Advances in research on virulence factors of Acinetobacter baumannii and their potential as novel therapeutic targets.

Acinetobacter baumannii is a strictly aerobic, nonmotile, nonfermenting, gram-negative bacillus. It is a highly infectious and invasive pathogen with high mortality and morbidity rates among immunodeficient patients. Due to increasing levels of drug resistance and the inefficiency of existing antimicrobial treatments, it is crucial to develop novel agents to control this pathogen. Several recent studies have investigated virulence factors that are associated with the pathogenesis of A. baumannii, and could thus serve as novel therapeutic targets. The present review comprehensively summarizes the current understanding of these virulence factors and their mechanisms in A. baumannii. We also highlight factors that could be potential therapeutic targets, as well as list candidate virulence factors for future researchers and clinical practitioners.

Differentiation Between Acinetobacter Baumannii Colonization and Infection and the Clinical Outcome Prediction by Infection in Lower Respiratory Tract.

Purpose: Acinetobacter baumannii is the most common microorganism in sputum cultures from long-term hospitalized patients and is often the cause of hospital-acquired pneumonia (HAP), which is usually associated with poor prognosis and high mortality. It is sometimes difficult to distinguish between A. baumannii infection and colonization. This study aimed to evaluate factors that differentiate infection from colonization and predict mortality in patients with nosocomial pneumonia caused by A. baumannii. Patients and Methods: The data used in this study were collected in our hospital between January 2018 and December 2020 from patients whose sputum cultures were positive for A. baumannii. Results: A total of 714 patients were included, with 571 in the infection group and 143 in the colonization group. The in-hospital mortality rate in the infection group was 20.5%. Univariate and multivariate logistic regression analyses showed that age, total number of inpatient departments, absolute neutrophil count, and C-reactive protein (CRP) level helped distinguish between infection and colonization. The area under the receiver operating characteristic curve (ROC) of the identification model was 0.694. In the infection group, age, Charlson comorbidity score, neutrophil-to-lymphocyte ratio, blood urea nitrogen/albumin ratio, CRP level, presence of multidrug resistance, and clinical pulmonary infection score (≥6) ratio were associated with in-hospital mortality. The area under the ROC curve for the prediction model was 0.828. The top three drug resistance rates in the infection group were 100% (cefazolin), 98.77% (ceftriaxone), and 71.8% (cefuroxime). Conclusion: The combination of common parameters helps identify A. baumannii respiratory tract infection or colonization. Several novel predictors can be used to predict the risk of death from A. baumannii pneumonia to reduce mortality. The drug resistance of A. baumannii remains high.

Nitrite Promotes ROS Production to Potentiate Cefoperazone-Sulbactam-Mediated Elimination to Lab-Evolved and Clinical-Evolved Pseudomonas aeruginosa.

Cefoperazone-sulbactam (SCF)-resistant Pseudomonas aeruginosa poses a big challenge in the use of SCF to treat infection caused by the pathogen. We have recently shown exogenous nitrite-enabled killing of naturally and artificially evolved Pseudomonas aeruginosa strains (AP-RCLIN-EVO and AP-RLAB-EVO, respectively) by SCF. However, the underlying mechanism is unknown. Here, reprogramming metabolomics was adopted to investigate how nitrite enhanced the SCF-mediated killing efficacy. Nitrite-reprogrammed metabolome displayed an activated pyruvate cycle (P cycle), which was confirmed by elevated activity of pyruvate dehydrogenase (PDH), α-ketoglutarate dehydrogenase, succinate dehydrogenase, and malate dehydrogenase. The activated P cycle provided NADH for the electron transport chain and thereby increased reactive oxygen species (ROS), which potentiated SCF to kill AP-RCLIN-EVO and AP-RLAB-EVO. The nitrite-enabled killing of AP-RCLIN-EVO and AP-RLAB-EVO by SCF was inhibited by PDH inhibitor furfural and ROS scavenger N-Acetyl-L-cysteine but promoted by ROS promoter Fe3+. SCF alone could not induce ROS, but SCF-mediated killing efficacy was enhanced by ROS. In addition, the present study demonstrated that nitrite repressed antioxidants, which were partly responsible for the elevated ROS. These results reveal a nitrite-reprogrammed metabolome mechanism by which AP-RCLIN-EVO and AP-RLAB-EVO sensitivity to SCF is elevated. IMPORTANCE Antibiotic-resistant Pseudomonas aeruginosa has become a real concern in hospital-acquired infections, especially in critically ill and immunocompromised patients. Understanding antibiotic resistance mechanisms and developing novel control measures are highly appreciated. We have recently shown that a reduced nitrite-dependent NO biosynthesis contributes to cefoperazone-sulbactam (SCF) resistance, which is reverted by exogenous nitrite, in both naturally and artificially evolved P. aeruginosa strains (AP-RCLIN-EVO and AP-RLAB-EVO, respectively). However, the mechanism is unknown. The present study reports that the nitrite-enabled killing of AP-RCLIN-EVO and AP-RLAB-EVO by SCF is attributed to the promoted production of reactive oxygen species (ROS). Nitrite activates the pyruvate cycle to generate NADH for the electron transport chain, which in turn promotes ROS generation. Nitrite-potentiated SCF-mediated killing is decreased by pyruvate dehydrogenase inhibitor furfural and ROS scavenger N-Acetyl-L-cysteine but increased by ROS promoter Fe3+. Furthermore, SCF-mediated killing is promoted by H2O2 in a dose-dependent manner. In addition, the combination of nitrite and H2O2 greatly enhances SCF-mediated killing. These results not only disclose a nitrite-ROS-potentiated SCF-mediated killing, but also show SCF-mediated killing is dependent upon ROS.

