Predictive Values of Handgrip Strength for Protein-Energy Wasting Among Patients Undergoing Maintenance Hemodialysis: A Systematic Review and Meta-Analysis

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

This article seems interesting and well-designed. However, as of today, there is no single PEW marker, and multiple markers must be used.

 

As the authors state, several parameters can modify muscle strength and should be considered in future articles.

 

It would be appropriate to mention in the reviewed articles and discussions that the dialysis regimen, as well as its frequency and duration, may influence improvements in nutritional status.

   

Author Response

Comment 1: This article seems interesting and well-designed. However, as of today, there is no single PEW marker, and multiple markers must be used.

Response 1:

Thank you for your valuable feedback. We acknowledge that there is currently no single PEW marker and that multiple markers are typically used. A commonly used tool in clinical practice is the Malnutrition-Inflammation Score (MIS), which is time-consuming and requires expertise. Our study aims to contribute to this field by evaluating handgrip strength (HGS) as a predictor of PEW among maintenance hemodialysis patients. In the conclusion, we also discuss the need for a multi-marker approach or a single marker with high predictive value and explore how our findings from HGS could complement existing markers. We appreciate any further insights you may have on integrating our findings with broader PEW marker panels.

 

Comment 2: As the authors state, several parameters can modify muscle strength and should be considered in future articles.

Response 2:

Thank you for your insightful comment. We agree that several parameters can influence muscle strength and should be considered in future studies. Factors such as age, sex, nutritional status, inflammation, comorbidities (e.g., diabetes, cardiovascular disease), physical activity levels, dialysis adequacy, and biochemical markers (e.g., albumin, C-reactive protein, and creatinine) (Nogueira et al 2022 and Ikizler et al 2020) have been reported to affect muscle strength in maintenance hemodialysis patients. In our study, we acknowledge these variables and suggest that future research should incorporate them to enhance the predictive accuracy of handgrip strength as a marker for PEW. We appreciate any additional suggestions on relevant parameters that could further refine this assessment.

Ref:

1. Nogueira Á, Álvarez G, Barril G. Impact of the Nutrition-Inflammation Status on the Functionality of Patients with Chronic Kidney Disease. Nutrients. 2022 Nov 10;14(22):4745.
2. Ikizler TA, Burrowes JD, Byham-Gray LD, Campbell KL, Carrero JJ, Chan W, Fouque D, Friedman AN, Ghaddar S, Goldstein-Fuchs DJ, Kaysen GA, Kopple JD, Teta D, Yee-Moon Wang A, Cuppari L. KDOQI Clinical Practice Guideline for Nutrition in CKD: 2020 Update. Am J Kidney Dis. 2020 Sep;76(3 Suppl 1):S1-S107.

 

Comment 3: It would be appropriate to mention in the reviewed articles and discussions that the dialysis regimen, as well as its frequency and duration, may influence improvements in nutritional status.

Response 3:

Thank you for your insightful comment. We agree that the dialysis regimen, including its frequency and duration, may play a significant role in influencing improvements in nutritional status. Evidence shows that each dialysis session can result in the loss of approximately 6–12 g of amino acids and 7–8 g of protein, which may contribute to hypoalbuminemia, a significant predictor of malnutrition and mortality (Sahathevan et al 2020). We have incorporated this important aspect in the reviewed articles and discussions to provide a more comprehensive understanding of the factors affecting nutritional outcomes in dialysis patients.

 

Ref: Sahathevan S, Khor BH, Ng HM, Gafor AHA, Mat Daud ZA, Mafra D, Karupaiah T. Understanding Development of Malnutrition in Hemodialysis Patients: A Narrative Review. Nutrients. 2020 Oct 15;12(10):3147.

Reviewer 2 Report

Comments and Suggestions for Authors

The study by Muhammad Haneef Ghifari is a systematic review and meta-analysis which evaluated the predictive value of HGS in identifying PEW in dialysis patients. The authors identified 5 studies for this analysis and found that HGS exhibited moderate sensitivity and specificity in predicting PEW status.

This is an interesting analysis, the manuscript is clearly written and the results are presented well.

Here are some suggestions which may help to further improve the manuscript:

Line 24: HGS needs to be explained at first time mentioned

Line 156: “On the other hand, we did not find any non-English papers”: would be better to write in a positive way: all papers were in English language.

Table 2: Patient characteristics should indicate the unit (number, years, kg/m²)

Table 2: If possible use the same number of decimal places for the same variable

Table 2: How was the cut-off determined?

Line: 186: What do the authors mean with high risk?

Figure 3 and 4: Explanation of the observed data points in the legend would be helpful. It is not clear why there are 6 data points if only 5 studies were analyzed.

Figure 3 and 4: Quality of figure could be improved as the 95% prediction contour is not visible in Figure 3 and the 95% confidence contour is not clear in the legend (blurred)

Discussion: The authors could consider discussing also other methods such as bioimpedance spectroscopy for determination of PEW.

