Optimal Threshold Level Research Articles

External Debt and Economic Growth in Sierra Leone: A Threshold Analysis

The main focus of this study is to investigate the impact of external debt on economic growth and determine the threshold level of external debt that is favourable for economic growth in Sierra Leone, within the framework of a non-linear model (quadratic function). The study employs the Ordinary Least Squares estimation technique with annual time series data for the period 1980 to 2022. The empirical findings reveal that, lagged GDP, external debt, external debt squared and investment are the main drivers of economic growth in Sierra Leone. Specifically, the result reveals that external debt, investment and lagged GDP have a positive impact on growth whilst, external debt squared has a harmful impact on growth. Furthermore, the study establishes a nonlinear relationship between external debt and economic growth. The result indicates that the optimal threshold level of external debt (as a % of GDP) in Sierra Leone is 115%. The findings reveal that, external debt below the threshold level is growth enhancing. However, the accumulation of external debt beyond the threshold level of 115% is detrimental to growth. The diagnostic result confirms that about 76% of the variation in economic growth is explained by the regressors (independent variables). Also, the granger causality test result suggests a unidirectional causality from external debt to economic growth with no reverse causality, indicating that external debt granger caused economic growth at the 5% level. Based on the findings, the study recommends that, government should develop a robust debt management policy, to keep debt levels within sustainable limits and also cultivate an economic culture of transparency, on the issue of debt management and contract negotiations.

Unveiling the relationship between the optimal debt threshold level and debt-economic growth in selected indebted countries: panel threshold analysis

Unveiling the relationship between the optimal debt threshold level and debt-economic growth in selected indebted countries: panel threshold analysis

Threshold effect of non-interest income disaggregates on commercial banks’ financial performance in Zimbabwe

Financial performance has become a trending concept in corporate finance and strategic management in recent times especially in the aftermath of the Global Financial Crisis (GFC) of 2007–2009. As an antidote to charter value erosion caused by stiff competition from incumbents in traditional banking activities, banks venture into non-core banking activities as a diversification and survival strategy. The purpose of the study is to determine the optimal threshold levels of non-interest income that stimulate financial performance of ten Zimbabwean commercial banks using non-interest income disaggregates over 2009–2020. Unfortunately, studies that examine the non-interest-income-financial performance nexus of banks involved in intermediation are scant and inconclusive. Furthermore, the use of threshold models to crack this puzzle are conspicuous. The study employed Fully Modified Ordinary Least Squares and Threshold difference Generalized Methods of Moment nonlinear threshold approaches. The aggregated and disentangled non-interest income dynamic optimal thresholds found are 26 %, 17 % and 10 % whereas the average static ones are 35 %, 28 % and 17 %. Compared to aggregated non-interest income, the study reveals that the disaggregates pose a greater positive impact on financial performance of banks in the upper regime than their counterparts in the lower regime. In addition, more banks were found to be operating below the required minimum thresholds. To avert episodes of bank failures and hedging against banking sector fragility, commercial bank managers should come up with well-diversified portfolios of income-generating ventures. Also, central bank regulations must promote non-interest activities, competition, growth and reduce leverage of commercial banks.

Predictors of Significant Histological Hepatic Abnormality in Treatment-Naive Patients Infected with HBeAg-Negative Chronic Hepatitis B.

