scholarly journals Spectral characteristics of the internal jugular vein and central venous pressure pulses: a proof of concept study

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Clive Beggs ◽  
Valentina Tavoni ◽  
Erica Menegatti ◽  
Mirko Tessari ◽  
Riccardo Ragazzi ◽  
...  

In this proof-of-concept study the impact of central venous pressure (CVP) on internal jugular veins cross-sectional area (CSA) and blood flow time-average velocity (TAV) was evaluated in eight subjects, with the aim of understanding the drivers of the jugular venous pulse. CVP was measured using a central venous catheter while CSA variation and TAV along a cardiac cycle were acquired using ultrasound. Analysis of CVP, CSA and TAV time-series signals revealed TAV and CSA to lag behind CVP by on average 0.129 s and 0.138 s, with an inverse correlation between CSA and TAV (r= –0.316). The respective autocorrelation signals were strongly correlated (mean r=0.729-0.764), with mean CSA periodicity being 1.062 Hz. Fourier analysis revealed the frequency spectrums of CVP, TAV and CSA signals to be dominated by frequencies at approximately 1 and 2 Hz, with those >1 Hz greatly attenuated in the CSA signal. Because the autocorrelograms and periodograms of the respective signals were aligned and dominated by the same underlying frequencies, this suggested that they are more easily interpreted in the frequency domain rather than the time domain.

2021 ◽  
Vol 10 (17) ◽  
pp. 3945
Author(s):  
Fridtjof Schiefenhövel ◽  
Ralf F. Trauzeddel ◽  
Michael Sander ◽  
Matthias Heringlake ◽  
Heinrich V. Groesdonk ◽  
...  

Background: Cardiac surgery patients represent a high-risk cohort in intensive care units (ICUs). Central venous pressure (CVP) measurement seems to remain an integral part in hemodynamic monitoring, especially in cardio-surgical ICUs. However, its value as a prognostic marker for organ failure is still unclear. Therefore, we analyzed postoperative CVP values after adult cardiac surgery in a large cohort with regard to its prognostic value for morbidity and mortality. Methods: All adult patients admitted to our ICUs between 2006 and 2019 after cardiac surgery were eligible for inclusion in the study (n = 11,198). We calculated the median initial CVP (miCVP) after admission to the ICU, which returned valid values for 9802 patients. An ROC curve analysis for optimal cut-off miCVP to predict ICU mortality was conducted with consecutive patient allocation into a (a) low miCVP (LCVP) group (≤11 mmHg) and (b) high miCVP (HCVP) group (>11 mmHg). We analyzed the impact of high miCVP on morbidity and mortality by propensity score matching (PSM) and logistic regression. Results: ICU mortality was increased in HCVP patients. In addition, patients in the HCVP group required longer mechanical ventilation, had a higher incidence of acute kidney injury, were more frequently treated with renal replacement therapy, and showed a higher risk for postoperative liver dysfunction, parametrized by a postoperative rise of ≥ 10 in MELD Score. Multiple regression analysis confirmed HCVP has an effect on postoperative ICU-mortality and intrahospital mortality, which seems to be independent. Conclusions: A high initial CVP in the early postoperative ICU course after cardiac surgery is associated with worse patient outcome. Whether or not CVP, as a readily and constantly available hemodynamic parameter, should promote clinical efforts regarding diagnostics and/or treatment, warrants further investigations.


2014 ◽  
Vol 31 (1) ◽  
pp. 50-51 ◽  
Author(s):  
Kasana Raksamani ◽  
Vachira Udompornmongkol ◽  
Suwannee Suraseranivongse ◽  
Manee Raksakietisak ◽  
Benno von Bormann

2020 ◽  
Vol 9 (1) ◽  
Author(s):  
Valentina Tavoni

In this paper an original reasoning about the post processing elaboration of medical studies is presented. The aim is to suggest a method to extrapolate numerical information from clinical images. The here described elaboration is referred to ultrasound examination of internal jugular veins and central venous pressure (CVP) measures. Firstly, the operator has to collect clinical images following precise indications, then specific techniques are applied to analyze the stored data and extrapolate quantifiable measures. Analyzing the studies with ImageJ software, jugular venous pulse, velocity, CVP and electrocardiogram traces can be drown in detail. Then, significant details can be highlighted using Matlab software. Finally, using R software, the traces can be cropped, aligned and synchronized together. The obtained results allow the operator to compare different kinds of traces of the same subject, or the same type of traces between a particular group of subjects. Before using these contents, everyone is invited to verify the accuracy of assumptions, calculations and conclusions.


2011 ◽  
Vol 115 (2) ◽  
pp. 231-241 ◽  
Author(s):  
Maxime Cannesson ◽  
Yannick Le Manach ◽  
Christoph K. Hofer ◽  
Jean Pierre Goarin ◽  
Jean-Jacques Lehot ◽  
...  

