Considering “Trifecta” as a Single Outcome when Comparing Robotic With Open Partial Nephrectomy: A Mathematical Model of Volume Conservation and Systematic Review

Materials and Methods

Methodology. Initially, a systematic literature search was carried out, for all studies that compare RPN/RAPN and OPN and highlight differences in the frequency of the composite outcome of trifecta achievement. The first objective included the investigation of all definitions attributed to the trifecta concept, and their classification at the minimum number of clusters. The second goal of the study was to highlight the feasibility of the complex “trifecta outcome” as a single parameter. This process aimed to investigate whether a quantitative representation of the comparative effect between the robotic and open approaches for partial nephrectomy on the “trifecta outcome”, as a single qualitative parameter, is possible from subsequent studies. The methodology was divided into four distinct parts. The first part concerns the literature search and the isolation of a set of relevant comparative studies, with data that can be used for estimating the comparative effect between the robotic and open approach in partial nephrectomy procedures as for the “trifecta outcome” frequency of achievement. The second part includes the process of grouping the studies based on the two main definitions found to prevail in the international literature concerning trifecta. The third part reflects the backbone of our analysis where we modeled partial nephrectomy with volume conservation equations in order to investigate by using mathematical notations whether or not the two main definitions can be reduced to a single conceptual parameter. In the fourth part, the relevant results of analytical procedure are presented, as well as the necessary conclusions for the potential of comparatively utilizing the respective trifecta achievement rates when examining the application of the robotic over the conventional open approach in partial nephrectomy.

Data acquisition. Regarding the first and second part of this study, a search of electronic databases was carried out using the keywords: “open”, “robotic”, “robot-assisted”, “partial nephrectomy”. The inclusion criteria were: studies only in the English language, comparative studies examining robotic or robot-assisted partial nephrectomy versus the open approach, comparative studies with useful data in both parts of the comparison for further statistical analysis, and also comparative studies which include cost analysis. The exclusion criteria were: studies that are not in English, studies that were retrieved only in the form of a summary or reports without the accompanying data or the necessary text, non-comparative studies, comparative studies with insufficient data for further statistical analysis, comparative studies which include data for only one part of the comparison, studies including patient populations with solitary kidney, and lastly studies involving pediatric patients.

The literature search procedure included all available comparative studies until December 2021. This process aimed at the extraction of all relevant reports from the “Google scholar”, “PubMed”, and the “CENTRAL” databases. Finally, and regarding the above, the open-source “R” programming language version: 4.2.0 (12), along with the “OriginPro 2017^®” (13) and the “Visible Body 3D^®” (14, 15) modeling software were used to configure the necessary graphical representations.

The “trifecta outcome” has been a real challenge in terms of content analysis as it is related to the adequacy of surgical treatment in the context of partial nephrectomy, which makes it an extremely important parameter for this intervention; however, the definition used by researchers in the international literature is not strictly defined. During the overview of the available literature, it was possible to derive two dominant definitions regarding trifecta. According to the first definition, the absence of positive surgical margins and complications and the absolute percentage decrement in the estimated glomerular filtration rate (|ΔeGFR|) by less than or equal to 10% were incorporated in the trinity of the trifecta concept (3, 16-18). On the other hand, according to the second definition, the trinity of the trifecta outcome included the absence of positive surgical margins and complications as well as duration of ischemia time (IT) less than 25 min (2, 19-23). In the present study, we considered valid the view of Zargar and his colleagues (11), according to which both definitions mentioned above correspond to the same basic concept, which is the effectiveness of surgery in partial nephrectomy for small renal tumors and the degree of recovery of renal function in the postoperative period. In order to mathematically investigate the interconnection between two definitions we worked successively on three different levels. At the first level, a model based on the principle of volume conservation was defined and the related equations were constructed appropriately. At the second level, a series of mathematical expressions and relationships between the variables of interest were formulated, as derived from data available in the literature. Finally at the third level, the proportionality expressions that will have already been formulated are written in the form of proper equations in order to finally arrive at our definitive conclusions.

Volume conservation model. The volume conservation principle-based model is shown in Figure 1. This figure shows the area of the tumor (V_tumor) which is incorporated into the resection volume corresponding to the volume of the surgical specimen (V_specimen) as well as the area of the renal parenchyma around the resection site, whose functionality is considered to be extremely reduced, even down to zero, due to the application of ischemia (V_ischemia). Equation 1 describes the baseline volume balance between preoperative (V_preoperative) and postoperative (V_{postoperative}) renal parenchyma.

