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Background: The role of corticosteroids in acute respiratory distress syndrome (ARDS) remains contentious. This study aims to investigate the prognostic significance of immune deficiency in patients with ARDS and its response to varying doses of corticosteroids. Methods: This single-center, retrospective cohort study enrolled 657 ARDS patients from January 24, 2008, to September 12, 2022, at Zhongshan Hospital of Fudan University, Shanghai, China. The patients were categorized into a discovery dataset (n=357) and a validation dataset (n=300), based on admission date. Further validation of the results in the validation dataset was used to enhance the credibility of the study conclusions. The study examined the association between immune deficiency and the patients' clinical characteristics, treatment measures, and prognosis. The primary outcome was 28-day mortality post disease onset. Data analysis was conducted from June 15, 2023 to August 15, 2023. Results: The initial risk factor analysis in the discovery dataset was primarily based on the clinical characteristics, and the results suggested that immune deficiency likely impacted overall survival among patients receiving different doses of corticosteroid treatment. Multivariate analysis identified immune deficiency as an independent prognostic factor for overall survival in both the discovery and validation datasets. The final analysis revealed that patients with mild to moderate ARDS [discovery dataset: hazard ratio (HR) =1.719; 95% confidence interval (CI): 1.229-2.406; log-rank test P=0.001; validation dataset: HR =1.874; 95% CI: 1.238-2.837; log-rank test P=0.002] or severe ARDS (discovery dataset: HR =1.874; 95% CI: 1.007-3.488; log-rank test P=0.04; validation dataset: HR =1.698; 95% CI: 1.042-2.768; log-rank test P=0.03) with immune deficiency exhibited lower overall survival rates. Patients with mild to moderate ARDS and immune deficiency showed greater benefits from low-dose corticosteroid treatment (HR =0.409; 95% CI: 0.249-0.671; P<0.001 for interaction), whereas those with severe ARDS and immune deficiency benefitted from both low and high-dose treatments (low corticosteroid: HR =0.299; 95% CI: 0.136-0.654; high corticosteroid: HR =0.458; 95% CI: 0.214-0.981; P=0.005 for interaction). Conclusions: Immune deficiency is an independent risk factor in ARDS. Incorporating it into the disease severity grading system based on the Berlin criteria may enhance personalized treatment approaches for ARDS patients. These findings warrant further validation through prospective, large-scale, multicenter randomized controlled trials (RCTs).
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OBJECTIVE: Pulmonary cavity lesion is one of the commonly seen lesions in lung caused by a variety of malignant and non-malignant diseases. Diagnosis of a cavity lesion is commonly based on accurate recognition of the typical morphological characteristics. A deep learning-based model to automatically detect, segment, and quantify the region of cavity lesion on CT scans has potential in clinical diagnosis, monitoring, and treatment efficacy assessment. METHODS: A weakly-supervised deep learning-based method named CSA2-ResNet was proposed to quantitatively characterize cavity lesions in this paper. The lung parenchyma was firstly segmented using a pretrained 2D segmentation model, and then the output with or without cavity lesions was fed into the developed deep neural network containing hybrid attention modules. Next, the visualized lesion was generated from the activation region of the classification network using gradient-weighted class activation mapping, and image processing was applied for post-processing to obtain the expected segmentation results of cavity lesions. Finally, the automatic characteristic measurement of cavity lesions (e.g., area and thickness) was developed and verified. RESULTS: the proposed weakly-supervised segmentation method achieved an accuracy, precision, specificity, recall, and F1-score of 98.48%, 96.80%, 97.20%, 100%, and 98.36%, respectively. There is a significant improvement (P < 0.05) compared to other methods. Quantitative characterization of morphology also obtained good analysis effects. CONCLUSIONS: The proposed easily-trained and high-performance deep learning model provides a fast and effective way for the diagnosis and dynamic monitoring of pulmonary cavity lesions in clinic. Clinical and Translational Impact Statement: This model used artificial intelligence to achieve the detection and quantitative analysis of pulmonary cavity lesions in CT scans. The morphological features revealed in experiments can be utilized as potential indicators for diagnosis and dynamic monitoring of patients with cavity lesions.
