Tracking Cardiac Rehabilitation Utilization in Medicare Beneficiaries: 2017 UPDATE

PURPOSE: This study updates cardiac rehabilitation (CR) utilization data in a cohort of Medicare beneficiaries hospitalized for CR-eligible events in 2017, including stratification by select patient demographics and state of residence. METHODS: We identified Medicare fee-for-service beneficiaries who experienced a CR-eligible event and assessed their CR participation (≥1 CR sessions in 365 d), engagement, and completion (≥36 sessions) rates through September 7, 2019. Measures were assessed overall, by beneficiary characteristics and state of residence, and by primary (myocardial infarction; coronary artery bypass surgery; heart valve repair/replacement; percutaneous coronary intervention; or heart/heart-lung transplant) and secondary (angina; heart failure) qualifying event type. RESULTS: In 2017, 412 080 Medicare beneficiaries had a primary CR-eligible event and 28.6% completed ≥1 session of CR within 365 d after discharge from a qualifying event. Among beneficiaries who completed ≥1 CR session, the mean total number of sessions was 25 ± 12 and 27.6% completed ≥36 sessions. Nebraska had the highest enrollment rate (56.1%), with four other states also achieving an enrollment rate \u3e50% and 23 states falling below the overall rate for the United States. CONCLUSIONS: The absolute enrollment, engagement, and program completion rates remain low among Medicare beneficiaries, indicating that many patients did not benefit or fully benefit from a class I guideline-recommended therapy. Additional research and continued widespread adoption of successful enrollment and engagement initiatives are needed, especially among identified populations

Long-term cardiovascular disease outcomes in non-hospitalized medicare beneficiaries diagnosed with COVID-19: Population-based matched cohort study.

BackgroundSARS-CoV2, the virus that causes coronavirus disease 2019 (COVID-19), can affect multiple human organs structurally and functionally, including the cardiovascular system and brain. Many studies focused on the acute effects of COVID-19 on risk of cardiovascular disease (CVD) and stroke especially among hospitalized patients with limited follow-up time. This study examined long-term mortality, hospitalization, CVD and stroke outcomes after non-hospitalized COVID-19 among Medicare fee-for-service (FFS) beneficiaries in the United States.MethodsThis retrospective matched cohort study included 944,371 FFS beneficiaries aged ≥66 years diagnosed with non-hospitalized COVID-19 from April 1, 2020, to April 30, 2021, and followed-up to May 31, 2022, and 944,371 propensity score matched FFS beneficiaries without COVID-19. Primary outcomes were all-cause mortality, hospitalization, and incidence of 15 CVD and stroke. Because most outcomes violated the proportional hazards assumption, we used restricted cubic splines to model non-proportional hazards in Cox models and presented time-varying hazard ratios (HRs) and Bonferroni corrected 95% confidence intervals (CI).ResultsThe mean age was 75.3 years; 58.0% women and 82.6% non-Hispanic White. The median follow-up was 18.5 months (interquartile range 16.5 to 20.5). COVID-19 showed initial stronger effects on all-cause mortality, hospitalization and 12 incident CVD outcomes with adjusted HRs in 0-3 months ranging from 1.05 (95% CI 1.01-1.09) for mortality to 2.55 (2.26-2.87) for pulmonary embolism. The effects of COVID-19 on outcomes reduced significantly after 3-month follow-up. Risk of mortality, acute myocardial infarction, cardiomyopathy, deep vein thrombosis, and pulmonary embolism returned to baseline after 6-month follow-up. Patterns of initial stronger effects of COVID-19 were largely consistent across age groups, sex, and race/ethnicity.ConclusionsOur results showed a consistent time-varying effects of COVID-19 on mortality, hospitalization, and incident CVD among non-hospitalized COVID-19 survivors

Optimal Load Distribution of CHP Based on Combined Deep Learning and Genetic Algorithm

