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Fazmin, I.T.; Ali, J.M. Prosthesis–Patient Mismatch. Encyclopedia. Available online: https://encyclopedia.pub/entry/48992 (accessed on 26 December 2024).
Fazmin IT, Ali JM. Prosthesis–Patient Mismatch. Encyclopedia. Available at: https://encyclopedia.pub/entry/48992. Accessed December 26, 2024.
Fazmin, Ibrahim Talal, Jason M. Ali. "Prosthesis–Patient Mismatch" Encyclopedia, https://encyclopedia.pub/entry/48992 (accessed December 26, 2024).
Fazmin, I.T., & Ali, J.M. (2023, September 09). Prosthesis–Patient Mismatch. In Encyclopedia. https://encyclopedia.pub/entry/48992
Fazmin, Ibrahim Talal and Jason M. Ali. "Prosthesis–Patient Mismatch." Encyclopedia. Web. 09 September, 2023.
Prosthesis–Patient Mismatch
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This entry is adapted from the peer-reviewed paper 10.3390/jcdd10090373

Prosthesis–patient mismatch (PPM) is defined as implanting a prosthetic that is insufficiently sized for the patient receiving it. PPM leads to high residual transvalvular gradients post-aortic valve replacement and consequently results in left ventricular dysfunction, morbidity and mortality in both the short and long term.

aortic root enlargement prosthesis–patient mismatch aortic stenosis

1. Introduction and Definition of Prosthesis–Patient Mismatch

Aortic valve replacement is one of the most performed procedures in adult cardiac surgical practice. Prosthesis–patient mismatch (PPM) was first described in 1978 as a complication of aortic valve replacement [1]. It is defined as occurring when a prosthetic valve effective orifice area (EOA) is too small relative to the size of the patient it is being implanted in. When indexed relative to a patient’s body surface area (BSA), it is expressed as the indexed EOA (iEOA). The degree of PPM can be expressed using the iEOA as follows: ≤0.85 cm2/m2—moderate PPM and ≤0.65 cm2/m2—severe PPM [2]. The definition has been recently updated by the valve academic research consortium 3 (VARC 3) criteria to also account for body mass index (BMI), as a high BSA would lead to the over-indexing of the iEOA and the overestimation of PPM. Thus, when BMI > 30 kg/m2, mild PPM is present; moderate PPM is present when iEOA < 0.70 cm2/m2 and severe PPM is present when iEOA is <0.55 cm2/m2 [3][4] (Table 1). The incidence of PPM shows variation across different studies and patient cohorts, but a recent meta-analysis demonstrated an incidence of 53.7% (with a range of 6.1–93.8% in included studies), highlighting that it is a common phenomenon [5]. It impacts the prostheses used in both surgical (SAVR) as well as transcatheter (TAVR) aortic valve replacement. Therefore, it is important for heart teams to understand PPM, its clinical impact, and strategies to account for and mitigate PPM, which include aortic root enlargement (ARE).
Table 1. Definitions of PPM based on iEOA. Adjustments according to BMI are also included. PPM—prosthesis–patient mismatch, iEOA—indexed effective orifice area, BMI—body mass index.
Definition iEOA BMI Adjustment (>30 kg/m2)
Moderate PPM ≤0.85 cm2/m2 <0.70 cm2/m2
Severe PPM ≤0.65 cm2/m2 <0.55 cm2/m2

