Effect of Natriuretic Peptide-Guided Therapy on Hospitalization or Cardiovascular Mortality in High-Risk Patients With Heart Failure and Reduced Ejection Fraction: A Randomized Clinical Trial.

Importance: The natriuretic peptides are biochemical markers of heart failure (HF) severity and predictors of adverse outcomes. Smaller studies have evaluated adjusting HF therapy based on natriuretic peptide levels ( guided therapy ) with inconsistent results. Objective: To determine whether an amino-terminal pro-B-type natriuretic peptide (NT-proBNP)-guided treatment strategy improves clinical outcomes vs usual care in high-risk patients with HF and reduced ejection fraction (HFrEF). Design, Settings, and Participants: The Guiding Evidence Based Therapy Using Biomarker Intensified Treatment in Heart Failure (GUIDE-IT) study was a randomized multicenter clinical trial conducted between January 16, 2013, and September 20, 2016, at 45 clinical sites in the United States and Canada. This study planned to randomize 1100 patients with HFrEF (ejection fraction ≤40%), elevated natriuretic peptide levels within the prior 30 days, and a history of a prior HF event (HF hospitalization or equivalent) to either an NT-proBNP-guided strategy or usual care. Interventions: Patients were randomized to either an NT-proBNP-guided strategy or usual care. Patients randomized to the guided strategy (n = 446) had HF therapy titrated with the goal of achieving a target NT-proBNP of less than 1000 pg/mL. Patients randomized to usual care (n = 448) had HF care in accordance with published guidelines, with emphasis on titration of proven neurohormonal therapies for HF. Serial measurement of NT-proBNP testing was discouraged in the usual care group. Main Outcomes and Measures: The primary end point was the composite of time-to-first HF hospitalization or cardiovascular mortality. Prespecified secondary end points included all-cause mortality, total hospitalizations for HF, days alive and not hospitalized for cardiovascular reasons, the individual components on the primary end point, and adverse events. Results: The data and safety monitoring board recommended stopping the study for futility when 894 (median age, 63 years; 286 [32%] women) of the planned 1100 patients had been enrolled with follow-up for a median of 15 months. The primary end point occurred in 164 patients (37%) in the biomarker-guided group and 164 patients (37%) in the usual care group (adjusted hazard ratio [HR], 0.98; 95% CI, 0.79-1.22; P = .88). Cardiovascular mortality was 12% (n = 53) in the biomarker-guided group and 13% (n = 57) in the usual care group (HR, 0.94; 95% CI; 0.65-1.37; P = .75). None of the secondary end points nor the decreases in the NT-proBNP levels achieved differed significantly between groups. Conclusions and Relevance: In high-risk patients with HFrEF, a strategy of NT-proBNP-guided therapy was not more effective than a usual care strategy in improving outcomes. Trial Registration: clinicaltrials.gov Identifier: NCT01685840

Deep learning-based automated segmentation of airway OCT images acquired during drug-induced sleep endoscopy (DISE)

Obstructive sleep apnea (OSA) is a common upper airway disorder with severe long-term health impacts. There is a critical need for methods that provide quantitative information on dynamic airway collapse during sleep; information not available from sleep studies or conventional Imaging (e.g., CT). We present an alternative minimally invasive approach that combines drug-induced sleep endoscopy (DISE) with optical coherence tomography (OCT) and deep learning. These studies generate a massive volume of data, hence automated methods are needed using deep learning/convolutional neural networks (CNNs) to segment images. This strategy enhances the identification of critical regions prone to collapse, providing a robust tool to optimize treatment for OSA

A prospective multicenter clinical research study validating the effectiveness and safety of a chest X-ray-based pulmonary tuberculosis screening software JF CXR-1 built on a convolutional neural network algorithm

BackgroundChest radiography (chest X-ray or CXR) plays an important role in the early detection of active pulmonary tuberculosis (TB). In areas with a high TB burden that require urgent screening, there is often a shortage of radiologists available to interpret the X-ray results. Computer-aided detection (CAD) software employed with artificial intelligence (AI) systems may have the potential to solve this problem.ObjectiveWe validated the effectiveness and safety of pulmonary tuberculosis imaging screening software that is based on a convolutional neural network algorithm.MethodsWe conducted prospective multicenter clinical research to validate the performance of pulmonary tuberculosis imaging screening software (JF CXR-1). Volunteers under the age of 15 years, both with or without suspicion of pulmonary tuberculosis, were recruited for CXR photography. The software reported a probability score of TB for each participant. The results were compared with those reported by radiologists. We measured sensitivity, specificity, consistency rate, and the area under the receiver operating characteristic curves (AUC) for the diagnosis of tuberculosis. Besides, adverse events (AE) and severe adverse events (SAE) were also evaluated.ResultsThe clinical research was conducted in six general infectious disease hospitals across China. A total of 1,165 participants were enrolled, and 1,161 were enrolled in the full analysis set (FAS). Men accounted for 60.0% (697/1,161). Compared to the results from radiologists on the board, the software showed a sensitivity of 94.2% (95% CI: 92.0–95.8%) and a specificity of 91.2% (95% CI: 88.5–93.2%). The consistency rate was 92.7% (91.1–94.1%), with a Kappa value of 0.854 (P = 0.000). The AUC was 0.98. In the safety set (SS), which consisted of 1,161 participants, 0.3% (3/1,161) had AEs that were not related to the software, and no severe AEs were observed.ConclusionThe software for tuberculosis screening based on a convolutional neural network algorithm is effective and safe. It is a potential candidate for solving tuberculosis screening problems in areas lacking radiologists with a high TB burden

