Does Inclusion of Stroke Severity in a 30-day Mortality Model Change Standardized Mortality Rates at VA Hospitals?

Background—The Centers for Medicare and Medicaid Services is considering developing a 30-day ischemic stroke hospital-level mortality model using administrative data. We examined whether inclusion of the National Institutes of Health Stroke Scale (NIHSS), a measure of stroke severity not included in administrative data, would alter 30-day mortality rates in the Veterans Health Administration. Methods and Results—A total of 2562 veterans admitted with ischemic stroke to 64 Veterans Health Administration Hospitals in the fiscal year 2007 were included. First, we examined the distribution of unadjusted mortality rates across the Veterans Health Administration. Second, we estimated 30-day all-cause, risk standardized mortality rates (RSMRs) for each hospital by adjusting for age, sex, and comorbid conditions using hierarchical models with and without the inclusion of the NIHSS. Finally, we examined whether adjustment for the NIHSS significantly changed RSMRs for each hospital compared with other hospitals. The median unadjusted mortality rate was 3.6%. The RSMR interquartile range without the NIHSS ranged from 5.1% to 5.6%. Adjustment with the NIHSS did not change the RSMR interquartile range (5.1%–5.6%). Among veterans ≥65 years, the RSMR interquartile range without the NIHSS ranged from 9.2% to 10.3%. With adjustment for the NIHSS, the RSMR interquartile range changed from 9.4% to 10.0%. The plot of 30-day RSMRs estimated with and without the inclusion of the NIHSS in the model demonstrated overlapping 95% confidence intervals across all hospitals, with no hospital significantly below or above the mean-unadjusted 30-day mortality rate. The 30-day mortality measure did not discriminate well among hospitals. Conclusions—The impact of the NIHSS on RSMRs was limited. The small number of stroke admissions and the narrow range of 30-day stroke mortality rates at the facility level in the Veterans Health Administration cast doubt on the value of using 30-day RSMRs as a means of identifying outlier hospitals based on their stroke care quality

Estimating and Reporting on the Quality of Inpatient Stroke Care by Veterans Health Administration Medical Centers

Background—Reporting of quality indicators (QIs) in Veterans Health Administration Medical Centers is complicated by estimation error caused by small numbers of eligible patients per facility. We applied multilevel modeling and empirical Bayes (EB) estimation in addressing this issue in performance reporting of stroke care quality in the Medical Centers. Methods and Results—We studied a retrospective cohort of 3812 veterans admitted to 106 Medical Centers with ischemic stroke during fiscal year 2007. The median number of study patients per facility was 34 (range, 12–105). Inpatient stroke care quality was measured with 13 evidence-based QIs. Eligible patients could either pass or fail each indicator. Multilevel modeling of a patient's pass/fail on individual QIs was used to produce facility-level EB-estimated QI pass rates and confidence intervals. The EB estimation reduced interfacility variation in QI rates. Small facilities and those with exceptionally high or low rates were most affected. We recommended 8 of the 13 QIs for performance reporting: dysphagia screening, National Institutes of Health Stroke Scale documentation, early ambulation, fall risk assessment, pressure ulcer risk assessment, Functional Independence Measure documentation, lipid management, and deep vein thrombosis prophylaxis. These QIs displayed sufficient variation across facilities, had room for improvement, and identified sites with performance that was significantly above or below the population average. The remaining 5 QIs were not recommended because of too few eligible patients or high pass rates with little variation. Conclusions—Considerations of statistical uncertainty should inform the choice of QIs and their application to performance reporting

Belediye Müzesi

Taha Toros Arşivi, Dosya No: 114-Müzelerİstanbul Kalkınma Ajansı (TR10/14/YEN/0033) İstanbul Development Agency (TR10/14/YEN/0033

The Heart and Cannabis (THC) Cohort: Differences in Baseline Health and Behaviors by Cannabis Use

BackgroundEvidence on the cardiovascular health effects of cannabis use is limited. We designed a prospective cohort study of older Veterans (66 to 68 years) with coronary artery disease (CAD) to understand the cardiovascular consequences of cannabis use. We describe the cohort construction, baseline characteristics, and health behaviors that were associated with smoking cannabis.ObjectiveTo understand the cardiovascular consequences of cannabis use.DesignWe designed a prospective cohort study of older Veterans (66 to 68 years) with CAD.ParticipantsA total of 1,015 current cannabis smokers and 3,270 non-cannabis smokers with CAD.Main measuresUsing logistic regression, we examined the association of baseline variables with smoking cannabis in the past 30 days.ResultsThe current cannabis smokers and non-current smokers were predominantly male (97.2% vs 97.1%, p=0.96). Characteristics associated with recent cannabis use in multivariable analyses included lack of a high school education (odds ratio [OR] 2.15, 95% confidence interval [CI]: 1.10 to 4.19), financial difficulty (OR 1.47, 95% CI: 1.02 to 2.11), tobacco use (OR 3.02, 95% CI: 1.66 to 5.48), current drug use (OR 2.82, 95% CI: 1.06 to 7.46), and prior drug use (OR 2.84, 95% CI: 2.11 to 3.82). In contrast, compared to individuals with 0 to 1 comorbid conditions, those with 5 chronic conditions or more (OR 0.43, 95% CI: 0.27 to 0.70) were less likely to smoke cannabis.ConclusionsIn this older high-risk cohort, smoking cannabis was associated with higher social and behavioral risk, but with fewer chronic health conditions

