Do Corticosteroids Still Have a Place in the Treatment of Chronic Pain?

Corticosteroids have played a standard role in the multimodal pain management in the treatment of chronic spinal pain (cervical and lumbar) and osteoarthritis pain over the past three decades. In this review we discuss different types of injectable steroids that are mainly used for injection into the epidural space (for the treatment of radicular back and neck pain), and as intra-articular injections for different types of osteoarthritis related pain conditions. Furthermore, we discuss different approaches taken for epidural corticosteroid injections and spinal surgical rates when injections fail to resolve painful conditions, as well as the possibility of using local anesthetics alone for neuraxial injections, instead of in combination with corticosteroids. While we present some beneficial effects of newly available treatment options for low back pain and osteoarthritis pain, such as use of PRP and hyaluronic acid, corticosteroids remain important considerations in the management of these chronic pain conditions

Imprecise knowledge based design and development of titanium alloys for prosthetic applications

Imprecise knowledge on the composition–processing–microstructure–property correlation of titanium alloys combined with experimental data are used for developing rule based models for predicting the strength and elastic modulus of titanium alloys. The developed models are used for designing alloys suitable for orthopedic and dental applications. Reduced Space Searching Algorithm is employed for the multi-objective optimization to find composition, processing and microstructure of titanium alloys suitable for orthopedic applications. The conflicting requirements attributes of the alloys for this particular purpose are high strength with low elastic modulus, along with adequate biocompatibility and low costs. The ‘Pareto’ solutions developed through multi-objective optimization show that the preferred compositions for the fulfilling the above objectives lead to β or near β-alloys. The concept of decision making employed on the solutions leads to some compositions, which should provide better combination of the required attributes. The experimental development of some of the alloys has been carried out as guided by the model-based design methodology presented in this research. Primary characterizations of the alloys show encouraging results in terms of the mechanical properties

Prevalence, associated factors and outcomes of pressure injuries in adult intensive care unit patients: the DecubICUs study

Funder: European Society of Intensive Care Medicine; doi: http://dx.doi.org/10.13039/501100013347Funder: Flemish Society for Critical Care NursesAbstract: Purpose: Intensive care unit (ICU) patients are particularly susceptible to developing pressure injuries. Epidemiologic data is however unavailable. We aimed to provide an international picture of the extent of pressure injuries and factors associated with ICU-acquired pressure injuries in adult ICU patients. Methods: International 1-day point-prevalence study; follow-up for outcome assessment until hospital discharge (maximum 12 weeks). Factors associated with ICU-acquired pressure injury and hospital mortality were assessed by generalised linear mixed-effects regression analysis. Results: Data from 13,254 patients in 1117 ICUs (90 countries) revealed 6747 pressure injuries; 3997 (59.2%) were ICU-acquired. Overall prevalence was 26.6% (95% confidence interval [CI] 25.9–27.3). ICU-acquired prevalence was 16.2% (95% CI 15.6–16.8). Sacrum (37%) and heels (19.5%) were most affected. Factors independently associated with ICU-acquired pressure injuries were older age, male sex, being underweight, emergency surgery, higher Simplified Acute Physiology Score II, Braden score 3 days, comorbidities (chronic obstructive pulmonary disease, immunodeficiency), organ support (renal replacement, mechanical ventilation on ICU admission), and being in a low or lower-middle income-economy. Gradually increasing associations with mortality were identified for increasing severity of pressure injury: stage I (odds ratio [OR] 1.5; 95% CI 1.2–1.8), stage II (OR 1.6; 95% CI 1.4–1.9), and stage III or worse (OR 2.8; 95% CI 2.3–3.3). Conclusion: Pressure injuries are common in adult ICU patients. ICU-acquired pressure injuries are associated with mainly intrinsic factors and mortality. Optimal care standards, increased awareness, appropriate resource allocation, and further research into optimal prevention are pivotal to tackle this important patient safety threat