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Aprendizaje Profundo , Pulmón , Tomografía Computarizada por Rayos X , Humanos , Tomografía Computarizada por Rayos X/métodos , Pulmón/diagnóstico por imagen , Pulmón/patología , Interpretación de Imagen Radiográfica Asistida por Computador/métodos , Enfermedades Pulmonares/diagnóstico por imagen , Enfermedades Pulmonares/patología , Neoplasias Pulmonares/diagnóstico por imagen , Neoplasias Pulmonares/patología , Redes Neurales de la Computación , Aprendizaje Automático Supervisado , AlgoritmosRESUMEN
Accurate diagnosis of chronic obstructive pulmonary disease (COPD) and exacerbations by metabolic biomarkers enables individualized treatment. Advanced metabolic detection platforms rely on designed materials. Here, we design mesoporous PdPt alloys to characterize metabolic fingerprints for diagnosing COPD and exacerbations. As a result, the optimized PdPt alloys enable the acquisition of metabolic fingerprints within seconds, requiring only 0.5 µL of native plasma by laser desorption/ionization mass spectrometry owing to the enhanced electric field, photothermal conversion, and photocurrent response. Machine learning decodes metabolic profiles acquired from 431 individuals, achieving a precise diagnosis of COPD with an area under the curve (AUC) of 0.904 and an accurate distinction between stable COPD and acute exacerbations of COPD (AECOPD) with an AUC of 0.951. Notably, eight metabolic biomarkers identified accurately discriminate AECOPD from stable COPD while providing valuable information on disease progress. Our platform will offer an advanced nanoplatform for the management of COPD, complementing standard clinical techniques.
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BACKGROUND: Little attention has been paid to the pathophysiological changes in the natural history of chronic obstructive pulmonary disease (COPD). The destructions of the small airways were visualized on thoracic micro-computed tomography scan. We investigated whether small airway inflammation (SAI) was the risk for the development of COPD. METHODS: A total of 1062 patients were enrolled and analyzed in the study. The partitioned airway inflammation was determined by exhaled nitric oxide (NO) of FnNO, FeNO50, FeNO200, and calculated CaNOdual. Both FeNO200 and CaNOdual were compared to detect the promising predictor for peripheral airway/alveolar inflammation in COPD. The correlation between exhaled NO and white cell classification was evaluated to determine the inflammation type during the development of COPD. RESULTS: Exhaled NO levels (FnNO, FeNO50, FeNO200, and CaNOdual) were the highest in the COPD group compared with all other groups. Furthermore, compared with controls, exhaled NO levels (FeNO50, FeNO200, and CaNOdual) were also significantly higher in the emphysema, chronic bronchitis, and smoking groups. FeNO200 was found to be a promising predictor for peripheral airway/alveolar inflammation (area under the curve [AUC] of the receiver operating characteristic [ROC] curve, area under the curve [AUC] = 0.841) compared with CaNOdual (AUC ROC = 0.707) in COPD. FeNO200 was the main risk factor (adjusted odds ratio, 2.191; 95% CI, 1.797-2.671; p = 0.002) for the development of COPD. The blood eosinophil and basophil levels were correlated with FeNO50 and FeNO200. CONCLUSION: The complete airway inflammations were shown in COPD, whereas SAI was the main risk factor for the development of COPD, which might relate to eosinophil and basophil levels.
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Bronquitis Crónica , Enfermedad Pulmonar Obstructiva Crónica , Enfisema Pulmonar , Humanos , Microtomografía por Rayos X , Inflamación , Óxido NítricoRESUMEN
Obesity is a principle causative factor of various metabolic dysfunctions, chronic inflammation, and multi-organ impairment. The global epidemic of obesity has constituted the greatest threat to global health. Emerging evidence has associated obesity with an increased risk of severe infection and poor outcomes from coronavirus disease 2019 (COVID-19). During current COVID-19 pandemic, the interaction between COVID-19 and obesity has exaggerated the disease burden of obesity more than ever before. Thus, there is an urgent need for consideration of universal measures to reduce the risk of complications and severe illness from severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) in obesity population. In this review, we first summarized the clinical evidence on the effect of obesity on susceptibility, severity, and prognosis of COVID-19. Then we discussed and the underlying mechanisms, including respiratory pathophysiology of obesity, dysregulated inflammation, upregulated angiotensin-converting enzyme 2 (ACE2) expression, hyperglycemia, and adipokines. Finally, we proposed recommendations on how to reduce the spread and pandemic of SARS-CoV-2 infection by prevention and treatment of obesity.