Large-scale unit commitment under uncertainty: an updated literature survey

The Unit Commitment problem in energy management aims at finding the optimal production schedule of a set of generation units, while meeting various system-wide constraints. It has always been a large-scale, non-convex, difficult problem, especially in view of the fact that, due to operational requirements, it has to be solved in an unreasonably small time for its size. Recently, growing renewable energy shares have strongly increased the level of uncertainty in the system, making the (ideal) Unit Commitment model a large-scale, non-convex and uncertain (stochastic, robust, chance-constrained) program. We provide a survey of the literature on methods for the Uncertain Unit Commitment problem, in all its variants. We start with a review of the main contributions on solution methods for the deterministic versions of the problem, focussing on those based on mathematical programming techniques that are more relevant for the uncertain versions of the problem. We then present and categorize the approaches to the latter, while providing entry points to the relevant literature on optimization under uncertainty. This is an updated version of the paper "Large-scale Unit Commitment under uncertainty: a literature survey" that appeared in 4OR 13(2), 115--171 (2015); this version has over 170 more citations, most of which appeared in the last three years, proving how fast the literature on uncertain Unit Commitment evolves, and therefore the interest in this subject

A Dual-loop Model Predictive Voltage Control/Sliding-mode Current Control for Voltage Source Inverter Operation in Smart Microgrids

The design of a robust controller for the voltage source inverter is essential for reliable operation of distributed energy resources in future smart microgrids. The design problem is challenging in the case of autonomous operation subsequent to an islanding situation. In this article, a dual-loop controller is proposed for voltage source inverter control. The outer loop is designed for microgrid voltage and frequency regulation based on the model predictive control strategy. This outer loop generates reference inverter currents for the inner loop. The inner loop is designed using a sliding-mode control strategy, and it generates the pulse-width modulation voltage commands to regulate the inverter currents. A standard space vector algorithm is used to realize the pulse-width modulation voltage commands. Performance evaluation of the proposed controller is carried out for different loading scenarios. It is shown that the proposed dual-loop controller provides the specified performance characteristics of an islanded microgrid with different loading conditions.http://www.tandfonline.com/loi/uemp20hb201

The bacterial infection of German cockroach (Blatella germanica) in hospitals of western Iran

Cockroaches are considered a serious health problem in some medical centers. They can move freely in hospital wards and transmit pathogenic organisms. This study was carried out in order to detect and identify bacterial infection on outer surface and in digestive organs of Blatella germanica as a dominant species of cockroach in hospitals. In this cross-sectional study 222 B. germanica were collected from 14 different wards and units of 5 hospitals in the city of Hamedan in western Iran. Most of them were collected from dining room (34.2%) followed by urology ward (13.5%). After applying anesthesia and washing in 2cc physiology serum, the culture was prepared from this suspension for identification of bacterial infection on outer surface. Next, the outer surface of each cockroach was sterilized and their guts were isolated from mouth to anus. Bacteria extraction and culture were done accordingly. A total of 12 bacteria species were identified from outer surface and digestive system of cockroaches. On outer surface, Escherichia coli was the most dominant species (40%) followed by Staphylococcus epidermidis (20%). In digestive system E. coli had also the highest percentage (45%) followed by Entrobacter aeroginosa (20%). This study can show the importance of cockroaches as potential vectors of medically important microorganisms such as pathogenic bacteria in hospitals. Control programs for removing cockroaches, especially in the hospitals are recommended

Comparative Effectiveness of Carotid Endarterectomy vs Initial Medical Therapy in Patients With Asymptomatic Carotid Stenosis

