- Email: [email protected]
Re: “Some Points to Make About an Original Article”
Letters to the Editors / The Journal of Arthroplasty 31 (2016) 548–558
With regard to the theoretical advantages of nuclear medicine to diagnose PJI, Glaudemans et al cite “convenience for the patient” and “cost-effectiveness.” A recent study published by our group, which was based on a formal method of decision-making, demonstrated that the current recommendation to approach the diagnosis of PJI with serum markers and joint fluid aspiration is the best alternative when cost, benefits, opportunities, and risks are taken into consideration [5]. Glaudemans et al emphasized that nuclear medicine studies are inexpensive and non-invasive when compared to other diagnostic tools. That strong statement must be supported with better evidence than pure conjecture. Currently, in this era of orthopedic care based on value [6], all interventions administered should have the highest cost effectiveness. It is important for future studies to validate the cost effectiveness of bone scan imaging, which appears to be a fairly invasive test. In addition, future studies on any diagnostic modality must go beyond statistical analyses and answer the most pertinent question: in what proportion of patients who underwent bone scan imaging did the result of the test result in a change in the treatment rendered? We are also surprised to read that the authors of the letter believe that the “pathology and/or microbiology, or at least a thorough clinical followup time of at least six months” should be the correct reference standard to diagnose PJI. The lack of a gold standard for diagnosis of PJI has lead many organizations, including the Musculoskeletal Infection Society, to propose diagnostic criteria. In closing, we are grateful to our colleagues for their interest in our study. We look forward to reading future studies evaluating the value of bone scan in the diagnosis of PJI when appropriate methodology for performing the test and interpretation of the data is utilized. Claudio Diaz-Ledezma, MD Courtney Lamberton, BS Paul M. Lichstein, MD Javad Parvizi, MD, FRCS⁎ The Rothman Institute at Thomas Jefferson University Philadelphia, Pennsylvania ⁎Reprint requests: Javad Parvizi, MD, FRCS, 125 S 9th St. Ste 1000 Philadelphia, PA 19107
553
Werner et al [1] published in The Journal of Arthroplasty (2015, vol. 30, no. 5). It is commendable that they have presented a currently “hot topic” in orthopedic surgery. However, we are writing to elaborate on some points in the article, and to raise some issues: 1. The focus of the study is on the super-obese patients (BMI N50 kg/m2). The investigators have identified these patients through V85.43– V85.45 ICD-9-CM (International Classification of Diseases, Ninth Revision, Clinical Modification) codes. These codes were not introduced until October 2010 [2]. While the study period is between 2005 and 2011, we assume that many “super-obese” patients in their database were not included in the cohort. Thus, their sample of “super obese” patients is not proportionally representative of “super obese” TKA patient population nationally. 2. A subset of the morbidly obese cohort (40 ≤ BMI ≤ 49.9) was identified through 278.01 code. The code identifies all patients with BMI N40 kg/m 2 (including super-obese patients). Therefore, some part of the morbidly obese cohort is actually super-obese. Because of this specific sample selection process, we are concerned about the possibility of selection bias in the study. 3. Another subset of the morbidly obese cohort was identified through V85.41–V85.42 codes. Again, these codes were added to the coding system late in 2010 [2]. 4. The unit of analysis, in arthroplasty outcome studies, is joint rather than patient. That is why investigators, in outcome studies, report the number of joints along with the number of patients. Were there any bilateral cases in this sample? If so, how were they accounted for? 5. The authors have compared a cohort of revision TKA patients with BMI b 40 kg/m 2 with a cohort of primary TKA patients with BMI N50 kg/m 2. These two cohorts have different covariates such that reporting a differential outcome doesn’t prove the effect of one variable (BMI) alone on the result. Therefore, this comparison does not appear to be methodologically sound. Since the authors of the article are experts in the field, we believe they have clear explanations for these issues.