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Figure 1.

Schematic representation of the renal parenchyma zones that are functionally affected after partial nephrectomy surgery. Green color corresponds to the tumor volume (V_tumor), yellow corresponds to the resection volume (V_specimen) and blue corresponds to the remaining renal parenchyma around the resection site, with reduced functionality due to previous application of some type of ischemia (V_ischemia). The anatomical 3D model was created via the Visible Body 3D^® software.

(1)

In this equation the difference in renal parenchymal volume pre- and post-surgery equals the volume of the removed surgical specimen. Subsequently, in Equation 2, a distinction is made regarding the postoperative renal parenchyma volume (V_{postoperative}), in functional (V_{postop.functional}) and non-functional (V_{postop.non functional}) parenchyma.

(2)

According to Mir et al., V_{postoperative} is the determining factor for maintaining renal function postoperatively. However, ischemia also plays a prominent role in this connection, as it has been found that post-ischemia nephrons recovery is not complete (24). In another study, Simmons et al. claim that the loss of functional renal tissue is mainly due to resection (V_specimen) and not to the volume of the ischemic zone (V_ischemia). According to the same authors, the above two parameters practically begin to acquire the same order of magnitude after the application of at least 40 minutes of ischemia (25). In fact, it is noted that ischemia leads mainly to loss of functionality without a corresponding loss of volume, with this effect being characterized as reduction in the glomerular density (GD) (26). Based on the above, and according to Bechara et al., it follows that around the resection site a volume-stable zone of ischemic renal parenchyma is formed, which is particularly evident after the application of both arterial and venous clamping (27). This technique is used in a significant number of partial nephrectomy procedures with the aim of limiting intraoperative blood loss (28-31). At this point, it was hypothesized that ischemia reflects the main mechanism responsible for the loss of functional renal parenchyma around the resection site, being caused either by applying hemostasis locally with heat release, or by proximal vascular clamping during the operation. Therefore, under this assumption, Equation 3 was derived.

(3)

Substituting Equation 3 into Equation 2 finally yields Equation 4, that identifies the preoperative renal parenchymal volume (V_preoperative) as a function of the remaining functional renal parenchyma postoperatively (V_{postop.functional}), the zone of virtually zero renal parenchymal functionality due to ischemia (V_ischemia), as well as the volume of the surgical specimen (V_specimen).

(4)

Rearranging the terms of Equation 1 and utilizing Equation 4 finally leads to Equation 5.1. The latter identifies the postoperative renal parenchyma volume as a function of the preoperative renal parenchyma and the specimen volume (V_preoperative, V_specimen), as well as the residual functional parenchyma and the ischemic zone volume (V_{postop.functional}, V_ischemia).

(5.1)

Finally, by reordering the terms of Equation 5.1 we arrive at Equation 5.2 presented below.

(5.2)

According to Pasichnyk et al., the functional renal parenchyma preoperatively is determined by the volume of the neoplastic lesion, while in the mathematical model developed by the authors the tumor volume was considered to have practically zero functionality (32). In Equation 6.1 we express the preoperative renal volume (V_preoperative) as the sum of functional (V_{preop.functional}) and non-functional parenchyma (V_{preop.non functional}), while in Equation 6.2 we assign the non-functional part to the lesion volume (V_tumor). Finally, in Equation 6.3 follows the combination of the above two equations.

(6.1)

(6.2)

(6.3)

Then, by combining Equations 5.2 and 6.3 we are led to the formulation of Equation 7.1.

(7.1)

After the rearrangement of the terms in Equation 7.1, finally Equation 7.2 emerges.

(7.2)

The difference: V_specimen − V_tumor practically expresses the marginal zone volume of healthy renal parenchyma around the tumor that is resected as part of the surgical specimen along with the neoplastic lesion (ΔV_threshold). Therefore, according to the above we can arrive at Equation 7.3.

(7.3)

The combination of Equations 7.3 and 7.2 finally results in Equation 8.1, which is the final equation describing renal parenchyma volume balance after partial nephrectomy procedures.

(8.1)

By rearranging the terms of Equation 8.1 we finally arrive at Equation 8.2 that is presented below.