Glucocorticoid hormones as modulators of the kynurenine pathway in chronic pain conditions

The pathogenesis of chronic pain entails a series of complex interactions among the nervous, immune, and endocrine systems. Defined as pain lasting or recurring for more than 3 months, chronic pain is becoming increasingly more prevalent among the US adult population. Pro-inflammatory cytokines from persistent low-grade inflammation not only contribute to the development of chronic pain conditions, but also regulate various aspects of the tryptophan metabolism, especially that of the kynurenine pathway (KP). An elevated level of pro-inflammatory cytokines exerts similar regulatory effects on the hypothalamic-pituitary-adrenal (HPA) axis, an intricate system of neuro-endocrine-immune pathways and a major mechanism of the stress response. As the HPA axis counters inflammation through the secretion of endogenous cortisol, we review the role of cortisol along with that of exogenous glucocorticoids in patients with chronic pain conditions. Considering that different metabolites produced along the KP exhibit neuroprotective, neurotoxic, and pronociceptive properties, we also summarize evidence rendering them as reliable biomarkers in this patient population. While more in vivo studies are needed, we conclude that the interaction between glucocorticoid hormones and the KP poses an attractive venue of diagnostic and therapeutic potential in patients with chronic pain

Modellering av fallissemang: Klassisk metod vs. maskininlärning

Fintech companies that offer Buy Now, Pay Later products are heavily dependent on accurate default probability models. This is since the fintech companies bear the risk of customers not fulfilling their obligations. In order to minimize the losses incurred to customers defaulting several machine learning algorithms can be applied but in an era in which machine learning is gaining popularity, there is a vast amount of algorithms to select from. This thesis aims to address this issue by applying three fundamentally different machine learning algorithms in order to find the best algorithm according to a selection of chosen metrics such as ROCAUC and precision-recall AUC. The algorithms that were compared are Logistic Regression, Random Forest and CatBoost. All these algorithms were benchmarked against Klarna's current XGBoost model. The results indicated that the CatBoost model is the optimal one according to the main metric of comparison, the ROCAUC-score. The CatBoost model outperformed the Logistic Regression model by seven percentage points, the Random Forest model by three percentage points and the XGBoost model by one percentage point.Fintechbolag som erbjuder Köp Nu, Betala Senare-tjänster är starkt beroende av välfungerande fallissemangmodeller. Detta då dessa fintechbolag bär risken av att kunder inte betalar tillbaka sina krediter. För att minimera förlusterna som uppkommer när en kund inte betalar tillbaka finns flera olika maskininlärningsalgoritmer att applicera, men i dagens explosiva utveckling på maskininlärningsfronten finns det ett stort antal algoritmer att välja mellan. Denna avhandling ämnar att testa tre olika maskininlärningsalgoritmer för att fastställa vilken av dessa som presterar bäst sett till olika prestationsmått så som ROCAUC och precision-recall AUC. Algoritmerna som jämförs är Logistisk Regression, Random Forest och CatBoost. Samtliga algoritmers prestanda jämförs även med Klarnas nuvarande XGBoost-modell. Resultaten visar på att CatBoost-modellen är den mest optimala sett till det primära prestationsmåttet ROCAUC. CatBoost-modellen var överlägset bättre med sju procentenheter högre ROCAUC än Logistisk Regression, tre procentenheter högre ROCAUC än Random Forest och en procentenhet högre ROCAUC än Klarnas nuvarande XGBoost-model

Analysis of factors affecting the fuel efficiency in passenger cars : Using multiple linear regression

