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Diabetic foot ulcer (DFU) is a chronic wound and a common diabetic complication as 2% – 6% of diabetic patients witness the onset thereof. The DFU can lead to severe health threats such as infection and lower leg amputations, Coordination of interdisciplinary wound care requires well-written but time-consuming wound documentation. Artificial intelligence (AI) systems lend themselves to be tested to extract information from wound images, e.g. maceration, to fill the wound documentation. A convolutional neural network was therefore trained on 326 augmented DFU images to distinguish macerated from unmacerated wounds. The system was validated on 108 unaugmented images. The classification system achieved a recall of 0.69 and a precision of 0.67. The overall accuracy was 0.69. The results show that AI systems can classify DFU images for macerations and that those systems could support clinicians with data entry. However, the validation statistics should be further improved for use in real clinical settings. In summary, this paper can contribute to the development of methods to automatic wound documentation.
The diabetic foot ulcer, which 2% – 6% of diabetes patients experience, is a severe health threat. It is closely linked to the risk of lower extremity amputation (LEA). When a DFU is present, the chief imperative is to initiate tertiary preventive actions to avoid amputation. In this light, clinical decision support systems (CDSS) can guide clinicians to identify DFU patients early. In this study, the PEDIS classification and a Bayesian logistic regression model are utilised to develop and evaluate a decision method for patient stratification. Therefore, we conducted a Bayesian cutpoint analysis. The CDSS revealed an optimal cutpoint for the amputation risk of 0.28. Sensitivity and specificity were 0.83 and 0.66. These results show that although the specificity is low, the decision method includes most actual patients at risk, which is a desirable feature in monitoring patients at risk for major amputation. This study shows that the PEDIS classification promises to provide a valid basis for a DFU risk stratification in CDSS.
Rationale:
Biomechanical analyses are capable of capturing and evaluating human motions. In addition to the major biomechanical fields of kinetics and kinematics, electromyography (EMG) provides a reliable way to analyse neuromuscular activities, e.g. inter- and intramuscular coordination or fatigue behavior. Based on these parameters it is possible to conclude to clinically relevant parameters such as motor control, muscular coordination or compensation strategies with different loads. In addition to this, EMG can be used in treatment itself, e.g. biofeedback-training with an EMG is an effective and evidenced based tool to improve neuromuscular control.
Purpose:
To show the advantages of implementing EMG in performing artists´ health and to demonstrate additional therapy and diagnostic options.
Educational Objectives:
At the end of the workshop, the participants will be able to…
1.understand and describe the basic principles of EMG
2.understand and describe the importance of EMG in the context of performing artists´ health, physical therapy and clinical reasoning
3.use EMG on performing artists in the performance process
Content of Presentation:
This workshop briefly introduces the theoretical principles of EMG and the clinical applications in the context of performing artists´ health. It explains why EMG provides an additional value in the clinical reasoning process and supports the therapist, but decision making in the clinical reasoning process should never be based on EMG solely.
In the further course of the workshop the use of EMG in diagnostics and therapy (biofeedback) with performing artists is practically demonstrated and discussed with the participants.
Approach of Presentation:
1.Short presentation: introduction and understanding of EMG (educational objective 1)
2.Short case presentation of a performing artist to introduce EMG in the field of performing artists´ health and clinical reasoning (educational objective 2)
3.Interactive practical demonstration (diagnosis and biofeedback-training) as the central part of the workshop. Questions and comments will be discussed directly throughout the group (educational objective 3)
Clinical Significance:
EMG based functional neuromuscular diagnostics and biofeedback-training provides both the therapist as well as the performing artist with additional value in their clinical work.
Introduction: Hamstring injuries are among the most common injuries in soccer players. Especially the danger of hamstring injuries increases in the final third of each half, with the biceps femoris muscle being highly susceptible, but currently there is no supporting evidence in soccer players. It is important to investigate to provide a basis for further clinical investigations in order to reduce the risk of hamstring injuries.
Objective: To investigate a soccer-specific muscle fatigue protocol has an effect on the activation patterns of the biceps and semitendinosus muscles and correlates with the subjectively perceived exertion of the soccer players.
Methods: 19 healthy soccer players aged 19 - 35 years were included and underwent a standardized procedure that included: (1) performance of the nordic hamstring curls (NHC) and a 10m sprint (pre-test), (2) a soccer-specific muscle fatigue loading protocol for 30 minutes with subsequent rating of perceived exertion (RPE), (3) re-assessed like pre-assessment (post- test). Electromyography (EMG) data were recorded the biceps and
semitendinosus muscles of both legs. Two parameters were analyzed: the peak amplitude during the NHC and the mean amplitude during the 10m sprint.
Results: The RPE score (9.5, p<0.001) and 10m sprint shows significant differences between pre- and post- test for the biceps (standing leg: -82.45, kicking leg: -81.77; p<0.01) and semitendinosus muscle (standing leg: -60.08, p=0.001); kicking leg: -65.30, p=0.03). Significant correlation exists between RPE score and biceps muscles at posttest (standing leg: r=-0.54, kicking leg: r=-0.51; p<0.05).
