Classification of platelet concentrates (Platelet-Rich Plasma-PRP, Platelet-Rich Fibrin-PRF) for topical and infiltrative use in orthopedic and sports medicine: current consensus, clinical implications and perspectives.

Platelet concentrates for topical and infiltrative use - commonly termed Platetet-Rich Plasma (PRP) or Platelet-Rich Fibrin (PRF) - are used or tested as surgical adjuvants or regenerative medicine preparations in most medical fields, particularly in sports medicine and orthopaedic surgery. Even if these products offer interesting therapeutic perspectives, their clinical relevance is largely debated, as the literature on the topic is often confused and contradictory. The long history of these products was always associated with confusions, mostly related to the lack of consensual terminology, characterization and classification of the many products that were tested in the last 40 years. The current consensus is based on a simple classification system dividing the many products in 4 main families, based on their fibrin architecture and cell content: Pure Platelet-Rich Plasma (P-PRP), such as the PRGF-Endoret technique; Leukocyte- and Platelet-Rich Plasma (LPRP), such as Biomet GPS system; Pure Platelet-Rich Fibrin (P-PRF), such as Fibrinet; Leukocyte- and Platelet-Rich Fibrin (L-PRF), such as Intra-Spin L-PRF. The 4 main families of products present different biological signatures and mechanisms, and obvious differences for clinical applications. This classification serves as a basis for further investigations of the effects of these products. Perspectives of evolutions of this classification and terminology are also discussed, particularly concerning the impact of the cell content, preservation and activation on these products in sports medicine and orthopaedics.

Effect of Pulmonary Hypertension Hemodynamic Presentation on Clinical Outcomes in Patients With Severe Symptomatic Aortic Valve Stenosis Undergoing Transcatheter Aortic Valve Implantation: Insights From the New Proposed Pulmonary Hypertension Classification.

BACKGROUND Pulmonary hypertension (PH) frequently coexists with severe aortic stenosis, and PH severity has been shown to predict outcomes after transcatheter aortic valve implantation (TAVI). The effect of PH hemodynamic presentation on clinical outcomes after TAVI is unknown. METHODS AND RESULTS Of 606 consecutive patients undergoing TAVI, 433 (71.4%) patients with severe aortic stenosis and a preprocedural right heart catheterization were assessed. Patients were dichotomized according to whether PH was present (mean pulmonary artery pressure, ≥25 mm Hg; n=325) or not (n=108). Patients with PH were further dichotomized by left ventricular end-diastolic pressure into postcapillary (left ventricular end-diastolic pressure, >15 mm Hg; n=269) and precapillary groups (left ventricular end-diastolic pressure, ≤15 mm Hg; n=56). Finally, patients with postcapillary PH were divided into isolated (n=220) and combined (n=49) subgroups according to whether the diastolic pressure difference (diastolic pulmonary artery pressure-left ventricular end-diastolic pressure) was normal (<7 mm Hg) or elevated (≥7 mm Hg). Primary end point was mortality at 1 year. PH was present in 325 of 433 (75%) patients and was predominantly postcapillary (n=269/325; 82%). Compared with baseline, systolic pulmonary artery pressure immediately improved after TAVI in patients with postcapillary combined (57.8±14.1 versus 50.4±17.3 mm Hg; P=0.015) but not in those with precapillary (49.0±12.6 versus 51.6±14.3; P=0.36). When compared with no PH, a higher 1-year mortality rate was observed in both precapillary (hazard ratio, 2.30; 95% confidence interval, 1.02-5.22; P=0.046) and combined (hazard ratio, 3.15; 95% confidence interval, 1.43-6.93; P=0.004) but not isolated PH patients (P=0.11). After adjustment, combined PH remained a strong predictor of 1-year mortality after TAVI (hazard ratio, 3.28; P=0.005). CONCLUSIONS Invasive stratification of PH according to hemodynamic presentation predicts acute response to treatment and 1-year mortality after TAVI.

