Clinical impact of monocyte distribution width and neutrophil-to-lymphocyte ratio for distinguishing COVID-19 and influenza from other upper respiratory tract infections: A pilot study.

The coronavirus disease 2019 (COVID-19) has become a pandemic. Rapidly distinguishing COVID-19 from other respiratory infections is a challenge for first-line health care providers. This retrospective study was conducted at the Taipei Medical University Hospital, Taiwan. Patients who visited the outdoor epidemic prevention screening station for respiratory infection from February 19 to April 30, 2020, were evaluated for blood biomarkers to distinguish COVID-19 from other respiratory infections. Monocyte distribution width (MDW) ≥ 20 (odds ratio [OR]: 8.39, p = 0.0110, area under curve [AUC]: 0.703) and neutrophil-to-lymphocyte ratio (NLR) < 3.2 (OR: 4.23, p = 0.0494, AUC: 0.673) could independently distinguish COVID-19 from common upper respiratory tract infections (URIs). Combining MDW ≥ 20 and NLR < 3.2 was more efficient in identifying COVID-19 (AUC: 0.840). Moreover, MDW ≥ 20 and NLR > 5 effectively identified influenza infection (AUC: 0.7055). Thus, MDW and NLR can distinguish COVID-19 from influenza and URIs.

Introduction

The novel coronavirus disease 2019 (COVID-19) is a highly contagious viral infection. The COVID-19 outbreak, which occurred in early 2020, was designated by the World Health Organization as a public health emergency of international concern, sixth in the last decade, on January 30, 2020 [1]. By April 23, 2020, the number of infectious patients and casualties had reached 2,544,792, and 175,694, respectively.

Severe acute respiratory syndrome (SARS) coronavirus 2 (SARS-CoV-2), isolated from the bronchoalveolar lavage of patients, is transmitted through respiratory droplets and contact [2, 3]. Moreover, SARS-CoV-2 can be transmitted through aerosols in a closed environment [4]. Its high basic reproduction number, ranging from 2.2 to 2.68, suggests that SARS-CoV-2 has high transmissibility [5-7].

Initially, pyretic patients with a respiratory illness and travel history to high-risk countries were considered suspected cases. The presentation of COVID-19 is similar to other respiratory infections, including influenza, bronchitis, and upper respiratory tract infection (URI). For a physician, evaluating whether to collect a nasal swab for examination or hospitalizing or isolating a patient is a challenge.

Radiologic studies could improve the early diagnosis of COVID-19; however, 18%–56% patients with nonsevere symptoms had nonspecific findings in chest radiography and computed tomography, with a lower rate observed in the early phase of the disease [8-10]. In addition, chest radiography or computed tomography images could not be used to confirm infection, with similar findings frequently seen in atypical pneumonia [11, 12].

Several blood biomarkers, including C-reactive protein (CRP), platelet-to-lymphocyte ratio (PLR), and neutrophil-to-lymphocyte ratio (NLR), have been used for evaluating inflammation and relative disease status [13-18]. Because circulating neutrophils and monocytes are among the first to respond to an infection, the increase in immune cell volume may be useful for early detection. Monocyte distribution width (MDW), a novel biomarker with a normal range of <20, was used to detect early sepsis [19].

In this study, MDW and other blood biomarkers were used to evaluate the likelihood of COVID-19 and distinguish the disease from other respiratory infections in the early phase.

Materials and methods

Study design

This prospective observational study was conducted at the Taipei Medical University Hospital, a major tertiary hospital with 750 beds in Taipei, Taiwan. Patients who visited the emergency department (ED) with suspected COVID-19 were recruited for the study. This study was approved by the Joint Institutional Review Board of Taipei Medical University (approval number: N201904066). Informed consent was waived with the approval of the aforementioned review board because anonymous and deidentified information were used.

Study population

We enrolled consecutive patients admitted to the ED from January 22 to April 30, 2020 with fever, respiratory symptoms, or travel history and with suspected COVID-19. Patients with fever, URI symptoms, or history of travel abroad in the previous 2 weeks were not permitted to enter the hospital and received medical treatment at the outdoor epidemic prevention screening station, managed by emergency physicians. Only patients who were hospitalized and had blood testing done were included in the study. If a patient had two or more records of admission, only the first record was documented for research; finally, 174 cases were analyzed. All confirmed patients with COVID-19 and URI were ethnically Han Chinese.

