107 resultados para Proximal algorithms
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Despite the fact that bone mineral density (BMD) is an important fracture risk predictor in human medicine, studies in equine orthopedic research are still lacking. We hypothesized that BMD correlates with bone failure and fatigue fractures of this bone. Thus, the objectives of this study were to measure the structural and mechanical properties of the proximal phalanx with dual energy X-ray absorptiometry (DXA), to correlate the data obtained from DXA and computer tomography (CT) measurements to those obtained by loading pressure examination and to establish representative region of interest (ROI) for in vitro BMD measurements of the equine proximal phalanx for predicting bone failure force. DXA was used to measure the whole bone BMD and additional three ROI sites in 14 equine proximal phalanges. Following evaluation of the bone density, whole bone, cortical width and area in the mid-diaphyseal plane were measured on CT images. Bones were broken using a manually controlled universal bone crusher to measure bone failure force and reevaluated for the site of fractures on follow-up CT images. Compressive load was applied at a constant displacement rate of 2 mm/min until failure, defined as the first clear drop in the load measurement. The lowest BMD was measured at the trabecular region (mean +/- SD: 1.52 +/- 0.12 g/cm2; median: 1.48 g/cm2; range: 1.38-1.83 g/cm2). There was a significant positive linear correlation between trabelcular BMD and the breaking strength (P = 0.023, r = 0.62). The trabecular region of the proximal phalanx appears to be the only significant indicator of failure of strength in vitro. This finding should be reassessed to further reveal the prognostic value of trabecular BMD in an in vivo fracture risk model.
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PURPOSE Segmentation of the proximal femur in digital antero-posterior (AP) pelvic radiographs is required to create a three-dimensional model of the hip joint for use in planning and treatment. However, manually extracting the femoral contour is tedious and prone to subjective bias, while automatic segmentation must accommodate poor image quality, anatomical structure overlap, and femur deformity. A new method was developed for femur segmentation in AP pelvic radiographs. METHODS Using manual annotations on 100 AP pelvic radiographs, a statistical shape model (SSM) and a statistical appearance model (SAM) of the femur contour were constructed. The SSM and SAM were used to segment new AP pelvic radiographs with a three-stage approach. At initialization, the mean SSM model is coarsely registered to the femur in the AP radiograph through a scaled rigid registration. Mahalanobis distance defined on the SAM is employed as the search criteria for each annotated suggested landmark location. Dynamic programming was used to eliminate ambiguities. After all landmarks are assigned, a regularized non-rigid registration method deforms the current mean shape of SSM to produce a new segmentation of proximal femur. The second and third stages are iteratively executed to convergence. RESULTS A set of 100 clinical AP pelvic radiographs (not used for training) were evaluated. The mean segmentation error was [Formula: see text], requiring [Formula: see text] s per case when implemented with Matlab. The influence of the initialization on segmentation results was tested by six clinicians, demonstrating no significance difference. CONCLUSIONS A fast, robust and accurate method for femur segmentation in digital AP pelvic radiographs was developed by combining SSM and SAM with dynamic programming. This method can be extended to segmentation of other bony structures such as the pelvis.
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In this paper, we propose a fully automatic, robust approach for segmenting proximal femur in conventional X-ray images. Our method is based on hierarchical landmark detection by random forest regression, where the detection results of 22 global landmarks are used to do the spatial normalization, and the detection results of the 59 local landmarks serve as the image cue for instantiation of a statistical shape model of the proximal femur. To detect landmarks in both levels, we use multi-resolution HoG (Histogram of Oriented Gradients) as features which can achieve better accuracy and robustness. The efficacy of the present method is demonstrated by experiments conducted on 150 clinical x-ray images. It was found that the present method could achieve an average point-to-curve error of 2.0 mm and that the present method was robust to low image contrast, noise and occlusions caused by implants.
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The variability of results from different automated methods of detection and tracking of extratropical cyclones is assessed in order to identify uncertainties related to the choice of method. Fifteen international teams applied their own algorithms to the same dataset - the period 1989-2009 of interim European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERAInterim) data. This experiment is part of the community project Intercomparison of Mid Latitude Storm Diagnostics (IMILAST; see www.proclim.ch/imilast/index.html). The spread of results for cyclone frequency, intensity, life cycle, and track location is presented to illustrate the impact of using different methods. Globally, methods agree well for geographical distribution in large oceanic regions, interannual variability of cyclone numbers, geographical patterns of strong trends, and distribution shape for many life cycle characteristics. In contrast, the largest disparities exist for the total numbers of cyclones, the detection of weak cyclones, and distribution in some densely populated regions. Consistency between methods is better for strong cyclones than for shallow ones. Two case studies of relatively large, intense cyclones reveal that the identification of the most intense part of the life cycle of these events is robust between methods, but considerable differences exist during the development and the dissolution phases.
