Key words : Key words: Cardiac output, Cardiovascular function, Central venous pressure, Hemodynamic parameters

Introduction
Liver transplantation is a definitive therapeutic intervention for patients with end-stage liver disease, offering a chance to improve their quality of life.¹ However, the perioperative period surrounding liver transplant presents intricate hemodynamic challenges that can greatly influence patient outcomes. Currently, cardiovascular resuscitation options are triggered by arterial pressure and cardiac output (CO) measures, which have focused on the oxygen delivery side of circulation.² The venous side of the circulation described by Starling and Bayliss as early as the 19th century has received less attention in daily practice because of the inability to appropriately assess the venous side of circulation at the bedside or in the operating room.³

The primary determinant of CO is the venous side. Veins are 30 to 50 times more compliant than arteries and contain approximately 75% of the total blood volume.⁴ Mean systemic filling pressure (MSFP) provides vital information on the venous side of circulation. Mean systemic filling pressure is defined as the pressure that would be measured if the heart should stop pumping and all the pressures (arterial and venous) in the entire circulatory system should be brought to equilibrium instantaneously.⁵ The total intravascular blood volume consists of the unstressed volume, which fills the blood vessels without causing intravascular pressure, and the stressed volume, which stretches the blood vessels, causing a distending pressure on the vascular walls and reflecting the effective circulating volume. Unstressed volume and stressed volume together define the total blood volume. Stressed volume is approximately 25% of the total blood volume. The pressure in the stressed volume amounts to the MSFP.⁵

To drive blood into the heart, a peripheral vascular pressure that exceeds the right atrial pressure (RAP) or central venous pressure (CVP) must exist. This peripheral vascular pressure is the MSFP, and the pressure gradient between the MSFP and RAP determines venous return (VR). When RAP or CVP is further increased, VR declines until it ceases. Venous return and CO can thus be formulated as follows: CO and VR = (MSFP – CVP)/resistance to VR.⁶ Mean systemic filling pressure is a fundamental parameter that reflects the balance between VR and CO; MSFP reliably reflects the total intravascular fluid compartment, thereby dictating cardiac preload and overall tissue perfusion.

The intricacies of liver transplant involve a complex interplay of factors, such as fluid shifts, alterations in SVR, and changes in cardiac contractility.⁷ Three methods have been described to record MSFP, with MSFParm defined as involving circulatory stop flow using rapid occlusion of the circulation in the arm for 60 seconds. Once the arterial and venous pressures in the arm equilibrate, the pressure measured is the MFSP.⁸ To our knowledge, no study has explored the trends and implications of MSFP alterations in patients with cirrhosis undergoing liver transplant. In this observational pilot study, we aimed to bridge the existing knowledge gap by investigating the dynamic changes in MSFP among liver transplant recipients during the perioperative period and to elucidate patterns of MSFP and the relationship between MSFP and other clinical parameters. We aimed to unravel the role of MSFP as an indicator of cardiovascular response to multifaceted challenges associated with liver transplant.

Materials and Methods
This prospective observational pilot study was conducted in a tertiary care hospital from May 2020 to October 2020 after we obtained approval from the Institutional Ethics Committee (approval number: IEC/2020/75/NA04). We registered the study with ClinicalTrials.gov (NCT04462874). We obtained written informed consent from all patients in accordance with the principles of the Declaration of Helsinki. At our institute, living liver donations are accepted from spouses and from other relatives up to the third degree of kinship, which includes parents, children, siblings, grandparents, uncles, and aunts. Donor eligibility was limited to the age of 60 years. Patients who refused to participate, pregnant patients, patients with acute liver failure, patients with creatinine clearance <30 mL/min, patients with preexisting severe cardiac disease, and patients with combined liver and kidney transplants were excluded.