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OBJECTIVE: To compare the atomization efficacy of a novel micro-dose mesh nebulizer (CVS-100) versus the traditional mesh nebulizer (M102) in nebulizing a combination of ipratropium bromide and salbutamol for treatment of stable moderate-to-severe chronic obstructive pulmonary disease (COPD). METHODS: A randomized, parallel, non-inferiority study was conducted. A total of 64 stable COPD patients were randomly assigned to either the experimental group or the control group in a 1:1 ratio. Each the experimental group received nebulized Combivent (Compound Ipratropium Bromide Solution) with CVS-100, while the control group received Combivent with M102. Lung ventilation function was measured before and 30 min after nebulization, and the difference in percentage of forced expiratory volume in the first second (FEV1) of predicted value (FEV1%pred), the forced expiratory flow at 50% (FEF50%), the forced expiratory flow at 75% (FEF75%), the mid-expiratory flow (FEF25-75%), and maximal voluntary ventilation (MVV) was evaluated. The non-inferiority margin for the lower 95% confidence limit was set at 3.5%. RESULTS: The lower limit of the 95% confidence interval for the difference in FEV1%pred between the two groups was -1.83357, which was greater than -3.5. No significant differences were found in FEF50%, FEF75%, FEF25â¼75%, MVV before and after nebulization between the two groups. CONCLUSION: The novel micro-dose mesh nebulizer (CVS-100) was found to be non-inferior to the traditional mesh nebulizer (M102) in terms of the change in FEV1%pred from baseline after nebulization. Similar results were observed for all other measures of efficacy.
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Broncodilatadores , Enfermedad Pulmonar Obstructiva Crónica , Humanos , Adulto , Broncodilatadores/uso terapéutico , Combinación Albuterol y Ipratropio , Mallas Quirúrgicas , Nebulizadores y Vaporizadores , Albuterol/uso terapéutico , Albuterol/farmacología , Ipratropio/uso terapéutico , Ipratropio/farmacología , Volumen Espiratorio Forzado , Administración por InhalaciónRESUMEN
BACKGROUND: Evidence of the acute effects of high-level air pollution on small airway function and systemic inflammation in adults is scarce. OBJECTIVE: To examined the associations of short-term (i.e., daily) exposure to multiple air pollutants with lung function and inflammatory markers. METHODS: We assessed short-term (daily) effects of air pollutants, including particulate matter with aerodynamic diameter less than 2.5 µm (PM2.5) and 10 µm (PM10), nitrogen dioxide (NO2), sulfur dioxide (SO2) and carbon monoxide (CO), on lung function and peripheral immune cell counts over various lag times using generalized linear regression models. RESULTS: A total of 4764 adults were included from the general community-dwelling population in Shanghai, China. Exposure to air pollutants and lung function were negatively correlated. Decline in FEF between 25% and 75% of vital capacity (FEF25-75%) were found associated with PM2.5, SO2, and CO, and decline in forced expiratory volume in 3 s (FEV3) to forced vital capacity (FVC) ratio were associated with all examined pollutants, indicating obstruction in small airways. Obstructed airflow in large and middle airways as indicated by decline in FEV1/FVC were also associated with all pollutants. In subgroup analysis, significant negative associations between the five pollutants and SAD parameters were found only in males but not in females. The difference in the associations of SO2 with FEF75% between males and females achieved statistical significance. Additionally, all examined pollutants were significantly associated with lower peripheral neutrophil count. IMPACT STATEMENT: Acute exposure to air pollutants were associated with airflow-limitation. Both small airways and proximal airways were affected. Acute exposure to air pollutants were accompanied with a lower neutrophil count.
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BACKGROUND: Data that guide selection of differing anticoagulant regimens for specific cancer-associated venous thromboembolism (VTE) are lacking. We aimed to compare the efficacy and safety of rivaroxaban and low-molecular-weight heparin (LMWH) against nonhigh-risk pulmonary embolism (PE) in Chinese lung cancer patients. METHODS: Four hundred forty-six Chinese lung cancer patients with nonhigh-risk PE who initiated treatment with rivaroxaban or LMWH were identified from Zhongshan Hospital database from 2016 to 2020. The primary outcomes were the composite event of VTE recurrence or major bleeding, and all-cause mortality. The secondary outcomes were VTE recurrence, major bleeding and clinically relevant non-major bleeding (CRNMB). Propensity score matching was used to balance baseline covariates. We conducted sensitivity analysis by stabilized inverse probability of treatment weighting and competing risk analysis by a Fine and Gray subdistribution hazard model. RESULTS: In propensity score-matched cohorts, rivaroxaban was similar to LMWH in the risks of the composite outcome (hazard ratio (HR), 0.73; 95% confidence interval (CI), 0.45-1.21; P = 0.22), VTE recurrence (HR, 0.69; 95% CI, 0.36-1.34; P = 0.28), major bleeding (HR, 0.79; 95% CI, 0.37-1.68; P = 0.54) and CRNMB (HR, 1.13; 95% CI, 0.62-2.09; P = 0.69). All-cause mortality was significantly lower in rivaroxaban group than LMWH group (HR, 0.52; 95% CI, 0.36-0.75; P < 0.001). The primary and secondary outcomes favored rivaroxaban over LMWH in all the subgroups expect for central PE and intermediate-risk PE. The sensitivity analysis yielded similar results, and competing risk analysis was in accordance with the primary findings. CONCLUSIONS: Rivaroxaban might be a promising alternative to LMWH as initial treatment for nonhigh-risk PE in lung cancer patients.
