1. Taking basic physiology to the clinic!
How to Optimize Automated Peritoneal Dialysis (APD)
Taking basic physiology to the clinic!
Carl M. Öberg
MD, PhD
Skåne University Hospital,
Department of Nephrology
Lund, SWEDEN

2. Disclosure CMÖ has received research funding from Baxter Healthcare.
CMÖ is the inventor of a pending patent filed by Gambro Lundia AB (Baxter) based on the content in the current presentation.
CMÖ has worked as a consultant for Gambro Lundia AB (Baxter)

3. Take home messages
DFRs exceeding 3L/h are of little benefit in terms of UF and small solute removal.
By using ”bi-modal” exchange techniques it is possible to reduce the glucose absorption by more than 20% while achieving the same Kt/V and UF as a standard treatment.
Although theoretically convincing, the current results are based on theoretical modeling and thus, validation is needed by means of clinical studies.

4. The 3-pore model of peritoneal dialysis
A mathematical model by Bengt Rippe [1] that can be used to simulate and predict solute and water transport in PD
Originally derived from patient data (in the 1990ies)
Has been validated in several studies
Several commercial softwares exist, e.g. PD Adequest® och PDC®.
[1] Rippe, B. A three-pore model of peritoneal transport. Peritoneal Dialysis International 13. Suppl 2 (1993): S35-S38.

5. Dialysate Flow Rate (DFR)
The dialysate flow rate is the total treatment volume (in litres) divided by the total treatment time (in minutes). In the literature it is often given in mL per minute, similar to GFR, but we chose L per hour because it is easier to relate to the total volume prescribed which is of course usually in the litre range.

6. Method
An extended 3-pore model [1] was applied having an additional compartment so that transport could be simulated to occur during drain and fill phases
25 cycles of several different DFRs were simulated using the extended 3-pm for
3 different glucose concentrations (1.36%, 2.27% and 3.86%) and
3 different peritoneal transport types: low (PET D/Pcrea < 0.6), high (PET D/Pcrea > 0.8) and average
4 different treatment regimes: Intermittent PD (IPD), Tidal PD (TPD) with a tidal fill volume of either 25%, 50% or 75% of the initial fill volume.
Sorry for all the text in this slide. 25 cycles per simulation was performed and the results are presented as averages over the whole treatment time. Three different glucose concentrations and three different peritoneal transport types were used for 4 different treatment modalities: Intermittent PD and Tidal PD with 3 different tidal fill volumes. So, all in all, there are 3x3x4 equals 36 different scenarios.
[1] Öberg CM, Rippe B. Optimizing Automated Peritoneal Dialysis Using an Extended 3-Pore Model. Kidney International Reports 2, 943–951, 2017

7. Urea Transport
So, to the main result for UREA clearance. At higher DFRs the treatment becomes inefficient due to the constant draining and filling of the peritoneal cavity. This draining and filling leaves too little time for effective contact with the peritoneum. Hence, as can be seen the clearance is actually reduced at high DFRs. Low transporters benefit very little from high DFRs due to their lower MTACs and DFRs > 2L/h provide no additional clearance.
Öberg CM, Rippe B. Optimizing Automated Peritoneal Dialysis Using an Extended 3-Pore Model. Kidney International Reports 2, 943–951, 2017

8. Ultrafiltration
Ok, there is something strange going on here. The peak values for the UF vs. DFR curves occur at almost identical DFRs compared to the urea clearance vs. DFR curves. At first glance, this might seem a bit surprising, since it is at these DFRs that the glucose absorption is at its greatest. However, the increased glucose dissipation at these high DFRs will be more than well compensated by the influx of fresh dialysis fluid. Thus the glucose gradient will be maintained despite increasing absorption. Hence, it is the addition of fresh dialysis fluid which will increase both UF and clearance of small solutes at higher DFRs. Another thing that can be seen is the marked inefficiency of flows around 1.3L compared to 2L – especially for fast and average transporters.
Öberg CM, Rippe B. Optimizing Automated Peritoneal Dialysis Using an Extended 3-Pore Model. Kidney International Reports 2, 943–951, 2017

9. Sodium modeling (IPD)
The kinetics of sodium in the APD simulations follow mainly the UF-curves that I showed previously so that the sodium removal is somewhere between 8-9 mmol per dL UF which reflects that only about 20% of the sodium transport occurs via diffusive mechanisms.

10. Therapeutic DFR intervals
Intermittent technique
Slow
Average
Fast
1.5 %
0.7 L/h – 2.7 L/h
1.0 L/h – 3.0 L/h
1.5 L/h – 3.5 L/h
2.27%
0.5 L/h – 2.7 L/h
0.7 L/h – 3.0 L/h
1.0 L/h – 3.5 L/h
3.86 %
0.3 L/h – 2.7 L/h
0.5 L/h – 3.0 L/h
0.7 L/h – 3.5 L/h
75% tidal technique
0.7 L/h – 4.1 L/h
1.0 L/h – 4.5 L/h
1.8 L/h – 5.5 L/h
0.5 L/h – 4.1 L/h
0.9 L/h – 4.5 L/h
1.0 L/h – 5.2 L/h
0.3 L/h – 4.0 L/h
0.5 L/h – 4.4 L/h
0.7 L/h – 5.1 L/h
50% tidal technique
0.8 L/h – 4.7 L/h
1.0 L/h – 5.1 L/h
1.8 L/h – 5.9 L/h
0.5 L/h – 4.7 L/h
0.8 L/h – 5.1 L/h
1.0 L/h – 5.9 L/h
0.3 L/h – 4.7 L/h
0.5 L/h – 5.0 L/h
0.8 L/h – 5.8 L/h
25% tidal technique
0.7 L/h – 4.4 L/h
1.3 L/h – 4.8 L/h
1.8 L/h – 6.0 L/h
0.5 L/h – 4.3 L/h
0.7 L/h – 4.8 L/h
1.0 L/h – 5.3 L/h
0.3 L/h – 4.3 L/h
0.7 L/h – 5.2 L/h
The lower limit represents the DFR at which a maximum UF per L dialysis fluid used is attained (see Fig. 6). Using a lower DFR than this value will be lead to less UF per L/dialysis fluid spent. Also, DFRs lower than 1L/h will increase the glucose absorption in relation to the achieved UF (see fig. 3). The high part of the interval is the DFR at which a maximum UF as a function of DFR is reached. Using a higher DFR will give less UF while spending more dialysis fluid.

