Explore the vast range of titles available.

IntroductionDyspnea is a common chief complaint leading to emergency department (ED) visits. Multiple conditions may cause or be associated with dyspnoea, including bacterial pneumonia, acute heart failure (AHF), exacerbation of chronic obstructive pulmonary disease (COPD) or asthma and pulmonary embolism. Each of these diagnoses has a specific treatment recommended by international guidelines. Inappropriate treatment in the ED is more frequent among elderly patients and is independently associated with in-hospital mortality. Point-of-care ultrasound is immediately available at the bedside. Lung and cardiac ultrasound (LuCUS) offers excellent diagnostic accuracy for bacterial pneumonia, AHF and COPD exacerbations, even in elderly patients. The primary objective of the LUC REED trial is to evaluate the impact of a LuCUS-guided strategy versus standard care on reducing inappropriate treatment of dyspnoea in elderly ED patients.Methods and analysisThe LUC REED trial is a prospective, interventional, multicentre, stepped-wedge randomised controlled trial designed to assess the superiority of a LuCUS-guided strategy over standard care in ensuring treatment appropriateness for dyspnoea in elderly ED patients. The study will include 504 patients over 2 years. Patients aged >65 years presenting with acute dyspnoea and signs of severity (respiratory rate ≥22 and SpO2 <92% on room air) will be enrolled. Each ED (cluster) will start with a control phase. Every 3 months, one centre will transition to the intervention phase (LuCUS-guided strategy). The primary outcome is treatment inappropriateness within the first hour after inclusion, assessed by comparing administered treatment to the final diagnosis adjudicated by two experts.Ethics and disseminationEthics final approval was obtained from the Institutional Review Board of France—Est IV on 4 April 2025 (2024-A01678-39). Results will be published in peer-reviewed international journals.Trial registration numberNCT06807983.

To evaluate the efficacy and safety of Fuzheng Jiedu Huayu Decoction (FJHD) in treating pneumonia in the elderly. Adopting a multi-center, double-blind, parallel, randomized controlled trial, 284 elderly pneumonia patients were enrolled and randomly allocated to the standard treatment with FJHD (treatment group, TG) and the standard treatment with placebo group (control group, CG). Efficacy and safety was evaluated through mortality rate, curative rate, symptom improvement, chest X-ray (CXR) lesion absorption, arterial blood gas (ABG), peripheral blood leukocyte count (PBLC) and adverse events. There was no significant difference in mortality rate between both groups (P > 0.05). TG significantly enhanced the curative rate of a 2-week treatment course (P < 0.05). Compared with CG, TG significantly decreased the expectoration score during the first and second week of treatment (P < 0.05). During the first week, improvement in expectoration was conducive to airway patency. During the second week, wheezing, shortness of breath and other symptoms were also significantly improved. During the third week, body temperature was stable. TG improved lesion absorption with Pneumonia Severity Index (PSI) class II (P < 0.05) and SMART-COP score 1 (P < 0.05). TG significantly decreased the arterial carbon dioxide partial pressure after a 1-week treatment. There were no serious adverse events in TG. Standard anti-infection treatment with FJHD is a safe and reliable method of treating elderly patients with pneumonia, improving the curative effect after a 2-week treatment course, ameliorating expectoration and promoting the absorption of pneumonia lesions.

In this study, a dataset of X-ray images from patients with common bacterial pneumonia, confirmed Covid-19 disease, and normal incidents, was utilized for the automatic detection of the Coronavirus disease. The aim of the study is to evaluate the performance of state-of-the-art convolutional neural network architectures proposed over the recent years for medical image classification. Specifically, the procedure called Transfer Learning was adopted. With transfer learning, the detection of various abnormalities in small medical image datasets is an achievable target, often yielding remarkable results. The datasets utilized in this experiment are two. Firstly, a collection of 1427 X-ray images including 224 images with confirmed Covid-19 disease, 700 images with confirmed common bacterial pneumonia, and 504 images of normal conditions. Secondly, a dataset including 224 images with confirmed Covid-19 disease, 714 images with confirmed bacterial and viral pneumonia, and 504 images of normal conditions. The data was collected from the available X-ray images on public medical repositories. The results suggest that Deep Learning with X-ray imaging may extract significant biomarkers related to the Covid-19 disease, while the best accuracy, sensitivity, and specificity obtained is 96.78%, 98.66%, and 96.46% respectively. Since by now, all diagnostic tests show failure rates such as to raise concerns, the probability of incorporating X-rays into the diagnosis of the disease could be assessed by the medical community, based on the findings, while more research to evaluate the X-ray approach from different aspects may be conducted.