Author Response

General comment: The study by Muhammad Haneef Ghifari is a systematic review and meta-analysis which evaluated the predictive value of HGS in identifying PEW in dialysis patients. The authors identified 5 studies for this analysis and found that HGS exhibited moderate sensitivity and specificity in predicting PEW status.

This is an interesting analysis, the manuscript is clearly written and the results are presented well.

Response to general comment: Thank you for your thoughtful feedback and kind words regarding the manuscript. We are glad that you found the analysis interesting and the results clearly presented. We greatly appreciate your suggestions and will carefully consider them in order to further improve the manuscript.

Here are some suggestions which may help to further improve the manuscript:

Comment 1: Line 24: HGS needs to be explained at first time mentioned

Response 1: Thank you for your comment. We have added a concise description of HGS: “Assessing a more practical and reliable tool, such as handgrip strength (HGS), is important, as it strongly correlates with PEW status in MHD patients, where increased protein and fat breakdown leads to muscle strength and function loss."

Comment 2: Line 156: “On the other hand, we did not find any non-English papers”: would be better to write in a positive way: all papers were in English language.

Response 2: Thank you for your suggestion. We have revised the sentence to reflect a more positive phrasing: "All papers included in the review were in English."

Comment 3: Table 2: Patient characteristics should indicate the unit (number, years, kg/m²)

Response 3: Thank you for your comment. We have updated Table 2 to include the appropriate units for patient characteristics (number [n], years, kg/m²) for clarity.

Comment 4: Table 2: If possible use the same number of decimal places for the same variable

Response 4: Thank you for your suggestion. We have standardized the number of decimal places for each variable in Table 2 to ensure consistency throughout.

Comment 5: Table 2: How was the cut-off determined?

Response 5: Thank you for your comment. We would like to clarify that our meta-analysis did not establish new cut-off values for handgrip strength (HGS). Instead, we extracted and reported the cut-off values as determined by the individual studies included in our review. Most studies selected their cut-offs by maximizing sensitivity and specificity, although the specific methods were not always fully explained. Only one study (Patoc et al., 2024) explicitly used the closest-to-(0,1) criterion. This has been clearly stated in the footnote of Table 2 and in the main text under the “Study Characteristics” section.

Comment 6: Line: 186: What do the authors mean with high risk?

Response 6: Thank you for your comment. By "high risk," we refer to studies where measurements of HGS were taken at only one time point (either pre- or post-hemodialysis), which may introduce variability and affect the predictive performance of HGS. We have clarified this in the revised manuscript to avoid any ambiguity.

Comment 7: Figure 3 and 4: Explanation of the observed data points in the legend would be helpful. It is not clear why there are 6 data points if only 5 studies were analyzed.

Response 7: Thank you for your comment. The six data points in Figures 3 and 4 represent the five studies included in the analysis, with one study contributing data for both pre- and post-hemodialysis measurements. This accounts for the additional data point. We have added a clarification in the figure legends to explain this.

Comment 8: Figure 3 and 4: Quality of figure could be improved as the 95% prediction contour is not visible in Figure 3 and the 95% confidence contour is not clear in the legend (blurred)

Response 8: Thank you for pointing this out. We apologize for the quality of the figures. We have improved the resolution of Figure 3 to make the 95% prediction contour more visible, and we have also clarified the legend to provide a clearer description of the 95% confidence contour. The updated figure has been revised for better clarity.

Comment 9: Discussion: The authors could consider discussing also other methods such as bioimpedance spectroscopy for determination of PEW.

Response 9: Thank you for your valuable suggestion. We agree that bioimpedance spectroscopy is an important method for determining PEW. We have now included a discussion on this technique in the manuscript, highlighting its advantages and limitations in comparison to handgrip strength. This addition broadens the scope of the discussion and provides a more comprehensive view of the methods available for assessing PEW.

“Another recent study also showed that bioelectrical impedance analysis (BIA)-derived phase angle (PhA) has shown potential for detecting PEW in hemodialysis patients. A multi-centre study in Malaysia found PhA to be an independent predictor of PEW (adjusted OR = 0.308, p = 0.001), with excellent discriminative performance (adjusted AUC for males = 0.809, females = 0.719). Gender-specific cut-offs were also identified, with males having a higher PhA threshold (4.26°) compared to females (3.30°). However, BIA's practicality may be limited by factors such as hydration status, which can affect its accuracy in HD patients (Lim et al 2021). Given these limitations, HGS is a more practical and reliable alternative for assessing PEW, due to its simplicity, low cost, and ease of use in clinical settings.”

Ref: Lim CK, Lim JH, Ibrahim I, Chan YM, Zakaria NF, Yahya R, Daud ZAM. Bioelectrical Impedance Analysis Derived-Phase Angle as a Pragmatic Tool to Detect Protein Energy Wasting among Multi-Ethnic Hemodialysis Patients. Diagnostics (Basel). 2021 Sep 23;11(10):1745