Conclusion: Muscle fatigue leads to significant changes in the activation behavior of the hamstring muscles. In particular, the biceps muscle shows a correlation with perceived exertion, the higher the exertion, the lower the muscle activity. This may help explain the higher prevalence of the biceps muscle in hamstring injuries and offers a basis for further clinical investigations
Today's development of client-side web applications is based on one of the JavaScript-frameworks, such as Angular or React. The excessive dependencies that arise in the ecosystem from the Node-Package-Manager increase the security risk and the dependency of your own web application on third-party packages. Moreover, the frameworkless approach proposes a renaissance of classic web development, because it strives to avoid external dependencies as far as possible and to fall back on the standards. Whether the implementation achieves maintainability and security of frameworks is questionable. Therefore, it makes sense to research which core concepts of the frameworks meet the requirements for maintainability and security and how these are implemented. The novelty is that the concepts to be explored are moved to a standard in order to ensure the developer efficiency, security, performance and maintainability in the long term. This allows existing approaches to focus on other essential features.
Apps have been attested to empower patients regarding disease self-management through numerous studies. However, it is still unclear what factors determine the perception of patients whether an app is a useful tool for this purpose. A multiple regression model that was informed by the Technology Acceptance Model (TAM 2) was tested based on the answers of 235 app users with Diabetes type 1 or 2. The model accounted for 59.2% of the variance of the perceived degree of self-management. Factors belonging to the relevance-usefulness-quality complex as well as factors reflecting the patient’s self-control were found to be significant in the model. Patient demographics, i.e. age, gender, app experience and type of Diabetes did not play any significant role. In conclusion, this study raises the question whether apps should be designed to strengthen self-management in the sense of self-control (e.g. own measurements, diary) as opposed to guiding and advice giving.
With the start of the 21st century, patient safety as a topic of special interest has attracted increasing attention in both academia and clinical practice. As technology has continued to develop since then, questions and focal points surrounding the topic have also shifted. In particular, questions regarding the impact of digitalization on patient safety and its measurement are now of high interest. This work aims to develop a maturity assessment instrument in the form of a criteria set for measuring structural requirements for digital patient safety in hospitals. Based on the results of a literature review and a derivation of maturity objects (MO) from known maturity models, 64 criteria across 11 categories were developed. Written comments of two digital patient safety experts as well as subsequent interviews were used to evaluate and refine the criteria catalog. The resulting catalog offers hospitals guidance for detecting possible areas of structural improvements in their information systems with regard to patient safety and represents a unique instrument for assessing digital maturity in this particular area.
Venous leg ulcers and diabetic foot ulcers are the most common chronic wounds. Their prevalence has been increasing significantly over the last years, consuming scarce care resources. This study aimed to explore the performance of detection and classification algorithms for these types of wounds in images. To this end, algorithms of the YoloV5 family of pre-trained models were applied to 885 images containing at least one of the two wound types. The YoloV5m6 model provided the highest precision (0.942) and a high recall value (0.837). Its mAP_0.5:0.95 was 0.642. While the latter value is comparable to the ones reported in the literature, precision and recall were considerably higher. In conclusion, our results on good wound detection and classification may reveal a path towards (semi-) automated entry of wound information in patient records. To strengthen the trust of clinicians, we are currently incorporating a dashboard where clinicians can check the validity of the predictions against their expertise.
Rationale:
Neck pain is a large health problem worldwide and often seen in musicians [1, 2]. Neck pain can radiate into the arm due to various underlying pain types and pain mechanisms making it heterogeneous in clinical signs and symptoms [3-5]. On the one hand, patients may present with dominant nociceptive neck-arm pain caused by activation of the nociceptors in muscles, joints, ligaments, fascia, tendons and the connective tissues of a nerve [6, 7]. Activation of nociceptors in nerve connective tissues may cause clinical signs of heightened nerve mechanosensitivity what is per definition categorized as nociceptive pain [6, 8, 9]. On the other hand, patients may present with dominant neuropathic pain, defined as pain as a direct consequence of a lesion or disease affecting the somatosensory system [10, 11]. The clinical profile of these different pain types is sometimes difficult to disentangle based on the localization and pain character [12]. Moreover, non-specific neck-arm pain patients shown a neuropathic pain component based on somatosensory changes detected via Quantitative Sensory Testing (QST) [3, 13]. Classifications with a defined physical examination pathway can be helpful to define subgroups to guide the clinical decision making [14]. This workshop updates the background about the pathophysiology of neck-arm pain and mediates an evidence-based examination to classify patients.
Purpose:
The aim of this workshop is to give a current insight into the background and evidence of neck-arm pain and to plan and practice a physical examination.
Content of Presentation:
This workshop will summarize evidence of neck-arm pain. Thereupon, current evidencebased diagnostic options will be presented and practiced together. Finally, a short insight in the management of neck-arm pain will be given.
Approach of Presentation:
QST testing and current cost-effective evidence-based methods will be presented to identify neuropathic components in neck-arm pain. Selected methods will be performed practically together, e.g. bedside sensory testing and neurodynamic tests.
Clinical Significance:
After the workshop, participants will have improved skills to diagnose in the spectrum of neck-arm pain for musicians with neck-arm pain.
At the end of the presentation, the participants will be able to:
- understand the heterogeneity of neck-arm pain,
- plan an appropriate diagnostic physical examination,
- have an insight in possible management strategies.
The expiry of national subsidies for biogas in Germany means that new business models are needed. Furthermore, hydrogen is expected to make a significant contribution to the energy transition in the future. Therefore, potentials for the production of hydrogen from biogas are identified in this study. A joint upgrading infrastructure is developed that models the collaborative upgrading of biogas to hydrogen for existing biogas plants with subsequent gas grid injection. Furthermore, regions are identified that are particularly suitable as pioneer regions in Germany due to a high potential for green hydrogen production and comparatively low costs for hydrogen production. The modeling shows that collaborative upgrading achieves significant cost savings compared to single-farm upgrading. Furthermore, the potential for hydrogen production from biogas and the costs of upgrading differ significantly within the administrative districts in Germany.