Background Respiratory arterial pulse pressure variations (PPV) are the best predictors of fluid responsiveness in mechanically ventilated patients during general anesthesia. However, previous studies were performed in a small number of patients and determined a single cutoff point to make clinical discrimination. The authors sought to test the predictive value of PPV in a large, multicenter study and to express it using a gray zone approach. Methods The authors studied 413 patients during general anesthesia and mechanical ventilation in four centers. PPV, central venous pressure, and cardiac output were recorded before and after volume expansion (VE). Response to VE was defined as more than 15% increase in cardiac output after VE. The following approaches were used to determine the gray zones: resampled and two-graph receiver operator characteristic curves. The impact of changes in the benefit-risk balance of VE on the gray zone was also evaluated. Results The authors observed 209 responders (51%) and 204 nonresponders (49%) to VE. The area under receiver operating characteristic curve was 0.89 (95% CI: 0.86-0.92) for PPV, compared with 0.57 (95% CI: 0.54-0.59) for central venous pressure (P < 10). The gray zone approach identified a range of PPV values (between 9% and 13%) for which fluid responsiveness could not be predicted reliably. These PPV values were seen in 98 (24%) patients. Changes in the cost ratio of VE moderately affected the gray zone limits. Conclusion Despite a strong predictive value, PPV may be inconclusive (between 9% and 13%) in approximately 25% of patients during general anesthesia.


2019 ◽  
Author(s):  
Li Hong Peng ◽  
Lin Ying Ning ◽  
Cheng Zhi Hui ◽  
Qu Wei ◽  
Zhang Liu ◽  
...  

Abstract Background: Mechanical ventilation (MV) with positive end-expiratory pressure (PEEP) is commonly applied in patients with severe traumatic brain injury (sTBI). However, non-indicators to predict the influence of PEEP on intracranial pressure (ICP) prevent the optimal use of PEEP. As the central venous pressure (CVP) could act as an intermediary to transduce the pressure from PEEP to ICP, we set up a new indicators PICGap (representing the gap between the baseline ICP and baseline CVP). The aim of the study was to explore the relationship between PICGap and the ICP responsiveness to PEEP. Methods: Total 112 patients with sTBI undergoing MV were finally enrolled. ICP, CVP, cerebral perfusion pressure (CPP), static compliance of respiratory system (Cst), and end-tidal carbon dioxide pressure (PetCO2) were recorded at initial level of PEEP (3 cmH2O) and adjusted levels of PEEP (15 cmH2O). PICGap was calculated by baseline ICP - baseline CVP (when PEEP=3 cmH2O). The patients enrolled were classified into either an ICP responder group or a non-responder group based on whether the increment of ICP when PEEP adjustment from 3 cmH2O to 15 cmH2O was greater than or less than 20% of baseline ICP. Parameters recorded above were compared between two groups and the prediction of ICP responsiveness to PEEP adjustment were evaluated by receiver operating characteristic (ROC). Results: Responder group had lower PICGap, lower baseline ICP, and higher baseline CVP compared with non-responder group. ROC analysis suggested that PICGap could act as a strongest predictive indicator for the ICP responsiveness to PEEP (AUC = 0.957, 95% CI: 0.918 - 0.996, p <0.001) compared with baseline ICP and baseline CVP, with a favorable sensitivity of 95.24% (95% CI: 86.91% - 98.70%) and specificity of 87.6% (95% CI: 75.76% - 94.27%) when the cut off value of 2.5mmHg was determined. Conclusion: The impact of PEEP on ICP depends on the GAP of between baseline ICP and baseline CVP, i.e. PICGap. The PICGap could be a potential predictor for ICP responsiveness to PEEP adjustment in patients with sTBI.


2021 ◽  
Vol 13 (2) ◽  
pp. 88-98
Author(s):  
Buyung Hartiyo Laksono ◽  
Arie Zainul Fatoni ◽  
Vilda Prasastri Yuwono ◽  
Aswoco Andyk Asmoro

Latar belakang: Pengukuran central venous pressure (CVP) merupakan salah satu metode guiding deresusitasi pada pasien dengan kasus tertentu. Kenaikan nilai CVP 1 mmHg dikaitkan dengan peningkatan angka kejadian acute kidney injury (AKI). Namun sebagai sebuah metode yang invasif, pemasangan CVP memiliki risiko yang perlu diperhatikan. Di sisilain, pengukuran diameter dan indeks IVC yang bermuara di atrium kanan dengan menggunakan ultrasonografi (USG) non-invasif dinilai mampu untuk memprediksi nilai CVP pada pasien. Namun beberapa penelitian hubungan antara CVP dengan diameter dan indeks IVC memberikan hasil yang kontroversial.Tujuan: Penelitian untuk mengetahui hubungan antara nilai CVP dengan diameter dan indeks IVC.Metode: Penelitian ini menggunakan metode cross-sectional pada 30 pasien yang dilakukan ventilasi mekanik dan pemasangan CVC di unit perawatan intensif. Parameter CVP, diameter minimum dan maksimum inferior vein cava (IVC mak, IVC min), distensibillity index (DI-index), dan aortacaval index (Cava/Ao index) diukur. Data dianalisis menggunakan uji korelasi pada SPPS 18.0 (p<0.05).Hasil: Didapatkan korelasi signifikan antara CVP dan semua variabel yang diuji (IVC mak, IVC min, DI-index, dan Cava/Ao index) (p<0.05), dengan korelasi terkuat antara CVP dan IVC min (R= 0,908). Korelasi bersifat positif, kecuali antara DI-index dan CVP.Kesimpulan: Parameter IVC min, IVC mak, Cava/Ao- index, dan DI-index signifikan berkorelasi kuat dengan CVP. Korelasi terjadi bersifat positif, kecuali antara DI-index dan CVP.


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