RESUMEN
Acute respiratory distress syndrome (ARDS) has a fibroproliferative phase that may be followed by pulmonary fibrosis. Pulmonary fibrosis following COVID-19 pneumonia has been described at autopsy and following lung transplantation. We hypothesized that protein mediators of tissue remodeling and monocyte chemotaxis are elevated in the plasma and endotracheal aspirates of critically ill patients with COVID-19 who subsequently develop features of pulmonary fibroproliferation. We enrolled COVID-19 patients admitted to the ICU with hypoxemic respiratory failure. (n = 195). Plasma was collected within 24h of ICU admission and at 7d. In mechanically ventilated patients, endotracheal aspirates (ETA) were collected. Protein concentrations were measured by immunoassay. We tested for associations between protein concentrations and respiratory outcomes using logistic regression adjusting for age, sex, treatment with steroids, and APACHE III score. In a subset of patients who had CT scans during hospitalization (n = 75), we tested for associations between protein concentrations and radiographic features of fibroproliferation. Among the entire cohort, plasma IL-6, TNF-α, CCL2, and Amphiregulin levels were significantly associated with in-hospital mortality. In addition, higher plasma concentrations of CCL2, IL-6, TNF-α, Amphiregulin, and CXCL12 were associated with fewer ventilator-free days. We identified 20/75 patients (26%) with features of fibroproliferation. Within 24h of ICU admission, no measured plasma proteins were associated with a fibroproliferative response. However, when measured 96h-128h after admission, Amphiregulin was elevated in those that developed fibroproliferation. ETAs were not correlated with plasma measurements and did not show any association with mortality, ventilator-free days (VFDs), or fibroproliferative response. This cohort study identifies proteins of tissue remodeling and monocyte recruitment are associated with in-hospital mortality, fewer VFDs, and radiographic fibroproliferative response. Measuring changes in these proteins over time may allow for early identification of patients with severe COVID-19 at risk for fibroproliferation.
Asunto(s)
COVID-19 , Fibrosis Pulmonar , Humanos , COVID-19/mortalidad , COVID-19/sangre , COVID-19/patología , Masculino , Femenino , Persona de Mediana Edad , Anciano , Fibrosis Pulmonar/patología , Fibrosis Pulmonar/sangre , Fibrosis Pulmonar/mortalidad , Monocitos/metabolismo , Mortalidad Hospitalaria , SARS-CoV-2 , Pulmón/patología , Quimiotaxis de Leucocito , QuimiotaxisRESUMEN
BACKGROUND: To assess changes in bone density and vertebral body height of patients undergoing lung transplant surgery using computed tomography (CT). METHODS: This institutional review board (IRB) approved retrospective observational study enrolled patients with a history of lung transplant who had at least two chest CT scans. Vertebral body bone density (superior, middle, and inferior sections) and height (anterior, middle, and posterior sections) were measured at T1-T12 at baseline and follow up CT scans. Changes in the mean bone density, mean vertebral height, vertebral compression ratio (VBCR), percentage of anterior height compression (PAHC), and percentage of middle height compression (PMHC) were calculated and analyzed. RESULTS: A total of 93 participants with mean age of 58 ± 12.3 years were enrolled. The most common underlying disease that led to lung transplants was interstitial lung diseases (57 %). The inter-scan interval was 34.06 ± 24.8 months. There were significant changes (p-value < 0.05) in bone density at all levels from T3 to T12, with the greatest decline at the T10 level from 163.06 HU to 141.84 HU (p-value < 0.05). The average VBCR decreased from 96.91 to 96.15 (p-value < 0.05). CONCLUSION: Routine chest CT scans demonstrate a gradual decrease in vertebral body bone density over time in lung transplant recipients, along with evident anatomic changes such as vertebral body bone compression. This study shows that utilizing routine chest CT for lung transplant recipients can be regarded as a cost-free tool for assessing the vertebral body bone changes in these patients and potentially aiding in the prevention of complications related to osteoporosis.
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RATIONALE AND OBJECTIVES: Managing contrast reactions is critical as contrast reactions can be life-threatening and unpredictable. Institutions need an effective system to handle these events. Currently, there is no standard practice for assigning trainees, radiologists, non-radiologist physicians, or other non-physician providers for management of contrast reaction. MATERIALS AND METHODS: The Association of Academic Radiologists (AAR) created a task force to address this gap. The AAR task force reviewed existing practices, studied available literature, and consulted experts related to contrast reaction management. The Society of Chairs of Academic Radiology Departments (SCARD) members were surveyed using a questionnaire focused on staffing strategies for contrast reaction management. RESULTS: The task force found disparities in contrast reactions management across institutions and healthcare providers. There is a lack of standardized protocols for assigning personnel for contrast reaction management. CONCLUSION: The AAR task force suggests developing standardized protocols for contrast reaction management. The protocols should outline clear roles for different healthcare providers involved in these events.
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PURPOSE: The purpose of this study was to systematically review the reported performances of ChatGPT, identify potential limitations, and explore future directions for its integration, optimization, and ethical considerations in radiology applications. MATERIALS AND METHODS: After a comprehensive review of PubMed, Web of Science, Embase, and Google Scholar databases, a cohort of published studies was identified up to January 1, 2024, utilizing ChatGPT for clinical radiology applications. RESULTS: Out of 861 studies derived, 44 studies evaluated the performance of ChatGPT; among these, 37 (37/44; 84.1%) demonstrated high performance, and seven (7/44; 15.9%) indicated it had a lower performance in providing information on diagnosis and clinical decision support (6/44; 13.6%) and patient communication and educational content (1/44; 2.3%). Twenty-four (24/44; 54.5%) studies reported the proportion of ChatGPT's performance. Among these, 19 (19/24; 79.2%) studies recorded a median accuracy of 70.5%, and in five (5/24; 20.8%) studies, there was a median agreement of 83.6% between ChatGPT outcomes and reference standards [radiologists' decision or guidelines], generally confirming ChatGPT's high accuracy in these studies. Eleven studies compared two recent ChatGPT versions, and in ten (10/11; 90.9%), ChatGPTv4 outperformed v3.5, showing notable enhancements in addressing higher-order thinking questions, better comprehension of radiology terms, and improved accuracy in describing images. Risks and concerns about using ChatGPT included biased responses, limited originality, and the potential for inaccurate information leading to misinformation, hallucinations, improper citations and fake references, cybersecurity vulnerabilities, and patient privacy risks. CONCLUSION: Although ChatGPT's effectiveness has been shown in 84.1% of radiology studies, there are still multiple pitfalls and limitations to address. It is too soon to confirm its complete proficiency and accuracy, and more extensive multicenter studies utilizing diverse datasets and pre-training techniques are required to verify ChatGPT's role in radiology.