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Article
Peer-Review Record

Measuring Erythrocyte Sedimentation Rate Using Photometric Rheology Technology Demonstrates Superior Sample Stability as Compared to the Westergren Method

Diagnostics 2026, 16(16), 2648; https://doi.org/10.3390/diagnostics16162648
by Thomas Koshy 1,*, Yenny Lamazares 2, Susan Evans 3 and Saeed Jortani 4
Reviewer 1: Anonymous
Reviewer 2:
Reviewer 3: Anonymous
Diagnostics 2026, 16(16), 2648; https://doi.org/10.3390/diagnostics16162648
Submission received: 7 July 2026 / Revised: 7 August 2026 / Accepted: 17 August 2026 / Published: 20 August 2026
(This article belongs to the Section Clinical Laboratory Medicine)

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

The article is well written and has useful information. But there is conflict of interest. Is there some data on comparison with other manufacturers. Note on that data should also be added.

 

Author Response

See attached Word document

Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

 I have reviewed your manuscript with considerable interest and find it to be a valuable and timely contribution to the field of laboratory hematology. The study addresses a pervasive pre-analytical challenge—the limited stability of blood samples for ESR testing—and provides compelling evidence that the iSED photometric rheology method offers a significant advantage over the classical Westergren method.

The findings are clinically and operationally important, with clear implications for improving laboratory workflow, reducing sample rejection rates, consolidating phlebotomy procedures, and enhancing patient care. The methodology is robust, the statistical approach is innovative, and the conclusions are well-supported by the data.

I have identified a number of points that require clarification or minor revision. These are outlined below and are intended to further strengthen an already excellent manuscript.

Major Points Requiring Response

1. Definition of Stability and Clinical Acceptability

You have defined sample stability using a stringent statistical framework: the 95% confidence interval (CI) of the Passing-Bablok slope must include 1.00, the 95% CI of the intercept must include 0.00, and the Spearman's correlation coefficient must be ≥ 0.90. This approach is scientifically rigorous and defensible.

However, as you correctly note in the Discussion, the ESR is a biological phenomenon rather than a defined analyte with an established total allowable error (TEa) under CLIA '88. At the 8-hour timepoint for the iSED cohorts, the intercept criterion was not met (CIs did not include 0.00), yet the actual deviations were minimal (intercepts of 1.89 and -1.62 mm/h). You reasonably concluded that these results were acceptable and that true instability would not resolve with time.

Request: Please clarify whether a secondary, clinically relevant threshold was considered during the analysis. For example, did you evaluate a bias limit such as ± 5 mm/h or ± 10% as an alternative acceptance criterion? If such a criterion was applied or referenced (e.g., from CLSI guidelines or previous ICSH recommendations), please include it explicitly in the Methods or Discussion. If not, please add a sentence in the Discussion justifying why the strict statistical approach was chosen and how the 8-hour findings should be interpreted clinically despite not meeting the intercept criterion.

2. Handling and Impact of Removed Outliers

You identified and excluded three samples from the iSED/RT cohort at the 24-hour timepoint due to an "uncharacteristic decline" in ESR values between 12 and 24 hours. These were identified as outliers using the interquartile fence method (Q3 + 1.5 × IQR). While this approach is statistically legitimate, the exclusion of outliers from a stability study is always a sensitive issue, as it could potentially influence the overall conclusion of stability.

Request: To enhance transparency and demonstrate the robustness of your findings, please provide a supplementary figure or table showing the Passing-Bablok regression results for the iSED/RT 24-hour timepoint including these three samples. This will allow readers and reviewers to assess the magnitude of their influence on the overall conclusion. If the results remain unchanged or only minimally affected, this would strengthen the paper. If the results change substantially, this should be acknowledged as a limitation.

3. Influence of Hematocrit (Hct) and Specific Disease States

The ESR is known to be influenced by hematocrit, with anemia generally increasing the ESR and polycythemia decreasing it. While the iSED method is marketed as being less sensitive to Hct than the Westergren method, you do not present any Hct data for your study population. The inclusion of patients with "conditions related to an elevated ESR or inflammation" may have introduced a wide range of Hct values.

Request: Please summarize the range or distribution of Hct values in your study cohort in the Results section. If available, please comment on whether Hct appeared to correlate with stability in either method (e.g., by performing a subgroup analysis comparing samples with low, normal, and high Hct). If Hct data were not collected, please add this as a limitation in the Discussion. Additionally, consider commenting on whether specific disease states (e.g., anemia of chronic disease, polycythemia vera, or sickle cell disease) might affect the stability patterns observed.