Data collection

Patient data were collected on June 1, 2020 from the electronic database of the web-based physician order entry system of the Taipei Medical University Hospital. We collected patient demographic, travel history, vital signs, clinical symptoms, and laboratory data. Demographic features included sex, age, and body mass index. Clinical symptoms related to COVID-19 and influenza included fever, cough, rhinorrhea, sore throat, dyspnea, nausea, diarrhea, and loss of smell.

Laboratory data included white blood cell (WBC), platelet (PLT), and differential blood counts; alanine aminotransferase, aspartate aminotransferase, creatinine, and CRP levels; as well as MDW. NLR and PLR values were calculated by dividing neutrophil and PLT counts by lymphocyte count, respectively.

MDW was analyzed on a Beckman Coulter UniCel DxH 900 analyzer, a quantitative, multiparameter automated hematology analyzer supplied by Beckman Coulter Taiwan INC., Taiwan branch. The WBC differential was established using three measurements: individual cell volume, high-frequency conductivity, and laser-light scatter. Monocytes were identified using this technology and MDW was calculated as the standard deviation of a set of monocyte cell volume values.

SARS-CoV-2 RNA was detected through real-time PCR on a MagPurix 12S System using a Zinexts MagPurix Viral/Pathogen Nucleic Acids Extraction Kit B.

Statistical analysis

The characteristics of patients with respiratory infections, including COVID-19, were analyzed using analysis of variance for continuous variables, including age, height, weight, body mass index, WBC, and CRP, and Pearson’s chi-square test for categorical variables, including sex, travel history, and clinical symptoms. Simple and multiple logistic regression was performed to obtain the odds ratio (OR). Receiver operating characteristic (ROC) curve analysis was used to determine the optimal cutoff value, with the highest Youden’s index for continuous variables, such as MDW and NLR, to distinguish COVID-19 from influenza and URI. All analyses were performed on SAS (version 9.4).

Results

Over January 22 to April 30, 2020, 2,335 ED patients with fever, respiratory symptoms, or travel history were screened. Of them, 775 were screened through the nasal swab reverse transcription polymerase chain reaction (RT-PCR). In total, 174 patients, who were hospitalized and had undergone blood testing, were enrolled in this study. Of them, 9 were confirmed as COVID-19 positive through nasal swab RT-PCR screening, 24 patients were confirmed to have influenza using the rapid-test for influenza, and 141 patients were diagnosed as having a common URIs clinically.

Baseline characteristics, including vital signs, symptoms, and laboratory results, were compared between patients with COVID-19, influenza, and common URIs (Table 1). Preponderance of older age and women was noted in the influenza (45.0 ± 29.0 years) and COVID-19 (88.9%) groups, respectively, but without a significant difference. The body mass index was similar in all groups. All COVID-19 cases had a history of travel abroad.

Table 1

Characteristics of patients presenting with URIs at the ED.