Microbial Contamination Characteristics on Touch Surfaces in Outpatient Self-Service Facilities.

BACKGROUND: With the development of science and technology, self-service facilities have been widely used in hospitals. This study aimed to assess the microbial contamination characteristics on touch surfaces in outpatient, self-service facilities from Monday to Friday. METHODS: Touch surfaces in outpatient facilities were swabbed and surveyed for total microbial growth before and after work every morning. Selected bacteria were identified to screen for pathogenic organisms. RESULTS: There were 360 samples collected, 87 samples (24.2%) were culture-positive. Staphylococcus species were the main microbial contamination. The three most common bacteria were S. hominis, S. epidermidis and S. hemolyticus. After work, more microbial contamination was found on Monday (p = 0.029). There was no difference in sample positive rates between self-service facilities and manual service area. Although, the antibiotic resistance patterns of different staphylococcus species were different, the overall drug resistance rate is low. Only one S. aureus was methicillin-Sensitive S. aureus. CONCLUSIONS: The self-service facilities' touch surfaces microbial contamination were similar to manual service area, but the more used, the more microbial contamination was found. Hospitals should enhance cleaning times of self-service facilities to keep them clean, especially on Mondays.

Inactivation of Nitrite-Dependent Nitric Oxide Biosynthesis Is Responsible for Overlapped Antibiotic Resistance between Naturally and Artificially Evolved Pseudomonas aeruginosa.

Metabolic flexibility of Pseudomonas aeruginosa could lead to new strategies to combat bacterial infection. The present study used gas chromatography-mass spectrometry (GC-MS)-based metabolomics to investigate global metabolism in naturally and artificially evolved strains with cefoperazone-sulbactam (SCF) resistance (AP-RCLIN-EVO and AP-RLAB-EVO, respectively) from the same parent strain (AP-RCLIN). Inactivation of the pyruvate cycle and nitric oxide (NO) biosynthesis was identified as characteristic features of SCF resistance in both evolved strains. Nitrite-dependent NO biosynthesis instead of an arginine-dependent NO pathway is responsible for the reduced NO, which is attributed to lower nitrite and electrons from the oxidation of NADH to NAD+ provided by the pyruvate cycle. Exogenous fumarate, NADH, nitrate, and nitrite promoted the NO level and thereby potentiated SCF-mediated killing. Unexpectedly, fumarate caused the elevation of nitrite, while nitrite/nitrate resulted in the increase of Cyt bc1 complex (providing electrons). These interesting findings indicate that the nitrite-dependent NO biosynthesis and the pyruvate cycle are mutual to promote NO metabolism. In addition, the NO-potentiated sensitivity to SCF was validated by NO donor sodium nitroprusside. These results reveal an endogenous NO-mediated SCF resistance and develop its reversion by metabolites in P. aeruginosa. IMPORTANCE Infections with Pseudomonas aeruginosa have become a real concern among hospital-acquired infections, especially in cystic fibrosis patients and immunocompromised individuals. Control of the pathogen is challenging due to antibiotic resistance. Since bacterial metabolic state impacts sensitivity and resistance to antibiotics, exploring and disclosing bacterial metabolic mechanisms can be used to develop a metabolome-reprogramming approach to elevate bacterial sensitivity to antibiotics. Therefore, GC-MS-based metabolomics is used to explore the similarities and differences of metabolomes between naturally and artificially evolved cefoperazone-sulbactam (SCF)-resistant P. aeruginosa (AP-RCLIN-EVO and AP-RLAB-EVO, respectively) from the same parent strain (AP-RCLIN). It identifies the depressed nitrite-dependent nitric oxide (NO) biosynthesis as the most overlapping characteristic feature between AP-RCLIN-EVO and AP-RLAB-EVO. This is because the pyruvate cycle fluctuates, thereby generating fewer NADH and providing fewer electrons for nitrite-dependent NO biosynthesis than the control. Interestingly, exogenous fumarate, NADH, nitrate, and nitrite as well as NO donor sodium nitroprusside promote NO generation to elevate sensitivity to SCF. These results highlight the way to understand metabolic mechanisms of antibiotic resistance and explore metabolic modulation to combat the bacterial pathogen.

Deep Learning-Based Available and Common Clinical-Related Feature Variables Robustly Predict Survival in Community-Acquired Pneumonia.