This study aimed to determine the predictors for significant hepatic abnormality (SHA), a treatment indication, by assessing demographic, laboratory, and radiological results of chronic hepatitis B (CHB) patients who underwent liver biopsy. In this retrospective study, individuals with untreated hepatitis B e-antigen (HBeAg)-negative CHB infection were enrolled. Multivariate analysis modeling was conducted with parameters identified as predictors for SHA in univariate analysis. Optimal threshold levels for variables to predict SHA in patients with chronic hepatitis B were determined based on receiver operating characteristic (ROC) curve analysis. A total of 566 patients with untreated chronic hepatitis B were included in the cohort; 61% (345/566) were male, and the median age was 41 years (interquartile range [IQR]=34-50). Notably, 36.9% (209/566) had SHA. In the multivariate analysis, utilizing different models, age, gender, HBV-DNA, LDL, ALT, and platelet count were identified as the most reliable predictors for SHA in CHB patients. For predicting SHA, the area under the ROC curve values of HBV-DNA, AST, and ALT were 0.704 (sensitivity=62.8%, specificity=76.2%; p<0.0001), 0.747 (sensitivity=51.9%, specificity=88.9%; p<0.0001), and 0.737 (sensitivity=68.6%, specificity=68.4%; p<0.0001), respectively. In our study, age, male gender, ALT, AST, HBV-DNA, LDL cholesterol, platelet count, and FIB-4 score were independent predictors of SHA in HBeAg-negative chronic hepatitis B. The most sensitive parameters for SHA were LDL and ALT. The most specific parameters were age, AST, and APRI score. SHA may occur in patients with high HBV-DNA levels, even if ALT values are normal in HBeAg-negative patients.

Threshold effects of inflation on the FDI – growth nexus: evidence from inflation-targeting countries in sub-Saharan Africa

The purpose of this study is to examine the threshold effect of inflation on the foreign direct investment (FDI) – economic growth nexus in sub-Saharan Africa using panel samples of countries that have adopted an inflation-targeting regime. The study sourced data from the World Bank’s World Development Indicators over a period of 1982–2020 and adopted the fixed-effect panel threshold model approach for its analysis. The findings reveal two separate thresholds of inflation in the FDI – growth nexus. The growth-enhancing effect of FDI is largely realized when inflation is below the optimal threshold level of 7.26%. Beyond the second threshold level of 16.49%, the beneficial effect of FDI on growth is seen to diminish in terms of effect-size. This study provides new insights into the growth effect of FDI and the role of inflation levels in this nexus. The thresholds of inflation and the attendant size-effect of FDI on growth can be benchmarks for Africa and other developing and emerging economies in assessing their situations. As African monetary authorities choose which inflation targets to set for their monetary policies, the findings raise significant implications for them.

GOVERNMENTEXPENDITUREONECONOMICGROWTH:EMPIRICAL EVIDENCE FROM GHANA

In free market finance, the government plays an essential role. The government really does a lot for an economy. When markets can't solve problems on their own, governments must step in to offer public goods, address externalities, and enforce competition. The issue for every economy that wants its government to fulfill its function is finding the right size of government (total expenditures by the government as a percentage of GDP) to promote long-term prosperity. Government spending in Ghana has increased over the previous two decades, according to data on fiscal behavior, but GDP growth has lagged behind. Using a time series data analysis, this study aimed to shed new empirical light on the connection between government size and economic growth in Ghana, as well as identify the optimal threshold level at which government final consumption may contribute to rapid development. The research found that higher levels of government spending contributed directly to economic expansion. The analysis concluded that a threshold of 0.114% for government spending was optimal for promoting growth in the economy. Therefore, the study urges fiscal discipline and control to maintain the optimal level of government spending, which would have a multiplier effect on other parts of the economy and prevent crowding out.

Negative impact of immunoparesis in response to anti-SARS-CoV-2 mRNA vaccination of patients with multiple myeloma.

Multiple myeloma reduces cellular and humoral immunity. Optimal prediction of antibody response to anti-severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccine in patients with MM and related disorders is essential to prevent coronavirus disease 2019 (COVID-19) during the SARS-CoV-2 pandemic. This study analyzed the humoral response to the anti-SARS-CoV-2 messenger ribonucleic acid (mRNA) vaccine and its associated factor in 83 patients from June to November 2021 at seven member institutions of the Kyoto Clinical Hematology Study Group. SARS-CoV-2 neutralizing antibody (nAb) was measured from 12 to 210days. The result revealed that 40 (48.2%) patients with MM and 59 (100%) healthy controls became seropositive after vaccination. Receiver operating characteristic curve analysis identified serum immunoglobulin (Ig) M of > 18mg/dL at vaccination as the optimal threshold level associated with seropositivity in the whole cohort. Moreover, the multivariate analysis identified serum IgM of > 18mg/dL as the independent predictor for a favorable response. Serum IgA level was positively associated with vaccine response in a sub-cohort. Our findings indicate a significant association between immunoparesis and impaired humoral response against mRNA vaccination, including that against SARS-CoV-2, and that serum non-M-protein Ig levels can serve as surrogate biomarkers of nAb production ability.