Importance Carotid endarterectomy (CEA) among asymptomatic patients involves a trade-off between a higher short-term perioperative risk in exchange for a lower long-term risk of stroke. The clinical benefit observed in randomized clinical trials (RCTs) may not extend to real-world practice. Objective To examine whether early intervention (CEA) was superior to initial medical therapy in real-world practice in preventing fatal and nonfatal strokes among patients with asymptomatic carotid stenosis. Design, Setting, and Participants This comparative effectiveness study was conducted from August 28, 2018, to March 2, 2020, using the Corporate Data Warehouse, Suicide Data Repository, and other databases of the US Department of Veterans Affairs. Data analyzed were those of veterans of the US Armed Forces aged 65 years or older who received carotid imaging between January 1, 2005, and December 31, 2009. Patients without a carotid imaging report, those with carotid stenosis of less than 50% or hemodynamically insignificant stenosis, and those with a history of stroke or transient ischemic attack in the 6 months before index imaging were excluded. A cohort of patients who received initial medical therapy and a cohort of similar patients who received CEA were constructed and followed up for 5 years. The target trial method was used to compute weighted Kaplan-Meier curves and estimate the risk of fatal and nonfatal strokes in each cohort in the pragmatic sample across 5 years of follow-up. This analysis was repeated after restricting the sample to patients who met RCT inclusion criteria. Cumulative incidence functions for fatal and nonfatal strokes were estimated, accounting for nonstroke deaths as competing risks in both the pragmatic and RCT-like samples. Exposures Receipt of CEA vs initial medical therapy. Main Outcomes and Measures Fatal and nonfatal strokes. Results Of the total 5221 patients, 2712 (51.9%; mean [SD] age, 73.6 [6.0] years; 2678 men [98.8%]) received CEA and 2509 (48.1%; mean [SD] age, 73.6 [6.0] years; 2479 men [98.8%]) received initial medical therapy within 1 year after the index carotid imaging. The observed rate of stroke or death (perioperative complications) within 30 days in the CEA cohort was 2.5% (95% CI, 2.0%-3.1%). The 5-year risk of fatal and nonfatal strokes was lower among patients randomized to CEA compared with patients randomized to initial medical therapy (5.6% vs 7.8%; risk difference, −2.3%; 95% CI, −4.0% to −0.3%). In an analysis that incorporated the competing risk of death, the risk difference between the 2 cohorts was lower and not statistically significant (risk difference, −0.8%; 95% CI, −2.1% to 0.5%). Among patients who met RCT inclusion criteria, the 5-year risk of fatal and nonfatal strokes was 5.5% (95% CI, 4.5%-6.5%) among patients randomized to CEA and was 7.6% (95% CI, 5.7%-9.5%) among those randomized to initial medical therapy (risk difference, −2.1%; 95% CI, −4.4% to −0.2%). Accounting for competing risks resulted in a risk difference of −0.9% (95% CI, −2.9% to 0.7%) that was not statistically significant. Conclusions and Relevance This study found that the absolute reduction in the risk of fatal and nonfatal strokes associated with early CEA was less than half the risk difference in trials from 20 years ago and was no longer statistically significant when the competing risk of nonstroke deaths was accounted for in the analysis. Given the nonnegligible perioperative 30-day risks and the improvements in stroke prevention, medical therapy may be an acceptable therapeutic strategy

Association of Social and Behavioral Risk Factors With Mortality Among US Veterans With COVID-19

Importance The US Department of Veterans Affairs (VA) offers programs that reduce barriers to care for veterans and those with housing instability, poverty, and substance use disorder. In this setting, however, the role that social and behavioral risk factors play in COVID-19 outcomes is unclear. Objective To examine whether social and behavioral risk factors were associated with mortality among US veterans with COVID-19 and whether this association might be modified by race/ethnicity. Design, Setting, and Participants This cohort study obtained data from the VA Corporate Data Warehouse to form a cohort of veterans who received a positive COVID-19 test result between March 2 and September 30, 2020, in a VA health care facility. All veterans who met the inclusion criteria were eligible to participate in the study, and participants were followed up for 30 days after the first SARS-CoV-2 or COVID-19 diagnosis. The final follow-up date was October 31, 2020. Exposures Social risk factors included housing problems and financial hardship. Behavioral risk factors included current tobacco use, alcohol use, and substance use. Main Outcomes and Measures The primary outcome was all-cause mortality in the 30-day period after the SARS-CoV-2 or COVID-19 diagnosis date. Multivariable logistic regression was used to estimate odds ratios, clustering for health care facilities and adjusting for age, sex, race, ethnicity, marital status, clinical factors, and month of COVID-19 diagnosis. Results Among 27 640 veterans with COVID-19 who were included in the analysis, 24 496 were men (88.6%) and the mean (SD) age was 57.2 (16.6) years. A total of 3090 veterans (11.2%) had housing problems, 4450 (16.1%) had financial hardship, 5358 (19.4%) used alcohol, and 3569 (12.9%) reported substance use. Hospitalization occurred in 7663 veterans (27.7%), and 1230 veterans (4.5%) died. Housing problems (adjusted odds ratio [AOR], 0.96; 95% CI, 0.77-1.19; P = .70), financial hardship (AOR, 1.13; 95% CI, 0.97-1.31; P = .11), alcohol use (AOR, 0.82; 95% CI, 0.68-1.01; P = .06), current tobacco use (AOR, 0.85; 95% CI, 0.68-1.06; P = .14), and substance use (AOR, 0.90; 95% CI, 0.71-1.15; P = .41) were not associated with higher mortality. Interaction analyses by race/ethnicity did not find associations between mortality and social and behavioral risk factors. Conclusions and Relevance Results of this study showed that, in an integrated health system such as the VA, social and behavioral risk factors were not associated with mortality from COVID-19. Further research is needed to substantiate the potential of an integrated health system to be a model of support services for households with COVID-19 and populations who are at risk for the disease