Plešnik Boštjan, Djokić Mihajlo, Djordjević Srdjan, Krašna Simon, Žumer Jan, Trotovšek Blaž
University Medical Centre Ljubljana, Zaloška cesta 7, Ljubljana, Slovenia.
Faculty of Medicine, University of Ljubljana, Vrazov trg 2, Ljubljana, Slovenia.
Sci Rep. 2025 Mar 28;15(1):10775. doi: 10.1038/s41598-025-95512-x.
Monitoring intra-abdominal pressure (IAP) in critical care patients is crucial for preventing intra-abdominal hypertension (IAH) and abdominal compartment syndrome (ACS), with their severe consequences. The muscle contraction sensor (MC) introduced in this study offers a novel, non-invasive method with promising accuracy based on previous findings. This study further evaluates the MC accuracy and reproducibility and examines its correlation with objective IAP measurements obtained through a CO insufflator. We enrolled 41 patients undergoing elective laparoscopic gallbladder removal under general anesthesia with complete muscle relaxation. Two MC sensors were placed on the right and left sides of the abdomen, and elevated IAP was induced by insufflating CO into the peritoneal cavity. IAP measurements from the MC sensors were compared to the randomized IAP values set on the CO insufflator. Data from both methods were analyzed to assess the accuracy and agreement with the insufflator measurements. The MC sensor provided continuous and accurate detection of IAP changes. A Pearson correlation coefficient of 0.963 indicated a strong positive linear correlation between the MC sensor readings and the IAP values set on the insufflator. The coefficient of determination (R) was 0.927, showing that the model explains 92.7% of the variation in IAP values based on the MC sensor signals. Receiver operating characteristic analysis demonstrated that the MC sensor system performed exceptionally well in identifying both IAH and ACS cases, with an area under the curve of 0.996 for IAH and 0.981 for ACS. The study introduces a transcutaneous pressure measuring device as an innovative, non-invasive method for assessing IAP. The system strongly correlates with IAP values measured by CO insufflation, indicating its accuracy. It thus could present an alternative to conventional IAP measurement in the future. The MC capability to deliver real-time, continuous data holds substantial potential for proactive patient care. By incorporating advanced analytics like machine learning, the system could detect trends and provide early warnings of dangerous IAP changes, enabling timely, targeted interventions to enhance outcomes for critically ill patients.
监测重症患者的腹内压（IAP）对于预防腹内高压（IAH）和腹腔间隔室综合征（ACS）及其严重后果至关重要。本研究中引入的肌肉收缩传感器（MC）基于先前的研究结果，提供了一种新颖的、具有良好准确性的非侵入性方法。本研究进一步评估了MC的准确性和可重复性，并检验了其与通过二氧化碳注入器获得的客观IAP测量值之间的相关性。我们纳入了41例在全身麻醉下进行择期腹腔镜胆囊切除术且肌肉完全松弛的患者。将两个MC传感器放置在腹部的右侧和左侧，并通过向腹腔内注入二氧化碳来诱导IAP升高。将MC传感器测得的IAP测量值与二氧化碳注入器上随机设置的IAP值进行比较。对两种方法的数据进行分析，以评估其准确性以及与注入器测量值的一致性。MC传感器能够连续、准确地检测IAP变化。皮尔逊相关系数为0.963，表明MC传感器读数与注入器上设置的IAP值之间存在强正线性相关。决定系数（R）为0.927，表明该模型基于MC传感器信号解释了IAP值变化的92.7%。受试者工作特征分析表明，MC传感器系统在识别IAH和ACS病例方面表现出色，IAH的曲线下面积为0.996，ACS的曲线下面积为0.981。该研究引入了一种经皮压力测量装置，作为一种创新的、非侵入性的评估IAP的方法。该系统与通过二氧化碳注入测量的IAP值高度相关，表明其准确性。因此，它未来可能成为传统IAP测量的替代方法。MC提供实时、连续数据的能力在主动式患者护理方面具有巨大潜力。通过纳入机器学习等先进分析方法，该系统可以检测趋势并提供危险IAP变化的早期预警，从而能够及时进行有针对性的干预，以改善重症患者的治疗效果。
