Search Results (108)

Introduction: Carbapenem-resistant Klebsiella pneumoniae (CRKP) represents a critical public health threat due to its rapid nosocomial dissemination, limited therapeutic options, and elevated mortality rates. This study aimed to characterize the epidemiology, carbapenemase profiles, and antimicrobial susceptibility patterns of CRKP isolates, as well as the clinical features and outcomes observed in infected or colonized patients. Materials and Methods: We conducted a retrospective analysis of clinical and microbiological data from patients with CRKP infections or colonization admitted between January 2023 and January 2024. Descriptive statistics were used to assess prevalence, resistance patterns, and patient outcomes. Two binary logistic regression models were applied to identify independent predictors of sepsis and in-hospital mortality. Results: Among 89 CRKP isolates, 45 underwent carbapenemase typing. More than half were metallo-β-lactamase (MBL) producers, with 44.4% co-harbouring NDM and OXA-48-like enzymes. Surgical intervention was associated with a significantly lower risk of sepsis (p < 0.01) and in-hospital mortality (p = 0.045), whereas intensive care unit (ICU) stay was a strong predictor of both outcomes. ICU admission conferred a 10-fold higher risk of sepsis (95%Cl 2.4–41.0) and a 40.8-fold higher risk of in-hospital death (95% Cl 3.5–473.3). Limitations: This single-center retrospective study included a limited number of isolates in certain groups. Additionally, cefiderocol (FDC) susceptibility was assessed by disk diffusion rather than by the broth microdilution method. Conclusions: Our study underscores the increasing prevalence of metallo-beta-lactamase-producing CRKP, particularly strains harbouring dual carbapenemases. Timely recognition of high-risk patients, combined with the implementation of targeted infection control measures and the integration of novel therapeutic options, is crucial to optimize clinical management and reduce mortality associated with CRKP. Full article

Background: Acute respiratory distress syndrome (ARDS) secondary to tuberculosis (TB) is rare and associated with high mortality. Management is further complicated by comorbidities and ICU-related complications. Methods: We report a 43-year-old woman with post-polio sequelae and uncontrolled diabetes who developed ARDS due to pulmonary TB, complicated by recurrent nosocomial infections and gastrointestinal bleeding. Early bronchoscopy and GeneXpert MTB/RIF PCR were performed on ICU Day 2, enabling anti-TB therapy initiation by ICU Day 3. The patient received lung-protective ventilation, prone positioning, tailored antibiotics, and multidisciplinary care. Results: The patient’s clinical course was complicated by two episodes of ventilator-associated pneumonia and gastrointestinal bleeding, but with individualized management, she achieved ventilator weaning and functional recovery. Conclusions: Early TB recognition in ARDS is crucial. Multidisciplinary ICU management, including prudent steroid use, improves outcomes. Full article

Context: Respiratory morbidity is a leading cause of children’s consultations with general practitioners. Auscultation, the act of listening to breath sounds, is a crucial diagnostic method for respiratory system diseases. Problem: Parents and caregivers often lack the necessary knowledge and experience to identify subtle differences in children’s breath sounds. Furthermore, obtaining reliable feedback from young children about their physical condition is challenging. Methods: The use of a human–artificial intelligence (AI) tool is an essential component for screening and monitoring young children’s respiratory diseases. Using clinical data to design and validate the proposed approaches, we propose novel methods for recognizing and classifying children’s breath sounds. Different breath sound signals were analyzed in the time domain, frequency domain, and using spectrogram representations. Breath sound detection and segmentation were performed using digital signal processing techniques. Multiple features—including Mel–Frequency Cepstral Coefficients (MFCCs), Linear Prediction Coefficients (LPCs), Linear Prediction Cepstral Coefficients (LPCCs), spectral entropy, and Dynamic Linear Prediction Coefficients (DLPCs)—were extracted to capture both time and frequency characteristics. These features were then fed into various classifiers, including K-Nearest Neighbor (KNN), artificial neural networks (ANNs), hidden Markov models (HMMs), logistic regression, and decision trees, for recognition and classification. Main Findings: Experimental results from across 120 infants and preschoolers (2 months to 6 years) with respiratory disease (30 asthma, 30 croup, 30 pneumonia, and 30 normal) verified the performance of the proposed approaches. Conclusions: The proposed AI system provides a real-time diagnostic platform to improve clinical respiratory management and outcomes in young children, thereby reducing healthcare costs. Future work exploring additional respiratory diseases is warranted. Full article

