Objective:To explore the effect of integrated medical and nursing care in patients with pulmonary tuberculosis combined with lung cancer.Methods:From August 2021 to August 2022,60 patients with pulmonary tuberculosis ...Objective:To explore the effect of integrated medical and nursing care in patients with pulmonary tuberculosis combined with lung cancer.Methods:From August 2021 to August 2022,60 patients with pulmonary tuberculosis combined with lung cancer were admitted.All patients were diagnosed with pulmonary tuberculosis according to the Guidelines for the Diagnosis and Treatment of Pulmonary Tuberculosis and with lung cancer by pathology.The patients were randomly divided into two groups,with 30 cases in each group.The control group received daily nursing care,whereas the study group received integrated medical and nursing care.The sputum conversion rate,tumor remission rate,and quality of life of patients were observed and analyzed.Results:The item function score and symptom function score of the observation group were higher than those of the control group(P<0.05);the total effective rate of the observation group was significantly higher than that of the control group(P<0.05);the sputum conversion rate of the observation group was significantly higher than that of the control group(P<0.05).Conclusion:For patients with pulmonary tuberculosis combined with lung cancer,the application of integrated medical and nursing care can help consolidate the treatment effect and improve the quality of life of patients;thus,it is worthy of promotion and application.展开更多
BACKGROUND Pulmonary tuberculosis(TB)and lung cancer(LC)are common diseases with a high incidence and similar symptoms,which may be misdiagnosed by radiologists,thus delaying the best treatment opportunity for patient...BACKGROUND Pulmonary tuberculosis(TB)and lung cancer(LC)are common diseases with a high incidence and similar symptoms,which may be misdiagnosed by radiologists,thus delaying the best treatment opportunity for patients.AIM To develop and validate radiomics methods for distinguishing pulmonary TB from LC based on computed tomography(CT)images.METHODS We enrolled 478 patients(January 2012 to October 2018),who underwent preoperative CT screening.Radiomics features were extracted and selected from the CT data to establish a logistic regression model.A radiomics nomogram model was constructed,with the receiver operating characteristic,decision and calibration curves plotted to evaluate the discriminative performance.RESULTS Radiomics features extracted from lesions with 4 mm radial dilation distances outside the lesion showed the best discriminative performance.The radiomics nomogram model exhibited good discrimination,with an area under the curve of 0.914(sensitivity=0.890,specificity=0.796)in the training cohort,and 0.900(sensitivity=0.788,specificity=0.907)in the validation cohort.The decision curve analysis revealed that the constructed nomogram had clinical usefulness.CONCLUSION These proposed radiomic methods can be used as a noninvasive tool for differentiation of TB and LC based on preoperative CT data.展开更多
Purpose: To assess the inter-observer agreement in reading adults chest radiographs (CXR) and determine the effectiveness of observers in radiographic diagnosis of pulmonary tuberculosis (PTB) in a tuberculosis endemi...Purpose: To assess the inter-observer agreement in reading adults chest radiographs (CXR) and determine the effectiveness of observers in radiographic diagnosis of pulmonary tuberculosis (PTB) in a tuberculosis endemic area. Methods: A quasi-observational study was conducted in the Pneumology Department of Yaounde Jamot Hospital (Cameroon) from January to March 2014. This included six observers (two chest physicians, two radiologists, two end-training residents in medical imaging) and 47 frontal CXRs (4 of diffuse interstitial lung disease, 6 normal, 7 of lung cancers, 7 of bacterial pneumonia, 23 of PTB). The sample size was calculated on the basis of an expected 0.47 Kappa with a spread of 0.13 (α = 5%, CI = 95%) for six observers and five diagnostic items. The analysis of concordance was focused on the detection of nodules, cavitary lesions, pleural effusion, adenomegaly and diagnosis of PTB and lung cancer. These intervals of kappa coefficient were considered: discordance (0.81). Results: The average score for the detection of caverns was the highest (58.3%) followed by that of the correct diagnosis of tuberculosis (49.3%). Pneumologists had the highest proportions of correct diagnosis of tuberculosis (69.6% and 73.9%) and better inter-observer agreement (k = 0.71) for PTB diagnosis. Observers were more in agreement for the detection of nodules (0.32 - 0.74), adenomegalies (0.43 - 0.69), and for the diagnosis of cancer (0.22 - 1) than for the diagnosis of tuberculosis (0.19 - 0.71). Disagreements were more frequent for the detection of pleural effusions (-0.08 - 0.73). Conclusion: The inter-observer agreement varies with the type of lesions and diagnosis. Pneumologists were most effective for the diagnosis of pulmonary tuberculosis. Observers were more in agreement for the detection of nodules and the diagnosis of cancer than for the diagnosis of pulmonary tuberculosis.展开更多
基金Baoding Science and Technology Plan Project“The Effect of Medical-Nurse Integrated Nursing Model Combined with Psychological Intervention on the Clinical Curative Effect of Tuberculosis and Lung Cancer Patients”(Project number:2141ZF318).