http://dx.doi.org/10.1016/j.arth.2015.07.004 References 1. Parvizi J, Jacovides C, Zmistowski B, et al. Definition of periprosthetic joint infection: is there a consensus? Clin Orthop Relat Res 2011;469:3022. 2. Diaz-Ledezma C, Higuera CA, Parvizi J. Success after treatment of periprosthetic joint infection: a Delphi-based international multidisciplinary consensus. Clin Orthop Relat Res 2013;471:2374. 3. American Academy of Orthopaedic Surgeons Clinical Practice Guidelines Unit. The diagnosis of periprosthetic joint infections of the hip and knee: guideline and evidence report. Adopted June 18 2010 http://www.aaos.org/research/guidelines/PJIguideline. pdf. [accessed July 2, 2015]. 4. Zmistowski B, Della Valle C, Bauer TW, et al. Diagnosis of periprosthetic joint infection. J Arthroplasty 2014;29:77. 5. Diaz-Ledezma C, Lichstein PM, Dolan JG, et al. Diagnosis of periprosthetic joint infection in Medicare patients: multicriteria decision analysis. Clin Orthop Relat Res 2014. http://dx.doi.org/10.1007/s11999-014-3492-2. 6. Bozic KJ. Improving value in healthcare. Clin Orthop Relat Res 2013;471:368.
Some Points to Make About an Original Article
Nader Toossi, MD Norman A. Johanson, MD Orthopaedic Surgery Department, Drexel University College of Medicine http://dx.doi.org/10.1016/j.arth.2015.07.016 References 1. Werner BC, Evans CL, Carothers JT, et al. Primary total knee arthroplasty in super-obese patients: dramatically higher postoperative complication rates even compared to revision surgery. J Arthroplast 2015;30(5):849. 2. Schraffenberger LA. New ICD-9-CM diagnosis codes for FY 2011. J AHIMA 2010; 81(9):66.
Re: “Some Points to Make About an Original Article” In Reply
We have read with great interest the article titled, “Primary total knee arthroplasty in super-obese patients: dramatically higher postoperative complication rates even compared to revision surgery” by
We thank the editor for the opportunity to respond to the Letter to the Editor regarding our manuscript entitled, “Primary total knee arthroplasty in super-obese patients: dramatically higher postoperative complication rates even compared to revision surgery.” We appreciate the readers’ interest in our manuscript and thank them for their careful
One or more of the authors of this paper have disclosed potential or pertinent conflicts of interest, which may include receipt of payment, either direct or indirect, institutional support, or association with an entity in the biomedical field which may be perceived to have potential conflict of interest with this work. For full disclosure statements refer to http://dx.doi.org/10.1016/j.arth.2015.07.016.
One or more of the authors of this paper have disclosed potential or pertinent conflicts of interest, which may include receipt of payment, either direct or indirect, institutional support, or association with an entity in the biomedical field which may be perceived to have potential conflict of interest with this work. For full disclosure statements refer to http://dx.doi.org/10.1016/j.arth.2015.07.021.
To the Editor:
554
Letters to the Editors / The Journal of Arthroplasty 31 (2016) 548–558
scrutiny of our methods. The writer of the letter raises five interesting points regarding the methods and database used for this study, which we will respond to individually. First, the reader notes that the ICD-9 codes for BMI N50 kg/m2 were not introduced until 2010. This is correct, although a review of the data demonstrates that many patients retroactively were assigned BMI codes for BMI N50 once these codes were introduced. Regardless, the goal of the study was to create a cohort of patients who, within the limitations of the database, were documented as super obese. The only way to do this was to use the ICD-9 codes for BMI N50 as was done in this manuscript and described in the methods. While there are likely some patients prior to 2010 who are super obese and were not coded as such, the integrity of the super obese cohort was of paramount importance, and this is assured regardless of the time frame for the introduction of the BMI codes. The reader also argues that this may not be representative of the “super obese” TKA patient population nationally. While this is possible, we are not aware of data that establish the incidence of super obesity in the TKA population nationally, nor did we claim that our study was designed to establish this number. We would counter that with 7666 super obese patients from a national Medicare database over two years may very well be fairly representative of the national Medicare population of super obese TKA patients during those years, and certainly the most representative sample of super obese TKA patients presented in the literature to date. We recognized this as a limitation of our study in the manuscript at the end of the discussion as follows: “While we attempted to accurately represent a large population of interest by using this database, we cannot assure that the database represents a true cross-section of the United States.” Second, the reader notes that a subset of the morbidly obese cohort (BMI between 40 and 50) was identified using the 278.01 code, which the reader correctly notes includes all patients with a BMI greater than 40, and may include some super obese patients. As stated before, the integrity of the super obese cohort was of paramount importance when constructing this study, so that all patients included in the super obese cohort carried a confirmed ICD-9 code for BMI N50. To accomplish this, we first created the super obese TKA cohort. We then next created the morbidly obese cohort by including all patients with BMI 40–49.9 ICD-9 codes