4. Asymmetric Timepoint Intervals

In the Methods, you outline that the Westergren/RT cohort was tested at 8, 10, 12, and 24 hours, whereas the iSED cohorts were tested at 8, 10, 12, 24, 28, 36, and 48 hours. While it is entirely logical not to extend testing of a method already showing instability at 24 hours to 48 hours, this asymmetry is worth noting.

Request: Please add a brief acknowledgment of this asymmetry as a minor limitation in the Discussion section. This will demonstrate transparency and completeness in your reporting.

Minor Points and Editorial Corrections

5. Table 3 – Visual Enhancement for Readability

Table 3 is comprehensive and contains the most critical data of the manuscript. However, it is information-dense and requires careful reading to identify which values failed the acceptance criteria.

Suggestion: To improve rapid interpretation, please bold or highlight in red the specific values (slope, intercept, or correlation coefficient) that did not meet the stability criteria for that timepoint. This will allow readers to quickly identify the timepoints at which instability was observed.

6. Figure 2 – Enhancement of Bland-Altman Drift Plot

The Bland-Altman drift plot is a central and innovative figure in this manuscript. However, it is presented without reference lines to guide interpretation.

Suggestion: Please add a horizontal reference line at 0% difference to clearly indicate the point of perfect agreement with baseline. If data permit, consider adding lines representing the upper and lower limits of agreement (e.g., mean ± 2SD) to allow readers to better appreciate the magnitude of dispersion and the trend of drift over time. This would significantly enhance the interpretability of the figure.

7. Figure 1 – Caption Clarity

The caption for Figure 1 currently states: "Individual Time 0 baseline data points are plotted against the results generated after 24 hours from all three cohorts." This is clear, but the figure itself could benefit from a legend differentiating the three regression lines more distinctly.

Suggestion: Please ensure that the legend clearly identifies each cohort (Westergren/RT, iSED/RT, iSED/4–8°C) with distinct symbols or colors that are also referenced in the caption. This is particularly important if the figure will be printed in grayscale.

Author Response

See attached Word document

Author Response File: Author Response.pdf

Reviewer 3 Report

Comments and Suggestions for Authors

The article examines an important aspect of blood sample stability for ESR determination -a topic of particular relevance to centralized laboratories with remote blood collection sites. The authors analyzed ESR results obtained via two methods—the Westergren method and photometric rheology using analyzers -across various temperature conditions and sample storage durations. The authors demonstrate promising results regarding the extension of the diagnostic window when using the rheological photometry method. However, there are certain points regarding the study that the authors should clarify:

Why do the authors compare sample stability across different methods under different storage conditions? The Westergren group is tested only at room temperature (RT), whereas the iSED group is tested at both RT and refrigerated temperatures (4–8°C). Standard procedure dictates that the Westergren ESR test is best performed within two hours of blood collection; if this is not possible, samples should be stored at 2–4°C for up to 24 hours and warmed to room temperature before testing. It remains unclear whether the results would differ if a comparison were made between the Westergren 4°C (24h) group and the iSED 4°C (24h) group.

The authors’ justification for excluding three iSED/RT samples -which showed an atypical ESR decrease between 12 and 24 hours -on the grounds that they were statistical outliers (Q3 + 1.5 × IQR) is unconvincing. Can the authors speculate on the cause of these outliers? Is it a biological or pre-analytical factor, such as the presence of micro-clots? Excluding 5% of the results merely to improve statistical metrics would be an unjustified action.

While the choice of Passing-Bablok regression is appropriate for method comparison, the authors apply, in my view, very stringent criteria for assessing blood sample stability: the slope’s confidence interval (CI) must include 1.00, the intercept’s CI must include 0.00, and the Spearman correlation coefficient must be at least 0.90. Such strict criteria may lead to the exclusion of samples that are otherwise perfectly acceptable based on clinical and laboratory parameters.

The Bland-Altman plot appears incorrect. The authors averaged the difference across all ESR levels for each time point to illustrate the trend in the mean ESR value; however, this fails to show how error variance might increase over time. This is a critical issue for the manuscript. A better approach might be to present two plots: one showing the trend in the mean, and a second (a true Bland-Altman plot) demonstrating the stability of the diagnostic test performed on the analyzer (i.e., showing that data dispersion remains constant across different ranges of the plot).

The manuscript may be accepted for publication subject to addressing these comments.

Author Response

See attached Word document

Author Response File: Author Response.pdf

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