2. Measuring and Predicting PPM

The measurement of prosthesis–patient mismatch (PPM) holds significant importance in various stages of both surgical and transcatheter intervention, including preoperative, intraoperative, and postoperative phases. Preoperatively, the assessment of PPM serves to guide the selection of appropriate valve choices. It aids in determining the optimal valve size that would mitigate the occurrence of PPM in potentially high-risk patients, such as those with a high BMI or poor LVEF. In some cases, it might highlight the necessity of performing root enlargement. In Table 2 and Table 3, an example is highlighted using the Medtronic Hancock II and Carpentier–Edwards Perimount Magna prosthetic valve, simulating predicted iEOA for a variety of patient BSA values and valve sizes taken from the literature [6]. Using this table, a patient with a BSA of 2 m2 will require a minimum size 27 Hancock II or size 21 Perimount Magna valve to avoid PPM. Furthermore, intraoperative PPM measurements facilitate a comprehensive evaluation of the implanted valve, thereby predicting the likelihood of PPM in the specific patient. Therefore, PPM assessment serves as a vital component in risk stratification, enabling the identification of patients who require closer follow-up and monitoring.
Table 2. Simulation of predicted iEOA for a range of patient BSA values and Medtronic Hancock II valve sizes. Moderate PPM values are highlighted in yellow, severe in red. BSA—body surface area, EOA—effective orifice area, PPM—prosthesis–patient mismatch.
Valve Size (mm) EOA (cm2) Indexed EOA (cm2/m2)
21 1.20 0.80 0.69 0.60 0.53
23 1.40 0.93 0.80 0.70 0.62
25 1.60 1.07 0.91 0.80 0.71
27 1.80 1.20 1.03 0.90 0.80
29 2.00 1.33 1.14 1.00 0.89
    1.50 1.75 2.00 2.25
    Patient BSA (m2)
Table 3. Simulation of predicted iEOA for a range of patient BSA values and Carpentier–Edwards Perimount Magna valve sizes. Moderate PPM values are highlighted in yellow. BSA—body surface area, EOA—effective orifice area, PPM—prosthesis–patient mismatch.
Valve Size (mm) EOA (cm2) Indexed EOA (cm2/m2)
21 1.20 0.80 0.69 0.60 0.53
23 1.40 0.93 0.80 0.70 0.62
25 1.60 1.07 0.91 0.80 0.71
27 1.80 1.20 1.03 0.90 0.80
29 2.00 1.33 1.14 1.00 0.89
    1.50 1.75 2.00 2.25
    Patient BSA (m2)
There are several methods that can be used to predict the iEOA prior to intervention. These are evaluated in a study by Bleiziffer et al. [7] who compared four different methods and calculated the correlation with postoperative in vivo transthoracic echocardiographic (TTE) measurements:
  • Method 1—Using in house TTE data obtained from patients 6 months postoperatively to create “home-grown” iEOA charts (r = 0.62);
  • Method 2—Using the geometric orifice area based on static parameters (the valve internal diameter specified by the manufacturer) (r = 0.27);
  • Method 3—Using commercial iEOA charts, which are produced by using data obtained through various methods but can include in vitro measurements (varies based on manufacturer; r = 0.27–0.59 for four different valve types);
  • Method 4—Using published EOA data from the literature (r = 0.53).
The authors concluded that the best methods were methods 1 and 4. The most reliable sources of data to make preoperative predictions about iEOA are echocardiographic studies involving large numbers of patients for each valve size. In the absence of data in in the literature, for example, in new valves, “Method 1” of creating an institutional database of TTE-measured EOA values should be used. Furthermore, use of in vitro data should be cautioned against. This is supported by a recent meta-analysis [5], which observed that regardless of whether predicted (by manufacturer or published in vivo data) or measured iEOA is used, the same correlation with outcomes (perioperative mortality) is found. Furthermore, each different method of preoperatively predicting iEOA showed different degrees of statistical heterogeneity when compared across the studies included in the meta-analysis, with Doppler echocardiography being the most reliable.
Counterarguments, however, have emerged. Two studies by Ternacle et al. showed that TTE-derived iEOA values demonstrate high variability, and suggest that this method overestimates PPM, compared with using predicted iEOA derived from manufacturer reference values [8][9]. Furthermore, they found that predicted iEOA correlated better with hemodynamic parameters (trans-prosthetic gradients and high residual gradients), whilst neither predicted nor measured iEOA correlated with clinical outcomes. The authors suggest that drawbacks of TTE measurements include inter-operator variability and the susceptibility of TTE to underestimate EOA in low-flow states [8][9]. However, a major drawback in the generalisability of these studies is that they looked at TAVR prosthetics as opposed to SAVR.
Another argument highlighting the limitations of TTE measurements is put forward by Vriesendorp et al. [10], who analyzed the predictive value of iEOA charts in a homogenous cohort of patients. They constructed “train” and “test” subgroups, wherein they measured EOA in the “train” cohort and tested the predictive value by comparing with the post-implant EOA in the “test” cohort. They demonstrated a large variation in measured EOA for each size of valve and a high degree of misclassification of PPM in the test cohort. Nonetheless, even using in vitro measurements, the correlation between projected iEOA (derived from iEOA charts created using TTE data from the train subset) and measured iEOA (in the test subset) was poor (r = 0.50) [10].

