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Objective To construct a risk prediction model for pulmonary infection in stroke patients and verify its clinical predictive performance. Methods Using convenience sampling, 750 stroke patients hospitalized in a tertiary hospital in Guizhou Province from January 2021 to January 2023 were selected as study subjects. They were divided into a pulmonary infection group (n=267) and a non-pulmonary infection group (n=483) based on whether pulmonary infection occurred. Comparative analysis of relevant data between the two groups was conducted. Logistic regression analysis was applied to establish a risk prediction model. The goodness-of-fit of the model was tested using the Hosmer-Lemeshow (H-L) test, and the predictive performance of the model was evaluated by the area under the receiver operating characteristic curve (ROC curve). Another 145 eligible patients from February to August 2023 were selected to validate the predictive performance of the model. Results Univariate and multivariate analyses revealed that dysphagia [odds ratio (OR) =10.462], coexisting pulmonary diseases (OR=6.046), hypokalemia (OR=2.266), hyponatremia (OR=3.807), low hemoglobin (OR=4.036), National Institutes of Health Stroke Scale (NIHSS) score at admission (OR=38.135), Activities of Daily Living (ADL) score at admission (OR=12. 942), and length of hospital stay (OR=8.992) were independent risk factors for pulmonary infection in stroke patients (P＜0.05). The risk prediction model formula was: Logit (P) =-4.761+2. 348× (dysphagia score) +1.799× (coexisting pulmonary diseases score) +0.818× (hypokalemia score) +1. 337× (hyponatremia score) +1.395× (low hemoglobin score) +3. 641× (NIHSS score) +2.560× (ADL score) +2.196× (length of hospital stay score). The area under the ROC curve of the modeling group was 0.953 [95% confidence interval (95%CI) 0.940-0. 967, P＜0.001], with a Youden index of 0.762, a sensitivity of 0.880, a specificity of 0. 882, and a P value of 0. 553 in the H-L test. The validation results showed that the area under the ROC curve of the validation group was 0. 946 (95%CI: 0. 927-0. 987, P＜0.001), with a sensitivity of 0. 898, a specificity of 0. 875, an accuracy of 88. 3%, and a P value of 0. 510 in the H-L test. Conclusion The established risk prediction model for pulmonary infection in stroke patients has good predictive performance, providing a reference for clinical healthcare professionals to early identify high-risk groups for stroke induced pulmonary infection and facilitating the timely adoption of preventive management measures. [ABSTRACT FROM AUTHOR]

Objective To analyze the influencing factors of pulmonary infection in patients with primary liver cancer (PHC) before intervention, and establish a nomogram risk prediction model to verify it. Methods A total of 1 635 patients with PHC diagnosed and hospitalized for the first time were selected and divided into the infected group (197 cases) and the non-infected group (1 438 cases) according to whether they had pulmonary infection. General data such as body mass index (BMI), chronic hepatitis B (CHB), chronic hepatitis C (CHC), Barcelona stage (BCLC), white blood cells (WBC), neutrophils (NEU), hemoglobin (Hb) and other blood routine indicators were collected. Total protein (TP), prealbumin (PA), aspartate aminotransferase (AST), gamma glutamylaminotransferase (GGT), alkaline phospholipase (ALP), abnormal prothrombin (PIVKA- Ⅱ), alpha-fetoprotein (AFP), carcinoembryonic antigen (CEA), procalcitonin (PCT), hypersensitive C-reactive protein (hs-CRP), cholinesterase (ChE), total cholesterol (TC) and other blood biochemical indicators, CD3 cell count (CD3+ ), CD4 cell count (CD4+ ), CD4/CD8 ratio (CD4+ /CD8+ ), CD19 cell count (CD19+ ), interleukin (IL)-2, interferon (IFN)-α, tumor necrosis factor (TNF) - α and other cytokines were also collected. Univariate analysis and Lasso regression were used to screen variables, and binary Logistic regression analysis was used to determine risk factors for pulmonary infection in PHC patients before intervention. The risk prediction model was established and evaluated. Results Compared with the noninfected group, age, smoking rate, CHC, pleural effusion, gastrointestinal hemorrhage, Child-Pugh grade C, BCLC Phase A /C /D ratio, WBC, NEU, AST, GGT, ALP, PIVKA-Ⅱ, AFP, CEA, PCT, hs-CRP, IL-2, IL-5, IL-6, IL-8, IL-10, IL-12, IFN-γ and TNF-α levels were higher in the infected group, and levels of BMI, CHB ratio, Hb, TP, PA, ChE, TC, CD3+, CD4+, CD4+ /CD8+, CD19+ and IFN-α were lower (P < 0.05). Lasso regression and binary Logistic regression analysis showed that pleural effusion, gastrointestinal hemorrhage, higher level of age, WBC, Hb and lower level of TP were independent risk factors for pulmonary infection in patients with PHC before intervention. The area under receiver operating curve (ROC) of the established nomogram model was 0.700（95%CI: 0.659-0.740), and Hosmer-Lemeshow test results showed good goodness-fit of the model. Self-sampling was repeated 1 000 times for internal verification. The consistency of the model was good. Conclusion Pleural effusion, gastrointestinal hemorrhage, higher level of age, WBC, Hb and lower level of TP are independent risk factors for pulmonary infection in PHC patients before intervention. The established nomogram prediction model can effectively evaluate the risk of pulmonary infection in PHC patients before intervention. [ABSTRACT FROM AUTHOR]