Detta kandidatexamensarbete inom tillämpad matematik och industriell ekonomi undersöker olika faktorers påverkan på bränsleförbrukningen i personbilar. Detta görs genom att utföra en multipel linjär regression med programmet R. Dessutom utfors en analys av bilbranschen som täcker de interna och externa faktorerna som påverkar biltillverkare for att presentera en optimal strategi gällande FoU for biltillverkare med relativt låg omsättning. Denna analys är baserad på Porter's femkraftsmodell och en PEST-analys. Datan som används i regressionen är tillhandahållen av U.S. Environmental Protection Agency (EPA) och bestod av 1245 personbilar och bearbetades for att utföra regressionen. Resultaten från regressionsanalysen indikerar att det är möjligt att förklara cirka 80 % av bränsleförbrukningen i personbilar. Mer specifikt är det antalet cylindrar, typ av växellåda och cylinderdeaktiverings-system som har störst inverkan på bränsleförbrukningen. Dessutom visar den ekonomiska analysen av bilindustrin att starkt påverkande yttre faktorer som regleringar och ändrande kundpreferenser tillsammans med konkurrens från andra faktorer inom industrin utgör det största hotet. Den primära slutsatsen av detta kandidatexamensarbete är att biltillverkare med relativt låg omsättning borde implementera cylinderdeaktiveringssystem och överge \turbo-downsizing"-trenden inom industrin. Tillika bör manuella växellådor överges for att reducera bränsleförbrukningen, produktionskostnaderna och öka komforten for konsumenter.This thesis in applied mathematics and industrial economics investigates different factors affecting the fuel consumption in passenger cars. This is done by performing a multiple linear regression using the software R. Further, an analysis of the car industry is done covering the internal and external factors affecting the car manufacturers, in order to present an optimal strategy regarding RnD for car manufacturers having relatively low revenues. This analysis is based on Porter's five forces framework and a PEST-analysis. The data used for the regression has been gathered by the U.S. Environmental Protection Agency (EPA) and consists of 1245 passenger cars which was then processed in order to apply the regression. The results of the regression analysis performed indicated that it is possible to explain approximately 80% of the fuel consumption in passenger cars. More precisely, the number of cylinders, type of transmission and cylinder deactivation-system had the biggest impact on the fuel consumption. Furthermore the economic analysis of the industry revealed highly influencing external factors such as regulations and changing consumer preferences together with competition from other actors within the industry being the biggest threat. The main conclusion from this thesis is that car manufacturers having relatively small revenues should implement cylinder deactivation systems and abandon the turbo-downsizing trend within the industry. Furthermore manual gearboxes should be abandoned in order to reduce the fuel consumption and manufacturing costs while increase the comfort for the consumer

Analysis of factors affecting the fuel efficiency in passenger cars : Using multiple linear regression

Detta kandidatexamensarbete inom tillämpad matematik och industriell ekonomi undersöker olika faktorers påverkan på bränsleförbrukningen i personbilar. Detta görs genom att utföra en multipel linjär regression med programmet R. Dessutom utfors en analys av bilbranschen som täcker de interna och externa faktorerna som påverkar biltillverkare for att presentera en optimal strategi gällande FoU for biltillverkare med relativt låg omsättning. Denna analys är baserad på Porter's femkraftsmodell och en PEST-analys. Datan som används i regressionen är tillhandahållen av U.S. Environmental Protection Agency (EPA) och bestod av 1245 personbilar och bearbetades for att utföra regressionen. Resultaten från regressionsanalysen indikerar att det är möjligt att förklara cirka 80 % av bränsleförbrukningen i personbilar. Mer specifikt är det antalet cylindrar, typ av växellåda och cylinderdeaktiverings-system som har störst inverkan på bränsleförbrukningen. Dessutom visar den ekonomiska analysen av bilindustrin att starkt påverkande yttre faktorer som regleringar och ändrande kundpreferenser tillsammans med konkurrens från andra faktorer inom industrin utgör det största hotet. Den primära slutsatsen av detta kandidatexamensarbete är att biltillverkare med relativt låg omsättning borde implementera cylinderdeaktiveringssystem och överge \turbo-downsizing"-trenden inom industrin. Tillika bör manuella växellådor överges for att reducera bränsleförbrukningen, produktionskostnaderna och öka komforten for konsumenter.This thesis in applied mathematics and industrial economics investigates different factors affecting the fuel consumption in passenger cars. This is done by performing a multiple linear regression using the software R. Further, an analysis of the car industry is done covering the internal and external factors affecting the car manufacturers, in order to present an optimal strategy regarding RnD for car manufacturers having relatively low revenues. This analysis is based on Porter's five forces framework and a PEST-analysis. The data used for the regression has been gathered by the U.S. Environmental Protection Agency (EPA) and consists of 1245 passenger cars which was then processed in order to apply the regression. The results of the regression analysis performed indicated that it is possible to explain approximately 80% of the fuel consumption in passenger cars. More precisely, the number of cylinders, type of transmission and cylinder deactivation-system had the biggest impact on the fuel consumption. Furthermore the economic analysis of the industry revealed highly influencing external factors such as regulations and changing consumer preferences together with competition from other actors within the industry being the biggest threat. The main conclusion from this thesis is that car manufacturers having relatively small revenues should implement cylinder deactivation systems and abandon the turbo-downsizing trend within the industry. Furthermore manual gearboxes should be abandoned in order to reduce the fuel consumption and manufacturing costs while increase the comfort for the consumer