We included 20 patients (aged 18-65 y) who underwent living related donor liver transplant. The primary outcome was observed trends of MSFP at various stages of living donor liver transplant surgery. Secondary outcomes were the correlations between MSFP and various hemodynamic parameters, such as heart rate, CVP, mean arterial pressure (MAP), CO, SVR, and stroke volume variation (SVV), and to correlate baseline MSFP with intraoperative fluid requirement, blood loss, lactate at the end of surgery, and blood products used.

All patients underwent a standardized anesthesia technique during liver transplant. After endotracheal intubation, mechanical ventilation was initiated in volume control mode and ventilated with a tidal volume of 8 mL/kg and a positive end-expiratory pressure of 5 cm H2O. Anesthesia was maintained with fentanyl infusion (1-2 µg/kg/min) along with isoflurane, and muscle relaxation was achieved with atracurium infusion (0.5 mg/kg/min). Invasive vascular lines, including a 9F advanced vascular access and 8.5F 4-lumen CVP catheter, were inserted into the right internal jugular vein under ultrasonograph guidance. A 20-gauge arterial cannula was inserted into the radial artery for invasive real-time arterial pressure monitoring, sample retrieval for arterial blood gas analysis, and for CO monitoring using a FloTrac™/Vigileo™ system (Edwards Lifesciences, Irvine, CA, USA) device. A 20-gauge intravenous cannula was placed on the same forearm as the radial artery cannula.

Patients underwent liver transplant in a single surgical unit and with widely accepted surgical procedures. All patients received grafts from living related donors, and the selection was either right or left hemi-liver, depending on the estimated graft-to-recipient weight ratio and residual liver volume in the donor. Patient management was guided by the liver transplant protocol at our institute. Packed red blood cells were administered to maintain hemoglobin level between 7 and 8 g/dL. Fresh frozen plasma, cryoprecipitate, and platelets were replaced under thromboelastographic guidance to improve intraoperative coagulopathy. Vaso-pressors (usually a norepinephrine starting dose of 0.1 ?g/kg/min) were administered when there was hemodynamic instability, usually when MAP was <60 mm Hg.

Administered fluids were based on the body weight and the institutional protocol and at the decision of the care provider, who was blinded to the study. Crystalloids were PlasmaLyte™ and 0.9% normal saline, and colloid was 5% albumin. After transplant, patients were transferred to the intensive care unit and sedated with propofol and fentanyl infusion. Tracheal extubation and postoperative care were performed according to the standard protocols. Hemodynamic parameters, including MSFP, MAP, CVP, SVR, CO, SVV, and heart rate, were measured after induction and hourly thereafter until the end of surgery. Intraoperative data related to the amount of crystalloid, colloid, and blood products transfused and lactate levels at the end of surgery were recorded for all patients.

The measurement of MSFP was performed using the MSFParm technique as previously described.⁸ For arm occlusion, a pneumatic tourniquet was inflated around the upper arm to 50 mm Hg above the systolic blood pressure for 60 seconds. Arterial and venous pressures were measured using a radial artery catheter and peripheral venous cannula in the forearm. When these 2 pressures were equalized after tourniquet inflation, the MSFParm values were obtained. The dissection phase was defined as the time from skin incision to clamping of the hepatic veins that followed the portal vein and hepatic artery. The anhepatic phase was from the moment the hepatic venous outflow was clamped up to graft reperfusion, and the neo-hepatic phase began from the moment liver reperfusion was established.

Statistical analyses
We presented normally distributed continuous data as mean ± SD and skewedly distributed data as median with interquartile range (IQR). We presented categorical data as percentages. We compared continuous variables across the 3 phases of transplant with analysis of variance. We analyzed correlations between continuous variables by using the Pearson correlation coefficient, with r values from 0.80 to 1.00 indicating perfect correlation, 0.50 to 0.79 indicating strong correlation, 0.30 to 0.49 indicating moderate correlation, and 0.00 to 0.29 indicating weak correlation. P < .05 indicated significance. We divided patients into 2 groups according to their MSFP, with the 75th percentile as the cut-off. We compared continuous variables by using the Mann-Whitney U test and categorical variables by using ?2 or Fisher exact tests. Although not a typical indication, we used the Bland-Altman plot to determine the relationship between CVP and MSFP (online generated). We used IBM SPSS Statistics for Windows version 26.0 (released 2019; IBM Corp) to perform statistical analyses.