and the 278.01 code, but excluding any patients with a code for BMI N50. In this fashion, patients with the code 278.01 for morbid obesity who were super obese and coded for BMI N50 were included in the super obese group only and excluded from the morbidly obese cohort. This process of creating mutually exclusive cohorts, starting first with the study population of interest (super obese TKA patients), substantially reduces the risk of selection bias. It is likely that some super obese patients prior to 2010 were not coded as super obese and thus remained in the morbidly obese cohort due to coding issues or the lack of an ICD-9 code for BMI N50 prior to that date. We again acknowledged in the manuscript that “the power of the analysis is dependent on the quality of the available data, which include accuracy of billing codes and miscoding or non-coding by physicians all as potential sources of error.” We would argue, however, that given the very striking results of the study, the inclusion of a small number of super obese patients in the morbid obese group would, if anything, result in our data underestimating the association of super obesity with complications following TKA when compared to morbid obesity. Third, the reader raises a similar point regarding BMI coding, but this time for BMI 40–49.9. This was the impetus for the use of ICD-9 code 278.01, which was present for the entire study period. ICD-9 code 278.01 would theoretically capture all patients coded as morbidly obese from 2005 to 2011. We also included the new V codes for BMI 40–49.9 to capture any patients who may have been coded as morbidly obese using the new coding from 2010 to 2011 that did not also have the 278.01 code for morbid obesity. Patients with both codes (278.01 and a V code for BMI 40–49.9) were only counted once. Fourth, the reader queries the use of patient rather than joint as the unit of analysis. The PearlDiver database is constructed in such a way as
to make the use of patient obligatory. This is described in our methods section and also highlighted in the first line of the results where we indicated that 1,681,681 unique patients underwent primary TKA. Thus, patients with sequential or bilateral TKA were only included only once in the study. The number of patients undergoing simultaneous bilateral TKA was not assessed; however, from experience in the database, this represents a very small portion of the overall population. If anything, the rate of simultaneous bilateral TKA is likely to be higher in the non-super obese population, which would make the discrepancy in complications even greater. Finally, the reader argues that the comparison of revision TKA patients with BMI b40 and primary TKA patients with BMI N 50 introduces numerous covariates such that reporting a differential outcome does not prove the effect of BMI alone on the result. The authors agree, and never stated in the manuscript that BMI was an independent predictor of increased complications following TKA. Comparing two cohorts with different covariates is methodologically sound as long as the conclusions are appropriate. In our conclusion, we were careful to state that super obesity was “associated’ with dramatically increased rates of complications after TKA compared to patients undergoing revision TKA, but we never claim that BMI has an independent effect on the differential outcome noted, because we had no method to control for the covariates that the reader mentions due to database limitations. As we state in our discussion, “the data are reported in cohorts, preventing multivariate analysis and thus the independent effect of BMI on postoperative complications cannot be reported, as factors such as age, gender, and medical comorbidities cannot be controlled.” We agree that further studies are required to determine the independent contribution of BMI on outcomes. Large administrative datasets provide a unique means to study orthopedic outcomes because of the ability to examine large sample sizes. As the reader points out, there are certainly limitations to this methodology. While our study does not provide all the definitive answers on this topic, we feel this study contributes to our understanding of TKA in these patient populations. Brian C. Werner, MD Cody L. Evans, MD Joshua T. Carothers, MD James A. Browne, MD⁎ ⁎Reprint requests: James A. Browne, MD http://dx.doi.org/10.1016/j.arth.2015.07.021
In Reply
We would like to appreciate and thank the authors of the letter for their interest in our study and their questions regarding our recent publication exploring and comparing the effects of continuous and singleshot adductor canal block technique [1]. The use of intermittent boluses was selected over a continuous infusion as our patients were reluctant to get up and walk after a total knee arthroplasty (TKA) when they had continuous infusions being injected in their thighs (personal observation on patients that were not a part of this study). The supporting studies [2,3] cited only signify that continuous infusion technique is not superior to the intermittent boluses. We appreciate the authors' concern over assessment of visual analog scale (VAS) score. The findings of the present study do show a lower VAS score in patients irrespective of the study group. The mean VAS score for patients in continuous adductor canal blockade (CACB) group reduced from 22.39 at 4 hours postsurgery to 20.76 at 24 hours, No author associated with this paper has disclosed any potential or pertinent conflicts which may be perceived to have impending conflict with this work. For full disclosure statements refer to http://dx.doi.org/10.1016/j.arth.2015.09.021.