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Objectives: To evaluate COVID-19 vaccines in primary prevention against infections and lessen the severity of illness following the most recent outbreak of the SARS-CoV-2 Omicron variant in Shanghai. Data sources: Data from 153,544 COVID-19 patients admitted to the Shanghai "Four-Leaf Clover" Fangcang makeshift shelter hospital were collected using a structured electronic questionnaire, which was then merged with electronic medical records of the hospital. For healthy controls, data on vaccination status and other information were obtained from 228 community-based residents, using the same structured electronic questionnaire. Methods: To investigate whether inactivated vaccines were effective in protecting against SARS-CoV-2 virus, we estimated the odds ratio (OR) of the vaccination by comparing cases and matched community-based healthy controls. To evaluate the potential benefits of vaccination in lowering the risk of symptomatic infection (vs. asymptomatic), we estimated the relative risk (RR) of symptomatic infections among diagnosed patients. We also applied multivariate stepwise logistic regression analyses to measure the risk of disease severity (symptomatic vs. asymptomatic and moderate/severe vs. mild) in the COVID-19 patient cohort with vaccination status as an independent variable while controlling for potential confounding factors. Results: Of the 153,544 COVID-19 patients included in the analysis, the mean age was 41.59 years and 90,830 were males (59.2%). Of the study cohort, 118,124 patients had been vaccinated (76.9%) and 143,225 were asymptomatic patients (93.3%). Of the 10,319 symptomatic patients, 10,031 (97.2%), 281 (2.7%), and 7 (0.1%) experienced mild, moderate, and severe infections, respectively. Hypertension (8.7%) and diabetes (3.0%) accounted for the majority of comorbidities. There is no evidence that the vaccination helped protect from infections (OR = 0.82, p = 0.613). Vaccination, however, offered a small but significant protection against symptomatic infections (RR = 0.92, p < 0.001) and halved the risk of moderate/severe infections (OR = 0.48, 95% CI: 0.37-0.61). Older age (≥60 years) and malignant tumors were significantly associated with moderate/severe infections. Conclusion: Inactivated COVID-19 vaccines helped provide small but significant protection against symptomatic infections and halved the risk of moderate/severe illness among symptomatic patients. The vaccination was not effective in blocking the SARS-CoV-2 Omicron Variant community spread.
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INTRODUCTION: Pulmonary infections are frequent in immunocompromised hosts (ICH), and microbial detection is difficult. As a new method, next-generation sequencing (NGS) may offer a solution. OBJECTIVES: This study aimed to assess the impact of NGS-assisted pathogenic detection on the diagnosis, treatment, and outcomes of ICH complicated by pulmonary infection and radiographic evidence of bilateral diffuse lesions. METHODS: This study enrolled 356 patients with ICH complicated by pulmonary infection that were admitted to Zhongshan Hospital, Fudan University, from November 17, 2017, to November 23, 2018, including 102 and 254 in the NGS and non-NGS groups, respectively. Clinical characteristics, detection time, rough positive rate, effective positive rate, impact on anti-infective treatment plan, 30-day/60-day mortality, and in-hospital mortality were compared. RESULTS: NGS-assisted pathogenic detection reduced detection time (28.2 h [interquartile range (IQR) 25.9-29.83 h] vs. 50.50 h [IQR 47.90-90.91 h], P < 0.001), increased positive rate, rate of mixed infection detected, effective positive rate, and proportion of antibiotic treatment modification (45.28% vs. 89.22%, 4.72% vs. 51.96%, 21.65% vs. 64.71%, 16.54% vs. 46.08%, P < 0.001). The NGS group had a significantly lower 60-day mortality rate (18.63% vs. 33.07%, P = 0.007). The difference in the Kaplan-Meier survival curve was significant (P = 0.029). After multivariate logistic regression, NGS-assisted pathogenic detection remained a significant predictor of survival (OR 0.189, confidence interval [CI], 0.068-0.526). CONCLUSION: NGS-assisted pathogenic detection may improve detection efficiency and is associated with better clinical outcomes in these patients.