Results
Of 24 patients enrolled, 4 patients were excluded, with the remaining 20 patients eligible for analysis (Figure 1). We divided patients into 2 groups according to their baseline MSFP by using the 75th percentile as the cut-off (42 mm Hg), with 14 patients in the low MSFP group and 6 patients in the high MSFP group. Median patient age was 49 years (IQR, 47-56 y) (Table 1). Patients in the high MSFP group tended to be younger (43 years [IQR, 42-48] vs 50 years [IQR, 47-56]; P = .01). The overall cohort included more male patients than female patients, and chronic liver disease from ethanol consumption was the most common etiology of liver disease. Patients with ethanol (50%) and other etiologies (50%) had a higher incidence of high MSFP than those with nonalcoholic steatohepatitis (0%; P = .04). Most patients had jaundice and ascites. The median Model for End-Stage Liver Disease (MELD) score was 25 (IQR, 21-28). Severity of liver disease, as measured by MELD, and the incidence of decompensations were similar in both groups. With regard to intraoperative details (Table 2), crystalloid requirement during the intraoperative period was lower in patients with a high MSFP (6250 mL [IQR, 5000-7000] vs 7500 mL [IQR, 6500-9000]; P = .04). Median blood loss was 1900 mL, which was similar in both groups. Blood product requirements were comparable between the groups.

The mean MSFP at baseline was 35.7 ± 8.6 mm Hg. We obtained 114 MSFP values in the dissection phase, 39 in the anhepatic phase, and 40 in the neo-hepatic phase. Mean MSFP results in the dissection, anhepatic, and neo-hepatic phase were 31.1 ± 8.3, 26.7 ± 5.8, and 27.9 ± 6.1 mm Hg, respectively (P = .002). As surgery progressed, the MSFP decreased and reached its nadir in the anhepatic phase, with a mean MSFP of 26.7 ± 5.8 mm Hg, and then increased in the neo-hepatic phase to a mean of 27.9 ± 6.1 mm Hg (Table 3 and Figure 2). Baseline values of other hemodynamic parameters are listed in Table 4.

Patient age and disease severity (MELD) did not correlate with baseline MSFP. Baseline MSFP did not correlate with intraoperative blood and blood products transfusion. Baseline MSFP and lactate levels at the end of surgery had a significant negative correlation (r = -0.69, P < .001), and baseline MSFP had a moderate negative correlation with intraoperative crystalloid use (r = -0.46, P = .048). The baseline CVP was significantly correlated with the baseline MSFP (r = 0.69, P < .001) (Table 5). We observed that MSFP correlated weakly with MAP (r = 0.37, P = .10) and SVR (r = 0.36, P = .12) and correlated negatively with baseline CO (r = -0.54, P = .01). We found that MSFP correlated poorly with SVV (r = 0.15, P = .51). Throughout surgery, MSFP values correlated positively with CVP (r = 0.69, P = .001) (Figure 3) and negatively with CO (r = -0.53, P = .015) (Figure 4).

The inverse relationship between CO and MSFP was in contrast to the existing literature; thus, we performed additional analyses to explore this finding. From the regression equation, we arrived at the following formula: expected CVP = 1.68 + (0.27 × MSFP). The correlation between the observed and expected CVP had an r value of 0.62 (P ? .001). Although the observed and expected values were not well correlated, we applied the Bland-Altman plot to check for the scattering pattern between the observed and expected CVP. We could not compare MSFP and CVP because of their difference in the normal range; hence, we used expected CVP as a surrogate of MSFP to observe its behavior with extremes of CVP. At high values, the observed values were higher than the expected CVP values; at the low values, the observed values were lower than the expected CVP values (Figure 5). In short, as we faced a high CVP, the increase in CVP would be greater than that extrapolated from MSFP.