BACKGROUND: Community-acquired pneumonia (CAP) is a leading cause of morbidity and mortality worldwide. Although there are many predictors of death for CAP, there are still some limitations. This study aimed to build a simple and accurate model based on available and common clinical-related feature variables for predicting CAP mortality by adopting machine learning techniques. METHODS: This was a single-center retrospective study. The data used in this study were collected from all patients (≥18 years) with CAP admitted to research hospitals between January 2012 and April 2020. Each patient had 62 clinical-related features, including clinical diagnostic and treatment features. Patients were divided into two endpoints, and by using Tensorflow2.4.1 as the modeling framework, a three-layer fully connected neural network (FCNN) was built as a base model for classification. For a comprehensive comparison, seven classical machine learning methods and their integrated stacking patterns were introduced to model and compare the same training and test data. RESULTS: A total of 3997 patients with CAP were included; 205 (5.12%) died in the hospital. After performing deep learning methods, this study established an ensemble FCNN model based on 12 FCNNs. By comparing with seven classical machine learning methods, the area under the curve of the ensemble FCNN was 0.975 when using deep learning algorithms to classify poor from good prognosis based on available and common clinical-related feature variables. The predicted outcome was poor prognosis if the ControlNet's poor prognosis score was greater than the cutoff value of 0.50. To confirm the scientificity of the ensemble FCNN model, this study analyzed the weight of random forest features and found that mainstream prognostic features still held weight, although the model is perfect after integrating other factors considered less important by previous studies. CONCLUSION: This study used deep learning algorithms to classify prognosis based on available and common clinical-related feature variables in patients with CAP with high accuracy and good generalizability. Every clinical-related feature is important to the model.

Blood urea nitrogen to serum albumin ratio independently predicts 30-day mortality and severity in patients with Escherichia coli bacteraemia

Background: Elevated blood urea nitrogen to serum albumin (BUN/ALB) ratio had been identified as an independent risk factor related to mortality in community-acquired and hospital-acquired pneumonia. This study aimed to investigate whether this clinical index can predict the clinical outcomes of E. coli bacteraemia.Material and methodsClinical data were collected from patients with E. coli bacteraemia attended at our hospital between January 2012 and December 2018. The endpoints were mortality within 30 days after the diagnosis of E. coli bacteraemia and intensive care (IC) requirement. Cox regression analysis was performed to evaluate the risk factors.ResultsA total of 398 patients with E. coli bacteraemia were enrolled in this study and 56 patients died within 30 days after bacteraemia onset. Multivariate Cox regression analysis showed that age greater than 65 years, lymphocyte count<.8×10e9/L, elevated BUN/ALB ratio, increased SOFA score, carbapenem resistance, central venous catheterization before onset of bacteraemia, and infection originating from abdominal cavity were independent risk factors for 30-day mortality (P<.05). The risk factors associated with IC requirement were similar to those for 30-day mortality except central venous catheterization before onset of bacteraemia. The area under the receiver-operating characteristic curve for BUN/ALB ratio predicting 30-day mortality and IC requirement was similar to that for SOFA score, but higher than that for lymphocyte count. The cut-off points of BUN/ALB ratio to predict 30-day mortality and IC requirement were both .3.ConclusionsBUN/ALB ratio is a simple but independent predictor of 30-day mortality and severity in E. coli bacteraemia. A higher BUN/ALB ratio at the onset of bacteraemia predicts a higher mortality rate and IC requirement. (AU)

Antecedentes: Se ha identificado la elevación de la proporción de nitrógeno ureico en sangre con respecto a albúmina sérica (NUS/ALB) como un factor de riesgo independiente asociado a la mortalidad de la neumonía adquirida en la comunidad y la neumonía intrahospitalaria. El objetivo de este estudio fue investigar si este índice clínico puede predecir los resultados clínicos de bacteremia por E. coli.Material y métodosSe recopilaron los datos clínicos de los pacientes con bacteremia por E. coli atendidos en nuestro hospital entre enero de 2012 y diciembre de 2018. Las variables de evaluación fueron la mortalidad a 30 días tras el diagnóstico de bacteremia por E. coli y la necesidad de cuidados intensivos (CI). Se realizó un análisis de regresión de Cox para evaluar los factores de riesgo.ResultadosSe incluyó en el estudio a un total de 398 pacientes con bacteremia por E. coli, falleciendo 56 pacientes en el plazo de 30 días tras el inicio de la bacteremia. El análisis de regresión de Cox multivariante reflejó que la edad superior a 65 años, el recuento linfocitario <0,8×109/l, la elevación del ratio NUS/ALB, el incremento de la puntuación SOFA, la resistencia al carbapenem, la cateterización venosa central anterior al inicio de la bacteremia y la infección originada por la cavidad abdominal eran factores de riesgo independientes de la mortalidad a 30 días (p<0,05). Los factores de riesgo asociados a la necesidad de CI fueron similares a los de la mortalidad a 30 días, exceptuando la cateterización venosa central anterior al inicio de la bacteremia. El área bajo la curva característica operador-receptor para el ratio NUS/ALB que predice la mortalidad a 30 días, y la necesidad de CI fue similar a la puntuación SOFA, aunque superior a la correspondiente al recuento linfocitario. Los puntos de corte del ratio NUS/ALB para predecir la mortalidad a 30 días y la necesidad de CI se situaron en 0,3. (AU)

Associations Between Gut Microbiota and Asthma Endotypes: A Cross-Sectional Study in South China Based on Patients with Newly Diagnosed Asthma.

