Computed tomography imaging and clinical significance of bacterium-positive pulmonary tuberculosis complicated with diabetes.

Background: The increasing prevalence of tuberculosis (TB) and diabetes on a global scale poses a significant health challenge, particularly due to their co-occurrence, which amplifies the severity, recurrence and mortality rates associated with both conditions. This highlights the need for further investigation into their inter-relationship.

Aim: To explore the computed tomography (CT) imaging and clinical significance of bacterium-positive pulmonary TB (PTB) combined with diabetes.

Methods: There were 50 patients with bacterium-positive PTB and diabetes, and 50 with only bacterium-positive PTB. The latter were designated as the control group. The CT imaging of the two groups of patients was compared, including lesion range, shape, density and calcification.

Results: No significant differences were observed in age, gender, smoking and drinking history, high blood pressure, hyperlipidemia and family genetic factors between the groups. However, compared to the patients diagnosed solely with simple bacterium-positive PTB, those with concurrent diabetes showed a wider range of lesions and more complex and diverse morphology on CT images. Among them, intrapulmonary tuberculosis lesions were often accompanied by manifestations of pulmonary infection, such as cavity formation and bronchiectasis. At the same time, diabetes-related signs were often seen on CT images, such as pulmonary infection combined with diabetic pulmonary lesions. Logistic regression analysis identified age and medical history as significant factors influencing the degree of pulmonary infection and CT imaging outcomes in patients with both TB and diabetes. This suggests that older age and specific medical histories may increase the risk or severity of pulmonary damage in these patients.

Conclusion: CT imaging reveals more complex lesions in PTB patients with diabetes, emphasizing the need for careful evaluation and comprehensive analysis to enhance diagnostic accuracy.