Management of work-relevant upper limb disorders: a review

Background Upper limb disorders (ULDs) are clinically challenging and responsible for considerable work loss. There is a need to determine effective approaches for their management. Aim To determine evidence-based management strategies for work-relevant ULDs and explore whether a biopsychosocial approach is appropriate. Methods Literature review using a best evidence synthesis. Data from articles identified through systematic searching of electronic databases and citation tracking were extracted into evidence tables. The information was synthesized into high-level evidence statements, which were ordered into themes covering classification/diagnosis, epidemiology, associations/risks and management/treatment, focusing on return to work or work retention and taking account of distinctions between non-specific complaints and specific diagnoses. Results Neither biomedical treatment nor ergonomic workplace interventions alone offer an optimal solution; rather, multimodal interventions show considerable promise, particularly for occupational outcomes. Early return to work, or work retention, is an important goal for most cases and may be facilitated, where necessary, by transitional work arrangements. The emergent evidence indicates that successful management strategies require all the players to be onside and acting in a coordinated fashion; this requires engaging employers and workers to participate. Conclusions The biopsychosocial model applies: biological considerations should not be ignored, but psychosocial factors are more influential for occupational outcomes. Implementation of interventions that address the full range of psychosocial issues will require a cultural shift in the way the relationship between upper limb complaints and work is conceived and handled. Dissemination of evidence-based messages can contribute to the needed cultural shift

Introduction of a cascaded segmentation pipeline for parametric T1 mapping in cardiovascular magnetic resonance to improve segmentation performance

The manual and often time-consuming segmentation of the myocardium in cardiovascular magnetic resonance is increasingly automated using convolutional neural networks (CNNs). This study proposes a cascaded segmentation (CASEG) approach to improve automatic image segmentation quality. First, an object detection algorithm predicts a bounding box (BB) for the left ventricular myocardium whose 1.5 times enlargement defines the region of interest (ROI). Then, the ROI image section is fed into a U-Net based segmentation. Two CASEG variants were evaluated: one using the ROI cropped image solely (cropU) and the other using a 2-channel-image additionally containing the original BB image section (crinU). Both were compared to a classical U-Net segmentation (refU). All networks share the same hyperparameters and were tested on basal and midventricular slices of native and contrast enhanced (CE) MOLLI T1 maps. Dice Similarity Coefficient improved significantly (p < 0.05) in cropU and crinU compared to refU (81.06%, 81.22%, 72.79% for native and 80.70%, 79.18%, 71.41% for CE data), while no significant improvement (p < 0.05) was achieved in the mean absolute error of the T1 time (11.94 ms, 12.45 ms, 14.22 ms for native and 5.32 ms, 6.07 ms, 5.89 ms for CE data). In conclusion, CASEG provides an improved geometric concordance but needs further improvement in the quantitative outcome

Introduction of Lazy Luna an automatic software-driven multilevel comparison of ventricular function quantification in cardiovascular magnetic resonance imaging

Cardiovascular magnetic resonance imaging is the gold standard for cardiac function assessment. Quantification of clinical results (CR) requires precise segmentation. Clinicians statistically compare CRs to ensure reproducibility. Convolutional Neural Network developers compare their results via metrics. Aim: Introducing software capable of automatic multilevel comparison. A multilevel analysis covering segmentations and CRs builds on a generic software backend. Metrics and CRs are calculated with geometric accuracy. Segmentations and CRs are connected to track errors and their effects. An interactive GUI makes the software accessible to different users. The software's multilevel comparison was tested on a use case based on cardiac function assessment. The software shows good reader agreement in CRs and segmentation metrics (Dice > 90%). Decomposing differences by cardiac position revealed excellent agreement in midventricular slices: > 90% but poorer segmentations in apical (> 71%) and basal slices (> 74%). Further decomposition by contour type locates the largest millilitre differences in the basal right cavity (> 3 ml). Visual inspection shows these differences being caused by different basal slice choices. The software illuminated reader differences on several levels. Producing spreadsheets and figures concerning metric values and CR differences was automated. A multilevel reader comparison is feasible and extendable to other cardiac structures in the future

Lazy Luna: extendible software for multilevel reader comparison in cardiovascular magnetic resonance imaging

BACKGROUND AND OBJECTIVES: Cardiovascular Magnetic Resonance (CMR) imaging is a growing field with increasing diagnostic utility in clinical routine. Quantitative diagnostic parameters are typically calculated based on contours or points provided by readers, e.g. natural intelligences (NI) such as clinicians or researchers, and artificial intelligences (AI). As clinical applications multiply, evaluating the precision and reproducibility of quantitative parameters becomes increasingly important. Although segmentation challenges for AIs and guidelines for clinicians provide quality assessments and regulation, the methods ought to be combined and streamlined for clinical applications. The goal of the developed software, Lazy Luna (LL), is to offer a flexible evaluation tool that is readily extendible to new sequences and scientific endeavours. METHODS: An interface was designed for LL, which allows for comparing annotated CMR images. Geometric objects ensure precise calculations of metric values and clinical results regardless of whether annotations originate from AIs or NIs. A graphical user interface (GUI) is provided to make the software available to non-programmers. The GUI allows for an interactive inspection of image datasets as well as implementing tracing procedures, which follow statistical reader differences in clinical results to their origins in individual image contours. The backend software builds on a set of meta-classes, which can be extended to new imaging sequences and clinical parameters. Following an agile development procedure with clinical feedback allows for a quick implementation of new classes, figures and tables for evaluation. RESULTS: Two application cases present LL's extendibility to clinical evaluation and AI development contexts. The first concerns T1 parametric mapping images segmented by two expert readers. Quantitative result differences are traced to reveal typical segmentation dissimilarities from which these differences originate. The meta-classes are extended to this new application scenario. The second applies to the open source Late Gadolinium Enhancement (LGE) quantification challenge for AI developers “Emidec”, which illustrates LL's usability as open source software. CONCLUSION: The presented software Lazy Luna allows for an automated multilevel comparison of readers as well as identifying qualitative reasons for statistical reader differences. The open source software LL can be extended to new application cases in the future

Widespread West Nile virus activity, eastern United States, 2000.