OBJECTIVE: This study aimed to investigate the gut microbiome profile in different inflammatory phenotypes of treatment-naive newly diagnosed asthmatic adults, to gain insight on the associations between intestinal microbiota and phenotypic features that characterize asthma heterogeneity to develop new treatments for asthma. METHODS: Fresh stool samples were obtained from 20 healthy subjects and 47 newly diagnosed asthmatic patients prior to any interventions. The asthmatics were divided into allergic and non-allergic cohorts. Intestinal microbiota was analyzed by 16S rRNA next-generation sequencing. Demographic and clinical parameters were collected. Alpha and beta diversity analysis were calculated to detect differences within sample phylotype richness and evenness between controls and asthmatic patients. Statistically significant differences between samples were analyzed for all used metrics, and features of gut bacterial community structure were evaluated in relation to extensive clinical characteristics of asthmatic patients. RESULTS: Gut microbial compositions were significantly different between asthmatic and healthy groups. Alpha-diversity of the gut microbiome was significantly lower in asthmatics than in controls. The microbiome between allergic and non-allergic asthmatic patients were also different, and 28 differential species were identified. PPAR signaling pathway, carotenoid biosynthesis, and flavonoid biosynthesis were significantly positively correlated with allergy-associated clinical index, including FENO value, blood eosinophil counts, and serum IgE and IL-4 levels. A combination of Ruminococcus bromii, Brevundimonas vesicularis, and Clostridium disporicum showed an AUC of 0.743 in the specific allergic/non-allergic cohort. When integrating C. disporicum, flavone, flavonol biosynthesis, and serum IL-4 values, the AUC achieved 0.929 to classify asthmatics. At the same time, C. colinum and its associated functional pathway exhibited an AUC of 0.78 to distinguish allergic asthmatics from those without allergies. CONCLUSION: We demonstrated a distinct taxonomic composition of gut microbiota in different asthmatic phenotypes, highlighting their significant relationships. Our study may support considerations of intestinal microbial signatures in delineating asthma phenotypes.

Combined Neutrophil-to-Lymphocyte Ratio and CURB-65 Score as an Accurate Predictor of Mortality for Community-Acquired Pneumonia in the Elderly.

PURPOSE: Community-acquired pneumonia (CAP) is common among the elderly; it typically has a poor prognosis and high mortality. This study evaluated the factors predicting CAP-related in-hospital mortality in the elderly to identify a simpler and more accurate predictor. PATIENTS AND METHODS: This was a single-center, retrospective study. The data used in this study was collected from all older patients (≥65) with CAP admitted to our hospital between January 2012 and April 2020. RESULTS: A total of 2028 older patients with CAP were included; 121 (5.97%) died in hospital. Of the patients in the study, 1267 (62.5%) were men and 261 (12.9%) had a history of malignant tumors. After performing univariate and multivariate Cox regression analyses, sex, history of malignant tumor, CURB-65 score, neutrophil-to-lymphocyte ratio (NLR), hemoglobin level, and NLR*CURB-65 levels were associated with CAP mortality. By comparing the area under the receiver operating characteristic (ROC) curves of the predicted factors, the NLR*CURB-65 level used to predict CAP mortality in the elderly was 0.755, and was superior to other measurements. All included patients were then dichotomized into two groups based on NLR*CURB-65 level (≤9.06 and >9.06) according to the ROC analysis. Patients with a high NLR*CURB-65 level had higher in-hospital mortality than those with a low NLR*CURB-65 level. The two divided groups showed significant differences in age, sex, smoking history, comorbidity, and laboratory findings. This indicates that NLR*CURB-65 is a predictive index that could reflect the comprehensive condition of older patients with CAP. CONCLUSION: NLR*CURB-65 is a simpler and more accurate predictor of CAP-related in-hospital mortality in the elderly.

Blood urea nitrogen to serum albumin ratio independently predicts 30-day mortality and severity in patients with Escherichia coli bacteraemia.