3. Clinical Impact of PPM

The impact of PPM on patients is profound. It can lead to higher morbidity and mortality and persistent symptoms, and accelerates the degeneration of bioprosthetic valves [2][11][12]. The most recently published large-scale clinical study involved 16,423 patients and demonstrated that severe PPM (adjudicated based on published EOA data and VARC3 criteria) impacted long-term (10 year) mortality, as well as leading to increased readmissions with heart failure [13]. However, the same study suggested that moderate PPM had a negligible effect. Therefore, some groups suggest that it may be too aggressive in taking steps to avoid moderate PPM, conducting more extensive surgeries for limited prognostic benefit [4].
There have been five meta-analyses looking at patient outcomes related to PPM. Sa et al. [5] included 108,182 patients with moderate and severe PPM, and demonstrated increased peri-operative mortality, and also mortality 1, 5, and 10 years after surgery. In a subgroup analysis, the mortality impact was worse in the severe PPM group compared to the moderate PPM group. Dayan et al. [14] assessed 40,381 patients (of which 813 had TAVR), and showed perioperative mortality was 56% higher and overall mortality 26% higher in the PPM group. PPM also has an increased effect of worsening mortality in patients aged <70 or with concomitant coronary artery bypass grafting (CABG). When divided into subsets of severe and moderate PPM, severe PPM caused increased mortality in the perioperative period and in the long-term, but moderate PPM only did so in the perioperative period, indicating perhaps a vulnerability of the myocardium to increased afterload immediately post-surgery. Chen et al. [15] included 14,874 patients and showed that PPM increased mid-term (5-year) and long-term (10-year) mortalities by 42% and 52%, respectively. They showed that this was the case for all patient sub-populations with severe PPM, but not those with moderate PPM. Younger patients, women, and patients with poor preoperative left-ventricular ejection fraction (LVEF) showed worse long-term outcomes in the presence of any degree of PPM. In patients with impaired LVEF, both moderate and severe PPM increased both perioperative and long-term mortality. Takagi et al. [16] included 16,021 patients and demonstrated a 31% increased risk of late mortality in PPM. However, when stratifying patients according to severe or moderate PPM, only those with severe PPM showed an increase in hazard ratio for mortality. Head et al. [17] included 27,186 patients and demonstrated a 34% increase in all-cause, long term mortality for all definitions of PPM. Additionally, when stratified by degree of PPM, both moderate and severe PPM were associated with increased all-cause and cardiac mortality. Therefore, PPM is associated with increased morbidity and mortality, with severe PPM being strongly associated with worse outcomes, although the impact of moderate PPM is not consistent across the published literature.
A particular subgroup of patients who are at significant risk of poor outcomes due to PPM are those with poor LVEF. Blais et al. [18] showed that in patients with LVEF ≥ 40%, early mortality was relatively low with non-severe or moderate PPM (mortality rate 2–5%). However, for patients with LVEF < 40%, mortality was 16%, and it was 77% for both those with moderate and those with severe PPM. The authors suggest that this is because an impaired LV is more vulnerable to increased afterload. This will have implications for the management of potential PPM when deciding to treat these patients, as a poor LVEF will be a strong indication to undertake strategies to mitigate potential PPM.