ICD-9-CM : International classification of diseases, 9th revision, clinical modification, third edition, volumes 1 and 2 : official authorized addendum, effective October 1, 1989.

Cover title.

Using secondary knowledge to support decision tree classification of retrospective clinical data

Retrospective clinical data presents many challenges for data mining and machine learning. The transcription of patient records from paper charts and subsequent manipulation of data often results in high volumes of noise as well as a loss of other important information. In addition, such datasets often fail to represent expert medical knowledge and reasoning in any explicit manner. In this research we describe applying data mining methods to retrospective clinical data to build a prediction model for asthma exacerbation severity for pediatric patients in the emergency department. Difficulties in building such a model forced us to investigate alternative strategies for analyzing and processing retrospective data. This paper describes this process together with an approach to mining retrospective clinical data by incorporating formalized external expert knowledge (secondary knowledge sources) into the classification task. This knowledge is used to partition the data into a number of coherent sets, where each set is explicitly described in terms of the secondary knowledge source. Instances from each set are then classified in a manner appropriate for the characteristics of the particular set. We present our methodology and outline a set of experiential results that demonstrate some advantages and some limitations of our approach. © 2008 Springer-Verlag Berlin Heidelberg.

Classification and clinical behavior of blastic plasmacytoid dendritic cell neoplasms according to their maturation-associated immunophenotypic profile

Blastic plasmacytoid dendritic cell neoplasm (BPDCN) is a rare subtype of leukemia/lymphoma, whose diagnosis can be difficult to achieve due to its clinical and biological heterogeneity, as well as its overlapping features with other hematologic malignancies. In this study we investigated whether the association between the maturational stage of tumor cells and the clinico-biological and prognostic features of the disease, based on the analysis of 46 BPDCN cases classified into three maturation-associated subgroups on immunophenotypic grounds. Our results show that blasts from cases with an immature plasmacytoid dendritic cell (pDC) phenotype exhibit an uncommon CD56- phenotype, coexisting with CD34+ non-pDC tumor cells, typically in the absence of extramedullary (e.g. skin) disease at presentation. Conversely, patients with a more mature blast cell phenotype more frequently displayed skin/extramedullary involvement and spread into secondary lymphoid tissues. Despite the dismal outcome, acute lymphoblastic leukemia-type therapy (with central nervous system prophylaxis) and/or allogeneic stem cell transplantation appeared to be the only effective therapies. Overall, our findings indicate that the maturational profile of pDC blasts in BPDCN is highly heterogeneous and translates into a wide clinical spectrum -from acute leukemia to mature lymphoma-like behavior-, which may also lead to variable diagnosis and treatment.

Advancing Bag-of-visual-words Representations For Lesion Classification In Retinal Images.

Diabetic Retinopathy (DR) is a complication of diabetes that can lead to blindness if not readily discovered. Automated screening algorithms have the potential to improve identification of patients who need further medical attention. However, the identification of lesions must be accurate to be useful for clinical application. The bag-of-visual-words (BoVW) algorithm employs a maximum-margin classifier in a flexible framework that is able to detect the most common DR-related lesions such as microaneurysms, cotton-wool spots and hard exudates. BoVW allows to bypass the need for pre- and post-processing of the retinographic images, as well as the need of specific ad hoc techniques for identification of each type of lesion. An extensive evaluation of the BoVW model, using three large retinograph datasets (DR1, DR2 and Messidor) with different resolution and collected by different healthcare personnel, was performed. The results demonstrate that the BoVW classification approach can identify different lesions within an image without having to utilize different algorithms for each lesion reducing processing time and providing a more flexible diagnostic system. Our BoVW scheme is based on sparse low-level feature detection with a Speeded-Up Robust Features (SURF) local descriptor, and mid-level features based on semi-soft coding with max pooling. The best BoVW representation for retinal image classification was an area under the receiver operating characteristic curve (AUC-ROC) of 97.8% (exudates) and 93.5% (red lesions), applying a cross-dataset validation protocol. To assess the accuracy for detecting cases that require referral within one year, the sparse extraction technique associated with semi-soft coding and max pooling obtained an AUC of 94.2 ± 2.0%, outperforming current methods. Those results indicate that, for retinal image classification tasks in clinical practice, BoVW is equal and, in some instances, surpasses results obtained using dense detection (widely believed to be the best choice in many vision problems) for the low-level descriptors.