Preoperative Level of Insulin-Like Growth Factor Binding Protein 2 Predicts The Suboptimal Outcome After Primary Debulking Surgery in Patients with Advance Ovarian Cancer

BACKGROUND: The need for clinically useful biomarkers which can predict the surgical outcome after primary debulking surgery (PDS) in patients with advance ovarian cancer (AOC) is really important. Insulin-like growth factor-binding protein 2 (IGFBP2) is the main binding protein expressed by ovarian cancer cells, which plays a prominent role in promoting proliferation, driving invasion, and suppressing apoptosis. This study was conducted to assess the performance of IGFBP2 in predicting the surgical outcome after PDS in patients with AOC.METHODS: Twenty-four subjects with AOC (Stage IIIc/IV) who underwent PDS were recruited consecutively. Clinicopathologic data were obtained from subjects' medical records. Blood samples were withdrawn form each subject and preoperative level of IGFBP2 were measured using enzyme-linked immunosorbent assay (ELISA). Multivariate analysis was employed to test the performance of multiple predictors of surgical outcome.RESULTS: Eighteen patients (75%) had suboptimal outcome after PDS. Mean IGFBP2 level was significantly higher in the suboptimal group (1157.5±359.9 ng/mL vs. 679.1±504.5 ng/mL, p=0.018). In bivariate model, higher preoperative level of IGFBP2 predict the suboptimal outcome with good accuracy (AUC: 0.796, sensitivity: 83.3%, specificity: 83.3%, p=0.033, optimal threshold level 870 ng/mL). Higher IGFBP2 level was associated with higher risk of suboptimal outcome, although IGFBP2 was not an independent risk factor (adjusted OR: 5.0, 95% CI: 0.43-57.9, p=0.198).CONCLUSION: IGFBP2 is a novel and promising biomarker for surgical outcome prediction following PDS in AOC patients. Since it is predictive for suboptimal outcome, patients with higher preoperative level of IGFBP2 needs more thorough preoperative evaluation as well as meticulous surgical technique to optimize the surgical outcome.KEYWORDS: IGFBP2, advance ovarian cancer, PDS, surgical outcome, predictor

Threshold level of Peptest in diagnosing gastroesophageal reflux disease with extraesophageal symptoms: Evidence from Vietnam.

We aimed to evaluate the application of Peptest, a novel technique to detect pepsin in the saliva, and identify its threshold level for the diagnosis of gastroesophageal reflux disease (GERD) with extraesophageal symptoms. A cross-sectional study was conducted in two groups: patients with extraesophageal GERD symptoms (symptomatic group divided into GERD and non-GERD groups according to 24-h esophageal pH-impedance monitoring [pH-I] results) and healthy controls. For the symptomatic group, endoscopy, pH 24 h, high-resolution manometry (HRM), and salivary Peptest were performed. For the healthy control group, only Peptest was done. The accuracy of Peptest was compared with that of pH-I by the Lyon consensus criteria. Chronic laryngitis was the most frequent extraesophageal symptom. On saliva testing, the GERD group had a higher prevalence of positive samples and pepsin concentration than the control group. Between GERD and non-GERD groups, the optimal threshold level was 31.2 ng/mL, with a sensitivity of 86.7% and specificity of 27.5%. The optimal threshold level was 31.4 ng/mL to differentiate GERD from healthy controls, with a sensitivity of 86.7% and specificity of 66.0%. Age, number of total refluxes, DeMeester score, post-reflux swallow-induced peristaltic wave (PSPW) index, and mean nocturnal baseline impedence (MNBI) were associated with pepsin concentration. Regarding HRM metrics, there was no significant difference of pepsin concentration between low/normal upper esophageal sphincter (UES) resting pressure, low/normal lower esophageal sphincter (LES) resting pressure, low/normal 4-s integrated relaxation pressure (IRP4s), and hypomotility/normal motility. Patients with extraesophageal symptoms had a higher prevalence of positive Peptest. The optimum threshold level of 31.4 ng/mL had high sensitivity and moderate specificity to differentiate between patients with GERD and healthy controls.