With regard to the theoretical advantages of nuclear medicine to diagnose PJI, Glaudemans et al cite “convenience for the patient” and “cost-effectiveness.” A recent study published by our group, which was based on a formal method of decision-making, demonstrated that the current recommendation to approach the diagnosis of PJI with serum markers and joint fluid aspiration is the best alternative when cost, benefits, opportunities, and risks are taken into consideration [5]. Glaudemans et al emphasized that nuclear medicine studies are inexpensive and non-invasive when compared to other diagnostic tools. That strong statement must be supported with better evidence than pure conjecture. Currently, in this era of orthopedic care based on value [6], all interventions administered should have the highest cost effectiveness. It is important for future studies to validate the cost effectiveness of bone scan imaging, which appears to be a fairly invasive test. In addition, future studies on any diagnostic modality must go beyond statistical analyses and answer the most pertinent question: in what proportion of patients who underwent bone scan imaging did the result of the test result in a change in the treatment rendered? We are also surprised to read that the authors of the letter believe that the “pathology and/or microbiology, or at least a thorough clinical followup time of at least six months” should be the correct reference standard to diagnose PJI. The lack of a gold standard for diagnosis of PJI has lead many organizations, including the Musculoskeletal Infection Society, to propose diagnostic criteria. In closing, we are grateful to our colleagues for their interest in our study. We look forward to reading future studies evaluating the value of bone scan in the diagnosis of PJI when appropriate methodology for performing the test and interpretation of the data is utilized. Claudio Diaz-Ledezma, MD Courtney Lamberton, BS Paul M. Lichstein, MD Javad Parvizi, MD, FRCS⁎ The Rothman Institute at Thomas Jefferson University Philadelphia, Pennsylvania ⁎Reprint requests: Javad Parvizi, MD, FRCS, 125 S 9th St. Ste 1000 Philadelphia, PA 19107
553
Werner et al [1] published in The Journal of Arthroplasty (2015, vol. 30, no. 5). It is commendable that they have presented a currently “hot topic” in orthopedic surgery. However, we are writing to elaborate on some points in the article, and to raise some issues: 1. The focus of the study is on the super-obese patients (BMI N50 kg/m2). The investigators have identified these patients through V85.43– V85.45 ICD-9-CM (International Classification of Diseases, Ninth Revision, Clinical Modification) codes. These codes were not introduced until October 2010 [2]. While the study period is between 2005 and 2011, we assume that many “super-obese” patients in their database were not included in the cohort. Thus, their sample of “super obese” patients is not proportionally representative of “super obese” TKA patient population nationally. 2. A subset of the morbidly obese cohort (40 ≤ BMI ≤ 49.9) was identified through 278.01 code. The code identifies all patients with BMI N40 kg/m 2 (including super-obese patients). Therefore, some part of the morbidly obese cohort is actually super-obese. Because of this specific sample selection process, we are concerned about the possibility of selection bias in the study. 3. Another subset of the morbidly obese cohort was identified through V85.41–V85.42 codes. Again, these codes were added to the coding system late in 2010 [2]. 4. The unit of analysis, in arthroplasty outcome studies, is joint rather than patient. That is why investigators, in outcome studies, report the number of joints along with the number of patients. Were there any bilateral cases in this sample? If so, how were they accounted for? 5. The authors have compared a cohort of revision TKA patients with BMI b 40 kg/m 2 with a cohort of primary TKA patients with BMI N50 kg/m 2. These two cohorts have different covariates such that reporting a differential outcome doesn’t prove the effect of one variable (BMI) alone on the result. Therefore, this comparison does not appear to be methodologically sound. Since the authors of the article are experts in the field, we believe they have clear explanations for these issues.