(8.2)

By defining the difference: V_{preop.functional} − V_{postop.functional} as the absolute decrement in functional renal parenchyma volume (FRPV) after partial nephrectomy (|ΔV_functional|), we are led to Equation 8.3.

(8.3)

Substituting Equation 8.3 into Equation 8.2 finally yields Equation 9.

(9)

Equation 9 expresses the total volume balance after partial nephrectomy procedures. The above mathematical relationship defines the absolute reduction of FRPV as the sum of the ischemic zone volume around the resection site, and the volume of normal renal parenchyma contained in the surgical specimen of the operation.

By delving into the above equation, we could hypothesize that since no predefined surgical margins threshold is required in NSS procedures (33), the average proportion of normal renal parenchyma removed along with the tumor could be considered approximately constant. The above assumption implies that the quantity ΔV_threshold can be considered fixed among different patients undergoing partial nephrectomy. Therefore, considering the parameters: |ΔV_functional| and V_ischemia as variables, while the ΔV_threshold parameter as a fixed term, it emerges that the change in FRPV depends on the zero-functionality zone (ZFZ) induced by the intraoperative application of ischemia among patients undergoing PN. The above position can be further supported by the assumption of uniformity in both GD as well as nephron functionality per unit of FRPV. Additionally, in order for the Equation 9 to be considered valid, the absence of complications such as the development of postoperative renal infarct away from the resection site is also necessary, as in this case the induced necrobiotic region would be added to ZFZ. An additional limitation stems from the fact that the ΔV_threshold term cannot be considered constant in the case of heterogeneous populations of patients with solitary and multiple renal tumors undergoing single-stage resection. Finally, an interesting observation has to do with the fact that due to the determination of the change in FRPV, the parameters of the size of the tumor as well as the level of functionality of the kidney are eliminated on a case-by-case basis.

Proportionality expressions. In this section, we focus our analysis on the key-parameters determining the two main trifecta definitions. Specifically, we are going to explore the proportionality relationships interconnecting each one of them with the volumetric terms already discussed in Equation 9. In the analysis that is to follow, the proportions are notated via the symbol “∝”, as in the corresponding study of Cerbus et al. (34). The first part of the section is concerned with investigating the relationship between ischemia time (IT) and the ZFZ volume (ZFZV) around the resection site. Finally, in the second part, the effect of the absolute change in FRPV on the corresponding decrement in eGFR is investigated.

According to Damasceno-Ferreira et al. (35), about a quarter of the glomeruli are lost after the application of about 30 min of ischemia, while the limit of 20 min is the beginning of the formation of the ischemia zone. In their study dealing with the effect of the application of warm ischemia in a pig model, the researchers observed a progressive loss of nephrons with the prolongation of the ischemia duration, attributing to the above parameters a clearly proportional relationship. The response of normal renal tissue to the application of ischemia is generally considered to be homogeneous, as supported by the relevant study of Bechara et al. (36). In a previous study it was determined that the effect of ischemia, results in the formation of a well-defined zone characterized microscopically by the destruction of the microvascular architecture (37). This finding was linked to the hypothesis that revascularization is not particularly likely in this area (ZFZ). In another study investigating the impact of warm ischemia time (WIT) on ZFZ formation in a porcine model, de Souza et al. observed a significant decrease in glomerular density (GD) with prolonged application of WIT (26). GD was defined as the quotient of the number of nephrons per unit of renal parenchyma volume, while an interesting finding was the observation of a decrease in the absolute number of functional nephrons without a corresponding decrease in their distribution area. In this study, it is clearly described that the ZFZ refers to a strictly defined spatial area characterized by an almost total loss of the number of functional nephrons, while in its development the effect of ischemia time is also implied to be linear. Another interesting finding was that the serum creatinine levels remained unchanged, which was attributed to the normal function of the contralateral kidney (26). Finally, Mir and her colleagues in their related study sought to formulate a model for predicting postoperative renal function based on data on the type and duration of ischemia and the percentage of normal renal parenchyma preservation in patients submitted to PN (24). Specifically, the researchers utilized as a control variable the ratio of the percentage of preserved GFR to the percentage of preserved renal parenchyma volume (PRPV). They attributed to this variable the property of representing the proportion of nephron function recovery in the parenchyma that remains after resection of the surgical specimen. Theoretically, the recovery rate would be expected to be around 100%, however in their results it was estimated at approximately 80% with the difference been attributed to the application of WIT. The point of intersection with what we have already mentioned, concerns the PRPV, defined as the volume difference between the preoperative renal parenchyma (V_preoperative) and the surgical specimen (V_specimen), thus representing V_{postop.functional}. This parameter appears to decrease almost linearly with increasing ischemia duration (24). Therefore, according to Equation 5.1 (V_{postop.functional} = V_{postoperative} − V_ischemia), an equally linear increase in ZFZV (V_ischemia) emerges. Assigning the weight factor k₁ to the interaction between IT, V_ischemia and based on the above, we can directly proceed to the assumption of the Expression 10.

