Community-acquired pneumonia (CAP) is the third leading cause of death worldwide and one of the most commonly infectious diseases. Its epidemiological characteristics vary with host and immune status, and corresponding pathogen spectrums migrate over time and space distribution. Meanwhile, with the outbreak of COVID-19, some unconventional treatment strategies are on the rise. This article reviewed the epidemiological characteristics, pathogen spectrum and treatment direction of CAP in China over the years, and aimed to provide guidance for the diagnosis and treatment of CAP in clinical practice.
Humans ; COVID-19 ; Pneumonia/diagnosis* ; Community-Acquired Infections/drug therapy* ; Causality ; Risk Factors

Humans ; Pneumonia, Mycoplasma/diagnosis*

Objective: Based on the diagnostic model established and validated by the machine learning algorithm, to investigate the value of seven tumor-associated autoantibodies (TAABs), namely anti-p53, PGP9.5, SOX2, GAGE7, GBU4-5, MAGEA1 and CAGE antibodies in the diagnosis of non-small cell lung cancer (NSCLC) and to differentiate between NSCLC and benign lung nodules. Methods: This was a retrospective study of clinical cases. Model building queue: a total of 227 primary patients who underwent radical lung cancer surgery in the Department of Thoracic Surgery, Shengjing Hospital of China Medical University, from November 2018 to June 2021 were collected as the NSCLC group, and 120 cases of benign lung nodules, 122 cases of pneumonia and 120 healthy individuals were selected as the control groups. External validation queue: a total of 100 primary patients who underwent radical lung cancer surgery in the Department of Thoracic Surgery, Shengjing Hospital of China Medical University, from May 2022 to December 2022 were collected as the NSCLC group, and 36 cases of benign lung nodules, 32 cases of pneumonia and 44 healthy individuals were selected as the control groups. In addition, NSCLC was divided into early (stage 0-ⅠB) and mid-to-late (stage ⅡA-ⅢB) subgroups. The levels of 7-TAABs were detected by enzyme immunoassay, and serum concentrations of CEA and CYFRA21-1 were detected by electrochemiluminescence. Four machine learning algorithms, XGBoost, Lasso logistic regression, Naïve Bayes, and Support Vector Machine are used to establish classification models. And the best performance model was chosen based on evaluation metrics and a multi-indicator combination model was established. In addition, an online risk evaluation tool was generated to assist clinical applications. Results: Except for p53, the levels of rest six TAABs, CEA and CYFRA21-1 were significantly higher in the NSCLC group (P<0.05). Serum levels of anti-SOX2 [1.50 (0.60, 10.85) U/ml vs. 0.8 (0.20, 2.10) U/ml, Z=2.630, P<0.05] and MAGEA1 antibodies [0.20 (0.10, 0.43) U/ml vs. 0.10 (0.10, 0.20) U/ml, Z=2.289, P<0.05], CEA [3.13 (2.12, 5.64) ng/ml vs. 2.11 (1.25, 3.09) ng/ml, Z=3.970, P<0.05] and CYFRA21-1 [4.31(2.37, 7.14) ng/ml vs. 2.53(1.92, 3.48) ng/ml, Z=3.959, P<0.05] were significantly higher in patients with mid-to late-stage NSCLC than in early stages. XGBoost model was used to establish a multi-indicator combined detection model (after removing p53). 6-TAABs combined with CYFRA21-1 was the best combination model for the diagnosis of NSCLC and early NSCLC. The optimal diagnostic thresholds were 0.410, 0.701 and 0.744, and the AUC was 0.828, 0.757 and 0.741, respectively (NSCLC vs. control, NSCLC vs. benign lung nodules, early NSCLC vs. benign lung nodules) in model building queue, and the AUC was 0.760, 0.710 and 0.660, respectively (NSCLC vs. control, NSCLC vs. benign lung nodules, early NSCLC vs. benign lung nodules) in external validation queue. Conclusion: In the diagnosis of NSCLC, 6-TAABs is superior to that of traditional tumor markers CEA and CYFRA21-1, and can compensate for the shortcomings of traditional tumor markers. For the differential diagnosis of NSCLC and benign lung nodule, "6-TAABs+CYFRA21-1" is the most cost-effective combination, and plays an important role in prevention and screening for early lung cancer.
Humans ; Carcinoma, Non-Small-Cell Lung/surgery* ; Lung Neoplasms/diagnosis* ; Retrospective Studies ; Autoantibodies ; Bayes Theorem ; Tumor Suppressor Protein p53 ; Carcinoembryonic Antigen ; Antigens, Neoplasm ; Biomarkers, Tumor ; Algorithms ; Pneumonia

