Cost effectiveness of silent discharge plasma for point-of-use VOC emissions control in semiconductor fabrication

Extensive research into the treatment and control of Volatile Organic Compounds (VOCs) from semiconductor industry manufacturing processes has identified the need for alternatives to existing combustion devices. Specifically, semiconductor manufacturing design is moving toward the application of effective, small-scale, abatement control technologies for specific point-of-use (POU) waste streams associated with a particular component or manufacturing tool. The consortium of companies involved in semiconductor precompetitive research and development known collectively as SEMATECH recently evaluated eleven emerging environmental technologies designed to treat POU process emissions of VOCs specific to the semiconductor industry. After rigorous technical review only one technology, the Silent Discharge Plasma (SDP) developed at Low Alamos National Laboratory, was considered to successfully meet the required technical performance standards and potential cost effectiveness necessary for continued consideration by SEMATECH in their point-of-use emissions control plans

A pooled analysis of fall incidence from placebo‐controlled trials of denosumab

Recent studies suggest that the RANK/RANKL system impacts muscle function and/or mass. In the pivotal placebo‐controlled fracture trial of the RANKL inhibitor denosumab in women with postmenopausal osteoporosis, treatment was associated with a lower incidence of non‐fracture‐related falls (p = 0.02). This ad hoc exploratory analysis pooled data from five placebo‐controlled trials of denosumab to determine consistency across trials, if any, of the reduction of fall incidence. The analysis included trials in women with postmenopausal osteoporosis and low bone mass, men with osteoporosis, women receiving adjuvant aromatase inhibitors for breast cancer, and men receiving androgen deprivation therapy for prostate cancer. The analysis was stratified by trial, and only included data from the placebo‐controlled period of each trial. A time‐to‐event analysis of first fall and exposure‐adjusted subject incidence rates of falls were analyzed. Falls were reported and captured as adverse events. The analysis comprised 10,036 individuals; 5030 received denosumab 60 mg subcutaneously once every 6 months for 12 to 36 months and 5006 received placebo. Kaplan–Meier estimates showed an occurrence of falls in 6.5% of subjects in the placebo group compared with 5.2% of subjects in the denosumab group (hazard ratio = 0.79; 95% confidence interval 0.66–0.93; p = 0.0061). Heterogeneity in study designs did not permit overall assessment of association with fracture outcomes. In conclusion, denosumab may reduce the risk of falls in addition to its established fracture risk reduction by reducing bone resorption and increasing bone mass. These observations require further exploration and confirmation in studies with muscle function or falls as the primary outcome

Deep learning with electronic health records for short-term fracture risk identification : crystal bone algorithm development and validation

Background: Fractures as a result of osteoporosis and low bone mass are common and give rise to significant clinical, personal, and economic burden. Even after a fracture occurs, high fracture risk remains widely underdiagnosed and undertreated. Common fracture risk assessment tools utilize a subset of clinical risk factors for prediction, and often require manual data entry. Furthermore, these tools predict risk over the long term and do not explicitly provide short-term risk estimates necessary to identify patients likely to experience a fracture in the next 1-2 years. Objective: The goal of this study was to develop and evaluate an algorithm for the identification of patients at risk of fracture in a subsequent 1- to 2-year period. In order to address the aforementioned limitations of current prediction tools, this approach focused on a short-term timeframe, automated data entry, and the use of longitudinal data to inform the predictions. Methods: Using retrospective electronic health record data from over 1,000,000 patients, we developed Crystal Bone, an algorithm that applies machine learning techniques from natural language processing to the temporal nature of patient histories to generate short-term fracture risk predictions. Similar to how language models predict the next word in a given sentence or the topic of a document, Crystal Bone predicts whether a patient’s future trajectory might contain a fracture event, or whether the signature of the patient’s journey is similar to that of a typical future fracture patient. A holdout set with 192,590 patients was used to validate accuracy. Experimental baseline models and human-level performance were used for comparison. Results: The model accurately predicted 1- to 2-year fracture risk for patients aged over 50 years (area under the receiver operating characteristics curve [AUROC] 0.81). These algorithms outperformed the experimental baselines (AUROC 0.67) and showed meaningful improvements when compared to retrospective approximation of human-level performance by correctly identifying 9649 of 13,765 (70%) at-risk patients who did not receive any preventative bone-health-related medical interventions from their physicians. Conclusions: These findings indicate that it is possible to use a patient’s unique medical history as it changes over time to predict the risk of short-term fracture. Validating and applying such a tool within the health care system could enable automated and widespread prediction of this risk and may help with identification of patients at very high risk of fracture

