Introduction: Persistent pain after stroke significantly impacts patients’ function, ability to participate in rehabilitation, and quality of life. We examined characteristics of stroke survivors discharged with pain. Methods: The sample consisted of 824 stroke patients admitted to a large, urban university based acute care facility in Texas with a completed pain assessment (numeric rating scale or Behavior Pain Scale) at discharge. Descriptive analysis of means and frequency distributions was conducted using a two-sided t-test for continuous variables and a Chi-squared test for categorical variables. Univariable and multivariable logistic regression models were used to determine the association between pain at discharge and type of stroke, adjusting for age, sex, race, smoking status, prevalent hypertension, BMI, and length of stay (LOS). We also tested for statistical interactions between stroke type and age, sex, and race. Results: The mean age was 64 years, with 56% (n=462) being males. Of the 824 stroke patients, 584 (71%) had ischemic stroke while 237 (29%) had hemorrhagic (ICH) stroke. At discharge, 43% (n=358) reported pain. In unadjusted analyses, those reporting pain were younger (p<0.001), had a higher BMI (p=0.009), had longer LOS (p<0.001), and were less likely to have ischemic stroke (p<0.001). Only sex modified the association between stroke type and pain at discharge (p=0.002; AUC=0.716). In sex-stratified analysis females with ischemic stroke had lowered odds of reporting pain at discharge by 75% compared to those having ICH (OR=0.25; 95% CI: 0.15-0.41). Conclusions: Our study finds that 43% of stroke survivors reported pain at discharge. Younger females with an increased BMI and an increased LOS were more likely to report pain. Our model AUC suggests that post stroke pain may be a complicated phenomenon that requires more complex models.
Introduction: Evidence shows a positive correlation between work hour (WH) duration and incident diabetes (DM). However, little is known about the association between longitudinal WH patterns and the risk of incident DM. Hypothesis: We hypothesized that the greatest risk of DM would be observed in consistently long WH patterns and that age, sex, and ethnicity would modify the relationship between WH patterns and incident DM. Methods: We utilized a representative sample of 15,843 U.S. adults from the Panel Study of Income Dynamics who reported weekly WH for a minimum of five years between 1985-2017 and did not have a history of DM prior to reporting five years of WH data. Latent class linear mixed modeling was used to identify distinct longitudinal WH trajectory patterns. Multivariable logistic regression analyses were then used to examine the association between WH patterns and incident DM, with initial adjustments made for sex, age, ethnicity, education, income-to-needs ratio, and occupation. We also tested for statistical interactions between WH patterns and baseline age, sex, and ethnicity. Results: Over a mean follow-up of 17.5 years, four WH trends were identified: standard, full-time (61.1%), increasing (11.5%), quickly decreasing (11.3%), and gradually decreasing (16.1%). Age (interaction p=0.013), but not ethnicity nor sex, modified the association between WH patterns and incident DM. In age stratified analyses, adults aged 18-29 showed no significant association between WH patterns and DM. In adults aged 30-39, a gradually decreasing WH trend showed lower DM risk compared to those working standard hours (OR=0.59; 95% CI: 0.45 - 0.77). Among those ≥40 years, both quickly decreasing (OR=0.66; 95% CI: 0.50 - 0.87) and gradually decreasing (OR=0.45; 95% CI: 0.34 - 0.60) WH patterns were associated with lower risk of DM compared to those working standard hours. Conclusion: Compared to individuals working standard WH over many years, decreasing WH patterns were associated with a lower risk of incident DM.
This paper focuses on California's regulatory environment and our role as industry, individuals, and the general public, in shaping its future. It provides a historical context of regulations, the current focus areas, and challenges moving forward. Improving our understanding of the energy industry empowers us to collaborate in shaping the future of California. The sustainability of the industry is important to the sustainability of the state - from families to small businesses to large employers. Since the Industrial Revolution, energy has been the backbone of human society. Medicine, agriculture, science, technology and more are all sustained by energy. Energy demand is categorized broadly as electricity and transportation demand. Oil is the major energy source for transportation, due to availability, reliability, and economics. In the U.S., roughly 50% of the oil consumed is imported (EIA 2017). In California, the number is closer to 67% (Californians for Energy Independence 2015). One reason for high oil imports is the challenging regulatory environment. Traditionally, the Oil and Gas (O&G) industry has relied on classic lobbying-based negotiations with agencies. However, with increasingly, widespread misunderstanding of the industry and an ever-changing landscape, it is crucial to incorporate a "boots on the ground" approach. Stakeholder engagement is key in responding to and exposing misleading tactics and messages of some industry critics. Aera Energy LLC (Aera) has been a leader in implementing an Ambassador Program, an education program focused on providing employees an opportunity to share simple, straightforward, and accurate messages with their families and local community. With safety and environmental responsibility as the foundation for all activities, it is the "Aera Way" of doing business. We hope you are interested to learn more and see how you can be an industry Ambassador within your local community!
Introduction: Evidence shows a positive correlation between work hour (WH) duration and incident hypertension (HTN). However, little is known about the association between longitudinal WH patterns and the risk of incident HTN. Hypothesis: We hypothesized that the greatest risk of HTN would be observed in consistently long WH patterns and that age, sex, and ethnicity would modify the relationship between WH patterns and incident HTN. Methods: We utilized a representative sample of 10,338 U.S. adults from the Panel Study of Income Dynamics who reported weekly WH for a minimum of five years between 1985-2017 and did not have a history of HTN prior to reporting five years of WH data. Latent class linear mixed modeling was used to identify distinct longitudinal WH trajectory patterns. Weighted Cox proportional hazards model was used to examine the association between WH patterns and incident HTN, adjusting for age, sex, ethnicity, education, number of children, BMI, and smoking status after backwards step-down selection. We also tested for statistical interactions between WH patterns and baseline age, sex, and ethnicity. Results: Over a mean follow-up of 18.6 years, four WH trends were identified: steady (66.1%), increasing (12.1%), quickly decreasing (8.7%), and gradually decreasing (13.0%). Only age (p<0.001) modified the association between WH patterns and incident HTN. In age-stratified analyses, adults aged 18-29 showed no significant association between WH patterns and HTN. In adults aged 30-39, a gradually decreasing WH trend showed lower HTN risk compared to those working steady hours (HR=0.51; 95% CI: 0.39-0.66). Among those ≥40 years, increasing (HR=0.59; 95% CI: 0.39-0.89), quickly decreasing (HR=0.49; 95% CI: 0.41-0.59) and gradually decreasing (HR=0.30; 95% CI: 0.23-0.40) WH patterns were associated with lower risk of HTN compared to those working steady hours. Conclusion: Compared to individuals working steady WH over many years, non-constant WH patterns were associated with a lower risk of incident HTN.
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