BACKGROUND: Despite the established value of genomic testing strategies, practice guidelines for their use do not exist in many indications. OBJECTIVES: We sought to validate a recently introduced scoring algorithm for dystonia, predicting the diagnostic utility of whole-exome sequencing (WES) based on individual phenotypic aspects (age-at-onset, body distribution, presenting comorbidity). METHODS: We prospectively enrolled a set of 209 dystonia-affected families and obtained summary scores (0-5 points) according to the algorithm. Singleton (N = 146), duo (N = 11), and trio (N = 52) WES data were generated to identify genetic diagnoses. RESULTS: Diagnostic yield was highest (51%) among individuals with a summary score of 5, corresponding to a manifestation of early-onset segmental or generalized dystonia with coexisting non-movement disorder-related neurological symptoms. Sensitivity and specificity at the previously suggested threshold for implementation of WES (3 points) was 96% and 52%, with area under the curve of 0.81. CONCLUSIONS: The algorithm is a useful predictive tool and could be integrated into dystonia routine diagnostic protocols. © 2021 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson Movement Disorder Society.

• Keywords
• diagnostic yield, dystonia, exome sequencing, prediction, rare disease, scoring algorithm,
• MeSH
• Algorithms MeSH
• Dystonic Disorders * genetics   MeSH
• Dystonia * diagnosis   genetics   MeSH
• Genetic Testing MeSH
• Humans MeSH
• Parkinson Disease * MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH

Multiple myeloma (MM) is a malignancy with varying survival outcomes and drivers of disease progression. Existing MM staging tools were developed using data from newly diagnosed patients. As patient characteristics and disease-related factors change between diagnosis and the initiation of second-line (2L) treatment, an unmet need exists for a tool that can evaluate risk of death at first relapse. We have developed a risk stratification algorithm (RSA) using data from patients with MM who were at 2L. Hazard ratios for independent predictors of overall survival (OS) were derived from a Cox models, and individual patient scores were calculated for total risk. K-adaptive partitioning for survival was used to stratify patients into groups based on their scores. Relative risk doubled with ascending risk group; median OSs for patients in group 1 (lowest risk)-4 (highest risk) were 61·6, 29·6, 14·2 and 5·9 months, respectively. Differences in OS between risk groups were significant. Similar stratification was observed when the RSA was applied to an external validation data set. In conclusion, we have developed a validated RSA that can quantify total risk, frailty risk and disease aggressiveness risk, and stratify patients with MM at 2L into groups with profoundly different survival expectations.

• Keywords
• algorithm, multiple myeloma, overall survival, relapsed, risk stratification,
• MeSH
• Algorithms * MeSH
• Survival Analysis MeSH
• Risk Assessment methods   MeSH
• Middle Aged MeSH
• Humans MeSH
• Multiple Myeloma diagnosis   mortality   pathology   MeSH
• Recurrence MeSH
• Registries MeSH
• Aged MeSH
• Check Tag
• Middle Aged MeSH
• Humans MeSH
• Male MeSH
• Aged MeSH
• Female MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Validation Study MeSH

INTRODUCTION: Risk stratification tools provide valuable information to inform treatment decisions. Existing algorithms for patients with multiple myeloma (MM) were based on patients with newly diagnosed disease, and these have not been validated in the relapsed setting or in routine clinical practice. We developed a risk stratification algorithm (RSA) for patients with MM at initiation of second-line (2L) treatment, based on data from the Czech Registry of Monoclonal Gammopathies. METHODS: Predictors of overall survival (OS) at 2L treatment were identified using Cox proportional hazards models and backward selection. Risk scores were obtained by multiplying the hazard ratios for each predictor. The K-adaptive partitioning for survival (KAPS) algorithm defined four groups of stratification based on individual risk scores. RESULTS: Performance of the RSA was assessed using Nagelkerke's R2 test and Harrell's concordance index through Kaplan-Meier analysis of OS data. Prognostic groups were successfully defined based on real-world data. Use of a multiplicative score based on Cox modeling and KAPS to define cut-off values was effective. CONCLUSION: Through innovative methods of risk assessment and collaboration between physicians and statisticians, the RSA was capable of stratifying patients at 2L treatment by survival expectations. This approach can be used to develop clinical decision-making tools in other disease areas to improve patient management. FUNDING: Amgen Europe GmbH.