Discussion
Mean systemic filling pressure has been studied in patients undergoing cardiac surgery. Maas and colleagues determined the baseline MSFP using the MSFParm technique as 19.8 ± 5.7 mm Hg in patients undergoing cardiac surgery.⁹ Similarly, in other studies involving cardiac surgery, the mean baseline MSFP was between 9 and 23 mm Hg.^10-12 To our knowledge, there are no data on MSFP in patients with liver cirrhosis. Our present study showed a baseline MSFP of 35.7 ± 8.6 mm Hg, which is much higher than that reported in patients undergoing cardiac surgery. Liver cirrhosis presents with altered systemic hemodynamics, described as a hyperdynamic state characterized by high CO, large blood volume, and low total peripheral resistance.¹³ We hypothesized that this increase in blood volume could be the cause for the higher values of baseline MSFP, with blood shifting from the unstressed compartment to the stressed compartment in patients with cirrhosis, thus causing a higher baseline MSFP.

We observed that MSFP tended to decrease with progression of liver transplant surgery and reached its nadir in the anhepatic phase, with a mean MSFP of 26.7 ± 5.8 mm Hg and then increased in the neo-hepatic phase. The MSFP had a strong positive correlation with CVP and a moderate negative correlation with CO during surgery.

The decrease in MSFP values as surgery progressed from the dissection phase to the anhepatic phase could be because of blood loss in the dissection phase, which is a common occurrence in this phase.¹⁴ Blood loss and clamps in portal vein and inferior vena cava might have caused a shift of blood from stressed volume, resulting in the observed drop in MSFP during this phase.⁵ The increased MSFP in the postreperfusion stage could be attributed to the release of clamps on the portal and hepatic veins during reperfusion, leading to increased blood volume.

We observed a positive correlation between MSFP and CVP values throughout surgery; as the MSFP decreased, CVP decreased and vice versa. In contrast, MSFP showed a negative correlation with CO throughout surgery; this finding is in contrast to the known literature, which states that CO or VR depends on the differential pressure (MSFP – RAP). To understand this, we must understand the Guyton concept, which states that the heart plays a permissive role rather than being the sole organ to regulate CO. According to the Guyton concept, the heart pumps as much blood as it receives, within the limits of intrinsic contractility and heart rate.¹⁵ This finding was later demonstrated in an animal model by the same team.¹⁶ The investigators explained that the amount of blood that the heart receives is dependent on the driving force, that is, the elastic recoil of the vessels, which Guyton named as “mean circulatory filling pressure.” Mean circulatory filling pressure is the pressure in the vascular system when there is no blood flow. Mean systemic filling pressure is the same, but in the systemic circulation and excludes the cardiopulmonary system. The difference between mean circulatory filling pressure and MSFP is negligible and is often used interchangeably in the literature.

In an example by Henderson and colleagues,¹⁷ the rate at which a bathtub empties is dependent on the height of water in the tub (potential energy), the tub drain’s characteristics (resistance), and finally the pressure downstream of the drain. In this analogy, the inflow tap may be thought of as arterial pressure and flow, the level of water in the tub as MSFP (the elastic recoil in the system), the drain as venous resistance to flow, and the sewer pipes as RAP. If the downstream pressure is the same as the pressure in the tub due to water logging in the sewer pipes, the tub will not empty quickly. Analogously, when the pressure downstream (RAP) is equal to MSFP, there is no flow; flow can occur only when MSFP is greater than RAP.