文摘Objective:To explore the effect of integrated medical and nursing care in patients with pulmonary tuberculosis combined with lung cancer.Methods:From August 2021 to August 2022,60 patients with pulmonary tuberculosis combined with lung cancer were admitted.All patients were diagnosed with pulmonary tuberculosis according to the Guidelines for the Diagnosis and Treatment of Pulmonary Tuberculosis and with lung cancer by pathology.The patients were randomly divided into two groups,with 30 cases in each group.The control group received daily nursing care,whereas the study group received integrated medical and nursing care.The sputum conversion rate,tumor remission rate,and quality of life of patients were observed and analyzed.Results:The item function score and symptom function score of the observation group were higher than those of the control group(P<0.05);the total effective rate of the observation group was significantly higher than that of the control group(P<0.05);the sputum conversion rate of the observation group was significantly higher than that of the control group(P<0.05).Conclusion:For patients with pulmonary tuberculosis combined with lung cancer,the application of integrated medical and nursing care can help consolidate the treatment effect and improve the quality of life of patients;thus,it is worthy of promotion and application.
基金Supported by Youth Science and Technology Innovation Leader Support Project,No.RC170497Shenyang Municipal Science and Technology Project,No.F16-206-9-23+5 种基金Natural Science Foundation of Liaoning Province of China,No.201602450National Key R&D Program of Ministry of Science and Technology of China,No.2016YFC1303002National Natural Science Foundation of China,No.81872363Major Technology Plan Project of Shenyang,No.17-230-9-07Supporting Fund for Big data in Health Care,No.HMB2019031012018 Key Research and Guidance Project of Liaoning Province,No.2018225038.
文摘BACKGROUND Pulmonary tuberculosis(TB)and lung cancer(LC)are common diseases with a high incidence and similar symptoms,which may be misdiagnosed by radiologists,thus delaying the best treatment opportunity for patients.AIM To develop and validate radiomics methods for distinguishing pulmonary TB from LC based on computed tomography(CT)images.METHODS We enrolled 478 patients(January 2012 to October 2018),who underwent preoperative CT screening.Radiomics features were extracted and selected from the CT data to establish a logistic regression model.A radiomics nomogram model was constructed,with the receiver operating characteristic,decision and calibration curves plotted to evaluate the discriminative performance.RESULTS Radiomics features extracted from lesions with 4 mm radial dilation distances outside the lesion showed the best discriminative performance.The radiomics nomogram model exhibited good discrimination,with an area under the curve of 0.914(sensitivity=0.890,specificity=0.796)in the training cohort,and 0.900(sensitivity=0.788,specificity=0.907)in the validation cohort.The decision curve analysis revealed that the constructed nomogram had clinical usefulness.CONCLUSION These proposed radiomic methods can be used as a noninvasive tool for differentiation of TB and LC based on preoperative CT data.
文摘Purpose: To assess the inter-observer agreement in reading adults chest radiographs (CXR) and determine the effectiveness of observers in radiographic diagnosis of pulmonary tuberculosis (PTB) in a tuberculosis endemic area. Methods: A quasi-observational study was conducted in the Pneumology Department of Yaounde Jamot Hospital (Cameroon) from January to March 2014. This included six observers (two chest physicians, two radiologists, two end-training residents in medical imaging) and 47 frontal CXRs (4 of diffuse interstitial lung disease, 6 normal, 7 of lung cancers, 7 of bacterial pneumonia, 23 of PTB). The sample size was calculated on the basis of an expected 0.47 Kappa with a spread of 0.13 (α = 5%, CI = 95%) for six observers and five diagnostic items. The analysis of concordance was focused on the detection of nodules, cavitary lesions, pleural effusion, adenomegaly and diagnosis of PTB and lung cancer. These intervals of kappa coefficient were considered: discordance (0.81). Results: The average score for the detection of caverns was the highest (58.3%) followed by that of the correct diagnosis of tuberculosis (49.3%). Pneumologists had the highest proportions of correct diagnosis of tuberculosis (69.6% and 73.9%) and better inter-observer agreement (k = 0.71) for PTB diagnosis. Observers were more in agreement for the detection of nodules (0.32 - 0.74), adenomegalies (0.43 - 0.69), and for the diagnosis of cancer (0.22 - 1) than for the diagnosis of tuberculosis (0.19 - 0.71). Disagreements were more frequent for the detection of pleural effusions (-0.08 - 0.73). Conclusion: The inter-observer agreement varies with the type of lesions and diagnosis. Pneumologists were most effective for the diagnosis of pulmonary tuberculosis. Observers were more in agreement for the detection of nodules and the diagnosis of cancer than for the diagnosis of pulmonary tuberculosis.
