Mathematical model under E-health context for diagnosis of head and neck space Gram infection through CT imaging

The study aimed to investigate the head and neck space infection by Gram bacteria using mathematical model-based CT (computer tomography) under e-health (electronic health). Specifically, a total of 180 clinical patients with head and neck space infection were collected as the research subjects. CT/MRI examination was adopted to diagnose the disease. A mathematical model was then established to be applied in CT imaging. The cause and treatment effect were analyzed by summarizing the data, including basic information, bacterial culture, source and extent of infection, serious complications, and other factors. The results showed that the CT/MRI imaging based on the mathematical model can effectively diagnose the disease and assess the disease progress. There were more male patients than female patients with head and neck space infection, and more elderly patients than younger patients. A total of 42 patients had serious complications, accounting for 23.3% of the total patients. The most common one was descending mediastinitis, followed by respiratory obstruction, pneumonia, pericarditis, orbital infection, and multiple organ failure. There were many sources of infection in the head and neck space. The main cause was dental infection, and there were 137 cases, accounting for 76.1% of the total. Among them, odontogenic infections included tooth apical periodontitis, wisdom tooth pericoronitis, and periodontal disease. Other sources of infection included glandular infections, iatrogenic infections, and traumatic foreign bodies. The most common part affected by head and neck space infection was the submandibular space, and other parts included the masseter space, the cheek space, and the sublingual space. Severe complications of head and neck space infection were mainly inferior mediastinitis and respiratory obstruction. In the bacterial culture experiment, a total of 75 bacterial cultures of 180 patients were positive, and 62 strains of bacteria were cultured, including 11 kinds of gram-positive bacteria and 4 kinds of gram-negative bacteria. The main pathogens cultivated were Streptococcus viridans, Staphylococcus aureus, and Klebsiella pneumoniae. In laboratory tests, the values of WBC and hs-CRP in patients with severe complications were significantly higher than those in patients with common head and neck space infection. Imipenem and ornidazole were the most commonly used antibiotics in the clinical treatment of patients with severe complications. In conclusion, head and neck space infection is a serious infectious disease that may be life-threatening and requires timely and effective treatment. © 2021 The Author(s)
This article is not available at CUD collection. The version of scholarly record of this article is published in Results in Physics (2021), available online at:
CT/MRI, E-health, Gram infection, Head and neck space infection, Mathematical model, Risk factors
Li, L., Shi, S., Miao, Z., Xu, J., Duan, X., Okasha, A., & Qeshta, M. H. (2021). Mathematical model under E-health context for diagnosis of head and neck space gram infection through CT imaging. Results in Physics, 26.