Clinical Factors and Quantitative CT Parameters Associated COVID-19 Pneumonia Essay

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The present article is primarily preoccupied with the examination of the COVID-19 phenomenon and its efficient treatment in the context of current medical opportunities and future interventions.

Since the virus’s emergence in China at the end of 2019, it has been associated with pneumonia as a major side effect of the infection, catalyzing a high number of deaths from pneumonia complications. The authors of the present research address the topic of diagnosing pneumonia at the early stages of the disease to prevent people from severe complications. The authors consider chest computer tomography (CT) as the most efficient means of detecting pneumonia among coronavirus patients. Thus, the broad topic area of the present research concerns the notion of pneumonia in the context of COVID-19 treatment. Moreover, the article also addressed the regularity of patients’ admission to the Intensive Care Units (ICUs) as a result of neglected CT diagnostics.

In terms of the present study, the primary objective was to define the extent to which chest CT intervention at an early admission stage could be a decisive factor in terms of preventing admission to the ICU. Although the study itself tackles many individual characteristics of a patient, including gender, health state, and exposure to the areas with high risks of coronavirus infection, the primary emphasis was placed on the patients’ exposure to timely chest CT screening.

Thus, the alternative hypothesis outlined by the researchers may be defined as follows:

H1: The quantitative parameters originated from chest CT, along with the clinical paraments on hospital admission, may potentially affect the prediction of risk of ICU admission among the COVID-19 pneumonia patients.

The data collected for the study variables were mostly quantitative, as the researchers had to define a tangible justification of the hypothesis.

The study comprises an extensive number of independent variables that tackle both CT factors and individual factors related to one’s hospital admission. The first segment of independent variables includes:

  • Age;
  • Gender;
  • Exposure to Wuhan for two weeks prior to the admission;
  • Family clusters;
  • Coexisting conditions include cardiovascular disease, COPD, chronic liver disease, diabetes, and others.

Another significant independent variable concerned whether the patient belonged to the ICU care.

Other variables included the onset of symptoms, vital signs, and laboratory findings both inside and outside ICU care. The dependent variable, in its turn, concerns the patient’s treatment process after the timely chest CT intervention among high-risk COVID-19 patients with pneumonia.

In order to secure the study’s efficiency, the authors did not impose any limitations on the age, gender, and health conditions of the target population. Thus, the primary population of interest for the existing study addressed COVID-19 patients admitted to the hospital premises with pneumonia. Since the study is multicenter, the population encompassed various medical facilities in China. A significant criterion for eligibility was the fact of a patient undergoing chest CT that indicated such major characteristics as the lung opacity (predicted volume of abnormalities in lungs in juxtaposition with the normal lung volume).

The sample was collected from different hospital facilities in China and eventually accounted for 221 patients that were admitted to the hospital with pneumonia and COVID-19 during the period from January 17, 2020, to February 17, 2020.

The further classification of the sample may be defined as follows:

  • Male patients – 125;
  • Female patients – 96.
  • Admitted to the ICU after pneumonia and COVID confirmation – 40;
  • Pneumonia and COVID handled without ICU admission – 181;
  • Deaths in the process of trial – 3 cases (all took place among the patients admitted to ICU).

The multicenter clinical trial was the primary sampling method. Thus, the researchers accounted for every registered COVID-19 case with pneumonia in the designated hospital settings. Once the patient passed the eligibility criteria, their medical history was recorded in order to create the demographic of the sample. If patients had no CT examination on admission or were sent directly to ICU without preliminary screening, they were excluded from the trial.

The data were collected with the help of the PRISMA framework, following such eligibility criteria:

  1. Identification. 310 patients with confirmed COVID-10 pneumonia were selected.
  2. Screening. 75 patients were excluded due to the lack of key laboratory data or direct ICU admission.
  3. Eligibility. 14 patients were excluded due to the absence of CT examination on admission.
  4. Included. The final sample pattern accounted for 221 participants (40 admitted to the ICU care). Excluding 3 patients that died during the hospital stay, 218 patients were discharged before March 14, 2020.

Reference

Yan, C., Chang, Y., Yu, H., Xu, J., Huang, C., Yang, M., Wang, Y., Wang, D., Yu, T., Wei, S., Li, Z., Gong, F., Kou, M., Gou, W., Zhao, Q., Sun, P., Jia, X., Fan, Z., Xu, J., Li, S., & Yang, Q. (2021).Frontiers in Public Health, 9(332). Web.

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IvyPanda. 2022. "Clinical Factors and Quantitative CT Parameters Associated COVID-19 Pneumonia." July 14, 2022. https://ivypanda.com/essays/clinical-factors-and-quantitative-ct-parameters-associated-covid-19-pneumonia/.

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