Background: Community-acquired bacterial pneumonia (CABP) is a common and costly cause of hospitalization. Although severe CABP (sCABP) occurs in 10–25% of all pneumonia hospitalizations, little generalizable data examine its characteristics and outcomes or hospital resource utilization. Methods: We conducted a retrospective single-group cohort study of adults within the IQVIA hospital Charge Data Master, 2018–2022. We identified CABP via an ICD-10 code algorithm and sCABP was defined as an episode requiring ICU care. We examined baseline characteristics and outcomes, including mortality, costs, and readmission rates. We developed models to identify risk factors associated with readmissions. Results: Among 24,149 patients with sCABP, 14,266 (58.4%) were ≥65 years old and 55.2% were male. The majority were hospitalized in large (300+ beds, 50.9%), urban (91.9%) teaching (62.7%) institutions in the US Southern region (52.3%). The mean (SD) Charlson Comorbidity Index was 1.35 (2.33). The most common comorbidities were hypertension (16.7%), diabetes mellitus (15.7%), and chronic obstructive pulmonary disease (COPD) (12.9%). Hospital mortality was 15.9%. The mean (SD) hospital length of stay (LOS) and costs were 13.6 (12.1) and USD 91,965 (USD 133,734), respectively. An amount of 20% required a readmission within 30 days. Readmission was most strongly associated with older age and the presence of select comorbidities (diabetes mellitus, congestive heart failure, and COPD), each with an odds ratio > 1.4 and 95% confidence intervals excluding 1.0. Conclusions: Patients with sCABP comprise a large population with high mortality and 30-day readmissions. The intrinsic factors related to the latter lend themselves to early recognition and aggressive efforts at reducing complications. Full article

Background/Objectives: Acute Fibrinous and Organizing Pneumonia (AFOP) is a rare pulmonary condition histologically characterized by intra-alveolar fibrin deposition and organizing pneumonia without hyaline membranes. This study aims to describe the clinicopathologic and radiologic features of isolated AFOP nodules presenting as solitary pulmonary nodules (SPNs) mimicking malignancy in patients with recent COVID-19 infection. Methods: We retrospectively analyzed consecutive cases of histologically confirmed AFOP (n = 20) and organizing pneumonia (OP; n = 119) presenting radiologically as SPNs suspicious for malignancy from January 2021 to December 2023. Clinical data, COVID-19 status, radiologic features (including nodular characteristics, ground-glass opacity [GGO], and consolidation), and histopathological findings were collected and analyzed. Digital image analysis quantified the intra-alveolar fibrin content. Results: AFOP nodules showed a significant association with previous COVID-19 infection compared to OP (55% vs. 0.8%, p < 0.001). Radiologically, AFOP lesions were predominantly located in the upper lobes, frequently exhibiting a mixed pattern of GGO and consolidation within solitary nodules (8–28 mm diameter), distinctly differing from the predominantly lower-lobe homogeneous consolidations in OP. Histologically, AFOP was defined by prominent intra-alveolar fibrin “balls,” correlating significantly with radiological consolidation patterns (r = 0.991, p < 0.05). Regions of consolidation demonstrated higher fibrin contents compared to areas of predominant GGO. Conclusions: Isolated AFOP nodules presenting as SPNs post-COVID-19 infection strongly mimic malignancy radiologically, highlighting the necessity for multidisciplinary diagnostic approaches integrating radiological and histopathological data to avoid unnecessary interventions. Recognition of this rare but distinctive clinical entity is essential for appropriate patient management. Full article

Background and Objectives: Sepsis is a leading cause of morbidity and mortality worldwide, yet data from Central and Eastern Europe remain scarce. Our study aims to address the scarcity of information regarding the characteristics and mortality rates of patients with sepsis by reporting recent data from one of the largest emergency centers in Romania over an 18-year period (2007–2024). Materials and Methods: A retrospective analysis was conducted on 12,089 adult patients diagnosed with sepsis at the University Emergency Hospital of Bucharest. Patients were identified using International Classification of Diseases (ICD-10) codes and free-text diagnosis. Demographic and clinical data were extracted, including comorbidities, interventions, and mortality outcomes. Associations between comorbidities and in-hospital mortality were assessed using odds ratios (ORs) and 95% confidence intervals (CIs). Results: The study population had a mean age of 68.7 years, with a slight predominance of males (50.9%). In-hospital mortality was 53.9%, and 30-day mortality reached 85.1%. The most common comorbidities were diabetes (27.2%), chronic kidney disease (14.0%), and cancer (12.9%). Pneumonia (OR = 2.08, 95% CI: 1.89–2.28), cirrhosis (OR = 1.69, 95% CI: 1.40–2.03), and chronic obstructive pulmonary disease (OR = 1.50, 95% CI: 1.27–1.77) were strong predictors of mortality, while diabetes was associated with a slightly lower risk (OR = 0.90, 95% CI: 0.83–0.97). Conclusions: Sepsis-related mortality in Romania is higher than reported in Western Europe and North America, resembling trends in resource-limited settings. Targeted early recognition, antimicrobial stewardship, and improved intensive care units (ICU) resource allocation are crucial for reducing mortality. Multicenter studies and microbiological analyses are needed to further understand sepsis outcomes in this region. Full article