11. Comparison with Clinical Data
Results from the clinical study by Aasaröd et al, 1994 (Average PET D/Pcrea = 0.77). 3-Pore Model PREDICTED Values Within Parenthesis. 9h
IPD Clurea
TPD 50% Clurea
10 L (DFR 1.1L/h)
14.3* mL/min (14.9)
13.3 mL/min (13.9)
14 L (DFR 1.6 L/h)
16.9 mL/min (17.0)
15.9 mL/min (16.2)
24 L (DFR 2.7 L/h
20.9 mL/min (18.8)
19.9 mL/min (19.1)
If we compare our theoretical results to previous clinical studies, we find a good agreement. Thus, Åsaröd and colleagues found that TPD with a 50% tidal fill volume had lower urea clearances compared to the intermittent technique. This is in agreement with our results. In the figure below the IPD i clearly more effective in terms of urea Cl for DFRs below 3L/h. With a D/Pcrea of 0.77 the patients in this study would be somewhere in between the average and high transporters in this figure. There was a tendency for the model to underestimate clearances at high flow rates perhaps reflecting the fact that initial vasodilation was not included in results shown here today (although I have actually prepared for simulations with vasodilation included).
* The Clurea was significantly higher for IPD in the clinical study. There were no
sig. differences for the two higher DFRs.

12. Solute (Urea) Removal Efficiency
The low glucose concentration (dotted line) gives the most urea removal per g glucose absorbed.
Shown in this slide is the small solute transport efficiency (in mmol urea removed per g glucose absorbed) as a function of DFR. Similar to the UF efficiency, the removal reaches a plateau at DFRs higher than 2L/h. The most interesting aspect here is that the situation is reversed compared to the UF efficiency. Here the the patient gets the most small-solute removal per g glucose invested using the low glucose concentration. Of course, the best situation is using no glucose at all.

13. Water Removal (”UF”) Efficiency
The high glucose concentration (dashed line) gives the most UF per g glucose absorbed.
Shown in this figure are the results for the UF efficiency in terms of UF in mL per gram glucose absorbed. For each milliliter of UF the patient has to pay a price in terms of glucose absorption – this is the so called ”metabolic cost” of each mL UF. As can be seen, slightly higher dialysate flows of up to 2L/h are beneficial. Additionally, using the strong glucose solution gives the patient more ultrafiltration for each gram of glucose invested. Thus, these results indicate that high glucose concentrations should be used if one wants to optimize UF with respect to the metabolic cost.

14. Glucose absorption and glucose concentration in CAPD patients
Shown in this slide is a figure from a study by Olle Heimburger and colleagues demonstrating the same effect as was demonstrated in the previous slide for UF efficiency. Thus, again, the high glucose concentration (triangles) gives the most UF per g glucose absorbed.
Heimburger O, Waniewski J, Werynski A, Lindholm B. Kidney Int 41 pp , 1992

15. Conclusions: Metabolic cost
The efficiency of solute small-solute transport (in mmol/g) is larger the weaker the glucose solution – and of course best for 0-glucose!
Metabolic efficiency for UF (in mL/g) is the opposite – larger for the stronger the glucose solution.
Therefore glucose sparing regimes can be constructed by mixing dwells with high and low glucose strengths.

16. NOVEL ’BI-MODAL’ APD REGIMENS
SHORT
DWELLS
LONG
DWELLS
HIGH GLUCOSE
WATER REMOVAL
LOW/NO GLUCOSE
SOLUTE REMOVAL

17. It would also appear that the total treatment time is shorter for the bi-modal regimens, especially at higher DFRs.
Regime
UreaR UF
Glucose abs.
Decrease
Total time
6x2L 1.36%
158 mmol
458 mL
41.5 g
0 %
540 min
4x2L 3.86% + 4x2L 0%
456 mL
33.8 g
-19%
510 min
5x2L 3.86% + 5x2L 0%
157 mmol
457 mL
32.3 g
-22%
475 min

18. Some more optimized regimens …

21. Take home messages
DFRs exceeding 3L/h are of little benefit in terms of UF and small solute removal.
By using ”bi-modal” exchange techniques it is possible to reduce the glucose absorption by more than 20% while achieving the same Kt/V and UF as a standard treatment.
It would also appear that such bi-modal regimens imply a shorter total treatment time - while still maintaining the same small-solute removal and UF - especially at higher DFRs.
Although theoretically convincing, the current results are based on theoretical modeling and thus, validation is needed by means of clinical studies.

22. Thank you for your attention!