In 1999, the U.S. West Nile (WN) virus epidemic was preceded by widespread reports of avian deaths. In 2000, ArboNET, a cooperative WN virus surveillance system, was implemented to monitor the sentinel epizootic that precedes human infection. This report summarizes 2000 surveillance data, documents widespread virus activity in 2000, and demonstrates the utility of monitoring virus activity in animals to identify human risk for infection

How Hepatitis D Virus Can Hinder the Control of Hepatitis B Virus

BACKGROUND: Hepatitis D (or hepatitis delta) virus is a defective virus that relies on hepatitis B virus (HBV) for transmission; infection with hepatitis D can occur only as coinfection with HBV or superinfection of an existing HBV infection. Because of the bond between the two viruses, control measures for HBV may have also affected the spread of hepatitis D, as evidenced by the decline of hepatitis D in recent years. Since the presence of hepatitis D is associated with suppressed HBV replication and possibly infectivity, it is reasonable to speculate that hepatitis D may facilitate the control of HBV. METHODOLOGY AND PRINCIPAL FINDINGS: We introduced a mathematical model for the transmission of HBV and hepatitis D, where individuals with dual HBV and hepatitis D infection transmit both viruses. We calculated the reproduction numbers of single HBV infections and dual HBV and hepatitis D infections and examined the endemic prevalences of the two viruses. The results show that hepatitis D virus modulates not only the severity of the HBV epidemic, but also the impact of interventions for HBV. Surprisingly we find that the presence of hepatitis D virus may hamper the eradication of HBV. Interventions that aim to reduce the basic reproduction number of HBV below one may not be sufficient to eradicate the virus, as control of HBV depends also on the reproduction numbers of dual infections. CONCLUSIONS AND SIGNIFICANCE: For populations where hepatitis D is endemic, plans for control programs ignoring the presence of hepatitis D may underestimate the HBV epidemic and produce overoptimistic results. The current HBV surveillance should be augmented with monitoring of hepatitis D, in order to improve accuracy of the monitoring and the efficacy of control measures

Plectin as a prognostic marker in non-metastatic oral squamous cell carcinoma

Background: Oral squamous cell carcinoma (OSCC) is associated with a poor 5-year survival rate. In general, patients diagnosed with small tumors have a fairly good prognosis, but some small tumors have an aggressive behavior leading to early death. There are at present no reliable prognostic biomarkers for oral cancers. Thus, to optimize treatment for the individual patient, there is a need for biomarkers that can predict tumor behavior. Method: In the present study the potential prognostic value of plectin was evaluated by a tissue microarray (TMA) based immunohistochemical analysis of primary tumor tissue obtained from a North Norwegian cohort of 115 patients diagnosed with OSCC. The expression of plectin was compared with clinicopathological variables and 5 year survival. Results: The statistical analysis revealed that low expression of plectin in the tumor cells predicted a favorable outcome for patients with non-metastatic disease (p = 0.008). Furthermore, the expression of plectin was found to correlate (p = 0.01) with the expression of uPAR, which we have previously found to be a potential prognostic marker for T1N0 tumors. Conclusions: Our results indicate that low expression of plectin predicts a favorable outcome for patients with non-metastatic OSCC and the expression level of plectin may therefore be used in the treatment stratification for patients with early stage disease

The interplay of matrix metalloproteinase-8, transforming growth factor-beta 1 and vascular endothelial growth factor-C cooperatively contributes to the aggressiveness of oral tongue squamous cell carcinoma

Background: Matrix metalloproteinase-8 (MMP-8) has oncosuppressive properties in various cancers. We attempted to assess MMP-8 function in oral tongue squamous cell carcinoma (OTSCC). Methods: MMP-8 overexpressing OTSCC cells were used to study the effect of MMP-8 on proliferation, apoptosis, migration, invasion and gene and protein expression. Moreover, MMP-8 functions were assessed in the orthotopic mouse tongue cancer model and by immunohistochemistry in patient samples. Results: MMP-8 reduced the invasion and migration of OTSCC cells and decreased the expression of MMP-1, cathepsin-K and vascular endothelial growth factor-C (VEGF-C). VEGF-C was induced by transforming growth factor-beta 1 (TGF-beta 1) in control cells, but not in MMP-8 overexpressing cells. In human OTSCC samples, low MMP-8 in combination with high VEGF-C was an independent predictor of poor cancer-specific survival. TGF-beta 1 treatment also restored the migration of MMP-8 overexpressing cells to the level of control cells. In mouse tongue cancer, MMP-8 did not inhibit metastasis, possibly because it was eliminated in the peripheral carcinoma cells. Conclusions: The suppressive effects of MMP-8 in OTSCC may be mediated through interference of TGF-beta 1 and VEGF-C function and altered proteinase expression. Together, low MMP-8 and high VEGF-C expression have strong independent prognostic value in OTSCC.Peer reviewe