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Background: Alcohol craving is an essential construct in research and treatment of alcohol use disorders (AUD). Craving is mostly investigated in association with concurrent variables or distal treatment outcomes at follow-up. Objectives: The aim of this study is to examine craving at admission and its relevance for essential proximal outcomes at discharge from AUD treatment such as positive alcohol expectancy, abstinent-related self-efficacy, and substance-related coping, as well as patients’ demographic and AUD characteristics. Methods: In total, 36 patients were recruited within an inpatient treatment AUD program. Results: An association between craving and positive alcohol expectancies at discharge was found in the regression model even when the respective expectancies, age, gender, and severity of alcohol dependence at admission were controlled for (F(2,29)1⁄432.71, p50.001). Craving explained 2.3% of the variance of change in positive alcohol expectancy. Conclusion: The results suggest a low predictive value of craving for positive alcohol expectancy. In addition, we found significant associations between the craving and the severity of AUD and alcohol consumption before admission. Future studies should include proximal outcomes related to treatment efficacy as well as distal outcomes.
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Dynamic systems, especially in real-life applications, are often determined by inter-/intra-variability, uncertainties and time-varying components. Physiological systems are probably the most representative example in which population variability, vital signal measurement noise and uncertain dynamics render their explicit representation and optimization a rather difficult task. Systems characterized by such challenges often require the use of adaptive algorithmic solutions able to perform an iterative structural and/or parametrical update process towards optimized behavior. Adaptive optimization presents the advantages of (i) individualization through learning of basic system characteristics, (ii) ability to follow time-varying dynamics and (iii) low computational cost. In this chapter, the use of online adaptive algorithms is investigated in two basic research areas related to diabetes management: (i) real-time glucose regulation and (ii) real-time prediction of hypo-/hyperglycemia. The applicability of these methods is illustrated through the design and development of an adaptive glucose control algorithm based on reinforcement learning and optimal control and an adaptive, personalized early-warning system for the recognition and alarm generation against hypo- and hyperglycemic events.
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Background: Patients presenting to the emergency department (ED) currently face inacceptable delays in initial treatment, and long, costly hospital stays due to suboptimal initial triage and site-of-care decisions. Accurate ED triage should focus not only on initial treatment priority, but also on prediction of medical risk and nursing needs to improve site-of-care decisions and to simplify early discharge management. Different triage scores have been proposed, such as the Manchester triage system (MTS). Yet, these scores focus only on treatment priority, have suboptimal performance and lack validation in the Swiss health care system. Because the MTS will be introduced into clinical routine at the Kantonsspital Aarau, we propose a large prospective cohort study to optimize initial patient triage. Specifically, the aim of this trial is to derive a three-part triage algorithm to better predict (a) treatment priority; (b) medical risk and thus need for in-hospital treatment; (c) post-acute care needs of patients at the most proximal time point of ED admission. Methods/design: Prospective, observational, multicenter, multi-national cohort study. We will include all consecutive medical patients seeking ED care into this observational registry. There will be no exclusions except for non-adult and non-medical patients. Vital signs will be recorded and left over blood samples will be stored for later batch analysis of blood markers. Upon ED admission, the post-acute care discharge score (PACD) will be recorded. Attending ED physicians will adjudicate triage priority based on all available results at the time of ED discharge to the medical ward. Patients will be reassessed daily during the hospital course for medical stability and readiness for discharge from the nurses and if involved social workers perspective. To assess outcomes, data from electronic medical records will be used and all patients will be contacted 30 days after hospital admission to assess vital and functional status, re-hospitalization, satisfaction with care and quality of life measures. We aim to include between 5000 and 7000 patients over one year of recruitment to derive the three-part triage algorithm. The respective main endpoints were defined as (a) initial triage priority (high vs. low priority) adjudicated by the attending ED physician at ED discharge, (b) adverse 30 day outcome (death or intensive care unit admission) within 30 days following ED admission to assess patients risk and thus need for in-hospital treatment and (c) post acute care needs after hospital discharge, defined as transfer of patients to a post-acute care institution, for early recognition and planning of post-acute care needs. Other outcomes are time to first physician contact, time to initiation of adequate medical therapy, time to social worker involvement, length of hospital stay, reasons fordischarge delays, patient’s satisfaction with care, overall hospital costs and patients care needs after returning home. Discussion: Using a reliable initial triage system for estimating initial treatment priority, need for in-hospital treatment and post-acute care needs is an innovative and persuasive approach for a more targeted and efficient management of medical patients in the ED. The proposed interdisciplinary , multi-national project has unprecedented potential to improve initial triage decisions and optimize resource allocation to the sickest patients from admission to discharge. The algorithms derived in this study will be compared in a later randomized controlled trial against a usual care control group in terms of resource use, length of hospital stay, overall costs and patient’s outcomes in terms of mortality, re-hospitalization, quality of life and satisfaction with care.