Cryptogenic organic pneumonia (COP) refers to organic pneumonia that has not been identified a clear cause by current medical methods. A small proportion of COP can exhibit severe and progressive characteristics, while severe COP can cause systemic inflammatory storms and can be secondary to hemophilia. This article reported a case of acute severe COP secondary to hemophilia. A 67-year-old male patient was admitted to the hospital due to cough, shortness of breath, and fever. At first, he was misdiagnosed as severe pneumonia, but failed to receive anti infection treatments. Sputum pathogenetic examination and Macrogene testing of alveolar lavage fluid were performed, and no etiology was found to explain the patient's condition. The condition was gradually worsened and hemophilia occurred to explain, suggesting that acute severe COP was relevant. After receiving hormone treatment, the condition gradually relieved and the absorption of lung lesions improved. Hemophilia secondary to COP is rare, and the specific mechanism needs further study.
Male ; Humans ; Aged ; Hemophilia A/complications* ; Pneumonia/diagnosis* ; Bronchoalveolar Lavage Fluid ; Cough ; Dyspnea/etiology*

OBJECTIVES: To investigate the risk factors for performing bronchoalveolar lavage (BAL) in children with Mycoplasma pneumoniae pneumonia (MPP) and pulmonary consolidation, and to construct a predictive model for performing BAL in these children. METHODS: A retrospective analysis was performed for the clinical data of 202 children with MPP who were hospitalized in the Department of Pediatrics, Changzhou No. 2 People's Hospital Affiliated to Nanjing Medical University, from August 2019 to September 2022. According to whether BAL was performed, they were divided into BAL group with 100 children and non-BAL group with 102 children. A multivariate logistic regression analysis was used to identify the risk factors for performing BAL in MPP children with pulmonary consolidation. Rstudio software (R4.2.3) was used to establish a predictive model for performing BAL, and the receiver operator characteristic (ROC) curve, C-index, and calibration curve were used to assess the predictive performance of the model. RESULTS: The multivariate logistic regression analysis demonstrated that the fever duration, C-reactive protein levels, D-dimer levels, and presence of pleural effusion were risk factors for performing BAL in MPP children with pulmonary consolidation (P<0.05). A nomogram predictive model was established based on the results of the multivariate logistic regression analysis. In the training set, this model had an area under the ROC curve of 0.915 (95%CI: 0.827-0.938), with a sensitivity of 0.826 and a specificity of 0.875, while in the validation set, it had an area under the ROC curve of 0.983 (95%CI: 0.912-0.996), with a sensitivity of 0.879 and a specificity of 1.000. The Bootstrap-corrected C-index was 0.952 (95%CI: 0.901-0.986), and the calibration curve demonstrated good consistency between the predicted probability of the model and the actual probability of occurrence. CONCLUSIONS The predictive model established in this study can be used to assess the likelihood of performing BAL in MPP children with pulmonary consolidation, based on factors such as fever duration, C-reactive protein levels, D-dimer levels, and the presence of pleural effusion. Additionally, the model demonstrates good predictive performance.
Child ; Humans ; Mycoplasma pneumoniae ; Retrospective Studies ; C-Reactive Protein/analysis* ; Pneumonia, Mycoplasma/diagnosis* ; Bronchoalveolar Lavage ; Pleural Effusion