As MSFP increases or decreases, a concomitant increase or decrease should occur in CO. If RAP (or CVP) is low and MSFP is high, there is a maximum difference in the pressure and maximum return of blood to the right heart. On the other hand, if RAP increases but MSFP does not change, then there will be a small difference between the 2 variables, and VR will decrease. In our study, we observed a positive correlation between CVP and MSFP; hence, any decrease or increase in MFSP might have been offset by the concomitant alteration in CVP, resulting in a negative correlation between MSFP and CO at a higher MSFP range, as observed in our patient cohort.

From the regression equation, we arrived at the following formula: expected CVP = 1.68 + (0.27 × MSFP). Thus, at higher values, the observed values were higher than those of expected CVP (what we extrapolated from the MSFP). This phenomenon of overshooting CVP at the higher ends might have reduced the difference between MSFP and CVP and, hence, the CO. This overshooting CVP at the higher ends could be due to the diastolic dysfunction that is seen in patients with liver disease, which is seen in 25% to 81% of patients according to different studies.^18,19 Because VR is the difference between MSFP and CVP (ie, RAP), sometimes the increase in CVP might have been much higher than the expected CVP; hence, we could have faced a suboptimal increase in VR at higher MSFP and CVP, which might explain the poor and the negative correlation with CO. Second, in patients with or without diastolic dysfunction, the heart might be operating in the flatter portion of the Frank-Starling curve; hence, CO responded poorly to increasing CVP or MSFP. Third, there are some criticisms and controversies regarding the Guyton model of VR-regulated CO. The contractility and SVR components cannot be ignored. For the changes in CO, there cannot be a single factor, but a dominant pathology occurring but still mixed with other factors that regulate CO. These speculations are supported by the explanation provided by Magder while decoding the Guyton approach.²⁰ Fourth, in the Guyton equation for VR, the denominator is venous resistance, which was not taken into account. Any increase in venous resistance would offset the difference between the MSFP and RAP. Another reason could be the method used to measure the CO. We utilized the Flotrac Vigilio device, which is an uncalibrated technology. Calibrated CO monitoring like pulse index contour continuous cardiac output (PiCCO; Pulsion Medical Systems, Munich, Germany) is not routinely used at our center because it is an invasive procedure. Although this is a calibrated method, puncturing the femoral artery in coagulopathic patients would not be optimal. Hence, the interpretation of the current observations should be confirmed by other methods, if possible, in the future.

Another interesting fact is that MSFP did not correlate with SVV. As mentioned, patients may have been at different parts of the Frank-Starling curve. Even at low levels of preload, sometimes patients might reach the flat part of the curve, which might have led to the poor correlation between MSFP and SVV. This finding was reinforced by the fact that the optimal cut-off of MSFP predicting fluid responsiveness was 14 mm Hg in a study involving patients without liver disease undergoing surgery for gastric, colonic, or rectal cancer.²¹ The mean value of MSFP in our study population was 35.7 ± 8.6 mm Hg, which is more than double the optimal cut-off; this value may have affected the correlation with SVV because of the difference in the operating part of the Frank-Starling curve.

We observed a negative correlation between baseline MSFP and lactate levels at the end of surgery. Similarly, we observed a negative correlation between baseline MSFP and crystalloids used intraoperatively in our study patients, indicating that patients with low MSFP might require more crystalloids intraoperatively to achieve the desired hemodynamic goals.

Venous return plays a major role in maintaining intraoperative hemodynamics; thus, its determinants (MSFP, CVP, and resistance to VR) are major hemodynamic variables. Although the determinants of VR have been well-examined in animal studies, MSFParm is an easy and reproducible maneuver for measuring MSFP in the operating room or intensive care unit. Normal values for different patient populations must be defined before MSFP can be implemented in standard care. Changes in MSFP values after fluid administration need to be studied further because they depend on vascular redistribution, vasomotor tone, and fluid loss into the interstitial space. Further studies that focus on clinical decision-making based on MSFP changes in fluid administration and vasopressor use are needed; further studies are also needed to examine whether interventions based on these measures can improve outcomes. Mean systemic filling pressure may not serve as an easy bedside marker for fluid responsiveness but may provide insights into understanding the volume status and altered physiology in patients with chronic liver disease. Further research involving larger cohorts and potential interventions is warranted to validate and expand on these findings.