• Keywords
• Algorithm, Multiple myeloma, Prognostic model, Risk, Survival,
• Publication type
• Journal Article MeSH

BACKGROUND: The identification of implant wear particles and non-implant related particles and the characterization of the inflammatory responses in the periprosthetic neo-synovial membrane, bone, and the synovial-like interface membrane (SLIM) play an important role for the evaluation of clinical outcome, correlation with radiological and implant retrieval studies, and understanding of the biological pathways contributing to implant failures in joint arthroplasty. The purpose of this study is to present a comprehensive histological particle algorithm (HPA) as a practical guide to particle identification at routine light microscopy examination. METHODS: The cases used for particle analysis were selected retrospectively from the archives of two institutions and were representative of the implant wear and non-implant related particle spectrum. All particle categories were described according to their size, shape, colour and properties observed at light microscopy, under polarized light, and after histochemical stains when necessary. A unified range of particle size, defined as a measure of length only, is proposed for the wear particles with five classes for polyethylene (PE) particles and four classes for conventional and corrosion metallic particles and ceramic particles. RESULTS: All implant wear and non-implant related particles were described and illustrated in detail by category. A particle scoring system for the periprosthetic tissue/SLIM is proposed as follows: 1) Wear particle identification at light microscopy with a two-step analysis at low (× 25, × 40, and × 100) and high magnification (× 200 and × 400); 2) Identification of the predominant wear particle type with size determination; 3) The presence of non-implant related endogenous and/or foreign particles. A guide for a comprehensive pathology report is also provided with sections for macroscopic and microscopic description, and diagnosis. CONCLUSIONS: The HPA should be considered a standard for the histological analysis of periprosthetic neo-synovial membrane, bone, and SLIM. It provides a basic, standardized tool for the identification of implant wear and non-implant related particles at routine light microscopy examination and aims at reducing intra-observer and inter-observer variability to provide a common platform for multicentric implant retrieval/radiological/histological studies and valuable data for the risk assessment of implant performance for regional and national implant registries and government agencies.

• Keywords
• Arthroplasty, Ceramic wear particles, Histological particle algorithm, Metallic wear particles, Non-implant related particles, Orthopaedic implant wear particles, Periprosthetic tissue, Polyethylene wear particles, Synovial crystals, Synovial-like interface membrane,
• Publication type
• Journal Article MeSH

PURPOSE: The aim of this study was to verify the possibility of summing the dose distributions of combined radiotherapeutic treatment of cervical cancer using the extended Lucas-Kanade algorithm for deformable image registration. MATERIALS AND METHODS: First, a deformable registration of planning computed tomography images for the external radiotherapy and brachytherapy treatment of 10 patients with different parameter settings of the Lucas-Kanade algorithm was performed. By evaluating the registered data using landmarks distance, root mean square error of Hounsfield units and 2D gamma analysis, the optimal parameter values were found. Next, with another group of 10 patients, the accuracy of the dose mapping of the optimized Lucas-Kanade algorithm was assessed and compared with Horn-Schunck and modified Demons algorithms using dose differences at landmarks. RESULTS: The best results of the Lucas-Kanade deformable registration were achieved for two pyramid levels in combination with a window size of 3 voxels. With this registration setting, the average landmarks distance was 2.35 mm, the RMSE was the smallest and the average gamma score reached a value of 86.7%. The mean dose difference at the landmarks after mapping the external radiotherapy and brachytherapy dose distributions was 1.33 Gy. A statistically significant difference was observed on comparing the Lucas-Kanade method with the Horn-Schunck and Demons algorithms, where after the deformable registration, the average difference in dose was 1.60 Gy (P-value: 0.0055) and 1.69 Gy (P-value: 0.0012), respectively. CONCLUSION: Lucas-Kanade deformable registration can lead to a more accurate model of dose accumulation and provide a more realistic idea of the dose distribution.

