Application of intracavitary electrocardiogram classification in peripherally inserted central catheter localization in cancer patients
Journal of Electrocardiology(2022)
Abstract
Objective: This study aimed to analyze the application value of intracavitary electrocardiogram (ECG) classification in peripherally inserted central catheter (PICC) tip localization in patients with cancer. Methods: Using a self-control study method, 325 patients with cancer underwent intracavitary ECGs to position the tip of a PICC catheter. The P wave, QRS wave amplitude, and waveform changes of each intracavitary ECG were recorded. Chest X-ray examination was performed after the catheterization to compare the results of different intracavity ECG maps with the results of the chest X-ray. Results: The intracavitary ECG positioning maps of the 325 patients were divided into four categories: (1) increased P wave (293 cases), accounting for 90.15% (293/325) of all cases; compared with the positioning results of the chest X-rays, the placement rate was 98.98% (290/293); (2) negative deepening of the P wave (1 case), accounting for 0.31% (1/325) of all cases and with a placement rate of 100% (1/1); (3) no change in P wave (19 cases), accounting for 5.85% (19/325) of all cases and with a placement rate of 42.11% (8/19); (4) atrial fibrillation/atrial flutter (12 cases), accounting for 3.69% (12/325) of all cases and with a placement rate of 58.33% (7/12). The four types of intracavitary ECG positioning maps had statistically significant differences (chi(2) = 133.924, P = 0.000). Conclusion: There are four types of intracavitary ECG localization maps: increased P wave, negative deepening of the P wave, no change in P wave, and atrial fibrillation/atrial flutter. The increased P wave pattern had the highest occurrence probability and high positioning accuracy. It therefore has strong clinical application value for PICC tip localization in patients with cancer. (C) 2021 Elsevier Inc. All rights reserved.
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Key words
Intracavitary electrocardiogram,Map classi fication,Cancer patients,PICC localization,Application
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