Evaluating the feasibility of delivering a pain management programme for adults living with sickle cell disease

Background Pain is the prominent feature of sickle cell disease (SCD) and negatively affects quality of life. Delivery of pain management programmes (PMPs) has been suggested in clinical guidelines for pain management in SCD; however, further evidence of the feasibility and effectiveness of PMPs in this population is needed. This study explored the feasibility of delivering a sickle cell pain management programme (SCPMP) for adults within a haemoglobinopathies service. Methods A single arm, repeated-measures observational design was used to determine feasibility of delivering the SCPMP at one study site. Primary feasibility outcomes were recruitment, completion of treatment and outcome measures, satisfaction, credibility and acceptability to participants. Secondary feasibility outcomes were treatment outcomes and processes, frequency of vaso-occlusive crisis (VOC) and healthcare utilisation. Results Four of five feasibility criteria were met. Annual recruitment of eight participants to a SCPMP was not achieved. Twenty-nine people began a SCPMP during the study period. Twenty-five (86.2%) participants attended ≥5/8 sessions and 21(84%) programme completers provided all end of programme questionnaires. Mean scores of >7 on ten-point scales were seen across satisfaction and credibility questions. At least moderate (Hedges g >0.5) effect sizes were seen in pre-post SCPMP measures of pain interference, anxiety, depression, self-efficacy, pain-related worry and acceptance. A small (Hedges g 0.4) effect size was seen in HRQoL. Following SCPMP attendance, mean frequency of self-reported VOC and hospital admissions reduced. Conclusions This study suggests that, given an adequate source of referrals, a SCPMP is feasible to deliver and appears acceptable and credible to participants. Exploration of influences on recruitment, such as barriers to group interventions, would be illuminating, prior to investigating feasibility of an adequately powered randomised-controlled trial

Mitochondrial DNA: Hotspot for potential gene modifiers regulating hypertrophic cardiomyopathy

Hypertrophic cardiomyopathy (HCM) is a prevalent and untreatable cardiovascular disease with a highly complex clinical and genetic causation. HCM patients bearing similar sarcomeric mutations display variable clinical outcomes, implying the involvement of gene modifiers that regulate disease progression. As individuals exhibiting mutations in mitochondrial DNA (mtDNA) present cardiac phenotypes, the mitochondrial genome is a promising candidate to harbor gene modifiers of HCM. Herein, we sequenced the mtDNA of isogenic pluripotent stem cell-cardiomyocyte models of HCM focusing on two sarcomeric mutations. This approach was extended to unrelated patient families totaling 52 cell lines. By correlating cellular and clinical phenotypes with mtDNA sequencing, potentially HCM-protective or -aggravator mtDNA variants were identified. These novel mutations were mostly located in the non-coding control region of the mtDNA and did not overlap with those of other mitochondrial diseases. Analysis of unrelated patients highlighted family-specific mtDNA variants, while others were common in particular population haplogroups. Further validation of mtDNA variants as gene modifiers is warranted but limited by the technically challenging methods of editing the mitochondrial genome. Future molecular characterization of these mtDNA variants in the context of HCM may identify novel treatments and facilitate genetic screening in cardiomyopathy patients towards more efficient treatment options

Decreasing net primary production due to drought and slight decreases in solar radiation in China from 2000 to 2012

Terrestrial ecosystems have continued to provide the critical service of slowing the atmospheric CO2 growth rate. Terrestrial net primary productivity (NPP) is thought to be a major contributing factor to this trend. Yet our ability to estimate NPP at the regional scale remains limited due to large uncertainties in the response of NPP to multiple interacting climate factors and uncertainties in the driver data sets needed to estimate NPP. In this study, we introduced an improved NPP algorithm that used local driver data sets and parameters in China. We found that bias decreased by 30% for gross primary production (GPP) and 17% for NPP compared with the widely used global GPP and NPP products, respectively. From 2000 to 2012, a pixel-level analysis of our improved NPP for the region of China showed an overall decreasing NPP trend of 4.65 Tg C a−1. Reductions in NPP were largest for the southern forests of China (−5.38 Tg C a−1), whereas minor increases in NPP were found for North China (0.65 Tg C a−1). Surprisingly, reductions in NPP were largely due to decreases in solar radiation (82%), rather than the more commonly expected effects of drought (18%). This was because for southern China, the interannual variability of NPP was more sensitive to solar radiation (R2 in 0.29–0.59) relative to precipitation (R2 \u3c 0.13). These findings update our previous knowledge of carbon uptake responses to climate change in terrestrial ecosystems of China and highlight the importance of shortwave radiation in driving vegetation productivity for the region, especially for tropical forests

Cost-effectiveness analysis of Chlamydia trachomatis screening in Dutch pregnant women