• Keywords
• Lucas-Kanade algorithm, deformable image registration, treatment planning,
• MeSH
• Algorithms MeSH
• Brachytherapy * MeSH
• Radiotherapy Dosage MeSH
• Humans MeSH
• Uterine Cervical Neoplasms * diagnostic imaging   radiotherapy   MeSH
• Radiotherapy Planning, Computer-Assisted MeSH
• Check Tag
• Humans MeSH
• Female MeSH
• Publication type
• Journal Article MeSH

MOTIVATION: G-quadruplex is a DNA or RNA form in which four guanine-rich regions are held together by base pairing between guanine nucleotides in coordination with potassium ions. G-quadruplexes are increasingly seen as a biologically important component of genomes. Their detection in vivo is problematic; however, sequencing and spectrometric techniques exist for their in vitro detection. We previously devised the pqsfinder algorithm for PQS identification, implemented it in C++ and published as an R/Bioconductor package. We looked for ways to optimize pqsfinder for faster and user-friendly sequence analysis. RESULTS: We identified two weak points where pqsfinder could be optimized. We modified the internals of the recursive algorithm to avoid matching and scoring many sub-optimal PQS conformations that are later discarded. To accommodate the needs of a broader range of users, we created a website for submission of sequence analysis jobs that does not require knowledge of R to use pqsfinder. AVAILABILITY AND IMPLEMENTATION: https://pqsfinder.fi.muni.cz, https://bioconductor.org/packages/pqsfinder. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

• MeSH
• Algorithms MeSH
• G-Quadruplexes * MeSH
• Genome MeSH
• RNA MeSH
• Software MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Names of Substances
• RNA MeSH

BACKGROUND: The European Society of Cardiology recommends a 0/1-hour algorithm for rapid rule-out and rule-in of non-ST-segment elevation myocardial infarction using high-sensitivity cardiac troponin (hs-cTn) concentrations irrespective of renal function. Because patients with renal dysfunction (RD) frequently present with increased hs-cTn concentrations even in the absence of non-ST-segment elevation myocardial infarction, concern has been raised regarding the performance of the 0/1-hour algorithm in RD. METHODS: In a prospective multicenter diagnostic study enrolling unselected patients presenting with suspected non-ST-segment elevation myocardial infarction to the emergency department, we assessed the diagnostic performance of the European Society of Cardiology 0/1-hour algorithm using hs-cTnT and hs-cTnI in patients with RD, defined as an estimated glomerular filtration rate <60 mL/min/1.73 m2, and compared it to patients with normal renal function. The final diagnosis was centrally adjudicated by 2 independent cardiologists using all available information, including cardiac imaging. Safety was quantified as sensitivity in the rule-out zone, accuracy as the specificity in the rule-in zone, and efficacy as the proportion of the overall cohort assigned to either rule-out or rule-in based on the 0- and 1-hour sample. RESULTS: Among 3254 patients, RD was present in 487 patients (15%). The prevalence of non-ST-segment elevation myocardial infarction was substantially higher in patients with RD compared with patients with normal renal function (31% versus 13%, P<0.001). Using hs-cTnT, patients with RD had comparable sensitivity of rule-out (100.0% [95% confidence interval {CI}, 97.6-100.0] versus 99.2% [95% CI, 97.6-99.8]; P=0.559), lower specificity of rule-in (88.7% [95% CI, 84.8-91.9] versus 96.5% [95% CI, 95.7-97.2]; P<0.001), and lower overall efficacy (51% versus 81%, P<0.001), mainly driven by a much lower percentage of patients eligible for rule-out (18% versus 68%, P<0.001) compared with patients with normal renal function. Using hs-cTnI, patients with RD had comparable sensitivity of rule-out (98.6% [95% CI, 95.0-99.8] versus 98.5% [95% CI, 96.5-99.5]; P=1.0), lower specificity of rule-in (84.4% [95% CI, 79.9-88.3] versus 91.7% [95% CI, 90.5-92.9]; P<0.001), and lower overall efficacy (54% versus 76%, P<0.001; proportion ruled out, 18% versus 58%, P<0.001) compared with patients with normal renal function. CONCLUSIONS: In patients with RD, the safety of the European Society of Cardiology 0/1-hour algorithm is high, but specificity of rule-in and overall efficacy are decreased. Modifications of the rule-in and rule-out thresholds did not improve the safety or overall efficacy of the 0/1-hour algorithm. CLINICAL TRIAL REGISTRATION: URL: https://www.clinicaltrials.gov. Unique identifier: NCT00470587.

