and buffalo that appear to be clinically healthy. Thus, prophylactic measures can be implemented to prevent the onset of a hemolytic crisis that is characteristic of copper intoxication.

Predictive Validity of Waterlow Scale for Pressure Ulcer Development Risk in Hospitalized Patients

AIM: We sought to evaluate the predictive validity of the Waterlow Scale in hospitalized patients. SUBJECTS AND SETTING: The study was conducted at a general private hospital with 220 beds and a mean time of hospitalization of 7.4 days and a mean occupation rate of approximately 80%. Adult patients with a Braden Scale score of 18 or less and a Waterlow Scale score of 16 or more were studied. The sample consisted of 98 patients with a mean age of 71.1 +/- 15.5 years. METHODS: Skin assessment and scoring by using the Waterlow and Braden scales were completed on alternate days. Patients were examined at least 3 times to be considered for analysis. The data were submitted to sensitivity and specificity analysis by using receiver operating characteristic (ROC) curves and positive (+LR) and negative (-LR) likelihood ratios. RESULTS: The cutoff scores were 17, 20, and 20 in the first, second, and third assessment, respectively. Sensitivity was 71.4%, 85.7%, and 85.7% and specificity was 67.0%, 40.7%, and 32.9%, respectively. Analysis of the area under the ROC curve revealed good accuracy (0.64, 95% confidence interval [CI]: 0.35-0.93) only for the cutoff score 17 in the first assessment. The results also showed probabilities of 14%, 10%, and 9% for the development of pressure ulcer when the test results were positive (+LR) and of 3% (-LR) when the test results were negative for the cutoff scores in the first, second, and third assessment, respectively. CONCLUSION: The Waterlow Scale achieved good predictive validity in predicting pressure ulcer in hospitalized patients when a cutoff score of 17 was used in the first assessment.

Accuracy of magnetic resonance imaging for diagnosis and preoperative assessment of deeply infiltrating endometriosis

Objective: To evaluate the accuracy of preoperative magnetic resonance imaging (MRI) findings relative to surgical presence of deeply infiltrating endometriosis (DIE). Methods: This prospective study included 92 women with clinical suspicion of DIE. The MR images were compared with laparoscopy and pathology findings. Sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of MRI for diagnosis of DIE were assessed. Results: DIE was confirmed at histopathology in 77 of the 92 patients (83.7%). Sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of MRI to diagnose DIE at each of the specific sites evaluated were as follows: retrocervical space (89.4%, 92.3%, 96.7%, 77.4%, 90.2%); rectosigmoid (86.0%, 92.9%, 93.5%, 84.8%, 89.1%); bladder (23.1%, 100%,100%, 88.8%, 89.1%); ureters (50.0%, 100%, 95.5%, 95.7%); and vagina (72.7%, 100%, 100%, 96.4%, 96.7%). Conclusion: MRI demonstrates high accuracy in diagnosing DIE in the retrocervical region, rectosigmoid. bladder, ureters, and vagina. (C) 2009 International Federation of Gynecology and Obstetrics. Published by Elsevier Ireland Lid. All rights reserved.

Predictive models for diagnosis of pleural effusions secondary to tuberculosis or cancer

Background and objective: Tuberculosis (TB) and cancer are two of the main causes of pleural effusions which frequently share similar clinical features and pleural fluid profiles. This study aimed to identify diagnostic models based on clinical and laboratory variables to differentiate tuberculous from malignant pleural effusions. Methods: A retrospective study of 403 patients (200 with TB; 203 with cancer) was undertaken. Univariate analysis was used to select the clinical variables relevant to the models composition. Variables beta coefficients were used to define a numerical score which presented a practical use. The performances of the most efficient models were tested in a sample of pleural exudates (64 new cases). Results: Two models are proposed for the diagnosis of effusions associated with each disease. For TB: (i) adenosine deaminase (ADA), globulins and the absence of malignant cells in the pleural fluid; and (ii) ADA, globulins and fluid appearance. For cancer: (i) patient age, fluid appearance, macrophage percentage and presence of atypical cells in the pleural fluid; and (ii) as for (i) excluding atypical cells. Application of the models to the 64 pleural effusions showed accuracy higher than 85% for all models. Conclusions: The proposed models were effective in suggesting pleural tuberculosis or cancer.