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Secuenciación de Nucleótidos de Alto Rendimiento , Huésped Inmunocomprometido , Humanos , Estudios RetrospectivosRESUMEN
Coronavirus disease 2019 (COVID-19), the highly contagious viral disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has spread worldwide with millions of cases and more than 5 million deaths to date. SARS-CoV-2 has caused serious damage all over the world with many countries experiencing the third or the fourth wave of the viral disease outbreaks, mainly due to the emergence of mutant variants. Those who unvaccinated remain most vulnerable to COVID-19 and its variants. COVID-19 vaccination, along with prevention strategies, is a critical measure to defense against the disease. COVID-19 vaccination can reduce the spread of virus and help protect susceptible population. Although herd immunity might not be realized solely by vaccination, COVID-19 vaccines have been proved to be effective in reducing the risk of severe disease, hospitalization, and even death. It is recommended that people get vaccinated as soon as they are eligible. This review summarizes the recent SARS-CoV-2 variants that brought challenges for vaccination and herd immunity and discusses promising management strategies.
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COVID-19 , SARS-CoV-2 , Humanos , COVID-19/prevención & control , Inmunidad Colectiva , Vacunas contra la COVID-19 , VacunaciónRESUMEN
BACKGROUND: Active targeted case-finding is a cost-effective way to identify individuals with high-risk for early diagnosis and interventions of chronic obstructive pulmonary disease (COPD). A precise and practical COPD screening instrument is needed in health care settings. METHODS: We created four statistical learning models to predict the risk of COPD using a multi-center randomized cross-sectional survey database (n = 5281). The minimal set of predictors and the best statistical learning model in identifying individuals with airway obstruction were selected to construct a new case-finding questionnaire. We validated its performance in a prospective cohort (n = 958) and compared it with three previously reported case-finding instruments. RESULTS: A set of seven predictors was selected from 643 variables, including age, morning productive cough, wheeze, years of smoking cessation, gender, job, and pack-year of smoking. In four statistical learning models, generalized additive model model had the highest area under curve (AUC) value both on the developing cross-sectional data set (AUC = 0.813) and the prospective validation data set (AUC = 0.880). Our questionnaire outperforms the other three tools on the cross-sectional validation data set. CONCLUSIONS: We developed a COPD case-finding questionnaire, which is an efficient and cost-effective tool for identifying high-risk population of COPD.
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Enfermedad Pulmonar Obstructiva Crónica , Estudios Transversales , Humanos , Tamizaje Masivo , Enfermedad Pulmonar Obstructiva Crónica/diagnóstico , Enfermedad Pulmonar Obstructiva Crónica/epidemiología , Fumar/epidemiología , Espirometría , Encuestas y CuestionariosRESUMEN
Accurate segmentation of lesions in medical images is of great significance for clinical diagnosis and evaluation. The low contrast between lesions and surrounding tissues increases the difficulty of automatic segmentation, while the efficiency of manual segmentation is low. In order to increase the generalization performance of segmentation model, we proposed a deep learning-based automatic segmentation model called CM-SegNet for segmenting medical images of different modalities. It was designed according to the multiscale input and encoding-decoding thoughts, and composed of multilayer perceptron and convolution modules. This model achieved communication of different channels and different spatial locations of each patch, and considers the edge related feature information between adjacent patches. Thus, it could fully extract global and local image information for the segmentation task. Meanwhile, this model met the effective segmentation of different structural lesion regions in different slices of three-dimensional medical images. In this experiment, the proposed CM-SegNet was trained, validated, and tested using six medical image datasets of different modalities and 5-fold cross validation method. The results showed that the CM-SegNet model had better segmentation performance and shorter training time for different medical images than the previous methods, suggesting it is faster and more accurate in automatic segmentation and has great potential application in clinic.