“Good” and “bad” volatilities: a realized semivariance GARCH approach

ABSTRACT In this article, we explore the realized semivariation measures using high-frequency intraday data within the framework of realized semivariance GARCH by taking an in-depth look. We derive general theoretical expressions for moment conditions of returns and realized semivariation measures, providing a convenient approach to investigate the statistical properties of realized semivariation dynamics. Notably, the introduction of threshold effects in the model reveals several intriguing empirical findings. One significant discovery is that during a substantial decline in returns, the negative realized semivariance exerts a more influential impact on future volatility compared to its positive counterpart. We further examine the forecasting performance under a realized semivariance heterogeneous autoregression environment. The results demonstrate that the inclusion of thresholds and the adoption of an optimal threshold level generally enhance the accuracy of volatility forecasting.

Link quality improvement analysis of relay-assisted hybrid RF/FSO systems in challenging environments

Hybrid RF/FSO systems have gained significant attention recently as a reliable approach to enhancing wireless data transmission rates. Intelligent selection between RF and FSO links, driven by the switching mechanism and diversity, plays a pivotal role in ascertaining the quality of the connection. This process, hinged upon a predefined threshold, significantly influences link quality determination. However, conventional methods for determining the switching rely on extensive numerical simulation leading to abrupt switching. To address this issue, this paper introduces an innovative relay-assisted multi-link hybrid switching mechanism that combines RF/FSO technologies. Notably, the proposed mechanism integrates a link-quality aware strategy to attain an optimal threshold level, thereby addressing the aforementioned problem effectively. The proposed mechanism utilizes an evolutionary seagull-based link quality-aware switching scheme to minimize bit error rates while maximizing capacity, considering the outage probability of both RF and FSO systems. The proposed methodology enhances the overall quality of links by introducing an intermediate decode-and-forward relay and multiple connections. Several criteria, including as outage probability, bit error rate, and ergodic capacity, are used to evaluate this improvement. A comparative analysis is conducted to evaluate the performance of the proposed approach in contrast to existing FSO systems. The findings highlight the promising capabilities of the relay-assisted hybrid RF/FSO system, showcasing its ability to significantly improve the quality of connections. This research contributes to advancing hybrid RF/FSO systems and their applicability in scenarios where atmospheric conditions, pointing errors, and fading effects influence link quality.

Mitigating the effects of a pandemic in sub-Saharan Africa: are fiscal and monetary policy complementary or contradictory?

PurposeThe study examined the roles of fiscal and monetary policy in reducing poverty in sub-Saharan Africa (SSA), while accounting for macroeconomic disruptions. In particular, the study examined the complementarity of fiscal and monetary policy to mitigate shocks and reduce poverty in SSA.Design/methodology/approachThe study adopts the fixed effect (within regression) model to account for country-specific characteristics, and a cross-sectional dependence – consistent model to control for the potential cross-sectional in panel data modelling. The study used the dummy variable approach to account for the macroeconomic shocks. The authors assigned 1 to the following years – 2008, 2014 and 2020; and 0 otherwise to take care of the global financial crisis, commodity terms of trade shocks and the COVID-19 pandemic respectively.FindingsThe study found that fiscal policy (particularly, government spending on health and education) has the greater capacity to reduce the level of poverty in SSA. The results also indicate that fiscal policy and monetary policy can work in tandem to reduce the negative effects of a pandemic. However, the study found an optimal threshold level of monetary policy beyond which monetary policy reduces the effectiveness of fiscal policy to reduce poverty in SSA. The research and policy implications are discussed.Originality/valueThe study, unlike previous studies, accounts for the impact of macroeconomic shocks in the monetary/fiscal policy and poverty literature.