Vascular Pattern In Enchondroma And Chondrosarcoma: Clinical And Immunohistologic Study.

Although cartilaginous tumors have low microvascular density, vessels are important for the provision of nutrition so that the tumor can grow and generate metastasis. The aim of this study was to assess the value of the vascular pattern classification as a prognostic tool in chondrosarcomas (CSs) and its relation with vascular endothelial growth factor (VEGF) expression. This was a retrospective study of 21 enchondromas and 57 conventional CSs. Clinical data and outcome were retrieved from medical files. CSs histologic grades (on a scale of 1 to 3) were determined according to the World Health Organization classification. The vascular pattern (on a scale of A to C) was assessed through CD34, according to Kalinski. CD105 and VEGF were also evaluated. Poor outcome was significantly associated with vascular pattern groups B and C. Higher vascular pattern were 6.5 times more frequent in moderate-grade and high-grade CSs than in grade 1 CS. On multivariate analysis, a clear correlation was found between VEGF overexpression and B/C vascular patterns. Only 18 (benign and malignant) tumors stained for CD105. The results point to the use of the vascular pattern classification as a prognostic tool in CSs and to differentiate low-grade from moderate-grade/high-grade CSs. Vascular pattern might be also used to complement histologic grade, VEGF immunostaining, and microvascular density, for indicating a patient's prognosis. Low-grade CSs develop under low neoangiogenesis, which conforms to the slow growth rate of these tumors.

[the New Classification Of Breast Cancers: Finding The Luminal A].

To compare the distributions of patients with clinical-pathological subtypes of luminal B-like breast cancer according to the 2011 and 2013 St. Gallen International Breast Cancer Conference Expert Panel. We studied 142 women with breast cancer who were positive to estrogen receptor and had been treated in São Paulo state, southeast Brazil. The expression of the following receptors was assessed by immunohistochemistry: estrogen, progesterone (PR) and Ki-67. The expression of HER-2 was measured by fluorescent in situ hybridization analysis in tissue microarray. There were 29 cases of luminal A breast cancers according to the 2011 St. Gallen International Breast Cancer Conference Expert Panel that were classified as luminal B-like in the 2013 version. Among the 65 luminal B-like breast cancer cases, 29 (45%) were previous luminal A tumors, 15 cases (20%) had a Ki-67 >14% and were at least 20% PR positive and 21 cases (35%) had Ki-67 >14% and more than 20% were PR positive. The 2013 St. Gallen consensus updated the definition of intrinsic molecular subtypes and increased the number of patients classified as having luminal B-like breast cancer in our series, for whom the use of cytotoxic drugs will probably be proposed with additional treatment cost.

Mucin pattern reflects the origin of the adenocarcinoma in Barrett's esophagus: a retrospective clinical and laboratorial study

Background: Mucin immunoexpression in adenocarcinoma arising in Barrett's esophagus (BE) may indicate the carcinogenesis pathway. The aim of this study was to evaluate resected specimens of adenocarcinoma in BE for the pattern of mucins and to correlate to the histologic classification. Methods: Specimens were retrospectively collected from thirteen patients who underwent esophageal resection due to adenocarcinoma in BE. Sections were scored for the grade of intestinal metaplasia. The tissues were examined by immunohistochemistry for MUC2 and MUC5AC antibodies. Results: Eleven patients were men. The mean age was 61 years old (varied from 40 to 75 years old). The tumor size had a mean of 4.7 +/- 2.3 cm, and the extension of BE had a mean of 7.7 +/- 1.5 cm. Specialized epithelium with intestinal metaplasia was present in all adjacent mucosas. Immunohistochemistry for MUC2 showed immunoreactivity in goblet cells, while MUC5AC was extensively expressed in the columnar gastric cells, localizing to the surface epithelium and extending to a variable degree into the glandular structures in BE. Tumors were classified according to the mucins in gastric type in 7/13 (MUC5AC positive) and intestinal type in 4/13 (MUC2 positive). Two tumors did not express MUC2 or MUC5AC proteins. The pattern of mucin predominantly expressed in the adjacent epithelium was associated to the mucin expression profile in the tumors, p = 0.047. Conclusion: Barrett's esophagus adenocarcinoma shows either gastric or intestinal type pattern of mucin expression. The two types of tumors developed in Barrett's esophagus may reflect the original cell type involved in the malignant transformation.