• Keywords
• 0/1-hour algorithm, chronic kidney disease, diagnosis of acute myocardial infarction, high-sensitivity cardiac troponin, renal dysfunction,
• MeSH
• Algorithms * MeSH
• Biomarkers blood   MeSH
• Time Factors MeSH
• Risk Assessment MeSH
• Glomerular Filtration Rate * MeSH
• Non-ST Elevated Myocardial Infarction blood   diagnosis   epidemiology   MeSH
• Creatinine blood   MeSH
• Kidney physiopathology   MeSH
• Middle Aged MeSH
• Humans MeSH
• Decision Support Techniques * MeSH
• Kidney Diseases blood   diagnosis   epidemiology   physiopathology   MeSH
• Predictive Value of Tests MeSH
• Prevalence MeSH
• Prognosis MeSH
• Prospective Studies MeSH
• Reproducibility of Results MeSH
• Risk Factors MeSH
• Aged, 80 and over MeSH
• Aged MeSH
• Triage * MeSH
• Troponin blood   MeSH
• Up-Regulation MeSH
• Check Tag
• Middle Aged MeSH
• Humans MeSH
• Male MeSH
• Aged, 80 and over MeSH
• Aged MeSH
• Female MeSH
• Publication type
• Journal Article MeSH
• Multicenter Study MeSH
• Research Support, Non-U.S. Gov't MeSH
• Geographicals
• Europe epidemiology   MeSH
• Names of Substances
• Biomarkers MeSH
• Creatinine MeSH
• Troponin MeSH

Rapid development of computer technologies leads to the intensive automation of many different processes traditionally performed by human experts. One of the spheres characterized by the introduction of new high intelligence technologies substituting analysis performed by humans is sleep scoring. This refers to the classification task and can be solved - next to other classification methods - by use of artificial neural networks (ANN). ANNs are parallel adaptive systems suitable for solving of non-linear problems. Using ANN for automatic sleep scoring is especially promising because of new ANN learning algorithms allowing faster classification without decreasing the performance. Both appropriate preparation of training data as well as selection of the ANN model make it possible to perform effective and correct recognizing of relevant sleep stages. Such an approach is highly topical, taking into consideration the fact that there is no automatic scorer utilizing ANN technology available at present.

• MeSH
• Electroencephalography methods   MeSH
• Humans MeSH
• Neural Networks, Computer * MeSH
• Polysomnography methods   MeSH
• Sleep physiology   MeSH
• Sleep Stages physiology   MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Review MeSH