The COVID-19 epidemic has a catastrophic impact on global well-being and public health. More than 27 million confirmed cases have been reported worldwide until now. Due to the growing number of confirmed cases, and challenges to the variations of the COVID-19, timely and accurate classification of healthy and infected patients is essential to control and treat COVID-19. We aim to develop a deep learning-based system for the persuasive classification and reliable detection of COVID-19 using chest radiography. Firstly, we evaluate the performance of various state-of-the-art convolutional neural networks (CNNs) proposed over recent years for medical image classification. Secondly, we develop and train CNN from scratch. In both cases, we use a public X-Ray dataset for training and validation purposes. For transfer learning, we obtain 100% accuracy for binary classification (i.e., Normal/COVID-19) and 87.50% accuracy for tertiary classification (Normal/COVID-19/Pneumonia). With the CNN trained from scratch, we achieve 93.75% accuracy for tertiary classification. In the case of transfer learning, the classification accuracy drops with the increased number of classes. The results are demonstrated by comprehensive receiver operating characteristics (ROC) and confusion metric analysis with 10-fold cross-validation.

With the use of metagenomic next-generation sequencing, patients diagnosed with Whipple pneumonia are being increasingly correctly diagnosed. We report a series of 3 cases in China that showed a novel pattern of movable infiltrates and upper lung micronodules. After treatment, the 3 patients recovered, and lung infiltrates resolved.

Background. Chest radiographs (CXRs) are frequently used to assess pneumonia cases. Variations in CXR appearances between epidemiological settings and their correlation with clinical signs are not well documented. Methods. The Pneumonia Etiology Research for Child Health project enrolled 4232 cases of hospitalized World Health Organization (WHO)–defined severe and very severe pneumonia from 9 sites in 7 countries (Bangladesh, the Gambia, Kenya, Mali, South Africa, Thailand, and Zambia). At admission, each case underwent a standardized assessment of clinical signs and pneumonia risk factors by trained health personnel, and a CXR was taken that was interpreted using the standardized WHO methodology. CXRs were categorized as abnormal (consolidation and/or other infiltrate), normal, or uninterpretable. Results. CXRs were interpretable in 3587 (85%) cases, of which 1935 (54%) were abnormal (site range, 35%–64%). Cases with abnormal CXRs were more likely than those with normal CXRs to have hypoxemia (45% vs 26%), crackles (69% vs 62%), tachypnea (85% vs 80%), or fever (20% vs 16%) and less likely to have wheeze (30% vs 38%; all P < .05). CXR consolidation was associated with a higher case fatality ratio at 30-day follow-up (13.5%) compared to other infiltrate (4.7%) or normal (4.9%) CXRs. Conclusions. Clinically diagnosed pneumonia cases with abnormal CXRs were more likely to have signs typically associated with pneumonia. However, CXR-normal cases were common, and clinical signs considered indicative of pneumonia were present in substantial proportions of these cases. CXR-consolidation cases represent a group with an increased likelihood of death at 30 days post-discharge.

Background Pneumonia is a major public health problem with an impact on morbidity and mortality. Its management still represents a challenge. The aim was to determine whether a new diagnostic algorithm combining lung ultrasound (LUS) and procalcitonin (PCT) improved pneumonia management regarding antibiotic use, radiation exposure, and associated costs, in critically ill pediatric patients with suspected bacterial pneumonia (BP). Methods Randomized, blinded, comparative effectiveness clinical trial. Children < 18y with suspected BP admitted to the PICU from September 2017 to December 2019, were included. PCT was determined at admission. Patients were randomized into the experimental group (EG) and control group (CG) if LUS or chest X-ray (CXR) were done as the first image test, respectively. Patients were classified: 1.LUS/CXR not suggestive of BP and PCT < 1 ng/mL, no antibiotics were recommended; 2.LUS/CXR suggestive of BP, regardless of the PCT value, antibiotics were recommended; 3.LUS/CXR not suggestive of BP and PCT > 1 ng/mL, antibiotics were recommended. Results 194 children were enrolled, 113 (58.2%) females, median age of 134 (IQR 39–554) days. 96 randomized into EG and 98 into CG. 1. In 75/194 patients the image test was not suggestive of BP with PCT < 1 ng/ml; 29/52 in the EG and 11/23 in the CG did not receive antibiotics. 2. In 101 patients, the image was suggestive of BP; 34/34 in the EG and 57/67 in the CG received antibiotics. Statistically significant differences between groups were observed when PCT resulted < 1 ng/ml ( p  = 0.01). 3. In 18 patients the image test was not suggestive of BP but PCT resulted > 1 ng/ml, all of them received antibiotics. A total of 0.035 mSv radiation/patient was eluded. A reduction of 77% CXR/patient was observed. LUS did not significantly increase costs. Conclusions Combination of LUS and PCT showed no risk of mistreating BP, avoided radiation and did not increase costs. The algorithm could be a reliable tool for improving pneumonia management. Clinical Trial Registration : NCT04217980.