Objective To investigate the factors influencing the development of severe pneumonia in patients with human immunodeficiency virus (HIV )/acquired immunodeficiency syndrome (AIDS). Methods This study retrospectively analyzed the clinical data of 139 patients with HIV/AIDS combined with pulmonary infections admitted to the Department of Infectious Diseases of General Hospital of Ningxia Medical University from January 2017 to August 2023, among which 48 cases were in the severe pneumonia group and 91 cases were in the non-severe pneumonia group. The influencing factors on the occurrence of severe pneumonia in patients with HIV/AIDS were analyzed by using logistic regression, and the predictive value of the indicators for severe pneumonia was analyzed by plotting the work characteristics of the subjects (ROC) curves. Results The incidence of severe pneumonia was 34. 5% (48/139) in 139 patients with HIV/AIDS coinfection of the lungs. Univariate analysis showed that cough, shortness of breath, percentage of neutrophils, percentage of lymphocytes, absolute value of lymphocytes, prothrombin activity (PTA), CD4+T and CD8+T lymphocyte counts, neutrophil/lymphocyte ratio (NLR), albumin, number of pathogens greater than or equal to two, and continuous strong antiretroviral therapy (ART) treatment (>three months) were significantly associated with severe pneumonia in HIV/AIDS patients (P <0. 05). Logistic stepwise regression analysis showed that previous pneumocystis pneumonia (PCP), number of pathogens greater than or equal to two, elevated NLR, elevated PTA, and shortness of breath were independent risk factors for severe pneumonia in HIV/AIDS patients, continuous ART treatment (>three months) and CD8+ T cell count were independent protective factors (P <0. 05). The area under the curve of multi-factor combined prediction is the largest (AUC=0. 917, 95%CI 0. 873-0. 961, P <0. 01). Conclusion The occurrence of severe pneumonia in HIV/ AIDS patients is closely related to previous PCP, number of pathogens greater than or equal to two, high NLR, high PTA, shortness of breath, continuous ART treatment (>three months), CD8+T cell count. Multifactor combined prediction have good predictive value [ABSTRACT FROM AUTHOR]