	COVID-19 (n = 9)	Influenza (n = 24)	Common URI (n = 141)	p
Age	40.4 ± 16.1	45.0 ± 29.0	40.0 ± 23.1	0.6395
Female sex (%)	8 (88.9%)	11 (45.8%)	73 (51.8%)	0.0731
Body mass index	23.3 ± 6.2	23.2 ± 6.4	23.2 ± 5.2	0.9989
Travel (outside Taiwan)	9 (100.0%)	4 (16.7%)	61 (43.3%)	< 0.0001
Symptoms (%)
Fever	6 (66.7%)	23 (95.8%)	95 (67.4%)	0.0165
Cough	3 (33.3%)	16 (66.7%)	70 (49.7%)	0.1667
Rhinorrhea	1 (5.2%)	0	17 (12.1%)	0.1827
Sore throat	1 (11.1%)	3 (12.5%)	30 (21.3%)	0.4883
Dyspnea	3 (33.3%)	6 (25.0%)	19 (13.5%)	0.1283
Nausea	0	5 (20.8%)	14 (9.9%)	0.2286
Diarrhea	0	0	20 (14.2%)	0.0736
Loss of smell	2 (22.2%)	0	1 (0.7%)	0.0122
Vital signs at ED
Body temperature	37.4 ± 0.9	38.4 ± 1.1	37.3 ± 0.9	< 0.0001
Heart Rate (beats/min)	91.4 ± 21.3	117.7 ± 25.8	101.9 ± 21.9	0.0029
Respiratory rate (/min)	17.4 ± 1.5	19.3 ± 3.0	18.1 ± 2.5	0.1015
Blood pressure
Systolic (mm Hg)	125.0 ± 14.1	140.6 ± 19.9	138.6 ± 22.7	0.1758
Diastolic (mm Hg)	80.1 ± 11.6	75.9 ± 13.5	84.3 ± 14.5	0.0424
Mean arterial (mm Hg)	95.1 ± 10.5	97.4 ± 13.3	102.4 ± 15.5	0.1709
Shock index	0.7 ± 0.2	0.8 ± 0.2	0.8 ± 0.2	0.2821
SpO2 (%)	98.1 ± 2.0	96.0 ± 7.4	97.6 ± 4.9	0.4037
Laboratory test
Creatinine (mg/dL)	0.7 ± 0.2	0.8 ± 0.3	0.9 ± 0.8	0.5976
AST (U/L)	21.4 ± 4.5	32.3 ± 10.7	27.7 ± 19.7	0.4801
ALT (U/L)	20.3 ± 6.6	29.1 ± 25.0	27.8 ± 22.0	0.5812
CRP (mg/dL)	1.1 ± 1.7	1.9 ± 1.5	3.5 ± 6.1	0.2472

ALT, alanine aminotransferase; AST, aspartate aminotransferase; BMI, body mass index; COVID, coronavirus disease; CRP, C-reactive protein; ED, emergency department; URI, upper respiratory infection.

Based on the vital signs at presentation to the ED, higher body temperature (38.4 ± 1.1°C, p < 0.0001) and tachycardia (117.7 ± 25.8 beats/min, p = 0.0029) were more significant in the influenza group. The differences in the respiratory rate, mean arterial pressure, shock index, and oxygen saturation levels between the three groups were nonsignificant.

Most clinical symptoms were not significantly different between the groups. Only fever (before ED visit) presented in 95.8% influenza cases. Two cases (22.2%) of COVID-19 had olfactory problems. Laboratory test results, including creatinine, alanine aminotransferase, aspartate aminotransferase, and CRP levels, did not differ significantly between the three groups.

Table 2 displays the blood parameters associated with systemic inflammation including WBC count, MDW, PLR, and NLR. Of these, only MDW demonstrated a significant between-group difference: 100% in COVID-19, 91.7% in influenza, and 53.9% in common URIs. Although the mean WBC count, MDW, NLR, and PLR were highest in the influenza group, the differences were nonsignificant.

Table 2

Blood parameters of patients presenting with URIs at the ED.

	COVID-19 (n = 9)	Influenza (n = 24)	URI (n = 141)	p
Blood Parameters
Hematocrit	40.6 ± 1.5	40.6 ± 4.1	40.3 ± 5.1	0.9626
WBC (103 counts/μL)	7.1± 3.0	9.7 ± 6.2	9.2 ± 3.2	0.1937
Neutrophil count (/μL)	5,036.0 ± 2,787.9	7,389.5 ± 4,700.2	6,682.8 ± 3,102.1	0.2286
Lymphocyte count (/μL)	1.298.0 ± 437.2	1,277.5 ± 1,470.0	1,629.6 ± 975.7	0.2286
MDW	23.5 ± 2.1	24.1 ± 4.3	21.8 ± 5.4	0.0960
MDW ≥ 20	9 (100%)	22 (91.7%)	76 (53.9%)	0.0001
PLR	202.6 ± 107.1	239.9 ± 138.1	197.0 ± 114.0	0.2559
NLR	4.1 ± 2.6	7.7 ± 4.0	6.1 ± 5.7	0.2067
Platelet (103 counts/μL)	239.6 ± 74.3	229.8 ± 158.1	250.3 ± 85.2	0.6219

BMI, body mass index; COVID, coronavirus disease; CRP, C-reactive protein; ED, emergency department; MDW, monocyte distribution width; NLR, neutrophil-to-lymphocyte ratio; PLR, platelet-to-lymphocyte ratio; URI, upper respiratory tract infection; WBC, white blood cell.