PURPOSE OF THE STUDY The aim of the present study was to evaluate the postoperative outcome of patients with pilon tibial fractures with a minimum follow-up of 24 months, treated according to a staged treatment algorithm. MATERIAL AND METHODS In total, 27 patients (mean age 43.6 ± 13 years, range 18-69) with a pilon tibial fracture and a minimum follow-up of 24 months were included in the study. Medical recordings (discharge documents and surgical reports) and radiographic examinations were analyzed. All enrolled patients were invited for a clinical and radiological follow-up examination (ROM, AOFAS hindfoot score, Kellgren score). The mean follow-up time was 44.5 ± 16 months (range 24-82). RESULTS In 21 cases a two-stage operative strategy with initial closed reduction and external fixation was necessary prior to definitive osteosynthesis. Overall, the patients scored 82.1 ± 20 points (range 30-100) in AOFAS hindfoot score, which represents a good clinical outcome. Patients with B-type fractures scored significantly better than those with C-type fractures. Patients with closed pilon tibial fractures reached significantly higher values in the AOFAS hindfoot score than those with open ones. Age and gender did not affect the functional outcome. Total ankle range of motion was 41° ± 10° for B-type fractures (range 20°-55°) and 35° ± 17° (range 0°-60°) for C-type fractures respectively (p > 0.05). Only five patients reached higher scores (Grade III) in Kellgren classification system. DISCUSSION Within the last decades, the therapeutic algorithm of pilon fractures underwent a paradigm shift; a two-stage protocol has prevailed today. However, the initial severity of the fracture in terms of initial absorbed energy, bony comminution and softtissue trauma still affects the outcome. Moreover, the necessity for bone grafting, as an indirect measurement of bone comminution and bone defects, resulted in higher degrees of osteoarthritis in the final follow-up. Higher initial soft-tissue injury also had an impact on the functional outcome of the patients, as patients with closed fractures scored better in AOFAS at the final follow-up. In order to counteract these risk factors and to reduce complications that define the outcome of these severe injuries, clearly defined surgical principles and standardized treatment protocols are needed. CONCLUSIONS The present study confirms the fact that meticulous planning, respect of the soft-tissues and choice of the optimal timepoint for the definitive osteosynthesis and overall treatment according to standardized protocols can optimize the outcome of this severe injury. Key words:pilon, distal tibia fracture, outcome, algorithm.

• MeSH
• Algorithms * MeSH
• Adult MeSH
• Tibial Fractures * surgery   MeSH
• Middle Aged MeSH
• Humans MeSH
• Adolescent MeSH
• Young Adult MeSH
• Follow-Up Studies MeSH
• Radiography MeSH
• Retrospective Studies MeSH
• Aged MeSH
• Fracture Fixation, Internal MeSH
• Treatment Outcome MeSH
• Check Tag
• Adult MeSH
• Middle Aged MeSH
• Humans MeSH
• Adolescent MeSH
• Young Adult MeSH
• Aged MeSH
• Publication type
• Journal Article MeSH

The aim of this study is to provide an easy tool to identify patients with a high cardiovascular risk, especially those qualifying for lipid-lowering treatment. The decision to treat with lipid-lowering drugs was assessed with five new risk algorithms. The Five Risk algorithm (5R) takes into account male gender, high systolic blood pressure, high total cholesterol, smoking and high blood sugar as independent risk factors. Patients with three independent risk factors qualify for lipid-lowering treatment. Compared to the Framingham Risk Score, the 5R has a Kappa coefficient of 0.62. Compared to the SCORE, the Six Risk algorithm (6RDF) has a Kappa coefficient of 0.70. The 6RDF uses only four independent risk factors (male gender, high systolic blood pressure, high total cholesterol and smoking) but having diabetes or a family history of premature coronary heart disease are exclusion criteria for which treatment with lipid-lowering drugs is always indicated.

• MeSH
• Algorithms * MeSH
• Diabetes Mellitus MeSH
• Risk Assessment MeSH
• Hypercholesterolemia diagnosis   drug therapy   MeSH
• Hypertension MeSH
• Hypolipidemic Agents therapeutic use   MeSH
• Cardiovascular Diseases prevention & control   MeSH
• Middle Aged MeSH
• Humans MeSH
• Sensitivity and Specificity MeSH
• Patient Selection * MeSH
• Health Surveys MeSH
• Check Tag
• Middle Aged MeSH
• Humans MeSH
• Male MeSH
• Female MeSH
• Publication type
• Journal Article MeSH
• Validation Study MeSH
• Names of Substances
• Hypolipidemic Agents MeSH