Pediatric pneumonia remains a critical global health challenge requiring accurate and interpretable diagnostic solutions. Although deep learning has shown potential for pneumonia recognition on chest X-ray images, gaps persist in understanding model interpretability and feature learning during training. We evaluated four convolutional neural network (CNN) architectures, i.e., InceptionV3, InceptionResNetV2, DenseNet201, and MobileNetV2, using three approaches—standard convolution, multi-scale convolution, and strided convolution—all incorporating the Mish activation function. Among the tested models, InceptionResNetV2, with strided convolutions, demonstrated the best performance, achieving an accuracy of 0.9718. InceptionV3 also performed well using the same approach, with an accuracy of 0.9684. For DenseNet201 and MobileNetV2, the multi-scale convolution approach was more effective, with accuracies of 0.9676 and 0.9437, respectively. Gradient-weighted class activation mapping (Grad-CAM) visualizations provided critical insights, e.g., multi-scale convolutions identified diffuse viral pneumonia patterns across wider lung regions, while strided convolutions precisely highlighted localized bacterial consolidations, aligning with radiologists’ diagnostic priorities. These findings establish the following architectural guidelines: strided convolutions are suited to deep hierarchical CNNs, while multi-scale approaches optimize compact models. This research significantly advances the development of interpretable, high-performance diagnostic systems for pediatric pneumonia using chest X-rays, bridging the gap between computational innovation and clinical application. Full article

Background: Pneumocystis jirovecii primarily causes pneumonia in immunosuppressed individuals, particularly those living with advanced HIV/AIDS. Extrapulmonary dissemination is uncommon, with bone marrow involvement described in only a handful of cases globally. Bone marrow infection occurs in the setting of severe immunosuppression, poses diagnostic challenges, and carries a high mortality rate. Methods: We describe the case of a 34-year-old man newly diagnosed with HIV/AIDS, presenting with severe immunosuppression and Pneumocystis jirovecii pneumonia. The patient initially improved with cotrimoxazole and corticosteroids, but was readmitted shortly after discharge with abdominal pain, diarrhea, and worsening pancytopenia. A bone marrow biopsy revealed Pneumocystis jirovecii cysts, confirming disseminated infection. Concomitant Kaposi sarcoma involving the skin and gastrointestinal tract was also diagnosed. Despite antimicrobial therapy, the patient’s condition worsened, leading to multisystem organ failure and death two months later. Conclusions: This case highlights a rare presentation of disseminated Pneumocystis jirovecii infection with bone marrow involvement in a patient with advanced HIV/AIDS. Although infrequent, this complication should be considered in individuals with Pneumocystis jirovecii pneumonia who develop persistent cytopenias and systemic symptoms. Diagnosis depends on histopathologic confirmation, which may lead to under-recognition. Early suspicion and individualized management are essential, though the optimal treatment approach for extrapulmonary infection remains undefined. Full article

Background: Radiomic features have been extensively used with machine learning and other Artificial Intelligence methods in medical imaging problems. Coronavirus Disease 2019 (COVID-19), which has been spreading worldwide since 2020, has motivated scientists to develop automatic COVID-19 recognition systems, to enhance the clinical routine in overcrowded hospitals. Purpose: To develop an automated system of recognizing COVID-19 and Community-Acquired Pneumonia (CAP) using radiomic features extracted from whole lung chest Computed Tomography (CT) images. Radiomic feature extraction from whole lung CTs simplifies the image segmentation for the malignancy region of interest (ROI). Methods: In this work, we used radiomic features extracted from CT images representing whole lungs to train various machine learning models that are capable of identifying COVID-19 images, CAP images and healthy cases. The CT images were derived from an open access data set, called COVID-CT-MD, containing 76 Normal cases, 169 COVID-19 cases and 60 CAP cases. Results: Four two-class models and one three-class model were developed: Normal–COVID, COVID–CAP, Normal–CAP, Normal–Disease and Normal–COVID–CAP. Different algorithms and data augmentation were used to train each model 20 times on a different data set split, and, finally, the model with the best average performance was selected for each case. The performance metrics of Accuracy, Sensitivity and Specificity were used to assess the performance of the different systems. Since COVID-19 and CAP share similar characteristics, it is challenging to develop a model that can distinguish these diseases. Result: The results were promising for the models finally selected for each case. The accuracy for the independent test set was 83.11% in the Normal–COVID case, 88.77% in the COVID–CAP case, 93.97% in the Normal–CAP case and 94.13% in the Normal–Disease case, when referring to two-class cases, while, in the three-class case, the accuracy was 78.55%. Conclusion: The results obtained suggest that radiomic features extracted from whole lung CT images can be successfully used to distinguish COVID-19 from other pneumonias and normal lung cases. Full article