Objective: Based on the diagnostic model established and validated by the machine learning algorithm, to investigate the value of seven tumor-associated autoantibodies (TAABs), namely anti-p53, PGP9.5, SOX2, GAGE7, GBU4-5, MAGEA1 and CAGE antibodies in the diagnosis of non-small cell lung cancer (NSCLC) and to differentiate between NSCLC and benign lung nodules. Methods: This was a retrospective study of clinical cases. Model building queue: a total of 227 primary patients who underwent radical lung cancer surgery in the Department of Thoracic Surgery, Shengjing Hospital of China Medical University, from November 2018 to June 2021 were collected as the NSCLC group, and 120 cases of benign lung nodules, 122 cases of pneumonia and 120 healthy individuals were selected as the control groups. External validation queue: a total of 100 primary patients who underwent radical lung cancer surgery in the Department of Thoracic Surgery, Shengjing Hospital of China Medical University, from May 2022 to December 2022 were collected as the NSCLC group, and 36 cases of benign lung nodules, 32 cases of pneumonia and 44 healthy individuals were selected as the control groups. In addition, NSCLC was divided into early (stage 0-ⅠB) and mid-to-late (stage ⅡA-ⅢB) subgroups. The levels of 7-TAABs were detected by enzyme immunoassay, and serum concentrations of CEA and CYFRA21-1 were detected by electrochemiluminescence. Four machine learning algorithms, XGBoost, Lasso logistic regression, Naïve Bayes, and Support Vector Machine are used to establish classification models. And the best performance model was chosen based on evaluation metrics and a multi-indicator combination model was established. In addition, an online risk evaluation tool was generated to assist clinical applications. Results: Except for p53, the levels of rest six TAABs, CEA and CYFRA21-1 were significantly higher in the NSCLC group (P<0.05). Serum levels of anti-SOX2 [1.50 (0.60, 10.85) U/ml vs. 0.8 (0.20, 2.10) U/ml, Z=2.630, P<0.05] and MAGEA1 antibodies [0.20 (0.10, 0.43) U/ml vs. 0.10 (0.10, 0.20) U/ml, Z=2.289, P<0.05], CEA [3.13 (2.12, 5.64) ng/ml vs. 2.11 (1.25, 3.09) ng/ml, Z=3.970, P<0.05] and CYFRA21-1 [4.31(2.37, 7.14) ng/ml vs. 2.53(1.92, 3.48) ng/ml, Z=3.959, P<0.05] were significantly higher in patients with mid-to late-stage NSCLC than in early stages. XGBoost model was used to establish a multi-indicator combined detection model (after removing p53). 6-TAABs combined with CYFRA21-1 was the best combination model for the diagnosis of NSCLC and early NSCLC. The optimal diagnostic thresholds were 0.410, 0.701 and 0.744, and the AUC was 0.828, 0.757 and 0.741, respectively (NSCLC vs. control, NSCLC vs. benign lung nodules, early NSCLC vs. benign lung nodules) in model building queue, and the AUC was 0.760, 0.710 and 0.660, respectively (NSCLC vs. control, NSCLC vs. benign lung nodules, early NSCLC vs. benign lung nodules) in external validation queue. Conclusion: In the diagnosis of NSCLC, 6-TAABs is superior to that of traditional tumor markers CEA and CYFRA21-1, and can compensate for the shortcomings of traditional tumor markers. For the differential diagnosis of NSCLC and benign lung nodule, "6-TAABs+CYFRA21-1" is the most cost-effective combination, and plays an important role in prevention and screening for early lung cancer.
Humans ; Carcinoma, Non-Small-Cell Lung/surgery* ; Lung Neoplasms/diagnosis* ; Retrospective Studies ; Autoantibodies ; Bayes Theorem ; Tumor Suppressor Protein p53 ; Carcinoembryonic Antigen ; Antigens, Neoplasm ; Biomarkers, Tumor ; Algorithms ; Pneumonia