This study had some limitations. First, this was a single-center study with a limited number of patients. Further studies are needed to establish the baseline MSFP values in this cohort of patients. Second, we did not analyze the effects of fluid boluses and vasopressor use on MSFP; further studies with larger number of patients are required. In addition, we did not analyze outcomes such as kidney injury, sepsis, duration of need for mechanical ventilation, and mortality, which would have provided more knowledge on MSFP. This study aimed to elucidate the physiology of patients with cirrhosis undergoing transplant. Another limitation is that the reason for the inverse correlation between MSFP and CO could not be elicited to the exact point. We measured CO by using uncalibrated pulse contour analysis, which is not the gold standard method. We do not prefer placing a femoral arterial line in coagulopathic patients; hence, a limitation is that we did not use calibrated or gold standard CO monitors, such as PiCCO or pulmonary artery catheters. Further studies with more reliable CO monitoring are required.

Conclusions

Baseline MSFP values in patients with liver cirrhosis were higher than those in patients who underwent cardiac surgery. Throughout liver transplant surgery, MSFP values tended to decrease during the anhepatic phase and increase in the neo-hepatic phase, with changes likely influenced by factors such as blood loss, reperfusion, and fluid administration. A strong positive correlation was observed between MSFP and CVP throughout the surgery; however, the expected positive correlation between MSFP and CO was not observed.

References:

1. Miró JM, Laguno M, Moreno A, Rimola A; Hospital Clinic OLT in HIV Working Group. Management of end stage liver disease (ESLD): what is the current role of orthotopic liver transplantation (OLT)? J Hepatol. 2006;44(1 Suppl):S140-S145. doi:10.1016/j.jhep.2005.11.028
   CrossRef - PubMed
   
2. Cherpanath TG, Geerts BF, Lagrand WK, Schultz MJ, Groeneveld AB. Basic concepts of fluid responsiveness. Neth Heart J. 2013;21(12):530-536. doi:10.1007/s12471-013-0487-7
   CrossRef - PubMed
   
3. Bayliss WM, Starling EH. Observations on venous pressures and their relationship to capillary pressures. J Physiol. 1894;16(3-4):159-318. doi:10.1113/jphysiol.1894.sp000498
   CrossRef - PubMed
   
4. Guyton AC, Hall JE. Cardiac output, venous return, and their regulation. In: Schmitt W, Gruliow R, eds. Textbook of Medical Physiology. 10 ed. W.B. Saunders Company; 2000:210-122.
   CrossRef - PubMed
   
5. Maas JJ. Mean systemic filling pressure: its measurement and meaning. Neth J Crit Care. 2015;19(1):6-11.
   CrossRef - PubMed
   
6. Guyton AC, Lindsey AW, Abernathy B, Richardson T. Venous return at various right atrial pressures and the normal venous return curve. Am J Physiol. 1957;189(3):609-615. doi:10.1152/ajplegacy.1957.189.3.609
   CrossRef - PubMed
   
7. Rudnick MR, Marchi LD, Plotkin JS. Hemodynamic monitoring during liver transplantation: a state of the art review. World J Hepatol. 2015;7(10):1302-1311. doi:10.4254/wjh.v7.i10.1302
   CrossRef - PubMed
   
8. Wijnberge M, Sindhunata DP, Pinsky MR, et al. Estimating mean circulatory filling pressure in clinical practice: a systematic review comparing three bedside methods in the critically ill. Ann Intensive Care. 2018;8(1):73. doi:10.1186/s13613-018-0418-2
   CrossRef - PubMed
   