(10)

In the above study, the authors also investigated the relationship between PRPV and renal function as expressed through GFR, additionally to the effect of ischemia. In particular, a direct correlation was observed between the change in GFR (ΔGFR) and the proportion of PRPV. In particular, this effect was found to be much stronger than that in which IT intervenes as a prognostic factor (24). Moreover, considering the glomerular filtration rate proportional to the number of nephrons (38), it follows that in case of homogeneous GD, there is a given d (GFR) per unit of FRPV. In this case the total GFR is obtained as the sum of the individual d (GFR), and is proportionally related to FRPV. In a study of renal function in living kidney donors (LKD), Nunes-Carneiro et al. observed a direct correlation between the ratio of residual kidney volume (RKV) to weight (W) and the medium-term renal function, as expressed through the eGFR (39). The RKV parameter utilized by the authors, corresponds in our study to the postoperative FRPV (V_{postop.functional}). Upon careful review of the model developed by the authors, it becomes apparent that in case of approximating ΔeGFR through the change in FRPV (|ΔV_functional|), then the weight of each patient is introduced as a multiplication constant to the decrement in renal function. In another related study carried out by Shinoda et al. in LKD it was observed that age, Body Mass Index (BMI), pre-operative GFR and preserved kidney volume (PKV) are independent predictors of postoperative GFR (40). It is noted that the PKV parameter used in the above study corresponds to that of V_{postop.functional} in the present investigation. From this model we can observe the direct proportional correlation of FRPV with GFR, while it is of particular interest that the other parameters that seem to interfere, are related to individual patient characteristics, and are therefore eliminated during the determination of ΔeGFR. In the study conducted by Pasichnyk et al., it is explicitly stated that GFR is directly proportional to the number of nephrons or otherwise to the functional renal parenchyma (32). In the model presented by the authors for the determination of GFR, the parameters involved included the patients’ age and weight, FRPV and the corresponding serum creatinine level. However, it is useful to note that creatinine concentration is expressed in units: mmol/l, while FRPV in mm³ and therefore there is a significant difference in the order of magnitude between the above two parameters. Finally, in this case as well, it becomes evident that the parameters related to patient characteristics are eliminated during the calculation of ΔeGFR. In another model intending to estimate postoperative GFR in living kidney donors (LKD), Herts et al. observed that renal parenchymal volume correlates well with the level of renal function, with their relationship being strongly linear (41). Specifically, the above model resulted in an equation for determining GFR (GFR=70.77−0.444A+0.366W+0.20V_R−37.317Cr), in which its proportional relationship with age (A), weight (W), residual normal renal parenchyma (V_R; FRPV), and serum creatinine level (Cr) was evident. Almost identical were the conclusions drawn from a similar study conducted by Goh et al. aiming also to determine postoperative GFR in LKD (42). Verifying the predictive value of the respective model formulated by Herts et al., the authors reported that it outperforms the already available MDRD₄, MDRD₆ (43) and CKD-EPI equations which have been judged to have the highest validities among all available equations for determining GFR (44). From the above two studies, the proportional relationship that exists between GFR and FRPV as well as the level of serum creatinine in patients undergoing nephrectomy as living donors becomes evident. Focusing now on studies involving patients undergoing partial nephrectomy, we observe that the role of creatinine may not be as important as the PRPV parameter. Specifically, Simmons et al. investigated the effect of volume preservation on postoperative renal function of patients undergoing partial nephrectomy (45). In their conclusions, the authors stated that the preoperative functional renal parenchyma as well as its preservation rate are the primary determinants of long-term functional outcomes post PN. In fact, the correlation coefficient between the proportion of preserved FRPV and eGFR was estimated ranging from 83% to 96%, highlighting a clearly linear relationship. Finally, in another study of similar interest, Liu et al. aimed to preoperatively predict the level of renal function in patients submitted to partial nephrectomy by developing an image-based volumetric analysis model (46). In their model the researchers utilized three basic equations, while they also included the volume of the contralateral healthy kidney in their volumetric calculations. In the first equation (V_post = V_pre − V_def), postoperative renal volume (V_post) was defined as the difference between the preoperative parenchymal volume (V_pre) and that remaining nonfunctional after the resection (V_def). The above equation lies in agreement with Equation 4 of the present study with V_post corresponding to V_{postop.functional}, V_pre to V_preoperative, and V_def to the sum: V_specimen + V_ischemia. In their second equation, the authors defined as “f” the proportion of renal parenchyma preservation