The diagnostic power of the ROC curve is described in Table 3. The area under curve (AUC) of MDW > 20 for COVID-19 and influenza was 0.703 and 0.6276, respectively (Fig 1a and 1b). The optimal cutoff of NLR was obtained from Youden’s index. The AUC of NLR < 3.2 was 0.6727 for COVID-19, and that of NLR > 5 was 0.6655 for influenza. On combining MDW ≥ 20 with NLR < 3.2, the AUC for COVID-19 increased to 0.840 (95% confidence interval [CI]: 0.739–0.942). Similarly, on combining MDW ≥ 20 with NLR ≥ 5, the AUC for influenza increased to 0.706 (95% CI: 0.622–0.789).

Table 3

Diagnostics of blood parameters.

	Odds Ratio (95% CI)	pe	Area Under Curve
COVID-19 group
Univariate
MDW ≥ 20	8.39 (1.67-∞)	0.0110	0.703 (0.665–0.741)
NLR < 3.2	4.23 (1.07–20.63)	0.0394	0.673 (0.501–0.840)
MDW ≥ 20 + NLR < 3.2	-	-	0.840 (0.739–0.942)
Influenza group
MDW ≥ 20	3.59 (1.30–9.92)	0.0140	0.628 (0.547–0.708)
NLR ≥ 5	4.05 (1.68–9.77)	0.0018	0.666 (0.574–0.757)
MDW ≥ 20 + NLR ≥ 5	-	-	0.706 (0.622–0.789)

BMI, body mass index; CI, confidence interval; COVID, coronavirus disease; CRP, C-reactive protein; ED, emergency department; MDW, monocyte distribution width; NLR, neutrophil-to-lymphocyte ratio.

Fig 1

Discussion

Early distinction of COVID-19 from common URIs is essential for disease control. A large meta-analysis reported that a higher WBC count, lower lymphocyte and PLT counts, and increased IL-6 and serum ferritin levels are significantly correlated with more severe COVID-19 [20]. Although various predictors have been used to evaluate disease severity, no comprehensive analysis for distinguishing laboratory findings for COVID-19 from other acute viral respiratory infections has been conducted.

In our study, elevated MDW was strongly associated with COVID-19 and influenza; this induced higher fever and elicited stronger inflammatory response than did common URIs. Furthermore, elevated MDW combined with NLR could further distinguish COVID-19 from influenza.

MDW, a new biomarker for systemic inflammation, is an early indicator of sepsis [19, 21], with excellent NPV(negative predictive value). Moreover, an MDW of <20 is correlated with advanced organ dysfunction and infection severity [19, 22–24]. In a study comparing the diagnostic powers of MDW and procalcitonin levels for sepsis, the AUC of MDW (0.87) was similar to that of procalcitonin levels (0.88) [22]. Because MDW is a component of the complete blood cell count and differential blood count, it can be performed in EDs and outdoor epidemic prevention screening stations to aid timely decision-making. Recent studies have confirmed the relationship between COVID-19 and elevated MDW [25-27]. Ognibene et al. reported that the mean MDW was 27.3 ± 4.9 in the COVID-19-positive group, whereas it was 20.3 ± 3.3 in the COVID-19-negative group—with an AUC of MDW of 0.91 [25]. Nevertheless, in the current study, this cutoff was higher because we included a separate influenza group and compared it with the COVID-19 and common URI groups. In general, a reason for the high cutoff for influenza and COVID-19 could be that influenza and COVID-19 lead to advanced inflammation compared with common URIs. Accordingly, when we included our influenza cases in the COVID-19-negative group, the cutoff increased.

NLR elevation is another discriminator for systemic inflammation, which occurs in various cancers [13-18], autoimmune disease [28-32], infection [33, 34], and osteoporosis [35]. Several studies have revealed that an increase in NLR and PLR indicates poor prognosis in many diseases [36]. However, NLR has low specificity. In our analysis, NLR elevation showed no difference between COVID-19 and URI. Combined with MDW, this predictive model can help in differential diagnosis.