Quantitative assessment of chlorine gas inhalation injury based on endoscopic OCT and spectral encoded interferometric microscope imaging with deep learning.

Chlorine exposure can cause severe airway injuries. While the acute effects of chlorine inhalation are well-documented, the structural changes resulting from the post-acute, high-level chlorine exposure remain less understood. Airway sloughing is one of the standards for doctors to evaluate the lung function. Here, we report the application of a high-resolution swept-source optical coherence tomography system to investigate the progression of injury based on airway sloughing evaluation in a chlorine inhalation rabbit model. This system employs a 1.2 mm diameter flexible fiberoptic endoscopic probe via an endotracheal tube to capture in vivo large airway anatomical changes before and as early as 30 min after acute chlorine exposure. We conducted an animal study using New Zealand white rabbits exposed to acute chlorine gas (800 ppm, 6 min) during ventilation and monitored them using optical coherence tomography (OCT) for 6 h. To measure the volume of airway sloughing induced by chlorine gas, we utilized deep learning for the segmentation task on OCT images. The results showed that the volume of chlorine induced epithelial sloughing on rabbit tracheal walls initially increased, peaked around 30 min, and then decreased. Furthermore, we utilized a spectral encoded interferometric microscopy system to study ex vivo airway cilia beating dynamics based on Doppler shift, aiding in elucidating how chlorine gas affects cilia beating function. Cilia movability and beating frequency were decreased because of the epithelium damage. This quantitative approach has the potential to enhance the diagnosis and monitoring of injuries from toxic gas inhalation and to evaluate the efficacy of antidote treatments for these injuries

Awareness and preparedness level of medical workers for radiation and nuclear emergency response

Radiological science and nuclear technology have made great strides in the twenty-first century, with wide-ranging applications in various fields, including energy, medicine, and industry. However, those developments have been accompanied by the inherent risks of exposure to nuclear radiation, which is a source of concern owing to its potentially adverse effects on human health and safety and which is of particular relevance to medical personnel who may be exposed to certain cancers associated with low-dose radiation in their working environment. While medical radiation workers have seen a decrease in their occupational exposure since the 1950s thanks to improved measures for radiation protection, a concerning lack of understanding and awareness persists among medical professionals regarding these potential hazards and the required safety precautions. This issue is further compounded by insufficient capabilities in emergency response. This highlights the urgent need to strengthen radiation safety education and training to ensure the well-being of medical staff who play a critical role in radiological and nuclear emergencies. This review examines the health hazards of nuclear radiation to healthcare workers and the awareness and willingness and education of healthcare workers on radiation protection, calling for improved training programs and emergency response skills to mitigate the risks of radiation exposure in the occupational environment, providing a catalyst for future enhancement of radiation safety protocols and fostering of a culture of safety in the medical community

Causes, Clinical Features, and Outcomes From a Prospective Study of Drug-Induced Liver Injury in the United States

Idiosyncratic drug-induced liver injury (DILI) is among the most common causes of acute liver failure in the United States, accounting for approximately 13% of cases. A prospective study was begun in 2003 to recruit patients with suspected DILI and create a repository of biological samples for analysis. This report summarizes the causes, clinical features, and outcomes from the first 300 patients enrolled

Causes, Clinical Features, and Outcomes From a Prospective Study of Drug-Induced Liver Injury in the United States

Background and Aims Idiosyncratic drug-induced liver injury (DILI) is among the most common causes of acute liver failure in the United States, accounting for approximately 13% of cases. A prospective study was begun in 2003 to recruit patients with suspected DILI and create a repository of biological samples for analysis. This report summarizes the causes, clinical features, and outcomes from the first 300 patients enrolled. Methods Patients with suspected DILI were enrolled based on predefined criteria and followed up for at least 6 months. Patients with acetaminophen liver injury were excluded. Results DILI was caused by a single prescription medication in 73% of the cases, by dietary supplements in 9%, and by multiple agents in 18%. More than 100 different agents were associated with DILI; antimicrobials (45.5%) and central nervous system agents (15%) were the most common. Causality was considered to be definite in 32%, highly likely in 41%, probable in 14%, possible in 10%, and unlikely in 3%. Acute hepatitis C virus (HCV) infection was the final diagnosis in 4 of 9 unlikely cases. Six months after enrollment, 14% of patients had persistent laboratory abnormalities and 8% had died; the cause of death was liver related in 44%. Conclusions DILI is caused by a wide array of medications, herbal supplements, and dietary supplements. Antibiotics are the single largest class of agents that cause DILI. Acute HCV infection should be excluded in patients with suspected DILI by HCV RNA testing. The overall 6-month mortality was 8%, but the majority of deaths were not liver related