OBJECTIVE: To clarify the clinical characteristics of influenza pneumonia in the elderly patients and the relationship between D-dimer and the severity of influenza pneumonia. METHODS: In the study, 52 hospitalized patients older than 65 years with confirmed influenza pneumonia diagnosed in Peking University People's Hospital on 5 consecutive influenza seasons from 2014 were retrospectively analyzed. General information, clinical symptoms, laboratory data, treatment methods and prognosis of the patients were collected. The relationship between D-dimer and pneumonia severity was analyzed, and receiver operating characteristic (ROC) curve was used to evaluate the predictive value of D-dimer. RESULTS: Among the 52 patients, 31 were male (31/52, 59.6%), the average age was (77.1±7.4) years, and 19 of them (36.5%) were diagnosed with severe pneumonia. About 70% patients presenting with fever. In the severe group, the patients were more likely to complain of dyspnea than in the non-severe group (14/19, 73.7% vs. 10/33, 30.3%, P=0.004), severe pneumonia group had higher level of CURB-65 (confusion, urea, respiratory rate, blood pressure, and age>65), pneumonia severity index (PSI), C-reactive protein, urea nitrogen, lactate dehydrogenase, fasting glucose, and D-dimer (P value was 0.004, < 0.001, < 0.001, 0.003, 0.038, 0.018, and < 0.001, respectively), albumin was lower than that in the non-severe group [(35.8±5.6) g/L vs. (38.9±3.5) g/L, t=-2.348, P=0.018]. There was a significant positive correlation between the D-dimer at the first admission and PSI score (r=0.540, 95%CI: 0.302 to 0.714, P < 0.001), while a significant negative correlation with PaO₂/FiO₂ (r=-0.559, 95%CI: -0.726 to -0.330, P < 0.001). Area under the curve of D-dimer was 0.765 (95%CI: 0.627 to 0.872). Area under the curve of PSI was 0.843 (95%CI: 0.716 to 0.929). There was no statistically significant difference in test efficacy between the two (Z=2.360, P=0.174). D-dimer level over 1 225 μg/L had a positive predict value for influenza pneumonia in hospital death with a sensitivity of 76.92% and a specificity of 74.36%. CONCLUSION Influenza pneumonia in the elderly always has atypical symptoms, dyspnea is a prominent feature in severe cases, D-dimer level is associated with the severity of influenza pneumonia, and greater than 1 200 μg/L has a good predictive value for in-hospital death in the elderly.
Aged ; Aged, 80 and over ; Fibrin Fibrinogen Degradation Products ; Hospital Mortality ; Humans ; Influenza, Human/diagnosis* ; Male ; Pneumonia/diagnosis* ; Prognosis ; ROC Curve ; Retrospective Studies ; Severity of Illness Index

