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American Journal of  
Life Science and Innovation (AJLSI)

Predictive Value of  RDW/PLT for Progression of  COVID-19 Pneumonia: A Potential 
Biomarker for Disease Severity

Kang Huang1, Salwa M. Imran2, Wafa Mohammad,3 Pengfei Liu4, Yali Chao5, Suming Zhang5*

Volume 3 Issue 1, Year 2024
ISSN: 2833-1397 (Online)

DOI: https://doi.org/10.54536/ajlsi.v3i1.2441
https://journals.e-palli.com/home/index.php/ajlsi

Article Information ABSTRACT

Received: February 02, 2024

Accepted: March 15, 2024

Published: March 19, 2024

Identifying reliable predictors for COVID-19 pneumonia progression is crucial for effective 
patient management. The purpose of  this study is to evaluate the Red Cell Distribution 
Width to Platelet Ratio (RDW/PLT) as a potential predictive biomarker for the development 
of  moderate to severe COVID-19 pneumonia. Conducting a retrospective analysis from 
August 2021 to March 2023, we categorized patients with moderate COVID-19 pneumonia at 
admission into different severity groups. The objective was to explore clinical and laboratory 
variables associated with disease progression. Fifty-three patients initially diagnosed with 
moderate COVID-19 were studied, of  which 17 progressed to severe disease. Univariate 
logistic regression analyzed various factors, including age, PLT, RDW-SD, RDW/PLT, AST, 
ALB, CRP, and IL-6, evaluating their correlation (P < 0.05) with higher odds ratios of  a poor 
prognosis. To ascertain these factors’ predictive power, Receiver Operating Characteristic 
(ROC) curve analysis was used. Univariate logistic regression highlighted several factors 
associated with increased odds ratios for poor prognosis. Notably, RDW/PLT exhibited 
the highest predictive value (AUC: 0.925, 95% CI 0.858–0.991) among single parameters 
in predicting the risk of  COVID-19 progression. This study underscores the potential 
of  RDW/PLT as an accessible and cost-effective biomarker for determining COVID-19 
pneumonia severity. The findings support its utility in risk stratification and clinical decision-
making, offering valuable insights for effective patient management strategies.

Keywords

COVID-19, Pneumonia, 
Disease Progression, Biomarker, 
Clinical Decision-Making

INTRODUCTION
Global health has been greatly impacted by the COVID-19 
pandemic, which has resulted in widespread illness and 
mortality (Cases, 2020; Fernandes et al., 2021). The 
persistent difficulties caused by the COVID-19 pandemic 
highlight the vital need for strong prognostic markers that 
can enable early identification of  patients at risk of  severe 
disease progression; the search for trustworthy indicators 
to predict disease severity and progression in COVID-19 
patients remains a crucial focus as the scientific community 
steps up efforts to unravel the complex pathophysiology 
of  SARS-CoV-2 infection (Chen et al., 2020; Sharma et al., 
2020; Sun et al., 2020).
Within the cohort of  COVID-19 patients initially 
presenting with moderate symptoms, a subset exhibited 
an alarming deterioration, progressing towards severe 
disease. Notably, an intriguing pattern emerged upon 
meticulous analysis: those experiencing the severe 
progression manifested elevated levels of  RDW/PLT. 
This observation serves as the fulcrum for exploring the 
predictive value of  RDW/PLT in predicting COVID-19 
severity.
RDW/PLT, amalgamating Red Cell Distribution Width 
(RDW) and Platelet Count (PLT) measurements, 
represents a composite metric derived from routine 
complete blood counts (Pulgar-Sánchez et al., 2021). 
The RDW captures the heterogeneity in red blood 
cell sizes, often indicative of  underlying physiological 

perturbations, while PLT reflects the platelet count 
critical for hemostasis and immune response regulation 
(Ullah et al., 2020; Wynants et al., 2020). These parameters, 
individually recognized for their diagnostic utility 
across various medical conditions, converge in RDW/
PLT, offering a potentially novel prognostic avenue for 
COVID-19.
The exploration of  RDW/PLT as a predictive biomarker 
holds significant implications for clinical practice. Should 
its predictive potential be validated, RDW/PLT could 
emerge as a non-invasive, cost-effective, and readily 
available tool for risk stratification among COVID-19 
patients. Its role in the early identification of  individuals 
prone to rapid disease progression may revolutionize 
clinical decision-making, enabling timely interventions 
and tailored therapeutic strategies aimed at averting 
severe complications (Albahri et al., 2020; Borghesi et al., 
2020; Tian et al., 2020; Ullah et al., 2020). Moreover, the 
integration of  RDW/PLT into prognostic models may 
streamline resource allocation within healthcare systems, 
optimizing the allocation of  limited resources toward 
high-risk patient cohorts.
This research endeavor transcends mere association 
establishment by delving into the temporal dynamics and 
clinical correlations of  RDW/PLT alterations concerning 
COVID-19 progression. Understanding whether changes 
in RDW/PLT precede the onset of  severe symptoms 
or coincide with disease exacerbation remains a pivotal 