COVID-19 and influenza are more invasive and induce more severe systemic inflammation than common URIs. A study reported elevated CRP levels and lymphopenia (<100/μL) in many patients with COVID-19 [37]. However, the differences in CRP levels and lymphocyte counts in our study were nonsignificant. This result could be explained by different control groups between the study above and our research. We compared the three groups of COVID-19, influenza, and other URI, but Zhang et al. compared patients with or without COVID-19. Moreover, we noted no significant differences in vital signs, including shock index, oxygen saturation, and mean arterial pressure, were observed between our groups.

Several advanced techniques have been used to detect COVID-19. Although RT-PCR is highly specific, it is time-consuming and has only 60%–70% sensitivity [38]. Application of multimodal approaches can improve COVID-19 diagnosis. In a study, chest CT combined with RT-PCR increased the sensitivity (up to 97%) of the diagnosis [25]. However, because of the high cost and low availability, chest CT combined with RT-PCR is not an optimal screening tool in ED settings.

In our study, two patients with COVID-19 experienced loss of smell; moreover, COVID-19 shares many clinical symptoms with influenza and common URIs, including fever, cough, coryza, and throat pain. In addition, several atypical presentations, including gastrointestinal, olfactory, and gustatory dysfunction and dermatological lesions, have been reported [39]. However, none of these clinical presentations can be used by the physicians to confidently diagnose COVID-19 in the early phase. Moreover, information on symptoms was difficult to obtain from patients who could not communicate due to dementia, sepsis, or severe physical disabilities. Thus, clinical manifestations should be integrated with other symptoms to help distinguish COVID-19 from other URIs. A rapid, low-cost, highly accurate COVID-19 test is needed urgently. MDW and NLR, the components of blood counts, can be easily used; moreover, they are inexpensive and can aid physicians in identifying patients with high COVID-19 risk in the early phase. Thereafter, RT-PCR can be employed for high-risk patients to confirm the diagnosis.

The limitation of our study is the small sample size of COVID-19 cases. No new cases were diagnosed at the Taipei Medical University Hospital after May 1, 2020. This trend was concordant with the small number of cases in Taiwan after April 2020. According to data from the Taiwan National Infectious Disease Statistics System, 435 confirmed cases of COVID-19, including 55 indigenous and 380 imported, were reported between March 1 and April 30, 2020. Thereafter, no indigenous case was reported. Only 41 imported cases were found between May 2 and July 31, 2020. Moreover, the MDW test is not popular in Taiwan at present. Based on our information, the MDW test is only available at two hospitals in Taiwan: Taipei Medical University Hospital and Chang Gung Memorial Hospital. COVID-19 cases from other hospitals lacked MDW data for our analysis. Therefore, including more cases was challenging. Su et al. concluded that despite being geographically close to mainland China, Taiwan limited the spread of COVID-19 by providing its public access to screening tests and medical care and promoting the use of masks, all at a low price [40]. Due to the small number of cases, we could not increase the sample size in this study. Nevertheless, to our best knowledge, this study is the first to use MDW with NLR to evaluate the likelihood of COVID-19 in the ED setting in a timely manner.

Conclusion

MDW is a readily available and inexpensive biomarker. Our predictive model combining MDW and NLR may help physicians to distinguish COVID-19 from influenza and common URIs.

The de-identified data of the present study was attached to the supporting information.

(XLSX)

Click here for additional data file.

7 Aug 2020

PONE-D-20-16913

Clinical Impact of Monocyte Distribution Width (MDW) and Neutrophil to Lymphocyte Ratio (NLR) to Distinguish COVID-19 and Influenza from General Upper Respiratory Tract Infection

PLOS ONE

Dear Dr. Hou,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

Please submit your revised manuscript by Sep 21 2020 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.

A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.

An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: http://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols

We look forward to receiving your revised manuscript.

Kind regards,

Wenbin Tan, Ph.D.

Academic Editor

PLOS ONE

Additional Editor Comments:

As reviewers suggested that the small sample size of COVID-91 (n=9) had compromised the conclusions, which should be fully addressed. The justification of cut-off value also needs to be elaborated.