Accuracy of Periapical Radiography and Cone-Beam Computed Tomography Scans in Diagnosing Apical Periodontitis Using Histopathological Findings as a Gold Standard

Introduction: The aim of this study was to evaluate the accuracy of two imaging methods in diagnosing apical periodontitis (AP) using histopathological findings as a gold standard. Methods: The periapex of 83 treated or untreated roots of dogs` teeth was examined using periapical radiography (PR), cone-beam computed tomography (CBCT) scans, and histology. Sensitivity, specificity, predictive values, and accuracy of PR and CBCT diagnosis were calculated. Results: PR detected AP in 71% of roots, a CBCT scan detected AP in 84%, and AP was histologically diagnosed in 93% (p = 0.001). Overall, sensitivity was 0.77 and 0.91 for PR and CBCT, respectively. Specificity was 1 for both. Negative predictive value was 0.25 and 0.46 for PR and CBCT, respectively. Positive predictive value was 1 for both. Diagnostic accuracy (true positives + true negatives) was 0.78 and 0.92 for PR and CBCT (p = 0.028), respectively. Conclusion: A CBCT scan was more sensitive in detecting AP compared with PR, which was more likely to miss AP when it was still present. (J Endod 2009;35:1009-1012)

Intrinsically Multivariate Predictive Genes

Canalizing genes possess such broad regulatory power, and their action sweeps across a such a wide swath of processes that the full set of affected genes are not highly correlated under normal conditions. When not active, the controlling gene will not be predictable to any significant degree by its subject genes, either alone or in groups, since their behavior will be highly varied relative to the inactive controlling gene. When the controlling gene is active, its behavior is not well predicted by any one of its targets, but can be very well predicted by groups of genes under its control. To investigate this question, we introduce in this paper the concept of intrinsically multivariate predictive (IMP) genes, and present a mathematical study of IMP in the context of binary genes with respect to the coefficient of determination (CoD), which measures the predictive power of a set of genes with respect to a target gene. A set of predictor genes is said to be IMP for a target gene if all properly contained subsets of the predictor set are bad predictors of the target but the full predictor set predicts the target with great accuracy. We show that logic of prediction, predictive power, covariance between predictors, and the entropy of the joint probability distribution of the predictors jointly affect the appearance of IMP genes. In particular, we show that high-predictive power, small covariance among predictors, a large entropy of the joint probability distribution of predictors, and certain logics, such as XOR in the 2-predictor case, are factors that favor the appearance of IMP. The IMP concept is applied to characterize the behavior of the gene DUSP1, which exhibits control over a central, process-integrating signaling pathway, thereby providing preliminary evidence that IMP can be used as a criterion for discovery of canalizing genes.

Accuracy of stone casts obtained by different impression materials

Several impression materials are available in the Brazilian marketplace to be used in oral rehabilitation. The aim of this study was to compare the accuracy of different impression materials used for fixed partial dentures following the manufacturers' instructions. A master model representing a partially edentulous mandibular right hemi-arch segment whose teeth were prepared to receive full crowns was used. Custom trays were prepared with auto-polymerizing acrylic resin and impressions were performed with a dental surveyor, standardizing the path of insertion and removal of the tray. Alginate and elastomeric materials were used and stone casts were obtained after the impressions. For the silicones, impression techniques were also compared. To determine the impression materials' accuracy, digital photographs of the master model and of the stone casts were taken and the discrepancies between them were measured. The data were subjected to analysis of variance and Duncan's complementary test. Polyether and addition silicone following the single-phase technique were statistically different from alginate, condensation silicone and addition silicone following the double-mix technique (p < .05), presenting smaller discrepancies. However, condensation silicone was similar (p > .05) to alginate and addition silicone following the double-mix technique, but different from polysulfide. The results led to the conclusion that different impression materials and techniques influenced the stone casts' accuracy in a way that polyether, polysulfide and addition silicone following the single-phase technique were more accurate than the other materials.