while in their third equation they implemented a parametric adjustment (FI) on their original hypothesis to include the contralateral kidney in the calculations [FI=0.5(1+f)]. From the analysis that was carried out, a robust linear relationship emerged between GFR and V_def. Moreover, kidney function expressed via GFR was even divided into short- and long-term, with WIT being an independent prognostic indicator for the first, and V_def mainly affecting the second.

From the bibliographic data discussed, it is possible to observe that in the studies dealing with patients undergoing PN and not radical surgery as kidney donors, the intrusion of the creatinine level as an additional parameter is not observed in the relevant models for the determination of GFR through FRPV. This observation can reasonably be attributed to the pronounced difference between the above procedures in terms of the volume of functional renal parenchyma removed by surgery. Therefore, in the following mathematical expressions, initially the creatinine term (Cr) is included, while after the final formulation of the proportionality relationships for the variables of interest, an appropriate assumption will be made for its elimination regarding patients undergoing partial nephrectomy. As it becomes evident in the relevant study of Herts et al., the effects from V_R and Cr on GFR are generally different from each other (41, 42). In the relationships listed below, k_V, k_Cr, refer to weighting constants of proportionality for volume and creatinine parameters respectively, in terms of the determination of eGFR. Thus, in line with the above and assuming a linear relationship among eGFR, FRPV, and Cr both pre- and postoperatively, the Expressions 11.1 and 11.2 emerge.

(11.1)

(11.2)

Then, substituting Equation 8.1 into the Expression 11.1 finally yields the Expression 11.3.

(11.3)

Subsequently, we consider the absolute decrease in glomerular filtration rate as defined in Equation 12.

(12)

Thus, substituting the Expressions 11.2 and 11.3 into Equation 12 finally results in Expression 13.1.

(13.1)

Rearranging the terms of Expression 13.1 finally yields the Expression 13.2.

(13.2)

In the above expression, the difference: Cr_{postoperative} − Cr_preoperative reflects the absolute increase in serum creatinine postoperatively due to the loss of functional renal parenchyma and is mathematically defined in Equation 14.

(14)

Thus, substituting Equation 14 in the Expression 13.2 finally results in the Expression 15.1.

(15.1)

Rendering the proportional relationship described in Expression 15.1 in the form of an equation, assuming “α” as the proportionality factor and “c” as a constant, yields Equation 15.2.

(15.2)

By rearranging the terms of Equation 15.2 we finally get Equation 15.3.

(15.3)

Finally, by rendering Equation 15.3 to reflect the proportionality relationship, we finally arrive at the Expression 15.4.

(15.4)

According to the above mathematical expression, the overall change in renal function as expressed by the absolute decrement in glomerular filtration rate and serum creatinine level adjusted by the factor α • k_Cr, is directly proportional to the sum of the ischemic zone volume around the resection site and the excess normal renal parenchyma that is resected along with the tumor as part of the surgical specimen. The above observation is reinforced by the position of Mir et al. in their relevant study, according to which preserving as much of well-vascularized healthy renal parenchyma as possible during PN procedures, represents the outmost importance strategy for maximizing postoperative renal function (24).

Linear equations. In the following, the final mathematical expressions of the previous section will first be rendered in the form of linear equations. Subsequently, the analysis is going to be extended by studying the interaction between the two parameters describing renal function (|ΔeGFR|, IT) and are involved in the various definitions of the “trifecta outcome”. To achieve the investigation of the above interconnection, the variability of parameters related to renal function is controlled for all patients undergoing partial nephrectomy according to the hypotheses already declared in the concluding part of the first section. Finally, appropriate conclusions will be drawn regarding all patients with solitary renal masses undergoing PN by formulating mathematical expressions containing differentials.