BACKGROUND: Elevated blood urea nitrogen to serum albumin (BUN/ALB) ratio had been identified as an independent risk factor related to mortality in community-acquired and hospital-acquired pneumonia. This study aimed to investigate whether this clinical index can predict the clinical outcomes of E. coli bacteraemia. MATERIAL AND METHODS: Clinical data were collected from patients with E. coli bacteraemia attended at our hospital between January 2012 and December 2018. The endpoints were mortality within 30 days after the diagnosis of E. coli bacteraemia and intensive care (IC) requirement. Cox regression analysis was performed to evaluate the risk factors. RESULTS: A total of 398 patients with E. coli bacteraemia were enrolled in this study and 56 patients died within 30 days after bacteraemia onset. Multivariate Cox regression analysis showed that age greater than 65 years, lymphocyte count<.8×10e9/L, elevated BUN/ALB ratio, increased SOFA score, carbapenem resistance, central venous catheterization before onset of bacteraemia, and infection originating from abdominal cavity were independent risk factors for 30-day mortality (P<.05). The risk factors associated with IC requirement were similar to those for 30-day mortality except central venous catheterization before onset of bacteraemia. The area under the receiver-operating characteristic curve for BUN/ALB ratio predicting 30-day mortality and IC requirement was similar to that for SOFA score, but higher than that for lymphocyte count. The cut-off points of BUN/ALB ratio to predict 30-day mortality and IC requirement were both .3. CONCLUSIONS: BUN/ALB ratio is a simple but independent predictor of 30-day mortality and severity in E. coli bacteraemia. A higher BUN/ALB ratio at the onset of bacteraemia predicts a higher mortality rate and IC requirement.

Comparison of Face-Touching Behaviors Before and During the Coronavirus Disease 2019 Pandemic.

Importance: There is insufficient evidence on the efficacy of masks in the general population for the prevention of coronavirus disease 2019 (COVID-19) in public areas. Therefore, it is imperative to investigate the association of mandatory mask-wearing policies with behaviors associated with the transmission of COVID-19. Objective: To assess the association of mask wearing with face-touching behavior among the general population in public areas. Design, Setting, and Participants: This cross-sectional study used videos recorded in public transportation stations, streets, and parks among the general population in China, Japan, South Korea, Western Europe (ie, England, France, Germany, Spain, and Italy), and the US to analyze mask-wearing and face-touching behavior in public areas. Videos before the COVID-19 pandemic were defined as those recorded from January 2018 to October 2019, and those during the COVID-19 pandemic were defined as those recorded during February 2020 to March 2020 in China, Japan, and South Korea and during March 2020 in Western Europe and the US. Individuals who clearly displayed their face and face-touching behavior were included, and those whose behaviors were influenced by filming or public events were excluded. Exposures: Mandatory mask-wearing policies enacted at various time points in China, Japan, South Korea, Western Europe, and the US. Main Outcomes and Measures: Proportion of individuals wearing masks and incidence of face touching. Results: This study included 4699 individuals before the COVID-19 pandemic and 2887 individuals during the pandemic. During the periods studied, mask wearing increased in all regions except the US, from 20 of 1745 individuals (1.1%) to 1090 of 1097 individuals (99.4%) in mainland China (P < .001), 44 of 1422 individuals (3.1%) to 346 of 893 individuals (38.7%) in Japan (P < .001), 6 of 717 individuals (0.8%) to 277 of 324 individuals (85.5% ) in South Korea (P < .001), 1 of 546 individuals (0.2%) to 6 of 379 individuals (1.6%) in Western Europe (P = .02), and 1 of 269 individuals (0.4%) to 4 of 194 individuals (2.1%) in the US (P = .17). Surgical masks were predominant in China (989 masks [89.1%]), and fabric masks were predominant in the other regions (Japan: 371 masks [95.1%]; South Korea: 240 masks [84.8%]; Western Europe: 6 masks [85.7%]; US: 5 masks [100%]). Face-touching behaviors decreased from before COVID-19 to during COVID-19 among individuals in China (72 incidences of 1745 observations [4.1%] to 12 incidences of 1097 observations [1.1%]; P < .001), South Korea (80 incidences of 717 observations [11.2%] to 7 incidences of 324 observations [2.2%]; P < .001), and Europe (62 incidences of 546 observations [11.4%] to 23 incidences of 379 observations [6.1%]; P = .01). Logistic regression found that mask wearing was associated with a reduction in face touching in China (odds ratio [OR], 3.91; 95% CI, 2.11-7.24) and South Korea (OR, 6.69; 95% CI, 2.69-16.69) and of touching the nose, mouth, and eyes (China: OR, 8.60; 95% CI, 2.65-27.86; South Korea: OR, 29.27; 95% CI, 1.79-478.22). Conclusions and Relevance: The findings of this cross-sectional study suggest that mandatory mask-wearing policies were associated with increased mask wearing during the COVID-19 pandemic. Mask wearing was associated with reduced face-touching behavior, especially touching of the eyes, nose, and mouth, which may prevent contact transmission of COVID-19 among the general population in public areas.

A promising approach for screening pulmonary hypertension based on frontal chest radiographs using deep learning: A retrospective study.