Remote Tracking of Distributed Dynamic Sources Over a Random Access Channel With One-Bit Updates

In this work, we consider a network, where distributed information sources whose states evolve according to a random process transmit their time-varying states to a remote estimator over a shared wireless channel. Each source generates packets in a decentralized manner and employs a slotted random access mechanism to transmit the packets. In particular, we are interested in networks with a large number of low-complexity devices that share low-capacity random access channels. Accordingly, we investigate update strategies for remote tracking of source states that require each update to constitute as few bits as possible. To that end, we develop update strategies requiring only one-bit of information per update that employ a local cancellation strategy. We further analytically compare the performance of the cancellation-enabled update policy to the optimal policy that does not restrict the number of bits for each update, which show that an asymptotic upper bound of the optimality ratio is <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\frac{13\sqrt{2}}{12}$</tex-math></inline-formula> . Through simulations, we compare the proposed cancellation-enabled one-bit update policy with zero-wait sampling and threshold-based sampling policies that require more than one-bit of information per update. The comparisons show that the cancellation-enabled update policy at its optimal threshold level outperforms the multi-bit update policies.

Performance of Galectin-9 for Identification of HIV Viremia in Adults Receiving Antiretroviral Therapy in a Resource-Limited Setting.

Targeted viral load (VL) testing has been proposed for antiretroviral treatment (ART) monitoring in resource-limited settings. In this study, we have investigated the performance of the host biomarker galectin-9 (Gal-9), alone and in combination with interferon-γ-inducible protein 10 (IP-10), in identifying individuals at increased likelihood of viremia during ART. Cohort of HIV-positive adults receiving ART at Ethiopian health centers. We included participants with detectable viremia (VL ≥150 copies/mL) 12 months after starting ART and sex-matched nonviremic controls. Performance to identify individuals with VL ≥1000 copies/mL was determined for Gal-9 and the Gal-9/IP-10 combination, respectively, using receiver operating characteristic (ROC) analysis. Among 191 participants (50.3% women), 46 (24.1%) had VL ≥1000 copies/mL, 23 (12.0%) had 150-999 copies/mL, and 122 (63.9%) had <150 copies/mL. Gal-9 and VL were positively correlated (r s = 0.451, P < 0.001). Sensitivity and specificity for Gal-9 to identify individuals with VL ≥1000 copies/mL were 91.3% (95% CI: 79.2-97.6) and 54.5% (95% CI: 46.0-62.8), respectively. The area under the ROC curve for Gal-9 was 0.810 (95% CI: 0.745-0.875), which was similar to that of the combination of Gal-9 and IP-10 [0.849 (95% CI: 0.792-0.905)]. Assuming 10% prevalence of VL ≥1000 copies/mL, using Gal-9 for targeted VL testing instead of universal VL testing would reduce the number of VL tests from 10 to 5 to identify 1 viremic individual, with misclassification of 1 in 10 viremic individuals. Gal-9 is a potential screening marker for targeted VL monitoring in ART recipients. Further studies are needed to determine optimal threshold levels.

Benchmarking framework for anomaly localization: Towards real-world deployment of automated visual inspection

Localizing defects in products is a critical component of industrial pipelines in manufacturing, retail, and many other industries to ensure consistent delivery of high quality products. Automated anomaly localization systems leveraging computer vision have the potential to replace laborious and subjective manual inspection of products. Recently, there have been tremendous efforts in this research domain investigating deep learning-based anomaly localization methods. However, such proposed methods, mainly considering product-specific evaluation, cannot be directly implemented for real-world use. Therefore, despite the advancements, there is still a gap between research and deployment of those methods to real-world production environments. Implementing any automated solution for manufacturing can involve a steep upfront investment. It is important to develop an industry-friendly benchmarking framework to ensure the feasibility and robustness of an automated quality control system. In this paper, we present a new anomaly localization benchmarking framework considering different aspects - (1) understand the performance of models in a generalizable product-agnostic manner, (2) explore pros and cons to find the most optimal modeling approach, (3) develop an efficient training and inference scheme with defect-free training samples and very few defective samples for evaluation, and (4) perform an ablation study of threshold estimation techniques to determine optimal threshold level for segmentation. We release a newly-labeled dataset for the research community with product-agnostic categorization of defective product images. To the best of our knowledge, this is the first anomaly localization work on developing a benchmarking framework focusing on real-world use. We believe domain experts from different industries will find this useful and can gain valuable insights to deploy automated visual inspection in production pipelines.