Analysis of factors affecting the fuel efficiency in passenger cars : Using multiple linear regression

Detta kandidatexamensarbete inom tillämpad matematik och industriell ekonomi undersöker olika faktorers påverkan på bränsleförbrukningen i personbilar. Detta görs genom att utföra en multipel linjär regression med programmet R. Dessutom utfors en analys av bilbranschen som täcker de interna och externa faktorerna som påverkar biltillverkare for att presentera en optimal strategi gällande FoU for biltillverkare med relativt låg omsättning. Denna analys är baserad på Porter's femkraftsmodell och en PEST-analys. Datan som används i regressionen är tillhandahållen av U.S. Environmental Protection Agency (EPA) och bestod av 1245 personbilar och bearbetades for att utföra regressionen. Resultaten från regressionsanalysen indikerar att det är möjligt att förklara cirka 80 % av bränsleförbrukningen i personbilar. Mer specifikt är det antalet cylindrar, typ av växellåda och cylinderdeaktiverings-system som har störst inverkan på bränsleförbrukningen. Dessutom visar den ekonomiska analysen av bilindustrin att starkt påverkande yttre faktorer som regleringar och ändrande kundpreferenser tillsammans med konkurrens från andra faktorer inom industrin utgör det största hotet. Den primära slutsatsen av detta kandidatexamensarbete är att biltillverkare med relativt låg omsättning borde implementera cylinderdeaktiveringssystem och överge \turbo-downsizing"-trenden inom industrin. Tillika bör manuella växellådor överges for att reducera bränsleförbrukningen, produktionskostnaderna och öka komforten for konsumenter.This thesis in applied mathematics and industrial economics investigates different factors affecting the fuel consumption in passenger cars. This is done by performing a multiple linear regression using the software R. Further, an analysis of the car industry is done covering the internal and external factors affecting the car manufacturers, in order to present an optimal strategy regarding RnD for car manufacturers having relatively low revenues. This analysis is based on Porter's five forces framework and a PEST-analysis. The data used for the regression has been gathered by the U.S. Environmental Protection Agency (EPA) and consists of 1245 passenger cars which was then processed in order to apply the regression. The results of the regression analysis performed indicated that it is possible to explain approximately 80% of the fuel consumption in passenger cars. More precisely, the number of cylinders, type of transmission and cylinder deactivation-system had the biggest impact on the fuel consumption. Furthermore the economic analysis of the industry revealed highly influencing external factors such as regulations and changing consumer preferences together with competition from other actors within the industry being the biggest threat. The main conclusion from this thesis is that car manufacturers having relatively small revenues should implement cylinder deactivation systems and abandon the turbo-downsizing trend within the industry. Furthermore manual gearboxes should be abandoned in order to reduce the fuel consumption and manufacturing costs while increase the comfort for the consumer