BACKGROUND: To date, the missed diagnosis rate of pulmonary hypertension (PH) was high, and there has been limited development of a rapid, simple, and effective way to screen the disease. The purpose of this study is to develop a deep learning approach to achieve rapid detection of possible abnormalities in chest radiographs suggesting PH for screening patients suspected of PH. METHODS: We retrospectively collected frontal chest radiographs and the pulmonary artery systolic pressure (PASP) value measured by Doppler transthoracic echocardiography from 762 patients (357 healthy controls and 405 with PH) from three institutes in China from January 2013 to May 2019. The wohle sample comprised 762 images (641 for training, 80 for internal test, and 41 for external test). We firstly performed a 8-fold cross-validation on the 641 images selected for training (561 for pre-training, 80 for validation), then decided to tune learning rate to 0.0008 according to the best score on validation data. Finally, we used all the pre-training and validation data (561+80 = 641) to train our models (Resnet50, Xception, and Inception V3), evaluated them on internal and external test dataset to classify the images as having manifestations of PH or healthy according to the area under the receiver operating characteristic curve (AUC/ROC). After that, the three deep learning models were further used for prediction of PASP using regression algorithm. Moreover, we invited an experienced chest radiologist to classify the images in the test dataset as having PH or not, and compared the prediction accuracy performed by deep learing models with that of manual classification. RESULTS: The AUC performed by the best model (Inception V3) achieved 0.970 in the internal test, and slightly declined in the external test (0.967) when using deep learning algorithms to classify PH from normal based on chest X-rays. The mean absolute error (MAE) of the best model for prediction of PASP value was smaller in the internal test (7.45) compared to 9.95 in the external test. Manual classification of PH based on chest X-rays showed much lower AUCs compared to that performed by deep learning models both in the internal and external test. CONCLUSIONS: The present study used deep learning algorithms to classify abnormalities suggesting PH in chest radiographs with high accuracy and good generalizability. Once tested prospectively in clinical settings, the technology could provide a non-invasive and easy-to-use method to screen patients suspected of having PH.

Neutrophil-To-Lymphocyte Ratio Predicted Long-Term Chemotherapy Benefits In Stage IIIB-IV Non-Squamous Non-Small Cell Lung Cancer Patients Without Sensitive Mutations.

PURPOSE: To investigate the predictive capability of clinical parameters for long-term chemotherapy benefits among stage IIIB-IV non-squamous non-small cell lung cancer (NSCLC) patients without sensitive mutations. PATIENTS AND METHODS: We investigated the clinical features of 206 stage IIIB-IV non-squamous NSCLC patients without sensitive mutations and assessed their predictive value for disease control rate (DCR) at 6 and 12 months post-treatment. RESULTS: Seventy-two patients received docetaxel and platinum-based chemotherapy while 134 received pemetrexed and platinum-based chemotherapy. The 6-month and 12-month DCR were 33 (45.8%) and 6 (8.3%) in the docetaxel group and 69 (51.5%) and 19 (14.2%) in the pemetrexed group, respectively. Univariate Cox regression revealed that age, sex, smoking history, adrenal gland metastasis, stage IV disease, neutrophil-to-lymphocyte ratio (NLR), and serum albumin were associated with unfavorable progression-free survival (PFS). Age, stage IV disease, and NLR were identified as independent predictors of PFS using multivariate analysis. NLR was the only parameter that could predict 3-month and 6-month DCRs. NLR and age were able to predict 12-month DCR, with NLR presenting a larger area under the curve. Kaplan-Meier curves demonstrated that patients with NLR > 2.231 displayed significantly reduced long-term disease control. The group with higher NLR had more male patients, lower ALB levels, and serum sodium levels as well as higher platelet counts. CONCLUSION: NLR was an independent predictor of long-term chemotherapy benefits among non-squamous NSCLC patients without sensitive mutations. Patients with lower NLR were optimal candidates for chemotherapy. Patients with high NLR may receive alternative treatments or be included in clinical trials.

Fast Prediction of Deterioration and Death Risk in Patients With Acute Exacerbation of Chronic Obstructive Pulmonary Disease Using Vital Signs and Admission History: Retrospective Cohort Study.

BACKGROUND: Chronic obstructive pulmonary disease (COPD) has 2 courses with different options for medical treatment: the acute exacerbation phase and the stable phase. Stable patients can use the Global Initiative for Chronic Obstructive Lung Disease (GOLD) to guide treatment strategies. However, GOLD could not classify and guide the treatment of acute exacerbation as acute exacerbation of COPD (AECOPD) is a complex process. OBJECTIVE: This paper aimed to propose a fast severity assessment and risk prediction approach in order to strengthen monitoring and medical interventions in advance. METHODS: The proposed method uses a classification and regression tree (CART) and had been validated using the AECOPD inpatient's medical history and first measured vital signs at admission that can be collected within minutes. We identified 552 inpatients with AECOPD from February 2011 to June 2018 retrospectively and used the classifier to predict the outcome and prognosis of this hospitalization. RESULTS: The overall accuracy of the proposed CART classifier was 76.2% (83/109 participants) with 95% CI 0.67-0.84. The precision, recall, and F-measure for the mild AECOPD were 76% (50/65 participants), 82% (50/61 participants), and 0.79, respectively, and those with severe AECOPD were 75% (33/44 participants), 68% (33/48 participants), and 0.72, respectively. CONCLUSIONS: This fast prediction CART classifier for early exacerbation detection could trigger the initiation of timely treatment, thereby potentially reducing exacerbation severity and recovery time and improving the patients' health.