A Review on Vitamin D Deficiency and Related Disorders: What is the Right Serum Vitamin D Level?

To maintain a healthy skeleton, vitamin D is crucial for phosphate as well as calcium uptake. It is of great significance for maintaining the various adaptive and innate immune response components. To reduce the development of various immune-related disorders, such as diabetes, hypertension, cardiovascular diseases, rheumatoid arthritis, and coronavirus disease 2019 (COVID-19), numerous studies evaluating the optimal threshold levels for serum 25-hydroxyvitamin D [25(OH)D]. It is documented in various evidence to increase the serum 25(OH)D intake from the current mindset of 30-50 ng/mL to attain the best overall vitamin D benefits. These values are in line with the results of various research showing that increased vitamin D intake is linked to a decreased risk of cancer and cardiovascular diseases. Therefore, it becomes vital to understand the "right" vitamin D levels to avoid deficiency along with its related disorders. In contrast to 30 ng/mL, this review emphasizes the significance of increasing vitamin D levels to 50 ng/mL to obtain several physiological benefits. An individual needs at least 60000 IU for 12 weeks to maintain serum vitamin D levels above 30 ng/mL. The article will interest physicians who desire to profit fully from vitamin D's influence on clinical practice.

Novel concept for water scarcity quantification considering nonconventional and virtual water resources in arid countries: Application in Gulf Cooperation Council countries

The lack of perennial streams or surface water in most arid countries necessitates input modification and water scarcity/security equation calculation as per the water resource systems and physiographic conditions in these countries. The contributions of nonconventional and virtual water resources to water security have been disregarded or undervalued in previous research on global water scarcity. This study addresses this knowledge gap by developing a new framework for estimating water scarcity/security. The proposed framework considers the contributions of unconventional and virtual water resources and the roles of economics, technology, water availability, service accessibility, water safety and quality, water management, and resilience to threats on water and food security, and considers institutional changes required to adjust to water scarcity. To manage water demand, the new framework incorporates metrics for all categories of water resources. Although the framework was specifically designed for arid regions, particularly the Gulf Cooperation Council (GCC) countries, it is applicable to non-arid nations too. The framework was implemented in GCC countries, which are suitable examples of arid countries with notable virtual commerce. The ratio of abstraction from freshwater resources to renewability from conventional water sources was calculated to determine the extent of water stress in each country. The values obtained from measurement varied from 0.4 (the optimal threshold level for Bahrain) to 22 (severe water stress/low water security in Kuwait). Considering the nonconventional and abstracted nonrenewable groundwater volumes from the total water demand in the GCC, the minimum water stress value measured was 0.13 in Kuwait, suggesting considerable reliance on nonconventional water resources along with little domestic food production to achieve water security. The novel water scarcity/stress index framework was found to be appropriate for arid and hyper-arid regions, such as the GCC, where virtual water trade has a major positive impact on water security.

Efficient Approach to Color Image Segmentation Based on Multilevel Thresholding Using EMO Algorithm by Considering Spatial Contextual Information.