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.

Upper limb assessment in tetraplegia: clinical, functional and kinematic correlations

The aim of this study was to correlate clinical and functional evaluations with kinematic variables of upper limp reach-to-grasp movement in patients with tetraplegia. Twenty chronic patients were selected to perform reach-to-grasp kinematic assessment using a target placed at a distance equal to the arm`s length. Kinematic variables (hand peak velocity, movement time, percent time-to-maximal velocity, index of curvature, number of peaks, and joint range of motion) were correlated to clinical (Standard Neurological Classification of Spinal Cord Injury-American Spinal Injury Association) and functional [Functional Independence Measure (FIM) and Spinal Cord Independence Measure II (SCIM II)) evaluation scores. Twenty control participants were also selected to obtain normal reference parameters. There was a positive correlation between total motor index and FIM (r=0.6089; P=0.0044) and SCIM II (r=0.5229; P=0.018). Both functional scores showed positive correlation with each other (r=0.8283; P<0.0001). A correlation was also observed between the right and left motor indices, the motor AM, and the SCIM II in most of the reach-to-grasp kinematic variables studied (hand peak velocity, movement time, index of curvature, and number of peaks). In contrast, for the joint range of motion (shoulder, elbow, and wrist), only the wrist in the horizontal plane showed correlation with clinical variables. This study shows that muscle strength assessed by the American Spinal Injury Association motor index influences the reach-to-grasp kinematic variables of patients with tetraplegia. However, the functional assessments did not present the same influence.

A Brazilian registry of juvenile dermatomyositis: onset features and classification of 189 cases

Objective To describe onset features, classification and treatment of juvenile dermatomyositis (JDM) and juvenile polymyositis (JPM) from a multicentre registry. Methods Inclusion criteria were onset age lower than 18 years and a diagnosis of any idiopathic inflammatory myopathy (IIM) by attending physician. Bohan & Peter (1975) criteria categorisation was established by a scoring algorithm to define JDM and JPM based oil clinical protocol data. Results Of the 189 cases included, 178 were classified as JDM, 9 as JPM (19.8: 1) and 2 did not fit the criteria; 6.9% had features of chronic arthritis and connective tissue disease overlap. Diagnosis classification agreement occurred in 66.1%. Medial? onset age was 7 years, median follow-up duration was 3.6 years. Malignancy was described in 2 (1.1%) cases. Muscle weakness occurred in 95.8%; heliotrope rash 83.5%; Gottron plaques 83.1%; 92% had at least one abnormal muscle enzyme result. Muscle biopsy performed in 74.6% was abnormal in 91.5% and electromyogram performed in 39.2% resulted abnormal in 93.2%. Logistic regression analysis was done in 66 cases with all parameters assessed and only aldolase resulted significant, as independent variable for definite JDM (OR=5.4, 95%CI 1.2-24.4, p=0.03). Regarding treatment, 97.9% received steroids; 72% had in addition at least one: methotrexate (75.7%), hydroxychloroquine (64.7%), cyclosporine A (20.6%), IV immunoglobulin (20.6%), azathioprine (10.3%) or cyclophosphamide (9.6%). In this series 24.3% developed calcinosis and mortality rate was 4.2%. Conclusion Evaluation of predefined criteria set for a valid diagnosis indicated aldolase as the most important parameter associated with de, methotrexate combination, was the most indicated treatment.