Journal requirements:

When submitting your revision, we need you to address these additional requirements.

1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at

https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and

https://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf

2. Thank you for stating in the text of your manuscript "This study was approved by Joint Institutional Review Board (JIRB) of Taipei Medical University with project approval number N201904066. Informed consent was waived by the approval of the JIRB because anonymous and de-identified information were used." Please also add this complete statement to your ethics statement in the online submission form.

3. We suggest you thoroughly copyedit your manuscript for language usage, spelling, and grammar. If you do not know anyone who can help you do this, you may wish to consider employing a professional scientific editing service.

Whilst you may use any professional scientific editing service of your choice, PLOS has partnered with both American Journal Experts (AJE) and Editage to provide discounted services to PLOS authors. Both organizations have experience helping authors meet PLOS guidelines and can provide language editing, translation, manuscript formatting, and figure formatting to ensure your manuscript meets our submission guidelines. To take advantage of our partnership with AJE, visit the AJE website (http://learn.aje.com/plos/) for a 15% discount off AJE services. To take advantage of our partnership with Editage, visit the Editage website (www.editage.com) and enter referral code PLOSEDIT for a 15% discount off Editage services.  If the PLOS editorial team finds any language issues in text that either AJE or Editage has edited, the service provider will re-edit the text for free.

Upon resubmission, please provide the following:

The name of the colleague or the details of the professional service that edited your manuscript

A copy of your manuscript showing your changes by either highlighting them or using track changes (uploaded as a *supporting information* file)

A clean copy of the edited manuscript (uploaded as the new *manuscript* file)

4. Please state the date(s) when you accessed the medical records of the patients included in this study. In addition, please state whether the data was obtained from an electronic database or by paper record review.

5. PLOS requires an ORCID iD for the corresponding author in Editorial Manager on papers submitted after December 6th, 2016. Please ensure that you have an ORCID iD and that it is validated in Editorial Manager. To do this, go to ‘Update my Information’ (in the upper left-hand corner of the main menu), and click on the Fetch/Validate link next to the ORCID field. This will take you to the ORCID site and allow you to create a new iD or authenticate a pre-existing iD in Editorial Manager. Please see the following video for instructions on linking an ORCID iD to your Editorial Manager account: https://www.youtube.com/watch?v=_xcclfuvtxQ

Reviewers' comments:

Comments to the Author

**********

Reviewer #1: I read this timely manuscript with much interest.

Even though the small number of COVID-19 patients in this study is the obvious weakness, as pointed out in the Discussion, I appreciate your contribution sharing your clinical insight in this important issue facing frontline healthcare workers and heroes.

The following is a list of tasks related to this manuscript for your reference.

* page 12: In the paragraph about "Data collection"; please clarify what is MDW in parenthesis. Is it neutrophil to lymphocyte ratio as stated in the sentence?

* page 12: In the paragraph about "Statistical method"; there were extra spaces in Pearson's Chi squared test.

* page 23: The formatting was not consistent among the three groups in Table 2.

* page 24: Is it possible to keep MDW + NLR in the same line for better readability in Table 3?

* page 25: This is empty, missing anything here?

* It would be a very good idea to include information about the hematology analyzer in this study. This information will help our readers to design future related studies, with monocyte distribution width.

Reviewer #2: The present study is highly relevant and novel. However, the small sample size (9 patients confirmed with COVID-19) brings doubt to the significance of the results. The conclusion is not supported by the data due to the extremely small sample size. This study would need to have a much larger sample size to be relevant.

Reviewer #3: This paper deals with the cutoff value of monocyte distribution width (MDW) and neutrophil to lymphocyte ratio (NLR), to diagnose patients with COVID-19 and to distinguish them from those with other respiratory infection. The authors have found that the inexpensive biomarkers are easy to use, and they showed that the predictive ability of its discrimination is higher by the combination use. I think that this concept is very interesting, and the diagnosis method is simple and useful because it was challenging for clinical physicians to diagnose patients whether they have COVID-19. However, I have serious concerns over the use of statistics, the sample size of this study, and its cutoff value. I would like to require a major revision of the manuscript before it can be accepted for publication. The authors should fix the problems listed below.