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Aprendizaje Profundo , Procesamiento de Imagen Asistido por Computador , Procesamiento de Imagen Asistido por Computador/métodos , Imagenología Tridimensional , Redes Neurales de la ComputaciónRESUMEN
BACKGROUND: Mesenchymal stem cells (MSCs) have been shown to improve acute lung injury (ALI) and acute respiratory distress syndrome (ARDS). However, the optimal source of MSCs for cell-based therapy remains unknown. To determine which kind of MSCs are more effective, we compared the effects of rat lung resident MSC (LRMSC), human chorion-derived MSC (HMSC-C) and human bone marrow derived MSC (HMSC-BM) in LPS-induced ALI in mice. METHODS: LPS (Pseudomonas aeruginosa) was used to induce ALI model. All three kinds of MSCs were administered via tail vein 4 h after LPS instillation. The mice were sacrificed 48 h after LPS instillation. H&E staining of lung section, wet-to-dry weight ratio of lung tissue, ratio of regulatory T cells (Tregs) and Th17 cells, and total protein concentration, leukocytes counting and cytokines in bronchoalveolar lavage fluid (BALF) were evaluated. RESULTS: The data showed that compared with LRMSC and HMSC-BM, HMSC-C more significantly attenuated lung injury, upregulated the Tregs/Th17 cells ratio, and inhibited release of inflammatory cytokines (IL-1ß, IL-6 and TNF-α) and recruitment of neutrophils and macrophages into alveolus. CONCLUSIONS: Although all three kinds of LRMSC, HMSC-C and HMSC-BM are protective against LPS-induced lung injury, HMSC-C was more effective than LRMSC and HMSC-BM to treat LPS-induced lung injury.
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Lesión Pulmonar Aguda , Células Madre Mesenquimatosas , Lesión Pulmonar Aguda/inducido químicamente , Lesión Pulmonar Aguda/metabolismo , Lesión Pulmonar Aguda/terapia , Animales , Médula Ósea/metabolismo , Corion/metabolismo , Citocinas/metabolismo , Lipopolisacáridos/metabolismo , Lipopolisacáridos/toxicidad , Pulmón/metabolismo , Células Madre Mesenquimatosas/metabolismo , RatonesRESUMEN
BACKGROUND: The impact of corticosteroid therapy on outcomes of patients with coronavirus disease 2019 (COVID-19) is highly controversial. We aimed to compare the risk of death between COVID-19-related ARDS patients with corticosteroid treatment and those without. METHODS: In this single-center retrospective observational study, patients with ARDS caused by COVID-19 between January 20, 2020, and February 24, 2020, were enrolled. The primary outcome was 60-day in-hospital death. The exposure was prescribed systemic corticosteroids or not. Time-dependent Cox regression models were used to calculate hazard ratios (HRs) and 95% confidence intervals (CIs) for 60-day in-hospital mortality. RESULTS: A total of 382 patients [60.7 ± 14.1 years old (mean ± SD), 61.3% males] were analyzed. The median of sequential organ failure assessment (SOFA) score was 2.0 (IQR 2.0-3.0). Of these cases, 94 (24.6%) patients had invasive mechanical ventilation. The number of patients received systemic corticosteroids was 226 (59.2%), and 156 (40.8%) received standard treatment. The maximum dose of corticosteroids was 80.0 (IQR 40.0-80.0) mg equivalent methylprednisolone per day, and duration of corticosteroid treatment was 7.0 (4.0-12.0) days in total. In Cox regression analysis using corticosteroid treatment as a time-varying variable, corticosteroid treatment was associated with a significant reduction in risk of in-hospital death within 60 days after adjusting for age, sex, SOFA score at hospital admission, propensity score of corticosteroid treatment, comorbidities, antiviral treatment, and respiratory supports (HR 0.42; 95% CI 0.21, 0.85; p = 0.0160). Corticosteroids were not associated with delayed viral RNA clearance in our cohort. CONCLUSION: In this clinical practice setting, low-dose corticosteroid treatment was associated with reduced risk of in-hospital death within 60 days in COVID-19 patients who developed ARDS.