The process of image segmentation is partitioning an image into its constituent parts and is a significant approach for extracting interesting features from images. Over a couple of decades, many efficient image segmentation approaches have been formulated for various applications. Still, it is a challenging and complex issue, especially for color image segmentation. To moderate this difficulty, a novel multilevel thresholding approach is proposed in this paper based on the electromagnetism optimization (EMO) technique with an energy curve, named multilevel thresholding based on EMO and energy curve (MTEMOE). To compute the optimized threshold values, Otsu's variance and Kapur's entropy are deployed as fitness functions; both values should be maximized to locate optimal threshold values. In both Kapur's and Otsu's methods, the pixels of an image are classified into different classes based on the threshold level selected on the histogram. Optimal threshold levels give higher efficiency of segmentation; the EMO technique is used to find optimal thresholds in this research. The methods based on an image's histograms do not possess the spatial contextual information for finding the optimal threshold levels. To abolish this deficiency an energy curve is used instead of the histogram and this curve can establish the spatial relationship of pixels with their neighbor pixels. To study the experimental results of the proposed scheme, several color benchmark images are considered at various threshold levels and compared with other meta-heuristic algorithms: multi-verse optimization, whale optimization algorithm, and so on. The investigational results are illustrated in terms of mean square error, peak signal-to-noise ratio, the mean value of fitness reach, feature similarity, structural similarity, variation of information, and probability rand index. The results reveal that the proposed MTEMOE approach overtops other state-of-the-art algorithms to solve engineering problems in various fields.

Spinal Epidural Abscess: Early Suspicion in Emergency Department Using C-Reactive Protein and Erythrocyte Sedimentation Rate Tests.

Spinal epidural abscess (SEA) is an uncommon but serious differential diagnosis of acute spinal pain with high paralysis and mortality rate. This study aims to provide local data on its bioclinical characteristics and evaluate potential strategies to enhance its diagnostic rate in accident and emergency department (AED). A retrospective case study from 2013 to 2019 was conducted in United Christian Hospital. SEA cases were classified as study group, spinal pain due to non-SEA cases were classified as control group. Data collected from study group included symptoms, radiological diagnosis, microbiological culture, treatment, and outcome. C-reactive protein (CRP) and erythrocyte sedimentation rate (ESR) of both groups were compared to analyze their diagnostic power. In the study group (n = 42), 93% of patients had spinal pain, 55% had fever, 60% had neurological deficits, and only 26% had the classic triad on presentation. Seventy-four percent of patients presented with spinal cord or cauda equina compression in their first magnetic resonance imaging. Mortality rate was 23.8%, and paralysis rate was 7.1%. Diagnostic accuracy in AED was 12%. Admission to orthopedic ward (n = 23) resulted in a significantly lower mean time-to-imaging (4.39 days vs. 14.58 days) and mean time-to-treatment (6.56 days vs. 16.9 days) as compared to other specialties. The area under curves of CRP and ESR were 0.893 and 0.874 respectively, the optimal threshold levels were 45.9 mg/L (sensitivity 82.9%, specificity 79%) and 59.5 mm/hr (sensitivity 87.2%, specificity 80.4%), respectively. Diagnosis of SEA in emergency department based on clinical symptomatology is not reliable due to low incidence of the classic triad, despite a more advanced disease on presentation. We proposed incorporating CRP and ESR tests into evaluation of patients with spinal pain since both tests demonstrated excellent discriminative power in diagnosing SEA.

A refracted Lévy process with delayed dividend pullbacks

ABSTRACT The threshold dividend strategy, under which dividends are paid only when the insurer's surplus exceeds a pre-determined threshold, has received considerable attention in risk theory. However, in practice, it seems rather unlikely that an insurer will immediately pull back the dividend payments as soon as its surplus level drops below the dividend threshold. Hence, in this paper, we propose a refracted Lévy risk model with delayed dividend pullbacks triggered by a certain Poissonian observation scheme. Leveraging the extensive literature on fluctuation identities for spectrally negative Lévy processes, we obtain explicit expressions for two-sided exit identities of the proposed insurance risk process. Also, penalties are incorporated into the analysis of dividend payouts as a mechanism to penalize for the volatility of the dividend policy and account for an investor's typical preference for more stable cash flows. An explicit expression for the expected (discounted) dividend payouts net of penalties is derived. The criterion for the optimal threshold level that maximizes the expected dividend payouts is also discussed. Finally, several numerical examples are considered to assess the impact of dividend delays on ruin-related quantities. We numerically show that dividend strategies with more steady dividend payouts can be preferred (over the well-known threshold dividend strategy) when penalty fee become too onerous.