Uremic pruritus: pathophysiology, clinical presentation, and treatments

Uremic pruritus is one of the most common and bothersome symptoms in patients with end-stage renal disease. Most patients with uremic pruritus experience a prolonged and relapsing course and significant impairments of quality of life. The pathophysiology of uremic pruritus is not completely understood. A complex interplay among cutaneous biology and the nervous and immune systems has been implicated, with the involvement of various inflammatory mediators, neurotransmitters, and opioids. Uremic pruritus treatment outcomes are often unsatisfactory. Clinical trials have mostly been small in scale and have reported inconsistent results. Recent evidence shows that gabapentinoids, nalfurafine, and difelikefalin are effective for relieving uremic pruritus in hemodialysis patients. This review provides an overview of the epidemiology and proposed mechanisms of uremic pruritus, then highlights the manifestations of and clinical approach to uremic pruritus. Current evidence regarding treatment options, including topical treatments, treatment of underlying disease, phototherapy, and systemic treatments, is also outlined. With a better understanding of uremic pruritus, more therapeutic options can be expected in the near future.

Feature generation and contribution comparison for electronic fraud detection.

Modern money transfer services are convenient, attracting fraudulent actors to run scams in which victims are deceived into transferring funds to fraudulent accounts. Machine learning models are broadly applied due to the poor fraud detection performance of traditional rule-based approaches. Learning directly from raw transaction data is impractical due to its high-dimensional nature; most studies construct features instead by extracting patterns from raw transaction data. Past literature categorizes these features into recency, frequency, monetary, and anomaly detection features. We use various machine learning algorithms to examine the performance of features in these four categories with real transaction data; we compare them with the performance of our feature generation guideline based on the statistical perspectives and characteristics of (non)-fraudulent accounts. The results show that except for the monetary category, other feature categories used in the literature perform poorly regardless of which machine learning algorithm is used; anomaly detection features perform the worst. We find that even statistical features generated based on financial knowledge yield limited performance on a real transaction dataset. Our atypical detection characteristic of normal accounts improves the ability to distinguish them from fraudulent accounts and hence improves the overall detection results, outperforming other existent methods.

Increased risk of Parkinson's disease among patients with age-related macular degeneration.

BACKGROUND: This study aimed to investigate the risk of Parkinson's disease (PD) among patients with age-related macular degeneration (AMD) and its association with confounding comorbidities. METHODS: A population-based retrospective cohort study was conducted using Longitudinal Health Insurance Database 2000 (LHID2000). We established AMD and non-AMD cohorts from January 1, 2000 to December 31, 2012 to determine the diagnosis of PD. A total of 20,848 patients were enrolled, with 10,424 AMD patients and 10,424 controls matched for age, sex, and index year at a 1:1 ratio. The follow-up period was from the index date of AMD diagnosis to the diagnosis of PD, death, withdrawal from the insurance program, or end of 2013. Multivariable Cox regression analysis was performed to examine the hazard ratio (HR) and 95% confidence interval (CI) for the risk of PD between the AMD and non-AMD cohorts. RESULT: After adjusting for potential confounders, there was a higher risk of developing PD in the AMD cohort than in the non-AMD cohort (adjusted HR = 1.35, 95% CI = 1.16-1.58). A significant association could be observed in both female (aHR = 1.42, 95% CI = 1.13-1.80) and male (aHR = 1.28, 95% CI = 1.05-1.57) patients, aged more than 60 years (60-69: aHR = 1.51, 95% CI = 1.09-2.09, 70-79: aHR = 1.30, 95% CI = 1.05-1.60; 80-100: aHR = 1.40, 95% CI = 1.01-1.95), and with more than one comorbidity (aHR = 1.40, 95% CI = 1.20-1.64). A significant association between increased risk of PD and AMD was observed among patients with comorbidities of osteoporosis (aHR = 1.68, 95% CI = 1.22-2.33), diabetes (aHR = 1.41, 95% CI = 1.12-1.78) and hypertension (aHR = 1.36, 95% CI = 1.15-1.62) and medications of statin (aHR = 1.42, 95% CI = 1.19-1.69) and calcium channel blocker (CCB) (aHR = 1.32, 95% CI = 1.11-1.58). The cumulative incidence of PD was significantly higher over the 12-year follow-up period in AMD cohort (log-rank test, p < 0.001). CONCLUSIONS: Patients with AMD may exhibit a higher risk of PD than those without AMD.

Late afternoon dosing of plerixafor for stem cell mobilization: a practical solution.

BACKGROUND: Plerixafor was recently approved for stem cell mobilization in patients who have non-Hodgkin lymphoma or multiple myeloma. However, the use of late evening (10 PM) injections is inconvenient for patients and requires an after-hours infrastructure that may not be readily available. PATIENTS AND METHODS: Based on an earlier study showing prolonged mobilization of stem cells in patients given plerixafor plus granulocyte colony-stimulating factor (G-CSF), we administered plerixafor at 5 PM and performed apheresis approximately 15 hours later. Plerixafor was administered primarily to patients who either had failed previous mobilization or were at risk for poor mobilization because of previous therapy, especially lenalidomide in patients who had multiple myeloma. RESULTS: Of 48 patients, including 24 with myeloma and 24 with lymphoma, 47 had enough stem cells collected (> 2 × 10E6 CD34+ cells/kg) to proceed to transplant, including all 13 patients who had failed previous chemotherapy plus G-CSF mobilization and 18 patients treated with four cycles or more of lenalidomide. The day +1 post-plerixafor increment in circulating CD34+ cells was greatest in patients who had the highest preplerixafor CD34 count; however, in patients with preplerixafor CD34+ cell counts < 10/µL (and who typically mobilize poorly), 83% of patients had enough stem cells collected to proceed to transplant. CONCLUSION: This study suggests that plerixafor is effective when given 15 hours before apheresis, even in a population at high risk for mobilization failure. A proposed cost-effective use of plerixafor is to administer it to patients who are inadequately mobilized with G-CSF alone or for salvage in patients who fail previous mobilization with chemotherapy plus G-CSF.