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OBJECTIVE To analyse the results after elective open total aortic arch replacement. METHODS We analysed 39 patients (median age 63 years, median logistic EuroSCORE 18.4) who underwent elective open total arch replacement between 2005 and 2012. RESULTS In-hospital mortality was 5.1% (n = 2) and perioperative neurological injury was 12.8% (n = 5). The indication for surgery was degenerative aneurysmal disease in 59% (n = 23) and late aneurysmal formation following previous surgery of type A aortic dissection in 35.9% (n = 14); 5.1% (n = 2) were due to anastomotical aneurysms after prior ascending repair. Fifty-nine percent (n = 23) of the patients had already undergone previous proximal thoracic aortic surgery. In 30.8% (n = 12) of them, a conventional elephant trunk was added to total arch replacement, in 28.2% (n = 11), root replacement was additionally performed. Median hypothermic circulatory arrest time was 42 min (21-54 min). Selective antegrade cerebral perfusion was used in 95% (n = 37) of patients. Median follow-up was 11 months [interquartile range (IQR) 1-20 months]. There was no late death and no need for reoperation during this period. CONCLUSIONS Open total aortic arch replacement shows very satisfying results. The number of patients undergoing total arch replacement as a redo procedure and as a part of a complex multisegmental aortic pathology is high. Future strategies will have to emphasize neurological protection in extensive simultaneous replacement of the aortic arch and adjacent segments.
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Background Tests for recent infections (TRIs) are important for HIV surveillance. We have shown that a patient's antibody pattern in a confirmatory line immunoassay (Inno-Lia) also yields information on time since infection. We have published algorithms which, with a certain sensitivity and specificity, distinguish between incident (< = 12 months) and older infection. In order to use these algorithms like other TRIs, i.e., based on their windows, we now determined their window periods. Methods We classified Inno-Lia results of 527 treatment-naïve patients with HIV-1 infection < = 12 months according to incidence by 25 algorithms. The time after which all infections were ruled older, i.e. the algorithm's window, was determined by linear regression of the proportion ruled incident in dependence of time since infection. Window-based incident infection rates (IIR) were determined utilizing the relationship ‘Prevalence = Incidence x Duration’ in four annual cohorts of HIV-1 notifications. Results were compared to performance-based IIR also derived from Inno-Lia results, but utilizing the relationship ‘incident = true incident + false incident’ and also to the IIR derived from the BED incidence assay. Results Window periods varied between 45.8 and 130.1 days and correlated well with the algorithms' diagnostic sensitivity (R2 = 0.962; P<0.0001). Among the 25 algorithms, the mean window-based IIR among the 748 notifications of 2005/06 was 0.457 compared to 0.453 obtained for performance-based IIR with a model not correcting for selection bias. Evaluation of BED results using a window of 153 days yielded an IIR of 0.669. Window-based IIR and performance-based IIR increased by 22.4% and respectively 30.6% in 2008, while 2009 and 2010 showed a return to baseline for both methods. Conclusions IIR estimations by window- and performance-based evaluations of Inno-Lia algorithm results were similar and can be used together to assess IIR changes between annual HIV notification cohorts.
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The Youngest Toba Tuff (YTT, erupted ca. 74 ka ago) is a distinctive and widespread tephra marker across south and southeast Asia. The climatic, human and environmental consequences of the YTT eruption are widely debated. Although a considerable body of geochemical data is available for this unit, there has not been a systematic study of the variability of the ash geochemistry. Intrinsic (magmatic) and extrinsic (post-depositional) chemical variations bring fundamental information regarding the petrogenesis of the magma, the distribution of the tephra and the interaction between the ash and the receiving environment. Considering the importance of the geochemistry of the YTT for stratigraphic correlations and eruptive models, it is central to the YTT debate to quantify and interpret such variations. Here we collate all published geochemical data on the YTT glass, including analyses from 68 sites described in the literature and three new samples. Two principal sources of chemical variation are investigated: (i) compositional zonation of the magma reservoir, and (ii) post-depositional alteration. Post-depositional leaching is responsible for up to ca. 11% differences in Na2O/K2O and ca. 1% differences in SiO2/Al2O3 ratios in YTT glass from marine sites. Continental tephra are 2% higher in Na2O/K2O and 3% higher in SiO2/Al2O3 respect to the marine tephra. We interpret such post-depositional glass alteration as related to seawater induced alkali migration in marine environments, or to site-specific water pH. Crystal fractionation and consequential magmatic differentiation, which produced order-of-magnitude variations in trace element concentrations reported in the literature, also produced major element differences in the YTT glass. FeO/Al2O3 ratios vary by about 50 %, which is analytically significant. These variations represent magmatic fractionation involving Fe-bearing phases. We also compared major element concentrations in YTT and Oldest Toba Tuff (OTT) ash samples, to identify potential compositional differences that could constrain the stratigraphic identity of the Morgaon ash (Western India); no differences between the OTT and YTT samples were observed.
