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Liu Wenjia, Zhou Runshi, Li Zunzhu, Su Longxiang, Cui Wenbo, Long Yun, He Huaiwu. Applying the electrical impedance tomography to assess lung regional ventilation distribution in ICU patients after a cardiac surgery and exploring its preliminary values[J]. Medical Journal of Peking Union Medical College Hospital. doi: 10.12290/xhyxzz.2023-0626
Citation: Liu Wenjia, Zhou Runshi, Li Zunzhu, Su Longxiang, Cui Wenbo, Long Yun, He Huaiwu. Applying the electrical impedance tomography to assess lung regional ventilation distribution in ICU patients after a cardiac surgery and exploring its preliminary values[J]. Medical Journal of Peking Union Medical College Hospital. doi: 10.12290/xhyxzz.2023-0626

Applying the electrical impedance tomography to assess lung regional ventilation distribution in ICU patients after a cardiac surgery and exploring its preliminary values

doi: 10.12290/xhyxzz.2023-0626
Funds:

National Key Research and Development Program of China (2022YFC2504505)

  • Available Online: 2024-04-18
  • Objective To apply electrical impedance tomography (EIT) technology to assess the lung regional ventilation distribution in patients admitted to the intensive care unit (ICU) after a cardiac surgery, and to analyze its value of predicting patients’ short-term prognosis. Methods Data from 46 patients admitted to ICU after a cardiac surgery from January to November 2023 were retrospectively collected. Using EIT, we assessed the lung regional ventilation of four regions of interest (ROI) and analyze its influence on patients’ length of stay in ICU, mechanical ventilation duration and tracheal intubation duration. Results Patients who received a cardiac surgery equal to or over 5 hours had worse ventilation in the dorsal region (ROI 4) (P = 0.022). Patients with worse dorsal region ventilation (ROI4 < 9%) had lower oxygenation index (P = 0.025), longer mechanical ventilation duration (P = 0.004), longer tracheal intubation duration (P = 0.010), and longer ICU stay (P = 0.018). A larger ROI 4 percent is a protective factor for patients’ prognosis (OR = 0.743, 95%CI: 0.587~0.941, P = 0.014) after controlling for the impact of age, gender, length of surgery and acute physiology and chronic health evaluation (APACHE) score at the admission. Using a cutoff value of 9.5%, ROI 4 has 85.7% sensitivity and 56.2% specificity to predict worse patients’ prognosis. The area under the curve (AUC) is 0.752 (95% CI: 0.599~0.905, P = 0.007). Conclusion The length of a cardiac surgery influences patients’ lung ventilation, which further impacts patients’ prognosis. EIT can be used as a bedside tool to assess patients’ lung ventilation and to inform corresponding clinical interventions to improve patients’ prognosis.
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