Purpose: Congenital diaphragmatic hernia (CDH) is associated with significant in-hospital mortality, morbidity and length-of-stay (LOS). We hypothesized that the degree of pulmonary support on hospital day-30 may predict in-hospital mortality, LOS, and discharge oxygen needs and could be useful for risk prediction and counseling.
Methods: 862 patients in the CDH Study Group registry with a LOS ≥ 30 days were analyzed (2007-2010). Pulmonary support was defined as (1) room-air (n=320) (2) noninvasive supplementation (n=244) (3) mechanical ventilation (n=279) and (4) extracorporeal membrane oxygenation (ECMO, n=19). Cox Proportional hazards and logistic regression models were used to determine the case-mix adjusted association of oxygen requirements on day-30 with mortality and oxygen requirements at discharge.
Results: On multivariate analysis, use of ventilator (HR 5.1, p=.003) or ECMO (HR 19.6, p<.001) was a significant predictor of in-patient mortality. Need for non-invasive supplementation or ventilator on day-30 was associated with a respective 22-fold (p<.001) and 43-fold (p<.001) increased odds of oxygen use at discharge compared to those on room-air.
Conclusions: Pulmonary support on Day-30 is a strong predictor of length of stay, oxygen requirements at discharge and in-patient mortality and may be used as a simple prognostic indicator for family counseling, discharge planning, and identification of high-risk infants.
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http://dx.doi.org/10.1016/j.jpedsurg.2013.03.012 | DOI Listing |
Nat Commun
January 2025
Department of Machine Learning, Moffitt Cancer Center, Tampa, FL, USA.
AI decision support systems can assist clinicians in planning adaptive treatment strategies that can dynamically react to individuals' cancer progression for effective personalized care. However, AI's imperfections can lead to suboptimal therapeutics if clinicians over or under rely on AI. To investigate such collaborative decision-making process, we conducted a Human-AI interaction study on response-adaptive radiotherapy for non-small cell lung cancer and hepatocellular carcinoma.
View Article and Find Full Text PDFInsights Imaging
January 2025
Department of Radiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
Objectives: The aim of this study was to determine the status of tertiary lymphoid structures (TLSs) using radiomic features in patients with invasive pulmonary adenocarcinoma (IA).
Methods: In this retrospective study, patients with IA from November 2015 to March 2024 were recruited from two independent centers (center 1, training and internal test data set; center 2, external test data set). TLS was divided into two groups according to hematoxylin-eosin staining.
Insights Imaging
January 2025
Department of Medical and Surgical Specialties, Radiological Sciences and Public Health, University of Brescia, Brescia, Italy.
Objectives: This article aims to evaluate the use and effects of an artificial intelligence system supporting a critical diagnostic task during radiology resident training, addressing a research gap in this field.
Materials And Methods: We involved eight residents evaluating 150 CXRs in three scenarios: no AI, on-demand AI, and integrated-AI. The considered task was the assessment of a multi-regional severity score of lung compromise in patients affected by COVID-19.
Sci Rep
January 2025
Amrita School of Artificial Intelligences, Coimbatore, Amrita Vishwa Vidyapeetham, Coimbatore, India.
Lung cancer is the leading cause of cancer-related fatalities globally, accounting for the highest mortality rate among both men and women. Mutations in the epidermal growth factor receptor (EGFR) gene are frequently found in non-small cell lung cancer (NSCLC). Since curcumin and CB[2]UN support various medicinal applications in drug delivery and design, we investigated the effect of curcumin and CB[2]UN-based drugs in controlling EGFR-mutant NSCLC through a dodecagonal computational approach.
View Article and Find Full Text PDFCardiovasc Revasc Med
January 2025
Department of Cardiovascular disease, Henry Ford, Detroit, MI, USA.
Introduction: Cardiogenic shock (CS) is marked by substantial morbidity and mortality. The two major CS etiologies include heart failure (HF) and acute myocardial infarction (AMI). The utilization trends of mechanical circulatory support (MCS) and their clinical outcomes are not well described.
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