Copyright of China Journal of Oral & Maxillofacial Surgery is the property of Shanghai Jiao Tong University, College of Stomatology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Objective To analyze the risk factors of lung cancer patients complicated with pulmonary infection after thoracoscopic surgery and establish a predictive nomogram model. Methods A total of 315 patients with primary lung cancer who had undergone thoracoscopic surgery from January 2018 to October 2021 in our hospital were divided into two groups according to the incidence of pulmonary infection. Two groups of clinical data were collected for single-factor and regression analyses, and independent predictors were obtained. On this basis, a risk model was constructed and its predictive effectiveness was evaluated. Results The independent risk factors of lung cancer patients complicated with pulmonary infection after thoracoscopic radical operation were as follows: age≥62.5 years, smoking index≥100, PEF≤72.1 ml/s, TNM stage Ⅲ/Ⅳ, and operation time≥188.5 min (P<0.05). Based on the above factors, the risk model of the column chart was established. Model-verification results showed that the C-index of the model was 0.909, and the correction curve showed that the column chart model had good differentiation and consistency. Conclusion Lung cancer patients’ age, smoking index, TNM stage, PEF, and operation time are closely related to pulmonary infection after thoracoscopic radical operation. The nomogram model is useful for identifying high-risk patients and reducing postoperative complications. [ABSTRACT FROM AUTHOR]

Copyright of China Tropical Medicine is the property of China Tropical Medicine Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Objective: To analyze the distribution and risk factors of pathogenic bacteria in liver cirrhosis complicated with pulmonary infection. Methods: 518 patients with liver cirrhosis who were treated in our Hospital from February 2013 to June 2018 were selected. The number of pulmonary infection in all patients was counted. The clinical data of the patients were collected,including gender, age, etiology, length of stay, with or without invasive operations, with or without ascites, Child-Pugh classification,with or without upper gastrointestinal bleeding and with or without the combination of basic diseases. The relationship between pulmonary infection and clinical data was analyzed, the distribution of pathogenic bacteria in patients with liver cirrhosis complicated with pulmonary infection was also detected, and multivariate logistic regression analysis was used to analyze the risk factors of pulmonary infection in patients with liver cirrhosis. Results: Among 518 patients with liver cirrhosis, 80 cases had pulmonary infection,the incidence rate was 15.44%. Univariate analysis showed that gender was not associated with lung infection in patients with cirrhosis (P>0.05). Age, etiology, length of stay, invasive operations, ascites, Child-Pugh classification, upper gastrointestinal bleeding and combined basic diseases were all the factors affecting the pulmonary infection in the patients with liver cirrhosis (P<0.05). Multivariate logistic regression analysis showed that age ≥60 years old, length of stay ≥2 weeks, with invasive operations and ascites, Child-Pugh classification with C grade, with upper gastrointestinal bleeding and combined basic disease were all risk factors for pulmonary infection in patients with liver cirrhosis (P<0.05). A total of 93 strains of pathogenic bacteria were detected in sputum samples from 80 patients with liver cirrhosis and pulmonary infection, including gram-negative bacteria with 51 strains, accounting for 54.84%,gram-positive bacteria with 37 strains, accounting for 39.78%, and fungi with 5 strains, accounting for 5.38%. Conclusion: The main pathogenic bacteria of liver cirrhosis complicated with pulmonary infection are Gram-positive bacteria and Gram-negative bacteria, and there are more risk factors for pulmonary infection. In clinically, corresponding preventive measures should be taken according to their risk factors to reduce the occurrence of pulmonary infection. [ABSTRACT FROM AUTHOR]

Objective: To investigate the pathogenic bacteria distribution and risk factors of pulmonary infection after tracheotomy in patients with stroke coma, and to put forward preventive measures. Methods: 96 patients with stroke coma from January 2016 to February 2017 in our hospital were retrospectively analyzed. The incidence of pulmonary infection and distribution of pathogenic bacteria of patients with stroke coma were analyzed. At the same time,the risk factors of pulmonary infection were analyzed by single factor and multiple factors logistic regression analysis, and corresponding preventive measures were put forward. Results: The incidence of pulmonary infection after tracheotomy in 96 patients with stroke coma was 48.96％ (47/96). A total of 104 pathogens were isolated and cultured, including gram negative bacteria 69 strains (66.35％), gram positive bacteria 20 strains (19.23％) and fungus 15 strains (14.42％). Single factor regression analysis results showed that pulmonary infection after tracheotomy in patients with stroke coma was closely related with age, basic diseases,time of tracheotomy, and bed time, use of broad-spectrum antibiotics, smoking history, artificial airway, times of sputum suction and inhalation(P＜0.05), and it was not related to the patient's gender, weight, stroke type (P＞0.05). Multivariate logistic regression analysis showed that age 45 years old, complicated with basic disease, time of tracheotomy 5 d, use of broad-spectrum antibiotics, smoking history and the establishment of artificial airway were risk factors of pulmonary infection after tracheotomy in patients with stroke coma (P＜0.05). ROC analysis results showed that the critical point (threshold C) of tracheotomy time was 4.3 days, and the sensitivity and specificity were 0.851 and 0.918 respectively. Conclusion: The main pathogenic bacteria of pulmonary infection after tracheotomy in patients with stroke coma is gram-negative bacteria, age 45 years old, complicated with basic disease, time of tracheotomy 5d, use of broad-spectrum antibiotics, smoking history and the establishment of artificial airway can lead to pulmonary infection after tracheotomy in patients with stroke coma, and the risk of pulmonary infection in patients with stroke coma will increase considerably after the time of tracheotomy for more than 4.3 days. Targeted measures should be taken to reduce the risk of pulmonary infection according to pathogenic features and risk factors. [ABSTRACT FROM AUTHOR]