4. Management of PPM by Aortic Root Enlargement

Given the consequences of PPM, efforts to address it must be considered—as per the 2021 ESC/EACTS Guidelines for the management of valvular heart disease, “Efforts to prevent PPM should receive more emphasis to improve long-term survival after either SAVR or TAVI” [19]. A proposed management scheme for PPM is described in a review by Bilkhu et al. [20], as shown below.
Preoperatively predict the iEOA of a chosen prosthesis for a patient, and then:
  • Proceed with the selected prosthesis if the predicted iEOA is >0.85.
  • If the predicted iEOA is ≤0.85 then:
    -
    Accept PPM in certain clinical contexts;
    -
    Choose a prosthetic with larger EOA;
    -
    Carry out an aortic root enlargement.
In terms of choosing a prosthetic with a larger EOA, some valve designs have larger EOA values for the same size of valve. This is demonstrated in Table 2 and Table 3 above, which show that for the same label size, a Carpentier–Edwards Perimount Magna has a larger EOA than a Medtronic Hancock II prosthesis. Additionally, newer-generation prosthetic valves are being produced, which have larger EOAs with the same external diameter. Stentless valves such as the Corcym Perceval valves also have larger EOAs [21], as do TAVR prostheses. Sutureless aortic valves [22] and TAVR valves [23] both offer larger EOAs due to the lack of a sewing ring [24]. Certainly, TAVR appears to confer advantages over SAVR in terms of a reduced incidence of PPM. Studies show that in TAVR, the incidence of moderate PPM is around 6–46%, and for severe PPM the incidence ranges from 0 to 15% [25]. A meta-analysis demonstrated a 77% relative risk reduction in TAVR patients of developing PPM [26], and a recent analysis of the PARTNER 2 trial data showed that there was a decreased incidence of PPM in the TAVR group (9.3%) vs. the SAVR group (27.9%) [9]. TAVR valves were advantageous in terms of having reduced transvalvular gradients, greater EOAs and reduced risk of PPM compared to SAVR [25]. However, newer-generation TAVR devices seem to have diminished advantages (i.e., higher rates of PPM) due to a reduction in EOA on account of external skirts designed to mitigate paravalvular leak [27]. Therefore, a variety of patient- and operation-related factors must be considered on a case-by-case basis and after undertaking a heart team multidisciplinary discussion before counselling patients and obtaining informed consent to proceed with an aortic root enlargement.
Indications for aortic root enlargement are risk of postoperative PPM, as defined above. Severe PPM would be a strong indication, with moderate PPM being a more controversial indication due to the conflicting evidence relating to its impact on clinical outcomes, with some studies suggesting a negligible effect of moderate PPM on morbidity and mortality [13]. Certainly, some authors urge caution with being too aggressive in prospectively avoiding PPM, as the operative risk of a root enlargement will outweigh the benefit in treating a moderate PPM [4]. Some patient-related factors will also influence this decision. For example, patients with a poor LVEF will be at high risk of early mortality if there is PPM post-AVR [18]. Demographic factors are also important. Sa et al. discuss this from a global health perspective in their recent meta-analysis [5]: in developed countries, a common scenario is deciding to implant a small, 21 mm prosthesis in a short, obese, frail elderly female patient with calcific aortic stenosis and a low functional baseline. A degree of PPM would be acceptable in this case [5]. In a developing country, a possible scenario would be having to replace rheumatic aortic valves in younger, more active patients wherein avoiding PPM would be a higher priority [5]. A further dimension to consider is that patients in developed countries will be implanted with newer prosthetics with better hemodynamic profiles [5]. Finally, the choice of a mechanical versus bioprosthetic valve should also be considered. Although calcific aortic stenosis predominantly affects older patients, younger patients with diseases such as bicuspid aortic valves are suitable candidates for mechanical valve prostheses, which, due to their construction, tend to have larger EOAs and better hemodynamic performance compared to similarly sized bioprosthetic valves [6][28].