Starting with the Expression 10, this can be written in the form of the linear Equation 16.1.

(16.1)

As mentioned above, the introduction of the creatinine term in the proportionality relationships obtained in the previous section, was based on studies involving radical nephrectomy operations in living kidney donors (39-42). In these types of operations, the volume of functional renal parenchyma that is removed is much lesser compared to partial nephrectomy procedures. This statement is supported by relevant volumetric analysis studies on the effect of FRPV change on renal function decrement in patients undergoing PN (45, 46). Consequently, by neglecting the term of the absolute change in creatinine levels in Expression 15.4, the linear Equation 16.2 is finally obtained.

(16.2)

We will then explore the forms that the Equations 16.1 and 16.2 can receive for the various patients undergoing partial nephrectomy. From Equation 16.1 it appears that the change in ZFZV [Δ(V_ischemia)] occurs mainly due to the change in intraoperatively applied ischemia duration [Δ(IT)]. Thus, by differentiating the above equation with respect to IT, Equation 16.3 is finally obtained.

(16.3)

While Equation 16.3 can be approximated in a simpler form through Equation 16.4.

(16.4)

On the other hand, in Equation 16.2 it becomes apparent that the variation in the absolute decrement in glomerular filtration rate [Δ(|ΔeGFR|)] among different patients undergoing PN is a linear combination of the change in ZFZV [Δ(V_ischemia)] and the variation in the volume of excess normal renal parenchyma excised along with the lesion [Δ(ΔV_threshold)]. Thus, by differentiating the above equation with respect to V_ischemia, Equation 16.5 is finally obtained.

(16.5)

As discussed above, among the various PN procedures no proportional relationship between tumor size and resection margin threshold is imposed oncologically (47). Therefore, it could be assumed that the variation of ΔV_threshold is relatively small among patients with solitary renal masses submitted to PN. In practice, this margin ranges around 5 mm beyond the periphery of the neoplastic lesion, while it does not seem to depend on the duration of ischemia (48). Consequently, the term

in Equations 16.5 can be eliminated and therefore it can receive the form of the Equation 16.6.

(16.6)

While Equation 16.6 can be approximated in a simpler form through Equation 16.7.

(16.7)

Finally, from the combination of Equations 16.3 and 16.6 it is possible to arrive at Equation 16.8.

(16.8)

While Equation 16.8 can be approximated in a simpler form through Equation 16.9.

(16.9)

From the above equation, the direct proportional relationship that appears to exist between the two main parameters of kidney function that are incorporated in the various trifecta definitions becomes apparent. Thus, for a given change in ischemia duration Δ(IT)=Δt, Equation 16.4 yields a corresponding change in the ischemic zone volume equal to:

Finally, from Equation 16.7 there is a corresponding change in the absolute reduction of the glomerular filtration rate equal to:

As can be seen from the calculation process of the above parameters, the sequence of effects follows the direct causality that connects the three variables according to the physiology of renal function. Expression 17.1 lists the causal sequence between the changes: Δ(IT), Δ(V_ischemia) and Δ(|ΔeGFR|), with the arrows connecting cause and effect in each case, while immediately above the arrows the transformation factor is also demonstrated (49).

(17.1)

Finally, the transformations of the above variables in both directions of causality become apparent in Expression 17.2. In this representation the corresponding transformation factor is assigned to each arrow that connects cause and effect.

(17.2)

By closing the present section, we finally arrived at the configuration of the Expressions 17.1 and 17.2 through the utilization of the available literature. The represented relationships describe in mathematical terms the central role played by ZFZ (V_ischemia) in shaping the postoperative renal function level of patients with solitary tumors undergoing one-stage partial nephrectomy. In fact, as can be seen from the combination of Equations 16.1 and 16.2, and Expressions 17.1 and 17.2, the ratio of the changes in each of the variables |ΔeGFR| and IT (α₂/α₁) is equal to the quotient of the effects that V_ischemia has respectively in their determination. Consequently, it was shown that the two parameters of renal function that are utilized in the various definitions of trifecta (|ΔeGFR|, IT) have as their point of intersection the parameter V_ischemia, thus constituting two different courses for its assessment. More simply they could be characterized as the two sides of the same coin regarding the theoretical estimation of the change in renal function.