Comments:

1. The cutoff value is very tricky because I think that it depends on the sample size. Other reports show the different MDW value in screening for it (Clinica Chimica Acta 509 (2020) 22–24, PLoS ONE 15(1): e0227300[ref 22]). One paper shows that "Reference interval of monocyte distribution width (MDW) in healthy blood donors"(Clinica Chimica Acta 510, (2020) 272-277). Its report shows that RIs obtained by the three calculation methods were about　16-23. On the other hand, the author indicated that "MDW ≥ 20" is a useful value to distinguish COVID-19 from general URI. I think that many healthy donors or patients without COVID-19 are including if we use this cutoff value. I think that more lager number of patients are needed to investigate this study.

2. The authors need to describe the materials and methods in exact detail. What was the ethnicity of patients? Which race was the most common? Which device was used for the analysis of MDW? Which reagent for SARS-CoV-2 RNA detection? The manuscript lacks the corresponding data. These descriptions should be needed.

3. I think that the use of the English language will still require considerable attention.

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.

17 Sep 2020

We thank the reviewers for their constructive comments. We have made revisions to the manuscript addressing all the questions and comments raised by the reviewers. The revised text is marked in blue. Our point-by-point responses to comments are as follows:

Response to the Academic Editor

� As reviewers suggested that the small sample size of COVID-91 (n=9) had compromised the conclusions, which should be fully addressed. The justification of cut-off value also needs to be elaborated

� We are grateful for your comments for this manuscript. The limited sample size is the main weakness of our study. No new cases were diagnosed at the Taipei Medical University Hospital after May 1, 2020. According to the data from the Taiwan National Infectious Disease Statistics System, 435 confirmed cases of COVID-19, including 55 indigenous and 380 imported, were reported between March 1, 2020, and April 30, 2020. Thereafter, no indigenous case was reported. Only 41 imported cases were found between May 2, 2020, and July 31, 2020.

� The MDW test is not popular in Taiwan at present. Based on our information, the MDW test is only available at two hospitals in Taiwan, including Taipei Medical University Hospital and Chang Gung Memorial Hospital. COVID-19 cases from other hospitals lacked MDW data for our analysis. Therefore, including more cases was a challenge for us. In-depth research with more cases is required in the future. We revised our title nu adding the phrase “a pilot study.”.

� In our study, the MDW cutoff was ≥20 for both influenza and COVID-19, which is consistent with studies on septic patients. A recent study showed similar findings. A large cohort study by Ognibene et al. reported that average MDW for the COVID-19 group was 27.3 ± 4.9 (106 negative vs. 41 positive). Although the number of cases in our study is small, the strength of our study is that it uses a combination of two markers, MDW and NLR, in distinguishing COVID-19 from influenza and general URI.

Response to Reviewer #1

We thank you for your valuable comments. We have modified in context as following:

1. In the paragraph about "Data collection"; please clarify what is MDW in parenthesis. Is it neutrophil to lymphocyte ratio as stated in the sentence?

� This was an error. We have corrected it to monocyte distribution width (MDW). Neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) have been defined in the next sentence.

2. In the paragraph about "Statistical method"; there were extra spaces in Pearson's Chi squared test.

� We have revised this to “Pearson’s chi-square test.”

3. The formatting was not consistent among the three groups in Table 2.

� Table 2 has been revised.

4. Is it possible to keep MDW + NLR in the same line for better readability in Table 3?

� The typesetting has been adjusted.

5. This is empty, missing anything here?

� It is redundant space, and we have removed it.

Response to Reviewer #2

The present study is highly relevant and novel. However, the small sample size (9 patients confirmed with COVID-19) brings doubt to the significance of the results. The conclusion is not supported by the data due to the extremely small sample size. This study would need to have a much larger sample size to be relevant.

� Thank you very much for appreciating our work. Small sample is a crucial limitation in our research. It was difficult to collect additional samples due to three main reasons. First, no new cases were diagnosed at the Taipei Medical University Hospital after May 1, 2020. This trend was concordant with the small number of cases in Taiwan after April 2020. According to data from Taiwan National Infectious Disease Statistics System, 435 confirmed cases of COVID-19, including 55 indigenous and 380 imported, were reported between March 1 and April 30, 2020. Thereafter, no indigenous case was reported. Only 41 imported cases were found between May 2 and July 31, 2020. Second, the MDW test is not popular in Taiwan at present. Based on our information, the MDW test is only available at two hospitals in Taiwan, including the Taipei Medical University Hospital and Chang Gung Memorial Hospital. COVID-19 cases from other hospitals lacked MDW data for our analysis. Therefore, including more cases was a challenge for us.

