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IntroductionCurrent evidence suggests that erectile dysfunction (ED) may be an early marker of atherosclerosis and systemic vascular disease. Cardiovascular disease (CVD) and ED share many common risk factors such as age, hypertension, dyslipidemia, smoking, obesity, sedentary lifestyle, and diabetes. 1 These risk factors have been shown to predict the development of future ED. 2 Penile erection is the result of a complex and coordinated series of events involving vascular response, neuronal pathways, and psychosomatic stimulation. The nitric oxide (NO) pathway is activated upon sexual stimulation, and NO is released into penile smooth muscle from both the vascular endothelium of the penis and the autonomic, cavernous nerve terminals. Within the penile smooth muscle, NO activates guanylyl cyclase, which increases the concentration of the second messenger, cyclic guanosine monophosphate (cGMP). The elevated concentrations of cGMP result in relaxation of arterial smooth muscle in the penis and a marked rise in penile blood pressure. In addition, cGMP relaxes trabecular smooth muscle, which facilitates engorgement of the sinusoidal spaces, lengthening and enlargement of the penis, and compression of the subtunical venules. The net result is complete occlusion of penile venous outflow and trapping of blood within the corpus cavernosa.Phosphodiesterase-5 (PDE-5) inhibition enhances the normal erectile response by inhibiting the enzyme that degrades cGMP. This inhibition results in greater smooth muscle relaxation of both arterial smooth Abstract: Phosphodiesterase-5 (PDE-5) inhibitors are an effective therapy for the majority of men with erectile dysfunction (ED). However, many men with ED still report a suboptimal or partial response even after an adequate trial of oral PDE-5 therapy. Since ED is associated with impaired vascular function and both atorvastatin and quinapril have been previously shown to improve vascular function, we examined the effects of adjunctive treatment with these medications in men with vasculogenic ED who were suboptimal responders to 100 mg of sildenafil. Men with ED and suboptimal response to sildenafil were randomly assigned to 3 months of treatment with atorvastatin 40 mg (n ϭ 12), quinapril 10 mg (n ϭ 10), or placebo (n ϭ 13), along with continued adjunctive sildenafil use. Measured variables included: International Index of Erectile Function (IIEF) questionnaire, brachial artery flow-mediated dilation (FMD), endothelium-independent dilation (EID) via nitroglycerin, penile Doppler blood flow, blood pressure (BP), lipids, and C-reactive protein (CRP). Compared to placebo, quinapril (p Ͻ 0.01) significantly improved symptoms of ED as measured by the IIEF-5 questionnaire. There was a trend toward a significant improvement in IIEF-5 with atorvastatin. Similarly, quinapril significantly improved the IIEF ED Domain (p Ͻ 0.05). Other peripheral and penile vascular parameters were unchanged with drug therapy as compared to placebo.In conclusion, treatment with quinapril, in combination with si...

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Corynebacterium acnes strains cross-resistant to clindamycin and erythromycin were observed following long-term selection or mutagenic treatment in the laboratory. Similar strains were found among clinical isolates from patients using clindamycin or erythromycin topically in the treatment of acne vulgaris. Clindamycin resistance was never observed in the absence of resistance to macrolides or other lincosaminides. It is suggested that this resistance may result from an alteration of the 50S ribosomal subunit.

Emergency medical services (EMS) in the United States are frequently used for nonurgent medical needs. Use of 911 and the emergency department (ED) for primary care-treatable conditions is expensive, inefficient, and undesirable for patients and providers. The objective is to describe the outcomes from community paramedicine (CP) and mobile integrated health care (MIH) interventions related to the Quadruple Aim. Three electronic databases were searched for peer-review literature on CP-MIH interventions in the United States. Eight articles reporting data from 7 interventions were included. Four studies reported high levels of patient satisfaction, and only 3 measured health outcomes. No study reported provider satisfaction measures. Reducing ED and inpatient utilization were the most common study outcomes, and programs generally were successful at reducing utilization. With reduced utilization, costs should be reduced; however, most studies did not quantify savings. Future studies should conduct economic analyses that not only compare the intervention to traditional EMS services, but also measure potential cost savings to the EMS agencies running the intervention. Most cost savings from reduced utilization will be to insurance companies and patients, but more efficient use of EMS agencies' resources could lead to cost savings that could offset intervention implementation costs. The other 3 aims (health, patient satisfaction, and provider satisfaction) were reported inconsistently in these studies and need to be addressed further. Given the small number of heterogeneous studies reviewed, the potential for CP-MIH interventions to comprehensively address the Quadruple Aim is still unclear, and more research on these programs is needed.

Background Asthma causes numerous hospital encounters annually, including emergency department visits and hospitalizations. To improve patient outcomes and reduce the number of these encounters, predictive models are widely used to prospectively pinpoint high-risk patients with asthma for preventive care via care management. However, previous models do not have adequate accuracy to achieve this goal well. Adopting the modeling guideline for checking extensive candidate features, we recently constructed a machine learning model on Intermountain Healthcare data to predict asthma-related hospital encounters in patients with asthma. Although this model is more accurate than the previous models, whether our modeling guideline is generalizable to other health care systems remains unknown. Objective This study aims to assess the generalizability of our modeling guideline to Kaiser Permanente Southern California (KPSC). Methods The patient cohort included a random sample of 70.00% (397,858/568,369) of patients with asthma who were enrolled in a KPSC health plan for any duration between 2015 and 2018. We produced a machine learning model via a secondary analysis of 987,506 KPSC data instances from 2012 to 2017 and by checking 337 candidate features to project asthma-related hospital encounters in the following 12-month period in patients with asthma. Results Our model reached an area under the receiver operating characteristic curve of 0.820. When the cutoff point for binary classification was placed at the top 10.00% (20,474/204,744) of patients with asthma having the largest predicted risk, our model achieved an accuracy of 90.08% (184,435/204,744), a sensitivity of 51.90% (2259/4353), and a specificity of 90.91% (182,176/200,391). Conclusions Our modeling guideline exhibited acceptable generalizability to KPSC and resulted in a model that is more accurate than those formerly built by others. After further enhancement, our model could be used to guide asthma care management. International Registered Report Identifier (IRRID) RR2-10.2196/resprot.5039

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