9. Maas JJ, Pinsky MR, Geerts BF, de Wilde RB, Jansen JR. Estimation of mean systemic filling pressure in postoperative cardiac surgery patients with three methods. Intensive Care Med. 2012;38(9):1452-1460. Published correction appears in Intensive Care Med. 2013;39(1):163. doi:10.1007/s00134-012-2586-0
   CrossRef - PubMed
   
10. Geerts BF, Maas J, de Wilde RB, Aarts LP, Jansen JR. Arm occlusion pressure is a useful predictor of an increase in cardiac output after fluid loading following cardiac surgery. Eur J Anaesthesiol. 2011;28(11):802-806. doi:10.1097/EJA.0b013e32834a67d2
    CrossRef - PubMed
    
11. Aya HD, Rhodes A, Fletcher N, Grounds RM, Cecconi M. Transient stop-flow arm arterial-venous equilibrium pressure measurement: determination of precision of the technique. J Clin Monit Comput. 2016;30(1):55-61. doi:10.1007/s10877-015-9682-y
    CrossRef - PubMed
    
12. Aya HD, Rhodes A, Chis Ster I, Fletcher N, Grounds RM, Cecconi M. Hemodynamic effect of different doses of fluids for a fluid challenge: a quasi-randomized controlled study. Crit Care Med. 2017;45(2):e161-e168. doi:10.1097/CCM.0000000000002067
    CrossRef - PubMed
    
13. Kim MY, Baik SK. Hyperdynamic circulation in patients with liver cirrhosis and portal hypertension. Korean J Gastroenterol. 2009;54(3):143-148. doi:10.4166/kjg.2009.54.3.143
    CrossRef - PubMed
    
14. Pandey CK, Singh A, Kajal K, et al. Intraoperative blood loss in orthotopic liver transplantation: the predictive factors. World J Gastrointest Surg. 2015;7(6):86-93. doi:10.4240/wjgs.v7.i6.86
    CrossRef - PubMed
    
15. Guyton AC, Polizo D, Armstrong GG. Mean circulatory filling pressure measured immediately after cessation of heart pumping. Am J Physiol. 1954;179(2):261-267. doi:10.1152/ajplegacy.1954.179.2.261
    CrossRef - PubMed
    
16. Cowley Jr AW, Guyton AC. Heart rate as a determinant of cardiac output in dogs with arteriovenous fistula. Am J Cardiol. 1971;28(3):321-325. doi:10.1016/0002-9149(71)90121-4
    CrossRef - PubMed
    
17. Henderson WR, Griesdale DE, Walley KR, Sheel AW. Clinical review: Guyton--the role of mean circulatory filling pressure and right atrial pressure in controlling cardiac output. Crit Care. 2010;14(6):243. doi:10.1186/cc9247.
    CrossRef - PubMed
    
18. Farouk H, Al-Maimoony T, Nasr A, El-Serafy M, Abdel-Ghany M. Echocardiographic assessment of the left ventricular diastolic function in patients with non-alcoholic liver cirrhosis. Cor Vasa. 2017;59(6):e540-e545. doi:10.1016/j.crvasa.2016.12.011
    CrossRef - PubMed
    
19. Patel RH, Pandya S, Nanjappa S, Greene JN. A case of refractory pulmonary coccidioidomycosis successfully treated with posaconazole therapy. J Fam Med. 2017;4(6):1130. doi:10.26420/jfammed.2017.1130
    CrossRef - PubMed
    
20. Magder S. The use of Guyton’s approach to the control of cardiac output for clinical fluid management. Ann Intensive Care. 2024;14(1):105. doi:10.1186/s13613-024-01316-z
    CrossRef - PubMed
    
21. Hahn R, He R, Li Y. Mean systemic filling pressure indicates fluid responsiveness and anaesthesia-induced unstressed blood volume. Anaesthesiol Intensive Ther. 2022;54(5):369-377. doi:10.5114/ait.2022.121003
    CrossRef - PubMed