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Corticoesteroides/administración & dosificación , Betacoronavirus , Infecciones por Coronavirus/tratamiento farmacológico , Infecciones por Coronavirus/mortalidad , Neumonía Viral/tratamiento farmacológico , Neumonía Viral/mortalidad , Puntaje de Propensión , Síndrome de Dificultad Respiratoria/tratamiento farmacológico , Síndrome de Dificultad Respiratoria/mortalidad , Anciano , COVID-19 , Estudios de Cohortes , Dexametasona/administración & dosificación , Femenino , Hospitalización/tendencias , Humanos , Masculino , Metilprednisolona/administración & dosificación , Persona de Mediana Edad , Pandemias , Estudios Retrospectivos , SARS-CoV-2 , Tasa de Supervivencia/tendenciasRESUMEN
INTRODUCTION: To investigate the risk factors for the death in patients with COVID-19 with type 2 diabetes mellitus (T2DM). RESEARCH DESIGN AND METHODS: We retrospectively enrolled inpatients with COVID-19 from Wuhan Jinyintan Hospital (Wuhan, China) between December 25, 2019, and March 3, 2020. The epidemiological and clinical data were compared between non-T2DM and T2DM or between survivors and non-survivors. Univariable and multivariable Cox regression analyses were used to explore the effect of T2DM and complications on in-hospital death. RESULTS: A total of 1105 inpatients with COVID-19, 967 subjects with without T2DM (n=522 male, 54.0%) and 138 subjects with pre-existing T2DM (n=82 male, 59.4%) were included for baseline characteristics analyses. The complications were also markedly increased in patients with pre-existing T2DM, including acute respiratory distress syndrome (ARDS) (48.6% vs 32.3%, p<0.001), acute cardiac injury (ACI) (36.2% vs 16.7%, p<0.001), acute kidney injury (AKI) (24.8% vs 9.5%, p<0.001), coagulopathy (24.8% vs 11.1%, p<0.001), and hypoproteinemia (21.2% vs 9.4%, p<0.001). The in-hospital mortality was significantly higher in patients with pre-existing T2DM compared with those without T2DM (35.3% vs 17.4%, p<0.001). Moreover, in hospitalized patients with COVID-19 with T2DM, ARDS and coagulopathy were the main causes of mortality, with an HR of 7.96 (95% CI 2.25 to 28.24, p=0.001) for ARDS and an HR of 2.37 (95% CI 1.08 to 5.21, p=0.032) for coagulopathy. This was different from inpatients with COVID-19 without T2DM, in whom ARDS and cardiac injury were the main causes of mortality, with an HR of 12.18 (95% CI 5.74 to 25.89, p<0.001) for ARDS and an HR of 4.42 (95% CI 2.73 to 7.15, p<0.001) for cardiac injury. CONCLUSIONS: Coagulopathy was a major extrapulmonary risk factor for death in inpatients with COVID-19 with T2DM rather than ACI and AKI, which were well associated with mortality in inpatients with COVID-19 without T2DM.
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COVID-19/complicaciones , COVID-19/epidemiología , Diabetes Mellitus Tipo 2/complicaciones , Coagulación Intravascular Diseminada/etiología , Coagulación Intravascular Diseminada/mortalidad , Mortalidad Hospitalaria , SARS-CoV-2/genética , Lesión Renal Aguda/complicaciones , Lesión Renal Aguda/mortalidad , Adulto , Anciano , COVID-19/virología , China/epidemiología , Femenino , Estudios de Seguimiento , Lesiones Cardíacas/complicaciones , Lesiones Cardíacas/mortalidad , Hospitalización , Humanos , Masculino , Persona de Mediana Edad , Síndrome de Dificultad Respiratoria/complicaciones , Estudios Retrospectivos , Factores de RiesgoRESUMEN
Etiological diagnosis is essential for anti-infective therapy in patients with ventilator-associated pneumonia (VAP). The present study aimed to evaluate the capacity of sequential PCR coupled to electrospray ionization mass spectrometry (PCR/ESI-MS) tests as a rapid diagnostic technique for patients with VAP. A total of 12 patients diagnosed with VAP were enrolled at the intensive care unit in Zhongshan Hospital, Fudan University. Mini-bronchoalveolar lavage fluid specimens were prospectively collected on VAP 0, 5 and 10 days following the beginning of mechanical ventilation. Routine clinical culture and PCR/ESI-MS were compared for identification of microorganisms in the specimens. A total of 51 bacterial species were detected by either of the two methods. The positive rates of routine clinical culture and PCR/ESI-MS were 38.2 and 88.2%, respectively. Out of the 16 specimens positive in routine cultures, 15 were also positive on PCR/ESI-MS, except for one, from which a mix of three distinct bacterial isolates were reported by culture. Among the 50 bacterial species identified by PCR/ESI-MS, 15 (35.7%) of the common VAP pathogens were confirmed by paired culture. Furthermore, of the 16 bacterial isolates that were finally confirmed to be responsible for VAP, 14 were identified by a sequential PCR/ESI-MS test concurrently when the culture results were obtained. PCR/ESI-MS identified pathogens that may cause VAP in 8 subjects prior to the occurrence of associated clinical manifestations. To conclude, PCR/ESI-MS was a potential rapid technique for diagnosis of VAP within 6 h. Regular respiratory specimen monitoring using PCR/ESI-MS provides information for selecting appropriate and adequate antibiotic therapies in ventilated patients.