Microbial Biomarkers of Intestinal Barrier Maturation in Preterm Infants

Intestinal barrier immaturity, or “leaky gut,” is the proximate cause of susceptibility to necrotizing enterocolitis in preterm neonates. However, the impact of intestinal microbiota development on intestinal mucosal barrier maturation has not been evaluated in this population. In this study, we investigated a longitudinally sampled cohort of 38 preterm infants < 33 weeks gestation monitored for intestinal permeability (IP) and fecal microbiota during the first 2 weeks of life. Rapid decrease in IP indicating intestinal barrier function maturation correlated with significant increase in community diversity. In particular, members of the Clostridiales and Bifidobacterium were highly transcriptionally active, and progressively increasing abundance in Clostridiales was significantly associated with decreased intestinal permeability. Further, neonatal factors previously identified to promote intestinal barrier maturation, including early exclusive breastmilk feeding and shorter duration antibiotic exposure, associate with the early colonization of the intestinal microbiota by members of the Clostridiales, which altogether are associated with improved intestinal barrier function in preterm infants

SegRap2023: A Benchmark of Organs-at-Risk and Gross Tumor Volume Segmentation for Radiotherapy Planning of Nasopharyngeal Carcinoma

Radiation therapy is a primary and effective NasoPharyngeal Carcinoma (NPC) treatment strategy. The precise delineation of Gross Tumor Volumes (GTVs) and Organs-At-Risk (OARs) is crucial in radiation treatment, directly impacting patient prognosis. Previously, the delineation of GTVs and OARs was performed by experienced radiation oncologists. Recently, deep learning has achieved promising results in many medical image segmentation tasks. However, for NPC OARs and GTVs segmentation, few public datasets are available for model development and evaluation. To alleviate this problem, the SegRap2023 challenge was organized in conjunction with MICCAI2023 and presented a large-scale benchmark for OAR and GTV segmentation with 400 Computed Tomography (CT) scans from 200 NPC patients, each with a pair of pre-aligned non-contrast and contrast-enhanced CT scans. The challenge's goal was to segment 45 OARs and 2 GTVs from the paired CT scans. In this paper, we detail the challenge and analyze the solutions of all participants. The average Dice similarity coefficient scores for all submissions ranged from 76.68\% to 86.70\%, and 70.42\% to 73.44\% for OARs and GTVs, respectively. We conclude that the segmentation of large-size OARs is well-addressed, and more efforts are needed for GTVs and small-size or thin-structure OARs. The benchmark will remain publicly available here: https://segrap2023.grand-challenge.orgComment: A challenge report of SegRap2023 (organized in conjunction with MICCAI2023

Design and pilot test of an implicit bias mitigation curriculum for clinicians

IntroductionClinician implicit racial bias (IB) may lead to lower quality care and adverse health outcomes for Black patients. Educational efforts to train clinicians to mitigate IB vary widely and have insufficient evidence of impact. We developed and pilot-tested an evidence-based clinician IB curriculum, “REACHing Equity.”MethodsTo assess acceptability and feasibility, we conducted an uncontrolled one-arm pilot trial with post-intervention assessments. REACHing Equity is designed for clinicians to: (1) acquire knowledge about IB and its impact on healthcare, (2) increase awareness of one's own capacity for IB, and (3) develop skills to mitigate IB in the clinical encounter. We delivered REACHing Equity virtually in three facilitated, interactive sessions over 7–9 weeks. Participants were health care providers who completed baseline and end-of-study evaluation surveys.ResultsOf approximately 1,592 clinicians invited, 37 participated, of whom 29 self-identified as women and 24 as non-Hispanic White. Attendance averaged 90% per session; 78% attended all 3 sessions. Response rate for evaluation surveys was 67%. Most respondents agreed or strongly agreed that the curriculum objectives were met, and that REACHing Equity equipped them to mitigate the impact of implicit bias in clinical care. Participants consistently reported higher self-efficacy for mitigating IB after compared to before completing the curriculum.ConclusionsDespite apparent barriers to clinician participation, we demonstrated feasibility and acceptability of the REACHing Equity intervention. Further research is needed to develop objective measures of uptake and clinician skill, test the impact of REACHing Equity on clinically relevant outcomes, and refine the curriculum for uptake and dissemination.ClinicalTrials.gov ID: NCT03415308