Articles: cations.
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Semin Respir Crit Care Med · Jun 2024
ReviewDiagnostic Approach to Interstitial Lung Diseases Associated with Connective Tissue Diseases.
Interstitial lung disorders are a group of respiratory diseases characterized by interstitial compartment infiltration, varying degrees of infiltration, and fibrosis, with or without small airway involvement. Although some are idiopathic (e.g., idiopathic pulmonary fibrosis, idiopathic interstitial pneumonias, and sarcoidosis), the great majority have an underlying etiology, such as systemic autoimmune rheumatic disease (SARD, also called Connective Tissue Diseases or CTD), inhalational exposure to organic matter, medications, and rarely, genetic disorders. ⋯ In a minority of patients, a definitive diagnosis cannot be established. Their clinical presentations and prognosis can be variable even within subsets of SARDs.
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Hospital-acquired urinary tract infections (UTIs) have a detrimental effect on patients, families, and hospital resources. The Sydney Children's Hospital Network (SCHN) participates in the NSQIP-Pediatric (NSQIP-P) to monitor postoperative complications. NSQIP-P data revealed that the median UTI rate at SCHN was 1.75% in 2019, 3.5 times higher than the NSQIP-P target rate of 0.5%. Over three quarters of the NSQIP-P identified patients with UTI also had a urinary catheterization performed intraoperatively. A quality improvement project was conducted between mid-2018 and 2021 to minimize catheter-associated UTIs (CAUTIs) at SCHN. ⋯ A multifactorial approach in quality improvement has been shown to be an effective strategy to reduce UTI rates at SCHN, and patient outcomes were improved within a 3-year timeframe. Although this project has reduced UTI rates at SCHN, there remain opportunities for further improvement.
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Curr Opin Anaesthesiol · Jun 2024
ReviewAdvances in pediatric perioperative care using artificial intelligence.
This article explores how artificial intelligence (AI) can be used to evaluate risks in pediatric perioperative care. It will also describe potential future applications of AI, such as models for airway device selection, controlling anesthetic depth and nociception during surgery, and contributing to the training of pediatric anesthesia providers. ⋯ The goal of using AI in pediatric anesthesia is to assist clinicians in providing safe and efficient care. Given that children are a vulnerable population, it is crucial to ensure that both clinicians and families have confidence in the clinical tools used to inform medical decision- making. While not yet a reality, the eventual incorporation of AI-based tools holds great potential to contribute to the safe and efficient care of our patients.
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Connective tissue diseases (CTD) are heterogeneous, immune-mediated inflammatory disorders often presenting with multiorgan involvement. With the advent of high-resolution computed tomography, CTD-related pleuritis-pleural thickening and effusion-is now increasingly recognized early in the disease trajectory. ⋯ Treatment of the underlying CTD is necessary to manage the pleural disease. Depending on the degree of symptom burden and physiological insult, specific treatment of pleural disease can include monitoring, repeated aspirations, systemic anti-inflammatory medication, and surgical decortication.
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Curr Opin Crit Care · Jun 2024
ReviewArtificial intelligence to advance acute and intensive care medicine.
This review explores recent key advancements in artificial intelligence for acute and intensive care medicine. As artificial intelligence rapidly evolves, this review aims to elucidate its current applications, future possibilities, and the vital challenges that are associated with its integration into emergency medical dispatch, triage, medical consultation and ICUs. ⋯ Despite promising academic strides, widespread artificial intelligence adoption in acute and critical care is hindered by ethical, legal, technical, organizational, and validation challenges. Despite these obstacles, artificial intelligence's potential to streamline clinical workflows is evident. When these barriers are overcome, future advancements in artificial intelligence have the potential to transform the landscape of patient care for acute and intensive care medicine.