References

  1. Rahimtoola, S.H. The Problem of Valve Prosthesis–patient Mismatch. Circulation 1978, 58, 20–24.
  2. Pibarot, P.; Dumesnil, J.G. Prosthesis–patient Mismatch: Definition, Clinical Impact, and Prevention. Heart 2006, 92, 1022–1029.
  3. VARC-3 WRITING COMMITTEE; Généreux, P.; Piazza, N.; Alu, M.C.; Nazif, T.; Hahn, R.T.; Pibarot, P.; Bax, J.J.; Leipsic, J.A.; Blanke, P.; et al. Valve Academic Research Consortium 3: Updated Endpoint Definitions for Aortic Valve Clinical Research. Eur. Heart J. 2021, 42, 1825–1857.
  4. Mack, M.J.; Adams, D.H. Avoidance of Patient Prosthesis Mismatch after Aortic Valve Replacement. J. Am. Coll. Cardiol. 2023, 81, 976–978.
  5. de Oliveira Sá, M.P.B.; de Carvalho, M.M.B.; Sobral Filho, D.C.; Cavalcanti, L.R.P.; Rayol, S.D.C.; Diniz, R.G.S.; Menezes, A.M.; Clavel, M.-A.; Pibarot, P.; Lima, R.C. Surgical Aortic Valve Replacement and Patient-Prosthesis Mismatch: A Meta-Analysis of 108182 Patients. Eur. J. Cardiothorac. Surg. 2019, 56, 44–54.
  6. Elmahdy, W.; Osman, M.; Farag, M.; Shoaib, A.; Saad, H.; Sullivan, K.; Krishnan, U.; Nashef, S.; Berman, M. Prosthesis–patient Mismatch Increases Early and Late Mortality in Low Risk Aortic Valve Replacement. Semin. Thorac. Cardiovasc. Surg. 2021, 33, 23–30.
  7. Bleiziffer, S.; Eichinger, W.B.; Hettich, I.; Guenzinger, R.; Ruzicka, D.; Bauernschmitt, R.; Lange, R. Prediction of Valve Prosthesis–patient Mismatch Prior to Aortic Valve Replacement: Which Is the Best Method? Heart 2007, 93, 615–620.
  8. Ternacle, J.; Guimaraes, L.; Vincent, F.; Côté, N.; Côté, M.; Lachance, D.; Clavel, M.-A.; Abbas, A.E.; Pibarot, P.; Rodés-Cabau, J. Reclassification of Prosthesis–Patient Mismatch after Transcatheter Aortic Valve Replacement Using Predicted vs. Measured Indexed Effective Orifice Area. Eur. Heart J.—Cardiovasc. Imaging 2021, 22, 11–20.
  9. Ternacle, J.; Pibarot, P.; Herrmann, H.C.; Kodali, S.; Leipsic, J.; Blanke, P.; Jaber, W.; Mack, M.J.; Clavel, M.-A.; Salaun, E.; et al. Prosthesis–patient Mismatch after Aortic Valve Replacement in the PARTNER 2 Trial and Registry. JACC Cardiovasc. Interv. 2021, 14, 1466–1477.
  10. Vriesendorp, M.D.; De Lind Van Wijngaarden, R.A.F.; Head, S.J.; Kappetein, A.-P.; Hickey, G.L.; Rao, V.; Weissman, N.J.; Reardon, M.J.; Moront, M.G.; Sabik, J.F., III; et al. The Fallacy of Indexed Effective Orifice Area Charts to Predict Prosthesis–Patient Mismatch after Prosthesis Implantation. Eur. Heart J.—Cardiovasc. Imaging 2020, 21, 1116–1122.
  11. Flameng, W.; Herregods, M.-C.; Vercalsteren, M.; Herijgers, P.; Bogaerts, K.; Meuris, B. Prosthesis–patient Mismatch Predicts Structural Valve Degeneration in Bioprosthetic Heart Valves. Circulation 2010, 121, 2123–2129.
  12. Zorn, G.L.; Little, S.H.; Tadros, P.; Deeb, G.M.; Gleason, T.G.; Heiser, J.; Kleiman, N.S.; Oh, J.K.; Popma, J.J.; Adams, D.; et al. Prosthesis–patient Mismatch in High-Risk Patients with Severe Aortic Stenosis: A Randomized Trial of a Self-Expanding Prosthesis. J. Thorac. Cardiovasc. Surg. 2016, 151, 1014–1022, 1023.e1–e3.
  13. Dismorr, M.; Glaser, N.; Franco-Cereceda, A.; Sartipy, U. Effect of Prosthesis–patient Mismatch on Long-Term Clinical Outcomes after Bioprosthetic Aortic Valve Replacement. J. Am. Coll. Cardiol. 2023, 81, 964–975.
  14. Dayan, V.; Vignolo, G.; Soca, G.; Paganini, J.J.; Brusich, D.; Pibarot, P. Predictors and Outcomes of Prosthesis–patient Mismatch after Aortic Valve Replacement. JACC Cardiovasc. Imaging 2016, 9, 924–933.
