PONE-D-22-00403Effects of regional limb perfusion technique on concentrations of antibiotic achieved at the target site: a meta-analysisPLOS ONE

Dear Dr. Ortved,

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Reviewer #1: Yes

Reviewer #2: Yes

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Reviewer #1: Yes

Reviewer #2: Yes

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Reviewer #1: Yes

Reviewer #2: Yes

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Reviewer #1: Yes

Reviewer #2: Yes

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5. Review Comments to the Author

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Reviewer #1: There are some inconsistencies in the results and discussion that are critical to have fixed prior to acceptance of this manuscript.

February 11, 2022

Comments to the authors.

Overall, this manuscript is well written and adds significant information to previously published literature for regional limb perfusion in horses.

There are a few introduction, results, and discussion points that could be expanded on. The most critical discussion point and figure results that need to be clarified are also critical.

In several areas in the manuscript it is confusing as to whether pneumatic tourniquets > 400 mm Hg achieved higher MICs than pneumatic tourniquets <400 mm Hg. I have noted all areas that I found a discrepancy. However the entire manuscript should be reviewed to ensure this is clarified.

Lines 298- 299 Should read tourniquest <400 mm Hg pressures instead of > 400 mm Hg pressure

Lines 310- 316. Can the authors also discuss other possibilities why local anesthesia could enhance the effectiveness of the regional limb perfusion if any.

Lines 324- 325. What time period is 10x> MIC typically reached in regional limb perfusion. For example it might say.. Typically the CMAX:MIC>10 is reached by 15- 20 minutes. However, the mean time to peak concentrations are at 29 minutes.

Lines 331 to 339 You might also include.. This may allow the clinician to start proximal with the regional limb perfusion and on sequential treatments go more distal if there is a problem with a previous regional limb perfusion site.

Line 348 I would state... Administering 1/3 the systemic dose can be considered efficacious... The inclusion of no more than 1/3 the systemic dose leaves the authors open to “what about < 2%...

Figures S1 and S2 appear to be mislabeled where the Pneumatic tourniquet > 400 should be listed second, below the rubber tourniquet with the higher MIC. Beneath that the tourniquet < 400 should be listed third below the rubber tourniquet with the lowest MIC. A small label at the top of S1 and S2 stating susceptible bacteria and resistant bacteria would be helpful.

Please clarify what the significance is in including Table S2 and S3 for the readers as a modified table.

Both Figures and Tables appear the same. Probably they should all be labeled either Figures or Tables.

Reviewer #2: I have four comments:

1. Using the word "trial" for a study arm was a little confusing because trial is commonly used in a clinical trial, which is a study. Trial is also used in veterinary gait analyses. In line 154, it appears that trial and study are defined somewhat interchangeably. I think it would help your readers to change trial to arm or group. For what it's worth, Wikipedia's entry for meta-regression uses the word arm.

2. It is not necessary to include the univariate regression analysis. The multivariate regression is superior to the univariate one, so the univariate analysis adds nothing to the article, and that's especially true when the two analyses give different results. As it stands, it appears that readers have to make up their own minds about which analysis to believe. However, if the univariate truly adds something to the understanding of the data, then keep it in, but please explain why.

3. The forest plots caused me the most difficulty.

4. I understand the forest plots are used to visualize the meta-regression results but are effect sizes on the forest plot from the multiple regression, univariate regression, or raw data?

There are several things on the plots that I wasn't sure about:

1. The heading on the 4th column is "effect size with 95% CI," but effect size isn't mentioned in the text. How is it defined?

2. Please describe:

3. what Qb(1) means

4. what do all the p-values in the last column mean. What is being tested?

5. What is Q(121)? Is 121 correct, or should it be Q(122)?

6. There appear to be three heterogeneity statistics, but I think only one is described in the manuscript. Please define them in the statistics section. (Or just keep one of them.)

7. In line 245, you state, "Finally, meta-analysis showed that synovial structure, % systemic dose, tourniquet location, general anesthesia vs. standing, and tourniquet time were not statistically significantly associated with the outcome (Figs 4 and 5).

But in figure 5, tourniquet time has a p=0.02. Why is that not statistically significant?

That raises a larger question. I didn't see a cutoff for statistical significance in the manuscript. The contemporary approach in a study like this would be to call it an exploratory study and omit a cutoff and any mention of statistical significance. The p-values would be used like effects sizes to find the best therapy. Alternatively, you could do some kind of Type I error inflation correction and then use that method to give an overall error rate of 5%.

But as the analysis stands, with a 0.05 cutoff for each test, some of your results may be false-positive discoveries.

***if heterogeneous, how do you justify the regression?

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Reviewer #1: No

Reviewer #2: No

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Effects of regional limb perfusion technique on concentrations of antibiotic achieved at the target site: a meta-analysis

PONE-D-22-00403R1

Dear Dr. Ortved,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

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Kind regards,

Richard Evans

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Thank you for responding promptly to our comments. One last thing to double-check: Near the bottom of your responses, you state, "we have used a Bonferroni-corrected p-value of 0.006 (0.05 divided by the 8 independent variables being tested)." However, the Bonferroni correction should be 0.05 divided by the number of statistical tests, not the number of independent variables. I'm assuming that in your case, those two adjustments are the same. Please check that your inferences don't change using the correct Bonferroni correction.