The diagnosis of pediatric pneumonia and determination of the likely pathogen are complicated as the clinical picture overlaps with other respiratory illnesses, interpretation of radiographs is subjective, and laboratory results are rarely diagnostic. This study was designed to describe the relative rates of bacterial and viral pneumonia in the pediatric Emergency Department (ED), determine the accuracy of pediatric ED physicians' ability to diagnose pneumonia and distinguish bacterial from viral etiology, and to determine clinical and laboratory predictors of bacterial pneumonia. Children 3 months to 16 years of age presenting to seven Canadian pediatric EDs before the COVID-19 pandemic with fever and cough who had a chest radiograph performed for possible pneumonia were enrolled and underwent standardized clinical investigations. An expert panel was convened and reached a Consensus Diagnosis of typical or atypical bacterial pneumonia, viral pneumonia or not pneumonia for each case. The expert panel assessed 247 cases with the Consensus Diagnosis being typical bacterial pneumonia (N = 44(18%)), atypical bacterial pneumonia (N = 18(7%)), viral pneumonia (N = 46(19%)) and no pneumonia (N = 139(56%)). Treating ED physician diagnoses were typical bacterial pneumonia (N = 126(51%)), atypical bacterial pneumonia (N = 3(1%)), viral pneumonia (N = 10(4%)) and no pneumonia (N = 108(44%)) with low agreement between a diagnosis of bacterial pneumonia by the ED physician and the panel's Consensus Diagnosis (Kappa 0.15 (95% CI 0.08, 0.21)). Cut off values that predicted bacterial pneumonia as the Consensus Diagnosis were ESR ≥ 47 mm/hour, CRP ≥ 42 mg/L and procalcitonin ≥0.85 ng/m. Age greater than 5 years and cough for 5 or more days also predict bacterial pneumonia. In this cohort, pediatric ED physicians over-diagnosed typical bacterial pneumonia and underdiagnosed viral and atypical bacterial pneumonia. Bacterial pneumonia is most likely in children over 5 years of age, with cough for 5 or more days and/or with elevated inflammatory markers.

Background Streptococcus salivarius is an opportunistic pathogen, and there have been no reported cases of Streptococcus salivarius pneumonia to date. Pneumomediastinum is usually secondary to tracheal or esophageal injury and is very rare as a complication of pneumonia. We report a case of Streptococcus salivarius pneumonia complicated by pneumomediastinum, aiming to enhance clinicians’ awareness of rare pathogens and uncommon complications in pneumonia. Case presentation The patient, a 36-year-old male, presented with a persistent cough and sputum production for one week, accompanied by a sore throat that had developed just one day prior. Chest computed tomography (CT) disclosed pneumomediastinum alongside obstructive atelectasis in the left lower lobe. Streptococcus salivarius infection was conclusively identified through bronchoalveolar lavage metagenomic next-generation sequencing (mNGS), as well as smear and culture analyses. The patient was administered intravenous amoxicillin-clavulanate potassium for a duration of seven days as part of the anti-infection regimen. Given the stability of the patient’s respiratory and circulatory systems, a tube drainage procedure was deemed unnecessary. Post-treatment, the patient’s clinical symptoms notably improved. A subsequent chest CT scan revealed the re-expansion of the left lower lung and near-complete resolution of pneumomediastinum. Conclusion There are numerous pathogens that can cause pneumonia. While focusing on common pathogens, it is important not to overlook rare ones. When considering infections from rare pathogens, it is recommended to promptly perform a bronchoscopy and submit bronchoalveolar lavage fluid for mNGS to improve pathogen detection rates. During the diagnosis and treatment of pneumonia, it is crucial to be vigilant for rare complications. When a patient presents with symptoms such as dyspnea or subcutaneous emphysema, it is advisable to immediately perform a chest CT scan to rule out pneumomediastinum.

In the coronavirus disease-2019 (COVID-19) era, point-of-care lung ultrasound (LUS) has attracted increased attention. Prospective studies on LUS for the assessment of pneumonia in adult patients were extensively carried out for more than 10 years before this era. None of these prospective studies attempted to differentiate bacterial and viral pneumonia in adult patients using LUS. The majority of studies considered the LUS examination to be positive if sonographic consolidations or multiple B-lines were observed. Significant differences existed in the accuracy of these studies. Some studies revealed that LUS showed superior sensitivity to chest X-ray. These results indicate that point-of-care LUS has the potential to be an initial imaging modality for the diagnosis of pneumonia. The LUS diagnosis of ventilator-associated pneumonia in intensive care units is more challenging in comparison with the diagnosis of community-acquired pneumonia in emergency departments due to the limited access to the mechanically ventilated patients and the high prevalence of atelectasis. However, several studies have demonstrated that the combination of LUS findings with other clinical markers improved the diagnostic accuracy. In the COVID-19 era, many case reports and small observational studies on COVID-19 pneumonia have been published in a short period. Multiple B-lines were the most common and consistent finding in COVID-19 pneumonia. Serial LUS showed the deterioration of the disease. The knowledge and ideas on the application of LUS in the management of pneumonia that are expected to accumulate in the COVID-19 era may provide us with clues regarding more appropriate management.