Chlamydia trachomatis infections during pregnancy may have serious consequences for women and their offspring. Chlamydial infections are largely asymptomatic. Hence, prevention is based on screening. The objective of this study was to estimate the cost-effectiveness of C. trachomatis screening during pregnancy. We used a health-economic decision analysis model, which included potential health outcomes of C. trachomatis infection for women, partners and infants, and premature delivery. We estimated the cost-effectiveness from a societal perspective using recent prevalence data from a population-based prospective cohort study among pregnant women in the Netherlands. We calculated the averted costs by linking health outcomes with health care costs and productivity losses. Cost-effectiveness was expressed as net costs per major outcome prevented and was estimated in base-case analysis, sensitivity, and scenario analysis. In the base-case analysis, the costs to detect 1000 pregnant women with C. trachomatis were estimated at €527,900. Prevention of adverse health outcomes averted €626,800 in medical costs, resulting in net cost savings. Sensitivity analysis showed that net cost savings remained with test costs up to €22 (test price €19) for a broad range of variation in underlying assumptions. Scenario analysis showed even more cost savings with targeted screening for women less than 30 years of age or with first pregnancies only. Antenatal screening for C. trachomatis is a cost-saving intervention when testing all pregnant women in the Netherlands. Savings increase even further when testing women younger than 30 years of age or with pregnancies only.</p

Real-Time Identification of Serious Infection in Geriatric Patients Using Clinical Information System Surveillance

To develop and characterize an automated syndromic surveillance mechanism for early identification of older emergency department (ED) patients with possible life-threatening infection. DESIGN : Prospective, consecutive-enrollment, single-site observational study. SETTING : A large university medical center with an annual ED census of 75,273. PARTICIPANTS : Patients aged 70 and older admitted to the ED and having two or more systemic inflammatory response syndrome (SIRS) criteria during their ED stay. MEASUREMENTS : A search algorithm was developed to screen the census of the ED through its clinical information system. A study coordinator confirmed all patients electronically identified as having a probable infectious explanation for their visit. RESULTS : Infection accounted for 28% of ED and 34% of final hospital diagnoses. Identification using the software tool alone carried a 1.63 relative risk of infection (95% confidence interval CI=1.09–2.44) compared with other ED patients sufficiently ill to require admission. Follow-up confirmation by a study coordinator increased the risk to 3.06 (95% CI=2.11–4.44). The sensitivity of the strategy overall was modest (14%), but patients identified were likely to have an infectious diagnosis (specificity=98%). The most common SIRS criterion triggering the electronic notification was the combination of tachycardia and tachypnea. CONCLUSION : A simple clinical informatics algorithm can detect infection in elderly patients in real time with high specificity. The utility of this tool for research and clinical care may be substantial.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/66036/1/j.1532-5415.2008.02094.x.pd

Genetics Ignite Focus on Microglial Inflammation in Alzheimer\u27s Disease

In the past five years, a series of large-scale genetic studies have revealed novel risk factors for Alzheimer\u27s disease (AD). Analyses of these risk factors have focused attention upon the role of immune processes in AD, specifically microglial function. In this review, we discuss interpretation of genetic studies. We then focus upon six genes implicated by AD genetics that impact microglial function: TREM2, CD33, CR1, ABCA7, SHIP1, and APOE. We review the literature regarding the biological functions of these six proteins and their putative role in AD pathogenesis. We then present a model for how these factors may interact to modulate microglial function in AD

Magnetic Tunnel Junction Random Number Generators Applied to Dynamically Tuned Probability Trees Driven by Spin Orbit Torque

Perpendicular magnetic tunnel junction (pMTJ)-based true-random number generators (RNG) can consume orders of magnitude less energy per bit than CMOS pseudo-RNG. Here, we numerically investigate with a macrospin Landau-Lifshitz-Gilbert equation solver the use of pMTJs driven by spin-orbit torque to directly sample numbers from arbitrary probability distributions with the help of a tunable probability tree. The tree operates by dynamically biasing sequences of pMTJ relaxation events, called 'coinflips', via an additional applied spin-transfer-torque current. Specifically, using a single, ideal pMTJ device we successfully draw integer samples on the interval 0,255 from an exponential distribution based on p-value distribution analysis. In order to investigate device-to-device variations, the thermal stability of the pMTJs are varied based on manufactured device data. It is found that while repeatedly using a varied device inhibits ability to recover the probability distribution, the device variations average out when considering the entire set of devices as a 'bucket' to agnostically draw random numbers from. Further, it is noted that the device variations most significantly impact the highest level of the probability tree, iwth diminishing errors at lower levels. The devices are then used to draw both uniformly and exponentially distributed numbers for the Monte Carlo computation of a problem from particle transport, showing excellent data fit with the analytical solution. Finally, the devices are benchmarked against CMOS and memristor RNG, showing faster bit generation and significantly lower energy use.Comment: 10 pages, 8 figures, 2 table