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Andrianiaina MMA, Raherison RE, Razanamparany T, Raharinavalona SA, Rakotomalala ADP, Andrianasolo RL. [Epidemiologic-clinical, biological and radiological features of pulmonary tuberculosis in patients with diabetes in Antananarivo, Madagascar]. Pan Afr Med J 2022; 42:49. [PMID: 35949462 PMCID: PMC9338721 DOI: 10.11604/pamj.2022.42.49.29199] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2021] [Accepted: 05/08/2022] [Indexed: 11/11/2022] Open
Abstract
Pulmonary tuberculosis is frequently associated with diabetes mellitus and, sometimes, it may present with atypical signs. The purpose of this study is to identify the epidemiological, clinical, biological and radiological features of pulmonary tuberculosis in patients with diabetes versus patients without diabetes in order to improve treatment. We conducted a retrospective, cross-sectional descriptive and analytical study in the Department of Endocrinology and Pneumology at the Joseph Raseta Befelatanana University Hospital Center and in the Department of Respiratory Diseases at the Soavinandriana Hospital Center in Antananarivo, Madagascar. It involved patients diagnosed with pulmonary tuberculosis who presented a positive bacilloscopy exam from January 2018 to January 2020 (25 months). In our study, the overall prevalence of diabetes among TB patients was 20.31 %. Older age, insidious clinical course, severe biologic inflammatory syndrome, fewer caves but more systematized opacities and diffuse radiological lesions in the basal zone (more commonly unilateral right lesions) were mainly detected in patients with diabetes compared to patients without diabetes. Knowledge of signs of pulmonary TB in patients with diabetes can help health care workers to make a diagnosis, even in patients with atypical signs. Moreover, as the majority of pulmonary tuberculosis occur in patients with unstable diabetes, a good glycemic balance can certainly reduce its incidence.
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Affiliation(s)
| | - Rija Eric Raherison
- Service d´Endocrinologie du Centre Hospitalier Universitaire Joseph Raseta Befelatanana Antananarivo, Antananarivo, Madagascar
| | - Thierry Razanamparany
- Service de Médecine du Centre Hospitalier Régional de Référence de Vakinakaratra Antsirabe, Vakinakaratra Antsirabe, Madagascar
| | - Sitraka Angelo Raharinavalona
- Service de Médecine Interne et des Maladies Cardiovasculaires du Centre Hospitalier de Soavinandriana, Soavinandriana, Madagascar
| | | | - Radonirina Lazasoa Andrianasolo
- Service d´Endocrinologie du Centre Hospitalier Universitaire Joseph Raseta Befelatanana Antananarivo, Antananarivo, Madagascar
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Li K, Jiang Z, Zhu Y, Fan C, Li T, Ma W, He Y. A valuable computed tomography-based new diagnostic tool for severe chest lesions in active pulmonary tuberculosis: combined application of influencing factors. Sci Rep 2020; 10:2023. [PMID: 32029876 PMCID: PMC7005193 DOI: 10.1038/s41598-020-59041-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2019] [Accepted: 01/23/2020] [Indexed: 12/30/2022] Open
Abstract
The objective of the present investigation was to explore the influencing factors and value of computed tomography (CT) for diagnosing severe chest lesions in active pulmonary tuberculosis (APTB). This retrospective investigation included 463 patients diagnosed with APTB. Relevant clinical features were collected. Patients were assigned to mild/moderate group or advanced group depending on the lesion severity on chest CT, severe chest CT lesion refers to the moderately dense or less diffuse lesion that exceeds the total volume of one lung, or the dense fusion lesion greater than one third of the volume of one lung, or the lesion with cavity diameter ≥4 cm. Independent risk factors for severe lesions were determined by univariate and multivariate logistic regression analyses, and the diagnostic efficiency of the risk factors was assessed by receiver operating characteristic curve (ROC). Chest CT demonstrated that there were 285 (61.56%) cases with severe lesions; multivariate Logistic regression analysis showed dust exposure [odds ratio (OR) = 4.108, 95% confidence interval (CI) 2.416–6.986], patient classification (OR = 1.792, 95% CI 1.067–3.012), age (OR = 1.018, 95% CI 1.005–1.030), and albumin-globulin ratio (OR = 0.179, 95% CI 0.084–0.383) to be independently correlated with severe lesions on chest CT. ROC curve analysis showed the cutoff values of age, albumin-globulin ratio and combined score to be 39 years, 0.918 and −0.085, respectively. The predictive value of combined score area under the curve 0.753 (95% CI 0.708–0.798) was higher than that of any single factor. The combined score of these four factors further improved the predictive efficacy.
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Affiliation(s)
- Kui Li
- Department of Infectious Diseases, The First Affiliated Hospital of Xi'an Jiaotong University, 277 West Yanta Road, Xi'an, 710061, Shaanxi, China.,Department of Infectious Diseases, Ankang Central Hospital, 85 South Jinzhou Road, Ankang, 725000, Shaanxi, China
| | - Zicheng Jiang
- Department of Infectious Diseases, Ankang Central Hospital, 85 South Jinzhou Road, Ankang, 725000, Shaanxi, China
| | - Yanan Zhu
- The Medical Imaging Centre, Ankang Central Hospital, 85 South Jinzhou Road, Ankang, 725000, Shaanxi, China
| | - Chuanqi Fan
- Department of Infectious Diseases, Ankang Central Hospital, 85 South Jinzhou Road, Ankang, 725000, Shaanxi, China
| | - Tao Li
- Department of Infectious Diseases, Ankang Central Hospital, 85 South Jinzhou Road, Ankang, 725000, Shaanxi, China
| | - Wenqi Ma
- Department of Ultrasound, The Second Affiliated Hospital of Xi'an Jiaotong University, 157 West 5 Road, Xi'an, 710004, Shaanxi, China
| | - Yingli He
- Department of Infectious Diseases, The First Affiliated Hospital of Xi'an Jiaotong University, 277 West Yanta Road, Xi'an, 710061, Shaanxi, China.
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