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BackgroundDeploying accurate computable phenotypes in pragmatic trials requires a trade-off between precise and clinically sensical variable selection. In particular, evaluating the medical encounter to assess a pattern leading to clinically significant impairment or distress indicative of disease is a difficult modeling challenge for the emergency department. ObjectiveThis study aimed to derive and validate an electronic health record–based computable phenotype to identify emergency department patients with opioid use disorder using physician chart review as a reference standard. MethodsA two-algorithm computable phenotype was developed and evaluated using structured clinical data across 13 emergency departments in two large health care systems. Algorithm 1 combined clinician and billing codes. Algorithm 2 used chief complaint structured data suggestive of opioid use disorder. To evaluate the algorithms in both internal and external validation phases, two emergency medicine physicians, with a third acting as adjudicator, reviewed a pragmatic sample of 231 charts: 125 internal validation (75 positive and 50 negative), 106 external validation (56 positive and 50 negative). ResultsCohen kappa, measuring agreement between reviewers, for the internal and external validation cohorts was 0.95 and 0.93, respectively. In the internal validation phase, Algorithm 1 had a positive predictive value (PPV) of 0.96 (95% CI 0.863-0.995) and a negative predictive value (NPV) of 0.98 (95% CI 0.893-0.999), and Algorithm 2 had a PPV of 0.8 (95% CI 0.593-0.932) and an NPV of 1.0 (one-sided 97.5% CI 0.863-1). In the external validation phase, the phenotype had a PPV of 0.95 (95% CI 0.851-0.989) and an NPV of 0.92 (95% CI 0.807-0.978). ConclusionsThis phenotype detected emergency department patients with opioid use disorder with high predictive values and reliability. Its algorithms were transportable across health care systems and have potential value for both clinical and research purposes.

This presented research delves into the challenges and approaches encompassed in allotting available resources for the maintenance and renovation of crucial infrastructure assets, focusing intently on buildings in Old Cairo earmarked for relocation to the new administrative capital, manipulating an integral empirical assessment and advanced modeling techniques. Amidst intensifying imperatives for robust infrastructure against a backdrop of financial constraints and hastened asset deterioration, this study proposes a cutting-edge, thorough approach to fund distribution. The developed approach incorporates asset hierarchy and classification, condition assessment via pilot survey, Markov chain model for degradation anticipation, stakeholder perception analysis through questionnaires for comparative analysis, and constructing an optimization model for fund allocation. The findings unveiled the dire condition of the selected infrastructure assets and the pressing requisite for strategic maintenance and renovation interventions. The developed approach offered a pragmatic evidence-based approach concerning decision-makers, improving resource allocation efficacy and fostering urban development schemes. This paper calls for protractible presented methodologies to a broad spectrum of assets and geographies and integrating incipient technologies for dynamic asset management approaches.

The COVID-19 outbreak has impacted many daily activities and services we depend on. Due to changes in waste quantity and types, solid waste management (SWM) services such as waste collection, transportation, and treatment/disposal suffered. Global rules and mandates were issued to address these changes and the COVID-19 pandemic. This mini review examines seven countries and summarises the pandemic’s effects on municipal solid waste (MSW) and medical waste (MW) generation in terms of amount and composition, the SWM sector’s challenges, and government or other SWM guidelines and management measures. The data are analysed to provide suggestions for stakeholders on SWM worker protection, waste segregation, and recycling. This article identified that extending MW incineration, separating infectious waste at the source, and discontinuing recycling for infection control are the best ways to manage solid waste. The waste management system’s readiness was crucial to the pandemic response. Thus, countries like China, which has a robust SWM system, were able to contain the crisis and restrict danger, while others with weaker systems struggled. Additionally, the study highlights the importance of revising waste management policies and developing crisis response strategies that integrate flexible, innovative solutions to adapt quickly to changing waste demands and ensure public health and environmental protection during global health crises.

Background: Micronutrient deficiencies and excesses may indeed contribute to bipolar disorder (BD) and major depressive disorder (MDD). Objectives: This study aimed to compare the concentrations of copper (Cu) and zinc (Zn) in patients with BD and MDD, as well as to determine the relationship between trace element levels and the profile of affective disorders as biomarkers for the disease. Patients and Methods: This case-control study was conducted on 135 patients between the ages of 18 and 40, both sexes, who met the DSM-V diagnostic criteria for BD and MDD (regardless of the stage of the illness). Patients were divided into three equal groups. Group A had MDD; group B had BD, while group C was a healthy control individual. Results: Groups A and B exhibited significantly higher Cu levels compared to group C (P