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BACKGROUND: Few studies have evaluated the effects of ambient air pollution exposure on lung function, especially in areas with high air pollution levels. OBJECTIVES: To investigate the associations of annual concentrations of particulate matter with diameters < 2.5 µm (PM2.5) and nitrogen dioxide (NO2) with adult lung function in Shanghai, China. METHODS: We included 5276 permanent residents aged ≥ 20 years. Annual residential exposure to PM2.5 and NO2 was estimated by validated satellite-based and land use regression models, respectively. The effects of PM2.5 and NO2 on lung function were estimated separately using multivariable linear regression, adjusting for potential confounders. RESULTS: Higher exposure to PM2.5 and NO2 was significantly associated with lower forced vital capacity (FVC), inspiration capacity (IC), and vital capacity (VC). An increase of 10 µg/m3 in the annual average PM2.5 exposure was associated with a 45.83 ml (95% CI: -82.59, -9.07) lower FVC, 1.36 (95% CI: -2.42, -0.29) lower FVC of % predicted (FVC%pred), 121.98 ml (95% CI: -164.38, -79.57) lower IC, and 89.12 ml (95% CI -124.94, -53.3) lower VC. For NO2, an increase of 10 µg/m3 in the annual average concentration was associated with 26.65 ml (95% CI: -46.29, -7.00) lower FVC, 0.70 (95% CI: -1.27, 0.13) lower FVC%pred, 65.26 ml (95% CI: -87.76, -42.76) lower IC, and 45.88 ml (95% CI: -65.03, -26.73) lower VC. The estimated effects on FEV1 were -10.25 ml (95% CI: -40.92, 20.42) and -0.29% (95% CI: -1.40, 0.82) per 10 µg/m3 increase in PM2.5 and -0.74 ml (95% CI: -17.13, 15.65) and 0.01% (95% CI: -0.58, 0.61) per 10 µg/m3 increase in NO2, which were not statistically significant. Stratified analysis showed that the estimated effects of PM2.5 were greater in the healthy subgroup than the COPD patients. Obese individuals were more susceptible to adverse effects of PM2.5 and NO2 on lung function. Education level showed no or only weak evidence of modification of the associations between air pollution and lung function. CONCLUSION: In this study, long-term exposure to ambient air pollutants was significantly associated with impaired lung function, presenting as restrictive ventilatory patterns.
Asunto(s)
Contaminantes Atmosféricos , Contaminación del Aire , Adulto , Contaminantes Atmosféricos/análisis , Contaminantes Atmosféricos/toxicidad , Contaminación del Aire/efectos adversos , Contaminación del Aire/análisis , China , Estudios Transversales , Exposición a Riesgos Ambientales/análisis , Humanos , Pulmón/química , Dióxido de Nitrógeno/toxicidad , Material Particulado/análisis , Material Particulado/toxicidadRESUMEN
OBJECTIVE: In the era of fast track surgery, early and accurately estimating whether postoperative length of stay (p-LOS) will be prolonged after lung cancer surgery is very important, both for patient's discharge planning and hospital bed management. Pulmonary function tests (PFTs) are very valuable routine examinations which should not be underutilized before lung cancer surgery. Thus, this study aimed to establish an accurate but simple prediction tool, based on PFTs, for achieving a personalized prediction of prolonged p-LOS in patients following lung resection. METHODS: The medical information of 1257 patients undergoing lung cancer surgery were retrospectively reviewed and served as the training set. p-LOS exceeding the third quartile value was considered prolonged. Using logistic regression analyses, potential predictors of prolonged p-LOS were identified among various preoperative factors containing PFTs and intraoperative factors. A nomogram was constructed and subjected to internal and external validation. RESULTS: Five independent risk factors for prolonged p-LOS were identified, including older age, being male, and ratio of residual volume to total lung capacity (RV/TLC) ≥ 45.0% which is the only modifiable risk factor, more invasive surgical approach, and surgical type. The nomogram comprised of these five predictors exhibited sufficient predictive accuracy, with the area under the receiver operating characteristic curve (AUC) of 0.76 [95% confidence interval (CI) 0.73-0.79] in the internal validation. Also its predictive performance remained fine in the external validation, with the AUC of 0.70 (95% CI 0.60-0.79). The calibration curves showed satisfactory agreements between the model predicted probability and the actually observed probability. CONCLUSIONS: Preoperative amelioration of RV/TLC may prevent lung cancer patients from unnecessary prolonged p-LOS. The integrated nomogram we developed could provide personalized risk prediction of prolonged p-LOS. This prediction tool may help patients perceive expected hospital stays and enable clinicians to achieve better bed management after lung cancer surgery.