http://dx.doi.org/10.1016/j.arth.2015.07.004 References 1. Parvizi J, Jacovides C, Zmistowski B, et al. Definition of periprosthetic joint infection: is there a consensus? Clin Orthop Relat Res 2011;469:3022. 2. Diaz-Ledezma C, Higuera CA, Parvizi J. Success after treatment of periprosthetic joint infection: a Delphi-based international multidisciplinary consensus. Clin Orthop Relat Res 2013;471:2374. 3. American Academy of Orthopaedic Surgeons Clinical Practice Guidelines Unit. The diagnosis of periprosthetic joint infections of the hip and knee: guideline and evidence report. Adopted June 18 2010 http://www.aaos.org/research/guidelines/PJIguideline. pdf. [accessed July 2, 2015]. 4. Zmistowski B, Della Valle C, Bauer TW, et al. Diagnosis of periprosthetic joint infection. J Arthroplasty 2014;29:77. 5. Diaz-Ledezma C, Lichstein PM, Dolan JG, et al. Diagnosis of periprosthetic joint infection in Medicare patients: multicriteria decision analysis. Clin Orthop Relat Res 2014. http://dx.doi.org/10.1007/s11999-014-3492-2. 6. Bozic KJ. Improving value in healthcare. Clin Orthop Relat Res 2013;471:368.
Some Points to Make About an Original Article
Nader Toossi, MD Norman A. Johanson, MD Orthopaedic Surgery Department, Drexel University College of Medicine http://dx.doi.org/10.1016/j.arth.2015.07.016 References 1. Werner BC, Evans CL, Carothers JT, et al. Primary total knee arthroplasty in super-obese patients: dramatically higher postoperative complication rates even compared to revision surgery. J Arthroplast 2015;30(5):849. 2. Schraffenberger LA. New ICD-9-CM diagnosis codes for FY 2011. J AHIMA 2010; 81(9):66.
Re: “Some Points to Make About an Original Article” In Reply
We have read with great interest the article titled, “Primary total knee arthroplasty in super-obese patients: dramatically higher postoperative complication rates even compared to revision surgery” by
We thank the editor for the opportunity to respond to the Letter to the Editor regarding our manuscript entitled, “Primary total knee arthroplasty in super-obese patients: dramatically higher postoperative complication rates even compared to revision surgery.” We appreciate the readers’ interest in our manuscript and thank them for their careful
One or more of the authors of this paper have disclosed potential or pertinent conflicts of interest, which may include receipt of payment, either direct or indirect, institutional support, or association with an entity in the biomedical field which may be perceived to have potential conflict of interest with this work. For full disclosure statements refer to http://dx.doi.org/10.1016/j.arth.2015.07.016.
One or more of the authors of this paper have disclosed potential or pertinent conflicts of interest, which may include receipt of payment, either direct or indirect, institutional support, or association with an entity in the biomedical field which may be perceived to have potential conflict of interest with this work. For full disclosure statements refer to http://dx.doi.org/10.1016/j.arth.2015.07.021.
To the Editor:
554
Letters to the Editors / The Journal of Arthroplasty 31 (2016) 548–558
scrutiny of our methods. The writer of the letter raises five interesting points regarding the methods and database used for this study, which we will respond to individually. First, the reader notes that the ICD-9 codes for BMI N50 kg/m2 were not introduced until 2010. This is correct, although a review of the data demonstrates that many patients retroactively were assigned BMI codes for BMI N50 once these codes were introduced. Regardless, the goal of the study was to create a cohort of patients who, within the limitations of the database, were documented as super obese. The only way to do this was to use the ICD-9 codes for BMI N50 as was done in this manuscript and described in the methods. While there are likely some patients prior to 2010 who are super obese and were not coded as such, the integrity of the super obese cohort was of paramount importance, and this is assured regardless of the time frame for the introduction of the BMI codes. The reader also argues that this may not be representative of the “super obese” TKA patient population nationally. While this is possible, we are not aware of data that establish the incidence of super obesity in the TKA population nationally, nor did we claim that our study was designed to establish this number. We would counter that with 7666 super obese patients from a national Medicare database over two years may very well be fairly representative of the national Medicare population of super obese TKA patients during those years, and certainly the most representative sample of super obese TKA patients presented in the literature to date. We recognized this as a limitation of our study in the manuscript at the end of the discussion as follows: “While we attempted to accurately represent a large population of interest by using this database, we cannot assure that the database represents a true cross-section of the United States.” Second, the reader notes that a subset of the morbidly obese cohort (BMI between 40 and 50) was identified using the 278.01 code, which the reader correctly notes includes all patients with a BMI greater than 40, and may include some super obese patients. As stated before, the integrity of the super obese cohort was of paramount importance when constructing this study, so that all patients included in the super obese cohort carried a confirmed ICD-9 code for BMI N50. To accomplish this, we first created the super obese TKA cohort. We then next created the morbidly obese cohort by including all patients with BMI 40–49.9 ICD-9 codes