Background/Objectives: Pertussis remains a significant cause of respiratory illness in children, particularly in regions with suboptimal vaccination coverage. This retrospective study analyzes the clinical presentations, co-infections, treatment, and outcomes of pediatric patients diagnosed with Bordetella pertussis at the Constanța County Clinical Emergency Hospital “St. Apostle Andrew” between 1 January and 30 September 2024. Methods: Thirty-eight children, predominantly under the age of 3 years (81.58%), were included. Demographic data, clinical features, coinfecting pathogens, antimicrobial regimens, and hospital outcomes were reviewed. Results: Only 7 out of 38 children (18.42%) had received pertussis vaccination, and none benefited from maternal immunization. The highest incidence occurred in infants under 1 year (44.74%). Intensive care was required in 18.42% of cases, and macrolides were the most frequently used antibiotics (68.42%). Co-detection of respiratory pathogens—particularly Streptococcus pneumoniae, enteroviruses, and human rhinoviruses—was common. Severe cases often exhibited hyperleukocytosis, which was associated with complications such as heart failure. Conclusions: These findings underscore the need for timely recognition and management of pertussis and its complications. Although macrolides remain the first-line therapy, adjunctive treatments like leukoreduction may be considered in critical cases. The persistence of pertussis despite vaccination efforts highlights the challenges posed by waning immunity and diagnostic limitations, reinforcing the need for strengthened public health strategies. Full article

Background/Objectives: Immune checkpoint inhibitors (ICIs) cause interstitial lung diseases (ILDs) as a type of immune-related adverse event (irAE). The characteristics of ICI-ILD are diverse. The objective of this study is to investigate the clinical features of ICI-ILD, with particular emphasis on insidiously progressive ICI-ILD. Methods: We retrospectively analyzed 232 patients with advanced lung cancer who were treated with ICIs (including combination therapy with cytotoxic agents). Results: IrAEs were observed in 85 patients (36.6%). The most frequent irAE was ICI-ILD (41 patients, 17.7% of all patients). The occurrence of ICI-ILD was associated with a significantly better response compared to the non-irAE group (response rates: 88% vs. 33%), longer progression-free survival (PFS) (median: 17.5 vs. 3.0 months), and longer overall survival (median: 52.6 vs. 16.6 months), respectively. However, six patients died from ICI-ILD, which could be divided into two patterns: early-onset ICI-ILD in three patients (median PFS: 1.2 months), and insidiously progressive ICI-ILD in three patients. In the latter type, ICI-ILD developed unnoticed, progressed insidiously, and led to respiratory failure (median PFS: 7.2 months). The non-organizing pneumonia pattern and a weak response to corticosteroid therapy were also common findings. On average, six cycles of ICI treatment were administered between the time when ICI-ILD became retrospectively recognizable and the discontinuation of ICI treatment. During this period, C-reactive protein levels and the extent of ILD involvement gradually increased. Conclusions: Insidiously progressive ICI-ILD can lead to fatal outcomes. Early discontinuation of ICIs upon recognition of this type of ICI-ILD may improve patient outcomes. Full article

Pediatric pneumonia remains a significant global health issue, particularly in low- and middle-income countries, where it contributes substantially to mortality in children under five. This study introduces a deep learning model for pediatric pneumonia diagnosis from chest X-rays that surpasses the performance of state-of-the-art methods reported in the recent literature. Using a DenseNet201 architecture with a Mish activation function and multi-scale convolutions, the model was trained on a dataset of 5856 chest X-ray images, achieving high performance: 0.9642 accuracy, 0.9580 precision, 0.9506 sensitivity, 0.9542 F1 score, and 0.9507 specificity. These results demonstrate a significant advancement in diagnostic precision and efficiency within this domain. By achieving the highest accuracy and F1 score compared to other recent work using the same dataset, our approach offers a tangible improvement for resource-constrained environments where access to specialists and sophisticated equipment is limited. While the need for high-quality datasets and adequate computational resources remains a general consideration for deep learning applications, our model’s demonstrably superior performance establishes a new benchmark and offers the delivery of more timely and precise diagnoses, with the potential to significantly enhance patient outcomes. Full article