In an effort to address the load adjustment time in the thermal and electrical load distribution of thermal power plant units, we propose an optimal load distribution method based on load prediction among multiple units in thermal power plants. The proposed method utilizes optimization by attention to fine-tune a deep convolutional long-short-term memory network (CNN-LSTM-A) model for accurately predicting the heat supply load of two 30 MW extraction back pressure units. First, the inherent relationship between the heat supply load and thermal power plant unit parameters is qualitatively analyzed, and the influencing factors of the power load are screened based on a data-driven analysis. Then, a mathematical model for load distribution optimization is established by analyzing and fitting the unit’s energy consumption characteristic curves on the boiler and turbine sides. Subsequently, by using a randomly chosen operating point as an example, a genetic algorithm is used to optimize the distribution of thermal and electrical loads among the units. The results showed that the combined deep learning model has a high prediction accuracy, with a mean absolute percentage error (MAPE) of less than 1.3%. By predicting heat supply load variations, the preparedness for load adjustments is done in advance. At the same time, this helps reduce the real-time load adjustment response time while enhancing the unit load’s overall competitiveness. After that, the genetic algorithm optimizes the load distribution, and the overall steam consumption rate from power generation on the turbine side is reduced by 0.488 t/MWh. Consequently, the coal consumption rate of steam generation on the boiler side decreases by 0.197 kg (coal)/t (steam). These described changes can greatly increase the power plant’s revenue by CNY 6.2673 million per year. The thermal power plant used in this case study is in Zhejiang Province, China

Comparative Proteomics of Thellungiella halophila Leaves from Plants Subjected to Salinity Reveals the Importance of Chloroplastic Starch and Soluble Sugars in Halophyte Salt Tolerance

Thellungiella halophila, a close relative of Arabidopsis, is a model halophyte used to study plant salt tolerance. The proteomic/physiological/transcriptomic analyses of Thellungiella plant leaves subjected to different salinity levels, reported herein, indicate an extraordinary ability of Thellungiella to adapt to large concentrations of exogenous saline by compartmentalizing Na+ into cell vacuoles and accumulating proline and soluble sugars as organic osmolytes. Salinity stress stimulated the accumulation of starch in chloroplasts, which resulted in a greatly increased content of starch and total sugars in leaves. Comparative proteomics of Thellungiella leaves identified 209 salt-responsive proteins. Among these, the sequences of 108 proteins were strongly homologous to Arabidopsis protein sequences, and 30 had previously been identified as Thellungiella proteins. Functional classification of these proteins into 16 categories indicated that the majority are involved in carbohydrate metabolism, followed by those involved in energy production and conversion, and then those involved in the transport of inorganic ions. Pathway analysis revealed that most of the proteins are involved in starch and sucrose metabolism, carbon fixation, photosynthesis, and glycolysis. Of these processes, the most affected were starch and sucrose metabolism, which might be pivotal for salt tolerance. The gene expression patterns of the 209 salt-responsive proteins revealed through hierarchical clustering of microarray data and the expression patterns of 29 Thellungiella genes evaluated via quantitative RT-PCR were similar to those deduced via proteomic analysis, which underscored the possibility that starch and sucrose metabolism might play pivotal roles in determining the salt tolerance ability of Thellungiella. Our observations enabled us to propose a schematic representation of the systematic salt-tolerance phenotype in Thellungiella and suggested that the increased accumulation of starch, soluble sugars, and proline, as well as subcellular compartmentalization of sodium, might collectively denote important mechanisms for halophyte salt tolerance

Tracking Cardiac Rehabilitation Utilization in Medicare Beneficiaries: 2017 UPDATE

PURPOSE: This study updates cardiac rehabilitation (CR) utilization data in a cohort of Medicare beneficiaries hospitalized for CR-eligible events in 2017, including stratification by select patient demographics and state of residence. METHODS: We identified Medicare fee-for-service beneficiaries who experienced a CR-eligible event and assessed their CR participation (≥1 CR sessions in 365 d), engagement, and completion (≥36 sessions) rates through September 7, 2019. Measures were assessed overall, by beneficiary characteristics and state of residence, and by primary (myocardial infarction; coronary artery bypass surgery; heart valve repair/replacement; percutaneous coronary intervention; or heart/heart-lung transplant) and secondary (angina; heart failure) qualifying event type. RESULTS: In 2017, 412 080 Medicare beneficiaries had a primary CR-eligible event and 28.6% completed ≥1 session of CR within 365 d after discharge from a qualifying event. Among beneficiaries who completed ≥1 CR session, the mean total number of sessions was 25 ± 12 and 27.6% completed ≥36 sessions. Nebraska had the highest enrollment rate (56.1%), with four other states also achieving an enrollment rate \u3e50% and 23 states falling below the overall rate for the United States. CONCLUSIONS: The absolute enrollment, engagement, and program completion rates remain low among Medicare beneficiaries, indicating that many patients did not benefit or fully benefit from a class I guideline-recommended therapy. Additional research and continued widespread adoption of successful enrollment and engagement initiatives are needed, especially among identified populations