Response to Reviewer #3

� The cutoff value is very tricky because I think that it depends on the sample size. Other reports show the different MDW value in screening for it (Clinica Chimica Acta 509 (2020) 22–24, PLoS ONE 15(1): e0227300[ref 22]). One paper shows that "Reference interval of monocyte distribution width (MDW) in healthy blood donors"(Clinica Chimica Acta 510, (2020) 272-277). Its report shows that RIs obtained by the three calculation methods were about 16-23. On the other hand, the author indicated that "MDW ≥ 20" is a useful value to distinguish COVID-19 from general URI. I think that many healthy donors or patients without COVID-19 are including if we use this cutoff value. I think that more lager number of patients are needed to investigate this study.

� Thank you very much for the constructive comment. We had difficulty in expanding the sample size because of two main reasons. First, no new indigenous case of COVID-19 in Taiwan has been diagnosed since May 2020. Second, the MDW test is only available at two hospitals in Taiwan, including Taipei Medical University Hospital and Chang Gung Memorial Hospital. As no new indigenous cases were found at the two hospitals, new MDW data for COVID-19 patients were not available for our analysis.

� We believe that “MDW ≥ 20” is a reasonable cutoff value. This is a crucial clue for clinicians to distinguish COVID-19 from upper URI and influenza in the early stages. In a study by Ognibene et al, the average MDW for the COVID-19 positive group was 27.3 ± 4.9, whereas the average MDW was 20.3 ± 3.3 for the COVID-19 negative group. For the ROC curve analysis, the AUC of MDW (without a cutoff) was 0.91, which was based on a population of 106 negative and 41 positive cases. Moreover, their MDW demonstrated a sensitivity of 98%, specificity of 65%, and cutoff of 20.

� The authors need to describe the materials and methods in exact detail. What was the ethnicity of patients? Which race was the most common? Which device was used for the analysis of MDW? Which reagent for SARS-CoV-2 RNA detection? The manuscript lacks the corresponding data. These descriptions should be needed.

� We appreciate your valuable suggestion. The indicated information has been added to our revised manuscript. All confirmed patients with COVID-19 and other URIs were ethnically Han Chinese.

� MDW was analyzed using the Beckman Coulter UniCel DxH 900 analyzer, a quantitative, multi-parameter, automated hematology analyzer. The WBC differential was established using three measurements: individual cell volume, high-frequency conductivity, and laser-light scatter. Monocytes are identified through this technology and MDW is calculated as the standard deviation of a set of monocyte cell volume values. SARS-CoV-2 RNA was detected through real time PCR using a MagPurix 12S System and a Zinexts MagPurix Viral/Pathogen Acids Extraction Kit B.

3. I think that the use of the English language will still require considerable attention.

� Our revised manuscript has been edited for proper English language, grammar, punctuation, spelling, and overall style by a native English-speaking editor.

Submitted filename: MDWCOVID0911_rebuttal letter_clean.doc

Click here for additional data file.

13 Oct 2020

Clinical impact of monocyte distribution width and neutrophil-to-lymphocyte ratio for distinguishing COVID-19 and influenza from other upper respiratory tract infections: a pilot study

PONE-D-20-16913R1

Dear Dr. Hou,

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.

An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org.

If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

Kind regards,

Wenbin Tan

Academic Editor

PLOS ONE

Reviewers' comments:

Reviewer #1: All comments have been addressed

15 Oct 2020

PONE-D-20-16913R1

Clinical impact of monocyte distribution width and neutrophil-to-lymphocyte ratio for distinguishing COVID-19 and influenza from other upper respiratory tract infections: a pilot study

Dear Dr. Hou:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

If we can help with anything else, please email us at plosone@plos.org.

Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr. Wenbin Tan

Academic Editor

PLOS ONE