Burnout among nursing home care aides and the effects on resident outcomes

While burnout among health care workers has been well studied, little is known about the extent to which burnout among health care workers impacts the outcomes of their care recipients. To test this, we used a multi-year (2014-2020) survey of care aides working in approximately 90 nursing homes (NHs); the survey focused on work-life measures, including the Maslach Burnout Inventory (MBI) and work-unit identifier. Resident Assessment Instrument Minimum Data Set (RAI-MDS 2.0) data were obtained on all residents in the sampled NHs during this time and included a unit identifier for each resident. We used multi-level models to test associations between the MBI emotional exhaustion and cynicism sub-scales reported by care aides and the resident outcomes of antipsychotics without indication, depressive symptoms, and responsive behaviors among residents on units. In 2019/2020, our sample included 3,547 care aides and 10,117 residents in 282 units. The mean frequency of emotional exhaustion and cynicism across units was 43% and 50%, respectively. While residents frequently experienced antipsychotics without indication 1,852 (18.3%), depressive symptoms 2,089 (20.7%), and responsive behaviors 3,891 (38.5%), none were found to be associated with either emotional exhaustion or cynicism among care aides.</p

Application of the National Osteoporosis Foundation Guidelines to postmenopausal women and men: the Framingham Osteoporosis Study.

Summary We applied the 2008 National Osteoporosis Foundation (NOF) Guidelines to Framingham Osteoporosis Study participants and found nearly one half of Caucasian postmenopausal women and one sixth of men aged 50 years and older would be recommended for osteoporosis treatment. Given the high proportion of persons recommended for treatment, NOF Guidelines may need to be re-evaluated with respect to budget impact. Introduction Little is known about the public health impact of the NOF Guidelines. Therefore, we determined the proportion of US Caucasians recommended for treatment of osteoporosis according to NOF Guidelines (2003 and 2008). Methods One thousand nine hundred and forty-six postmenopausal women and 1,681 men aged ≥50 years from the Framingham Study with information on bone mineral density (1987–2001) were included. Information on clinical predictors was used to estimate the 10-year probability of hip and major osteoporotic fracture by FRAX® (version 3.0). Results Overall proportion of women meeting treatment criterion was less when the 2008 NOF Guidelines were applied (41.1%) compared with 2003 Guidelines (47.8%). The proportion of women aged 75 years increased slightly (78.3% in 2003, 86.0% in 2008). Seventeen percent of men aged ≥50 years met treatment criterion (2.5% aged 50–64 years, 49.8% aged >75 years). Conclusions Nearly one half of Caucasian postmenopausal women and one sixth of men aged 50 years and older would be recommended for osteoporosis treatment according to 2008 NOF Guidelines. Given the high proportion of persons recommended for treatment, NOF Guidelines may need to be re-evaluated with respect to budget impact

The risk of hip and non-vertebral fractures in patients with Parkinson's disease and parkinsonism : a systematic review and meta-analysis