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OBJECTIVE To develop and evaluate a method for ultrasound-guidance in performing the proximal paravertebral block for flank anaesthesia in cattle through a cadaveric study, followed by clinical application. STUDY DESIGN prospective experimental cadaveric study and clinical series. ANIMALS Previously frozen lumbar sections of cows without known spinal abnormalities were used. The clinical case group comprised of ten animals for which a right flank laparotomy was indicated. METHODS Twenty cow cadavers were used to perform ultrasound-guided bilateral injections of 1.0 mL dye (1.0 mL 1% Toluidine Blue in 1% Borax) at the intervertebral foramen at the level of T13, L1 and L2 spinal nerves. Distance and depth of injection, staining of the dorsal and ventral nerve branches, and deviation from the target were evaluated. The investigator's confidence as to visualisation and expected success at staining the nerve was assessed. Ten clinical cases received the ultrasound-guided proximal paravertebral anaesthesia. Analgesic success was evaluated using a 4-grade scoring system at 10 minutes after the injection and during surgery, respectively. Categorical variables were described using frequencies and proportions. RESULTS Both dorsal and ventral branches of the spinal nerves T13, L1 or L2 were at least partially stained in 41% of injections, while in 77% of injections one of the branches was stained. Five out of ten clinical cases had a satisfactory anaesthesia. There was no significant association between confidence at injection and either staining or analgesic success. CONCLUSION Results from the cadaveric and clinical study suggest no significant improvement using ultrasound guidance to perform proximal paravertebral block in cows compared to our previous clinical experience and to references in the literature using the blind method. CLINICAL RELEVANCE Further research should be conducted to improve the ultrasound-guided technique described in this study.
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Cloud Computing has evolved to become an enabler for delivering access to large scale distributed applications running on managed network-connected computing systems. This makes possible hosting Distributed Enterprise Information Systems (dEISs) in cloud environments, while enforcing strict performance and quality of service requirements, defined using Service Level Agreements (SLAs). {SLAs} define the performance boundaries of distributed applications, and are enforced by a cloud management system (CMS) dynamically allocating the available computing resources to the cloud services. We present two novel VM-scaling algorithms focused on dEIS systems, which optimally detect most appropriate scaling conditions using performance-models of distributed applications derived from constant-workload benchmarks, together with SLA-specified performance constraints. We simulate the VM-scaling algorithms in a cloud simulator and compare against trace-based performance models of dEISs. We compare a total of three SLA-based VM-scaling algorithms (one using prediction mechanisms) based on a real-world application scenario involving a large variable number of users. Our results show that it is beneficial to use autoregressive predictive SLA-driven scaling algorithms in cloud management systems for guaranteeing performance invariants of distributed cloud applications, as opposed to using only reactive SLA-based VM-scaling algorithms.
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REASONS FOR PERFORMING STUDY: There is limited information on potential diffusion of local anaesthetic solution after various diagnostic analgesic techniques of the proximal metacarpal region. OBJECTIVE: To document potential distribution of local anaesthetic solution following 4 techniques used for diagnostic analgesia of the proximal metacarpal region. METHODS: Radiodense contrast medium was injected around the lateral palmar or medial and lateral palmar metacarpal nerves in 8 mature horses, using 4 different techniques. Radiographs were obtained 0, 10 and 20 min after injection and were analysed subjectively. A mixture of radiodense contrast medium and methylene blue was injected into 4 cadaver limbs; the location of the contrast medium and dye was determined by radiography and dissection. RESULTS: Following perineural injection of the palmar metacarpal nerves, most of the contrast medium was distributed in an elongated pattern axial to the second and fourth metacarpal bones. The carpometacarpal joint was inadvertently penetrated in 4/8 limbs after injections of the palmar metacarpal nerves from medial and lateral approaches, and in 1/8 limbs when both injections were performed from the lateral approach. Following perineural injection of the lateral palmar nerve using a lateral approach, the contrast medium was diffusely distributed in all but one limb, in which the carpal sheath was inadvertently penetrated. In 5/8 limbs, following perineural injection of the lateral palmar nerve using a medial approach, the contrast medium diffused proximally to the distal third of the antebrachium. CONCLUSIONS AND POTENTIAL RELEVANCE: Inadvertent penetration of the carpometacarpal joint is common after perineural injection of the palmar metacarpal nerves, but less so if both palmar metacarpal nerves are injected using a lateral approach. Following injection of the lateral palmar nerve using a medial approach, the entire palmar aspect of the carpus may be desensitised.