Copyright of China Tropical Medicine is the property of China Tropical Medicine Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Objective To analyze the risk factors of multiple drug resistant bacterial infections in patients with chronic obstructive pulmonary disease (COPD), and provide guidance for disease control and prevention. Methods Clinical data of 814 COPD patients were retrospectively analyzed from June 2011 to May 2015, including patient's age, gender, smoking history, age of onset, severity, aggravated frequency, duration of exacerbations, diabetes mellitus, complications, use frequency and use duration of glucocorticoid, use frequency of antimicrobial agents and use duration of each time, types of antimicrobial drugs used, combined with antibacterial drugs, plasma albumin concentration, blood glucose, bacteria culture detection of multi drug resistant bacteria infection. The risk factors of multi drug resistant bacteria infection were analyzed. Results A total of 857 pathogenic bacteria were isolated from 814 COPD patients with pulmonary infection. Multiple drug resistant bacteria infection were detected in 170 cases, and 175 strains (20.42%) were detected. The detection rate of multi drug resistant/PAN resistant pseudomonas aeruginosa (MDR/PDR- PA) was 55.38% (36/65). There were significant differences in patients with multi drug resistant bacteria infection between different clinical pathological characteristics. Logistic regression analysis showed that the acute exacerbation duration (days), long time use of antimicrobial drugs, and high frequency of corticosteroids and antibiotics use were independent risk factor of multi drug resistant bacteria infection in COPD patients. Conclusion Prevention and treatment of multiple drug resistant bacteria infection in COPD patients should pay attention to the combination of community and hospital, and take effective measures to prevent and control the risk factors. [ABSTRACT FROM AUTHOR]

Objective: To investigate the pathogenic bacteria distribution characteristics and associated risk factors of pulmonary infection in patients with cardiovascular disease in order to reduce the infection rate.Methods:From August 2015 to March 2016,154 patients admitted to hospital because of cardiovascular disease were selected,the date of patients were collected and analyzed retrospectively.Sputum samples of patients with hospital infection were collected for bacterial culture,and distribution and risk factors of pathogenic bacteria were analysis.Retslts:patients with pulmonary infection in 154 cases of patients with cardiovascular disease had 27 cases,the incidence rate was 16.23.There were 27 strains of pathogenic bacteria,including 16 strains of gram negative bacteria (59.26％),7 strains of gram positive bacteria (25.93％)and 4 strains of fungi(14.81％).Single factor analysis showed that age,basic diseases,invasive operation,length of hospital stay,antibiotic use and other were related to hospital infection rate,the differences were statistically significant (P＜0.05);Logistic regression analysis found that age (≥ 60years),wtih basic diseases,with invasive operation,used antibiotic,length of hospital stay (＞14d)were risk factors for cardiovascular disease complicated with lung infection.Conclusion:The main pathogenic bacteria of cardiovascular disease complicated with pulmonary infection are escherichia coli,klebsiella pneumoniae,staphylococcus aureus,etc,related intervene should be aimed at risk factors,in order to reducehospital infection rates. [ABSTRACT FROM AUTHOR]