Risk Factors for Mortality Due to Ventilator-Associated Pneumonia in a Chinese Hospital: A Retrospective Study.

BACKGROUND As a common nosocomial infection, ventilator-associated pneumonia (VAP) often has high mortality. This study aimed to assess the risk factor for mortality owing to VAP. MATERIAL AND METHODS This retrospective clinical audit study screened medical records between the period of January 2014 and December 2017. All patients under mechanical ventilation MV) for ≥72 hours were screened against previously reported diagnostic criteria for VAP. The medical records were obtained for cases of documented diagnosis of VAP. RESULTS In all, 145 patients (5.0%) diagnosed with VAP were included in the study; the morbidity of VAP was 19.5 episodes per 1000 days of MV. The 30-day mortality rate was 42.8%. Univariate logistic analysis showed that elevated neutrophil-to-lymphocyte ratio (NLR), high blood urea nitrogen/albumin (BUN/ALB) ratio, Multidrug-resistant organism infection, and a higher sequential organ failure assessment (SOFA) score were risk factors for mortality caused by VAP. In the second multivariate analysis, elevated NLR levels (P=0.038), high BUN/ALB ratio (P=0.016), multidrug-resistant organism infections (P=0.036), and a higher SOFA score (P<0.001) were still associated with the 30-day mortality rate. CONCLUSIONS The 30-day mortality rate of VAP was high. Blood NLR and BUN/ALB levels can be used as risk factors to assess the 30-day VAP-related mortality to help clinicians improve the prognosis of VAP.

Elevated Blood Urea Nitrogen-to-Serum Albumin Ratio as a Factor That Negatively Affects the Mortality of Patients with Hospital-Acquired Pneumonia.

This study aimed to evaluate the factors that affect 30-day mortality of patients with HAP. The data used in this study were collected from all HAP occurred in our hospital between January 2014 and December 2017. A total of 1158 cases were included. 150 (13.0%) of whom died within 30 days. This reported mortality identified by the univariate Cox regression analysis is found to have been affected by the following factors: age greater than 70 years, presence of diabetes mellitus and chronic obstructive pulmonary disease, gastric tube intubation, administration of proton-pump inhibitor, blood albumin level less than 30 g/l, elevated neutrophil-to-lymphocyte ratio, antibiotics therapy in the preceding 90 days, intensive care unit (ICU) admission, blood lymphocyte count less than 0.8 × 109/L, elevated blood urea nitrogen/albumin (BUN/ALB) level, and presence of multidrug-resistant (MDR) pathogens. In the second multivariate analysis, administration of proton-pump inhibitor, administration of antibiotics in the preceding 90 days, ICU admission, blood lymphocyte count less than 0.8 × 109/L, elevated BUN/ALB level, and presence of MDR pathogens were still associated with 30-day mortality. The area under the receiver operating characteristic curves in the BUN/ALB predicting 30-day mortality due to HAP was 0.685. A high BUN/ALB was significantly associated with a worse survival than a low BUN/ALB (P < 0.001). Therefore, an elevated BUN/ALB level is a risk factor for mortality on patients with HAP.

Differences in microbial etiology between hospital-acquired pneumonia and ventilator-associated pneumonia: a single-center retrospective study in Guang Zhou.

Purpose: Nosocomial pneumonia is a common nosocomial infection that includes hospital-acquired pneumonia (HAP) and ventilator-associated pneumonia(VAP). It is an important cause of morbidity and mortality in hospitalized patients. This study aimed to evaluate the differences in microbial etiology and outcomes between HAP and VAP, particularly in related risk factors of multidrug-resistant organism (MDRO) causing HAP and VAP. Patients and methods: This single-center retrospective, observational study included patients with HAP/VAP. Clinical and epidemiological data of nosocomial pneumonia confirmed by microbial etiology that occurred in the Third Affiliated Hospital of Sun Yat-sen University, China, from January 2014 to December 2017 were obtained. Results: A total of 313 HAP cases and 106 VAP cases were included. The leading pathogens of HAP and VAP were similar, including Acinetobacter baumannii, Pseudomonas aeruginosa, and Klebsiella pneumoniae. Antimicrobial susceptibility of the pathogens was low, and P. aeruginosa in VAP was less susceptible. In the multivariate logistic regression analysis, the risk factors associated with MDRO-HAP were chronic obstructive pulmonary disease, antibiotic therapy in the preceding 90 days, and prior endotracheal tracheostomy. The risk factor of MDRO-VAP was ≥5 days of hospitalization. The 30-day mortality rates of HAP and VAP were 18.5% and 42.5%. Conclusion: The leading pathogens were similar in both HAP and VAP, and antimicrobial susceptibility of the pathogens was low. The risk factors associated with MDRO infection in HAP and VAP have significant variability; hence, attention should be paid to improve prognosis. VAP was associated with poorer outcomes compared with HAP.