OBJECTIVE: To investigate the clinical characteristics and risk factor analysis of necrotizing pneumonia in children. METHODS: A retrospective study was used to analyze the case data of 218 children with severe pneumonia hospitalized in the Department of Respiratory Medicine, Children's Hospital of Capital Institute of Pediatrics from January 2016 to January 2020, and they were divided into 96 cases in the necrotizing pneumonia group (NP group) and 122 cases in the non-necrotizing pneumonia group (NNP group) according to whether necrosis of the lung occurred. The differences in clinical characteristics (malnutrition, fever duration, hospitalization time, imaging performance, treatment and regression follow-up), laboratory tests [leukocytes, neutrophil ratio, platelet (PLT), C-reactive protein (CRP), procalcitonin (PCT), D-dimer, and lactate dehydrogenase (LDH)] and bronchoscopic performance between the two groups were compared, and Logistic regression analysis of clinical risk factors associated with necrotizing pneumonia was performed to further determine the maximum diagnostic value of each index by subject operating characteristic curve (ROC). The critical value of each index was further determined by the ROC. RESULTS: The differences in age, gender, pathogenic classification, and bronchoscopic presentation between the two groups of children were not statistically significant (P>0.05); whereas the imaging uptake time of the children in the NP group was higher than that in the NNP group (P < 0.05). The differences in malnutrition, fever duration, length of stay, white blood cell count, neutrophil ratio, CRP, PCT, and D-dimer were statistically significant between the two groups (P < 0.05). The imaging uptake time was lower in children under 6 years of age than in those over 6 years of age, and the imaging uptake time for bronchoalveolar lavage within 10 d of disease duration was lower than that for those over 10 d; the imaging uptake time was significantly longer in the mixed infection group than that in the single pathogen infection group. Logistic regression analysis of the two groups revealed that the duration of fever, hospital stay, CRP, PCT, and D-dimer were risk factors for secondary pulmonary necrosis (P < 0.001, P < 0.001, P < 0.001, P=0.013, P=0.001, respectively). The ROC curves for fever duration, CRP, PCT, and D-dimer were plotted and found to have diagnostic value for predicting the occurrence of pulmonary necrosis when fever duration >11.5 d, CRP >48.35 mg/L, and D-dimer > 4.25 mg/L [area under ROC curve (AUC)=0.909, 0.836, and 0.747, all P < 0.001]. CONCLUSION Children with necrotizing pneumonia have a longer heat course and hospital stay, and the imaging uptake time of mixed pathogenic infections is significantly longer than that of single pathogenic infections. Children with necrotizing pneumonia under 6 years of age have more advantageous efficacy of electronic bronchoscopic alveolar lavage within 10 d of disease duration compared with children in the group over 6 years of age and children in the group with disease duration >10 d. Inflammatory indexes CRP, PCT, and D-dimer are significantly higher. The heat course, CRP, PCT, and D-dimer are risk factors for secondary lung necrosis in severe pneumonia. Heat course >11.5 d, CRP >48.35 mg/L, and D-dimer >4.25 mg/L have high predictive value for the diagnosis of necrotizing pneumonia.
C-Reactive Protein/analysis* ; Child ; Child, Preschool ; Humans ; Malnutrition ; Necrosis ; Pneumonia/diagnosis* ; Pneumonia, Necrotizing ; Prognosis ; ROC Curve ; Retrospective Studies ; Risk Factors

In recent years, with the widespread use of immunodepressant agents, Pneumocystis jirovecii pneumonia (PJP) has been significantly found in non-human immunodeficiency virus (HIV) patients, such as those with malignancies, post-transplantation and autoimmune diseases. Although the risk factors and management of PJP have been extensively studied in the hematologic tumor and post-transplant populations, the research on real tumor cases is insufficient. Lung cancer has been the most common tumor with the highest number of incidence and death worldwide, and the prognosis of lung cancer patients infected with PJP is poor in clinical practice. By reviewing the previous studies, this paper summarized the epidemiology and clinical manifestations of PJP in lung cancer patients, the risk factors and possible mechanisms of PJP infection in lung cancer patients, diagnosis and prevention, and other research progresses to provide reference for clinical application.
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Humans ; Incidence ; Lung Neoplasms/complications* ; Pneumocystis carinii ; Pneumonia, Pneumocystis/diagnosis* ; Risk Factors

It was generally believed that psittacosis pneumonia (pneumonia caused by Chlamydia psittaci) was rarely combined with pleural effusion and the characteristics of pleural effusion were rarely reported in the domestic literature.Herein,we reported three cases of pleural effusion due to psittacosis pneumonia,with elevated level of adenosine deaminase and lymphocyte-predominant exudative pleural effusion.Further,we reviewed the psittacosis pneumonia reports with complete clinical and lung imaging data.The imaging manifestations included pulmonary consolidation and common occurrence of a small amount of pleural effusion.The patients of psittacosis pneumonia combined with pleural effusion had severe symptoms,obvious hypoxia,and increased risk of invasive ventilation.
Humans ; Psittacosis/diagnosis* ; Chlamydophila psittaci ; Pleural Effusion/diagnosis* ; Pneumonia ; Lymphocytes