Parkinson's disease (PD) is a neurodegenerative disorder that is common in older individuals. PD patients have an increased risk of fractures compared to the general population, perhaps due to multiple falls. However, the fracture risk has not been fully assessed. To assess the impact of PD on the risk of hip and non-vertebral fractures, we conducted a systematic review and meta-analysis. Comprehensive searches of three key bibliographic databases were conducted to identify reviews and primary studies relating to the risk of fractures in patients with PD. Search terms included all relevant terms for Parkinson's disease and for fractures. We selected observational studies with data on the risk of fractures in adults with PD compared to controls without the diagnosis. Study quality was assessed using the Newcastle Ottawa Scale. The random-effects model was used to pool the results. Eighteen studies were included in the review. Seventeen independent studies (14 cohort and 3 case-control studies) were included in the hip fracture analysis. Nine studies (all cohorts, no case-control studies) were included in the non-vertebral fracture analysis. Study quality was judged to be moderate to good. Overall, PD patients had an increased risk for both hip fractures (2.40, 95% CI 2.04 to 2.82) and non-vertebral fractures (1.80, 95% CI 1.60 to 2.01) compared to controls. The relative risk for hip fractures was higher in men (2.93, 95% CI 2.05 to 4.18) than in women (1.81, 95% CI 1.61 to 2.04). There were no effects of the study design, geographical region, or criteria for diagnosing Parkinson's disease on these estimates of fracture risk. There is an increase in the risk of hip and non-vertebral fractures in patients with Parkinson's disease and we recommend a re-evaluation of the clinical guidelines on bone health in patients with PD to address this

The risk of hip and non-vertebral fractures in type 1 and type 2 diabetes: A systematic review and meta-analysis update

Background Diabetes is associated with increased fracture risk but we do not know what affects this risk. We investigated the risk of hip and non-vertebral fractures in diabetes and whether this risk was affected by age, gender, body mass index, diabetes type and duration, insulin use and diabetic complications. Methods We selected a previously published review to be updated. MEDLINE, Embase and Cochrane databases were searched up to March 2020. We included observational studies with age and gender-adjusted risk of fractures in adults with diabetes compared to adults without diabetes. We extracted data from published reports that we summarised using random effects model. Findings From the 3140 records identified, 49 were included, 42 in the hip fracture analysis, reporting data from 17,571,738 participants with 319,652 fractures and 17 in the non-vertebral fracture review, reporting data from 2,978,487 participants with 181,228 fractures. We found an increase in the risk of fracture in diabetes both for hip (RR 4.93, 3.06–7.95, in type 1 diabetes and RR1.33, 1.19–1.49, in type 2 diabetes) and for non-vertebral fractures (RR 1.92, 0.92–3.99, in type 1 and RR 1.19, 1,11–1.28 in type 2). At the hip, the risk was higher in the younger population in both type 1 and type 2 diabetes. In those with type 2 diabetes, longer diabetes duration and insulin use was associated with an increased risk. We did not investigate the effect of bone density, falls, anti-diabetic drugs and hypoglycemia. Conclusion Diabetes is associated with an increase in both hip and non-vertebral fracture risk

Large-scale pharmacogenomic study of sulfonylureas and the QT, JT and QRS intervals: CHARGE Pharmacogenomics Working Group

Sulfonylureas, a commonly used class of medication used to treat type 2 diabetes, have been associated with an increased risk of cardiovascular disease. Their effects on QT interval duration and related electrocardiographic phenotypes are potential mechanisms for this adverse effect. In 11 ethnically diverse cohorts that included 71 857 European, African-American and Hispanic/Latino ancestry individuals with repeated measures of medication use and electrocardiogram (ECG) measurements, we conducted a pharmacogenomic genome-wide association study of sulfonylurea use and three ECG phenotypes: QT, JT and QRS intervals. In ancestry-specific meta-analyses, eight novel pharmacogenomic loci met the threshold for genome-wide significance (P&lt;5 × 10−8), and a pharmacokinetic variant in CYP2C9 (rs1057910) that has been associated with sulfonylurea-related treatment effects and other adverse drug reactions in previous studies was replicated. Additional research is needed to replicate the novel findings and to understand their biological basis

Scintillation Counters for the D0 Muon Upgrade

We present the results of an upgrade to the D0 muon system. Scintillating counters have been added to the existing central D0 muon system to provide rejection for cosmic ray muons and out-of-time background, and to provide additional fast timing information for muons in an upgraded Tevatron. Performance and results from the 1994-1996 Tevatron run are presented.Comment: 30 pages, 25 postscript figure