Factors influencing mortality in hospital-acquired pneumonia caused by Gram-negative bacteria in China.

BACKGROUND: Hospital-acquired pneumonia (HAP) remains an important cause of morbidity and mortality despite advances in antimicrobial therapy. The emergence of Gram-negative bacteria (GNB) is of major concern. The objective of this study was to describe the epidemiology, microbiology, and predictors of infection-related 30-day mortality in HAP with GNB. METHODS: We performed a retrospective, single-center analysis of HAP patients with GNB occurring from January 2014 and December 2017. Univariate and multivariate analyses were performed to identify the risk factors for mortality. RESULTS: During the observational period, there were 1472 cases of HAP; 314 cases were bacterial culture-positive, 269 cases were caused by GNB, with a predominance of Acinetobacter baumannii and Pseudomonas aeruginosa. The mortality related to GNB was 14.5% (39 deaths).In the multivariate logistic regression analysis, the risk factors for mortality were age >70 years, intensive care unit (ICU) admission, blood lymphocyte count < 0.8 × 109/L, multidrug-resistant Gram-negative bacteria(MDR-GNB) infection, and elevation of blood urea nitrogen(BUN) level. We identified these factors as significant predictors of GNB related mortality; the area under the receiver operating characteristic (ROC) curves was 0.836. CONCLUSION: The results provided can help clinicians in identifying individuals who are at risk of infection-related 30-day mortality in HAP with GNB.

Lower neutrophil-to-lymphocyte ratio predicts high risk of multidrug-resistant Pseudomonas aeruginosa infection in patients with hospital-acquired pneumonia.

BACKGROUND AND PURPOSE: Hospital-acquired pneumonia (HAP) remains an important cause of morbidity and mortality despite advances in antimicrobial therapy. The emergence of multidrug resistant (MDR) Pseudomonas aeruginosa (PA) is of major concern. Our aim was to evaluate the risk factors and prognosis of HAP due to MDR-PA infection. PATIENTS AND METHODS: In a retrospective observational study, we collected data on all episodes of HAP caused by PA (PA-HAP) occurring from January 2013 to December 2016. Characteristics of patients with drug-sensitive PA were compared with those with MDR-PA. Data of demographic, underlying conditions, peripheral neutrophil-to-lymphocyte ratio (NLR), and clinical outcomes were collected and analyzed. RESULTS: One hundred fifty-seven patients with PA-HAP were included, of which 69 (43.9%) patients were diagnosed with MDR-PA infection. There were significant differences between MDR-PA group and non-MDR-PA group on the following variables: initial inappropriate antibiotic therapy (P<0.001, OR 0.103, 95% CI 0.044-0.244), admission in more than two departments in previous 30 days (P<0.001, OR 0.186, 95% CI 0.072-0.476), and NLR level (P=0.020, OR 0.911, 95% CI 0.843-0.985). The effect of antibiotic treatment was significantly different (P<0.001, OR 4.263, 95% CI 2.142-8.483). The 30-day mortality was higher in MDR-PA group than that in non-MDR-PA group (P<0.001). CONCLUSION: We have shown that lower NLR level was identified as a clinical predictor of MDR-PA infection in HAP patients. Even with goal-directed therapy, MDR-PA infection implicates poor outcomes in patients with HPA.

Selection of glucocorticoid-sensitive patients in interstitial lung disease secondary to connective tissue diseases population by radiomics.

PURPOSE: The effect of glucocorticoid(s) on connective tissue disease (CTD)-related interstitial lung disease (ILD) is controversial. This multicenter study aimed to identify glucocorticoid-sensitive patients using a radiomics approach. METHODS: A total of 416 CTD-ILD patients who began glucocorticoid treatment at the discretion of the attending physician, with or without cyclophosphamide, were included in this study. High doses were defined as pulsed intravenous methylprednisolone, an initial dose of 1 mg/kg/day of prednisolone or 0.8 mg/kg/day of methylprednisolone. Low doses were defined as those less than high doses. Radiomics features were manually extracted from primary lung lesions delineated on computed tomography images, and selected by variance, univariate feature selection, and least absolute shrinkage and selection operator regression model. The prediction models were developed using data from 309 patients from two centers and externally validated in 107 patients from four other hospitals. RESULTS: Treatment response in the training and validation groups was 38.5% and 36.4%, respectively. Eleven radiomics features were selected from 1,029 features with predictive value. Random forest models built for radiomics features to predict treatment response yielded a sensitivity of 0.897. The calibration curve of a nomogram demonstrated good agreement between prediction and observation. Decision curve analysis indicated that glucocorticoid was beneficial if the predicted response rate was 50%-60% for an individual. High doses of glucocorticoids and cyclophosphamide yielded superior efficacy. CONCLUSION: Radiomics-based predictive models reliably identified glucocorticoid-sensitive CTD-ILD patients. Short-term, high-dose glucocorticoid with cyclophosphamide yielded promising results as a potential therapy.