  15. Chen, J.; Lin, Y.; Kang, B.; Wang, Z. Indexed Effective Orifice Area Is a Significant Predictor of Higher Mid- and Long-Term Mortality Rates Following Aortic Valve Replacement in Patients with Prosthesis–patient Mismatch. Eur. J. Cardio-Thorac. Surg. 2014, 45, 234–240.
  16. Takagi, H.; Yamamoto, H.; Iwata, K.; Goto, S.; Umemoto, T. A Meta-Analysis of Effects of Prosthesis–Patient Mismatch after Aortic Valve Replacement on Late Mortality. Int. J. Cardiol. 2012, 159, 150–154.
  17. Head, S.J.; Mokhles, M.M.; Osnabrugge, R.L.J.; Pibarot, P.; Mack, M.J.; Takkenberg, J.J.M.; Bogers, A.J.J.C.; Kappetein, A.P. The Impact of Prosthesis–patient Mismatch on Long-Term Survival after Aortic Valve Replacement: A Systematic Review and Meta-Analysis of 34 Observational Studies Comprising 27186 Patients with 133141 Patient-Years. Eur. Heart J. 2012, 33, 1518–1529.
  18. Blais, C.; Dumesnil, J.G.; Baillot, R.; Simard, S.; Doyle, D.; Pibarot, P. Impact of Valve Prosthesis–patient Mismatch on Short-Term Mortality after Aortic Valve Replacement. Circulation 2003, 108, 983–988.
  19. Vahanian, A.; Beyersdorf, F.; Praz, F.; Milojevic, M.; Baldus, S.; Bauersachs, J.; Capodanno, D.; Conradi, L.; De Bonis, M.; De Paulis, R.; et al. 2021 ESC/EACTS Guidelines for the Management of Valvular Heart Disease: Developed by the Task Force for the Management of Valvular Heart Disease of the European Society of Cardiology (ESC) and the European Association for Cardio-Thoracic Surgery (EACTS). Eur. Heart J. 2022, 43, 561–632.
  20. Bilkhu, R.; Jahangiri, M.; Otto, C.M. Patient-Prosthesis Mismatch Following Aortic Valve Replacement. Heart 2019, 105, s28–s33.
  21. Belluschi, I.; Moriggia, S.; Giacomini, A.; Del Forno, B.; Di Sanzo, S.; Blasio, A.; Scafuri, A.; Alfieri, O. Can Perceval Sutureless Valve Reduce the Rate of Patient-Prosthesis Mismatch?†. Eur. J. Cardio-Thorac. Surg. 2017, 51, 1093–1099.
  22. Fiore, A.; Gueldich, M.; Folliguet, T. Sutureless Valves Fit/Perform Well in a Small Aortic Annulus. Ann. Cardiothorac. Surg. 2020, 9, 414–416.
  23. Leone, P.P.; Regazzoli, D.; Pagnesi, M.; Sanz-Sanchez, J.; Chiarito, M.; Cannata, F.; Van Mieghem, N.M.; Barbanti, M.; Tamburino, C.; Teles, R.; et al. Predictors and Clinical Impact of Prosthesis–patient Mismatch after Self-Expandable TAVR in Small Annuli. JACC Cardiovasc. Interv. 2021, 14, 1218–1228.
  24. Weltert, L.P.; Lucertini, G. Simplification of the Manougian Approach to Treat Small Annuli: Finally a Reproducible Low Risk Approach on the Horizon? J. Card. Surg. 2022, 37, 579–580.
  25. Leone, P.P.; Fazzari, F.; Cannata, F.; Sanz-Sanchez, J.; Mangieri, A.; Monti, L.; Cozzi, O.; Stefanini, G.G.; Bragato, R.; Colombo, A.; et al. Clinical and Technical Challenges of Prosthesis–Patient Mismatch after Transcatheter Aortic Valve Implantation. Front. Cardiovasc. Med. 2021, 8, 670457.
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  27. Chakravarty, T.; Makar, M.; Ahmad, Y. Patient-Prosthesis Mismatch after SAVR and TAVR: The Importance of Comparing Apples with Apples. JACC Cardiovasc. Interv. 2021, 14, 1478–1480.
  28. Pibarot, P.; Dumesnil, J.G. Prosthetic Heart Valves: Selection of the Optimal Prosthesis and Long-Term Management. Circulation 2009, 119, 1034–1048.
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Subjects: Cardiac & Cardiovascular Systems
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