Accuracy of three electronic apex locators in the presence of different irrigating solutions

The present study compared the accuracy of three electronic apex locators (EALs) - Elements Diagnostic®, Root ZX® and Apex DSP® - in the presence of different irrigating solutions (0.9% saline solution and 1% sodium hypochlorite). The electronic measurements were carried out by three examiners, using twenty extracted human permanent maxillary central incisors. A size 10 K file was introduced into the root canals until reaching the 0.0 mark, and was subsequently retracted to the 1.0 mark. The gold standard (GS) measurement was obtained by combining visual and radiographic methods, and was set 1 mm short of the apical foramen. Electronic length values closer to the GS (± 0.5 mm) were considered as accurate measures. Intraclass correlation coefficients (ICCs) were used to verify inter-examiner agreement. The comparison among the EALs was performed using the McNemar and Kruskal-Wallis tests (p < 0.05). The ICCs were generally high, ranging from 0.8859 to 0.9657. Similar results were observed for the percentage of electronic measurements closer to the GS obtained with the Elements Diagnostic® and the Root ZX® EALs (p > 0.05), independent of the irrigating solutions used. The measurements taken with these two EALs were more accurate than those taken with Apex DSP®, regardless of the irrigating solution used (p < 0.05). It was concluded that Elements Diagnostic® and Root ZX® apex locators are able to locate the cementum-dentine junction more precisely than Apex DSP®. The presence of irrigating solutions does not interfere with the performance of the EALs.

Fine needle aspiration biopsy in the oral cavity and head and neck region

The objective of the current study was to evaluate the sensitivity, specificity and accuracy of fine needle aspiration biopsy (FNAB) of submucous nodules from the oral cavity and head and neck region as an auxiliary diagnostic tool. Fifty patients with nodule lesions in the oral cavity and the head and neck region were selected. All of them were submitted to FNAB and to either incisional or excisional biopsy. The diagnoses from the FNABs were compared with the biopsy diagnosis as the gold standard. All the cases of FNAB were analyzed by a single oral pathologist prior to the biopsy diagnosis. The results showed that the sensitivity of FNAB was 75%, its specificity was 96% and its accuracy was 58.8%. The false positive and false negative rates were 6.7% and 13.3%, respectively. The positive predictive value was 86% and the negative predictive value was 93%. The inconclusive rate was 16/50. FNAB displayed a high success rate for identifying both malignant and benign lesions, but a low accuracy for making a final diagnosis.

Microlithiasis of the gallbladder: role of endoscopic ultrasonography in patients with idiopathic acute pancreatitis

OBJECTIVES: Causes may be found in most cases of acute pancreatitis, however no etiology is found by clinical, biological and imaging investigations in 30% of these cases. Our objective was to evaluate results from endoscopic ultrasonography (EUS) for diagnosis of gallbladder microlithiasis in patients with unexplained (idiopathic) acute pancreatitis. METHODS: Thirty-six consecutive non-alcoholic patients with diagnoses of acute pancreatitis were studied over a five-year period. None of them showed signs of gallstones on transabdominal ultrasound or tomography. We performed EUS within one week of diagnosing acute pancreatitis. Diagnosis of gallbladder microlithiasis on EUS was based upon findings of hyperechoic signals of 0.5-3.0 mm, with or without acoustic shadowing. All patients (36 cases) underwent cholecystectomy, in accordance with indication from the attending physician or based upon EUS diagnosis. RESULTS: Twenty-seven patients (75%) had microlithiasis confirmed by histology and nine did not (25%). EUS findings were positive in twenty-five. Two patients had acute cholecystitis diagnosed at EUS that was confirmed by surgical and histological findings. In two patients, EUS showed cholesterolosis and pathological analysis disclosed stones not detected by EUS. EUS diagnosed microlithiasis in four cases not confirmed by surgical treatment. In our study, sensitivity, specificity and positive and negative predictive values to identify gallbladder microlithiasis (with 95% confidence interval) were 92.6% (74.2-98.7%), 55.6% (22.7-84.7%), 86.2% (67.4-95.5%) and 71.4% (30.3-94.9%), respectively. Overall EUS accuracy was 83.2%. CONCLUSIONS: EUS is a very reliable procedure to diagnose gallbladder microlithiasis and should be used for the management of patients with unexplained acute pancreatitis. This procedure should be part of advanced endoscopic evaluation.