and the 278.01 code, but excluding any patients with a code for BMI N50. In this fashion, patients with the code 278.01 for morbid obesity who were super obese and coded for BMI N50 were included in the super obese group only and excluded from the morbidly obese cohort. This process of creating mutually exclusive cohorts, starting first with the study population of interest (super obese TKA patients), substantially reduces the risk of selection bias. It is likely that some super obese patients prior to 2010 were not coded as super obese and thus remained in the morbidly obese cohort due to coding issues or the lack of an ICD-9 code for BMI N50 prior to that date. We again acknowledged in the manuscript that “the power of the analysis is dependent on the quality of the available data, which include accuracy of billing codes and miscoding or non-coding by physicians all as potential sources of error.” We would argue, however, that given the very striking results of the study, the inclusion of a small number of super obese patients in the morbid obese group would, if anything, result in our data underestimating the association of super obesity with complications following TKA when compared to morbid obesity. Third, the reader raises a similar point regarding BMI coding, but this time for BMI 40–49.9. This was the impetus for the use of ICD-9 code 278.01, which was present for the entire study period. ICD-9 code 278.01 would theoretically capture all patients coded as morbidly obese from 2005 to 2011. We also included the new V codes for BMI 40–49.9 to capture any patients who may have been coded as morbidly obese using the new coding from 2010 to 2011 that did not also have the 278.01 code for morbid obesity. Patients with both codes (278.01 and a V code for BMI 40–49.9) were only counted once. Fourth, the reader queries the use of patient rather than joint as the unit of analysis. The PearlDiver database is constructed in such a way as
to make the use of patient obligatory. This is described in our methods section and also highlighted in the first line of the results where we indicated that 1,681,681 unique patients underwent primary TKA. Thus, patients with sequential or bilateral TKA were only included only once in the study. The number of patients undergoing simultaneous bilateral TKA was not assessed; however, from experience in the database, this represents a very small portion of the overall population. If anything, the rate of simultaneous bilateral TKA is likely to be higher in the non-super obese population, which would make the discrepancy in complications even greater. Finally, the reader argues that the comparison of revision TKA patients with BMI b40 and primary TKA patients with BMI N 50 introduces numerous covariates such that reporting a differential outcome does not prove the effect of BMI alone on the result. The authors agree, and never stated in the manuscript that BMI was an independent predictor of increased complications following TKA. Comparing two cohorts with different covariates is methodologically sound as long as the conclusions are appropriate. In our conclusion, we were careful to state that super obesity was “associated’ with dramatically increased rates of complications after TKA compared to patients undergoing revision TKA, but we never claim that BMI has an independent effect on the differential outcome noted, because we had no method to control for the covariates that the reader mentions due to database limitations. As we state in our discussion, “the data are reported in cohorts, preventing multivariate analysis and thus the independent effect of BMI on postoperative complications cannot be reported, as factors such as age, gender, and medical comorbidities cannot be controlled.” We agree that further studies are required to determine the independent contribution of BMI on outcomes. Large administrative datasets provide a unique means to study orthopedic outcomes because of the ability to examine large sample sizes. As the reader points out, there are certainly limitations to this methodology. While our study does not provide all the definitive answers on this topic, we feel this study contributes to our understanding of TKA in these patient populations. Brian C. Werner, MD Cody L. Evans, MD Joshua T. Carothers, MD James A. Browne, MD⁎ ⁎Reprint requests: James A. Browne, MD http://dx.doi.org/10.1016/j.arth.2015.07.021
In Reply
We would like to appreciate and thank the authors of the letter for their interest in our study and their questions regarding our recent publication exploring and comparing the effects of continuous and singleshot adductor canal block technique [1]. The use of intermittent boluses was selected over a continuous infusion as our patients were reluctant to get up and walk after a total knee arthroplasty (TKA) when they had continuous infusions being injected in their thighs (personal observation on patients that were not a part of this study). The supporting studies [2,3] cited only signify that continuous infusion technique is not superior to the intermittent boluses. We appreciate the authors' concern over assessment of visual analog scale (VAS) score. The findings of the present study do show a lower VAS score in patients irrespective of the study group. The mean VAS score for patients in continuous adductor canal blockade (CACB) group reduced from 22.39 at 4 hours postsurgery to 20.76 at 24 hours, No author associated with this paper has disclosed any potential or pertinent conflicts which may be perceived to have impending conflict with this work. For full disclosure statements refer to http://dx.doi.org/10.1016/j.arth.2015.09.021.