Background: Eosinophilic pneumonias denote a rare condition, wherein infiltrating eosinophilic granulocytes accumulate within the lung parenchyma. Although eosinophilic pneumonias may be idiopathic, they are also associated with secondary causes. More than 110 medications have been linked to eosinophilic pneumonia, including several antidepressants. This review presents an analysis of case reports of eosinophilic pneumonia correlated to antidepressants. Objectives: The objectives of this study are to provide a contemporary overview of the literature delineating eosinophilic pneumonia as a potential sequela of antidepressant medication treatment, and to discuss possible pathogenetic mechanisms linking antidepressants to eosinophilic pneumonia. Methods and Data Selection: A literature search was performed in PubMed and Scopus databases from 1963 to October 2024. The search strategy used the terms “eosinophilic pneumonia AND antidepressants”. Sources included in this review were screened for relevance, focusing on references discussing eosinophilic pneumonia associated with any class of antidepressants. Case reports meeting the diagnostic criteria for acute eosinophilic pneumonia (AEP) or chronic eosinophilic pneumonia (CEP) were included in the review. Clinical, epidemiological, laboratory, radiology and bronchoscopy data, implicated antidepressant and dosage, and therapeutic interventions were reported. Results: This study found that various types of antidepressants are associated with AEP and CEP. The clinical presentation ranges from mild symptoms to respiratory failure and intubation. Outcomes were favorable in most cases, with complete remission achieved after discontinuation of the causative drug and, in severe cases, a short course of corticosteroids. Conclusions: Although a rare cause, antidepressants may lead to eosinophilic pneumonia, and should be considered in the differential diagnosis of unexplained pulmonary infiltrates. Clinical suspicion must be aroused, as early recognition would prevent unnecessary work-up and navigation of the diagnosis. Full article

Background: Human metapneumovirus (hMPV) is a respiratory pathogen that has gained increasing recognition due to advancements in molecular diagnostic tools, which have improved its detection and characterization. While severe disease manifestations are traditionally associated with pediatric, elderly, or immunocompromised patients, hMPV-related pneumonia in immunocompetent adults remains underexplored. Methods: This case report describes a 68-year-old male who developed severe community-acquired pneumonia (CAP) caused by hMPV despite being immunocompetent and having no significant comorbidities. The diagnosis was confirmed via multiplex RT-PCR, excluding bacterial and viral coinfections. Laboratory and imaging findings supported a viral etiology, while empirical antibiotics were initially prescribed due to diagnostic uncertainty. Results: The patient presented with respiratory symptoms that progressed to hypoxia, productive cough, and fatigue, requiring hospitalization. Imaging revealed bilateral ground-glass opacities and consolidations typical of viral pneumonia. Molecular diagnostics enabled accurate pathogen identification and guiding appropriate management, and the patient fully recovered with supportive care. Conclusion: This case underscores the importance of rapid molecular diagnostics for hMPV, reducing unnecessary antibiotics and enhancing management. Routine incorporation of hMPV testing into clinical protocols could improve the diagnosis and resource use. The development of vaccines, such as the IVX-A12 in phase II trials, offers hope for targeted prevention, underscoring the need for further research and therapeutic innovations. Full article

Background: The brain is protected from invading pathogens by the blood−brain barrier (BBB) and the innate immune system. Pattern recognition receptors play a crucial role in detecting bacteria and initiating the innate immune response. Among these are G-protein-coupled formyl peptide receptors (FPR), which are expressed by immune cells in the central nervous system. In this study, we investigated the influence of the FPR ligand Ac2-26 on the integrity of the BBB during pneumococcal meningitis. Methods: Wild-type (WT) and Fpr1- and Fpr2-deficient mice were intrathecally infected with Streptococcus pneumoniae. Subsequently, different groups of mice were treated with intraperitoneal injections of Ac2-26. The integrity of the BBB was analyzed using various markers through immunohistochemistry and immunofluorescence. Results: The results showed reduced BBB integrity during the course of bacterial meningitis. Treatment with Ac2-26 in WT mice significantly prolonged the maintenance of BBB integrity. However, this effect was not observed in Fpr2-deficient mice. Conclusions: This study extends previous findings on the anti-inflammatory properties of Ac2-26 by demonstrating that Ac2-26 positively affects BBB integrity via FPR2 during pneumococcal meningitis. These findings suggest that further investigation of Ac2-26 and other FPR modulators as potential therapies for Streptococcus pneumoniae-induced meningitis is warranted. Full article