1 Department of  Emergency Intensive Care Unit, Affiliated Hospital of  Xuzhou Medical University, Jiangsu, China
2 Xuzhou Medical University, Jiangsu, China
3 King Abdulaziz University Hospital, Jeddah, Saudi Arabia
4 Shandong First Medical University, Shandong, China &Department of  Anesthesiology, The Affiliated Hospital of  Xuzhou 
   Medical University, Jiangsu, China
5 Department of  Intensive Care Unit, Affiliated Hospital of  Xuzhou Medical University, Jiangsu, China
* Corresponding author’s e-mail: SumingZhang18@outlook.com



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aspect to unravel for effective predictive utility. The 
nuances of  RDW/PLT kinetics throughout the disease 
course may provide critical insights into the trajectory of  
COVID-19 and guide intervention strategies.
Additionally, investigating demographic variations and 
potential associations with comorbidities concerning 
RDW/PLT elevations in COVID-19 patients presents 
an intriguing avenue. Determining whether specific 
patient subgroups exhibit distinct RDW/PLT profiles 
could facilitate personalized risk assessment, tailored 
monitoring protocols, and targeted interventions. 
This pursuit aligns with the broader goal of  precision 
medicine, aiming to tailor treatments based on individual 
patient characteristics and disease progression patterns.
This study aims to scrutinize the Red Cell Distribution 
Width to Platelet Ratio (RDW/PLT) as a potential 
harbinger of  the progression of  COVID-19 pneumonia 
from moderate to severe stages. Amid the diverse 
clinical manifestations and trajectories observed in 
COVID-19 cases, identifying specific markers that herald 
a transition to severe illness holds paramount importance 
in clinical management and resource allocation. This 
study endeavors to bridge an essential knowledge gap 
in understanding COVID-19 prognosis by exploring 
RDW/PLT as a potential predictive biomarker. Beyond 
establishing its association with disease progression, the 
comprehensive investigation aims to lay the groundwork 
for its potential clinical utility, stressing the necessity for 
robust validation and integration of  RDW/PLT into 
existing prognostic frameworks.

LITERATURE REVIEW
COVID-19 Pathophysiology and Prognostic Markers
The clinical spectrum of  COVID-19, which is caused 
by SARS-CoV-2, is varied and ranges from mild 
respiratory symptoms to severe pneumonia and multi-
organ dysfunction. Finding trustworthy prognostic 
markers requires an understanding of  the complex 
pathophysiological mechanisms guiding the course 
of  the disease (Huang et al., 2020; Zhang et al., 2020). 
Research into markers that reflect this dysregulation 
has been prompted by emerging evidence that points 
to a dysregulated immune response and an elevated 
inflammatory cascade as indicators of  severe disease 
(Levi et al., 2020; Tay et al., 2020).

Red Cell Distribution Width (RDW) and Platelet 
Count (PLT) in Disease Evaluation
RDW, traditionally a marker of  red blood cell size 
heterogeneity, has garnered attention beyond its 
conventional utility. It has been linked to systemic 
inflammation and adverse outcomes in various 
pathological conditions (Lippi & Mattiuzzi, 2020; Patel et 
al., 2015). In the context of  COVID-19, elevated RDW 
levels have been observed and correlated with disease 
severity, possibly reflecting underlying inflammatory 
processes and physiological stress (Foy et al., 2020a; Lippi 
& Plebani, 2020). Similarly, alterations in platelet count 

(PLT) have been implicated in COVID-19 pathogenesis, 
with thrombocytopenia often associated with severe 
disease and adverse clinical outcomes (Althaus et al., 2021; 
Xu et al., 2020).

RDW/PLT Ratio as a Potential Biomarker
The integration of  RDW and PLT into the RDW/PLT ratio 
represents a composite marker that may hold significant 
prognostic value in COVID-19. Previous studies across 
various medical conditions have demonstrated the potential 
of  RDW/PLT as a prognostic indicator, reflecting systemic 
inflammation and disease severity (Zhou et al., 2020; Zorlu 
et al., 2012). Applying this ratio specifically in COVID-19 
patients presents a novel approach to anticipate disease 
progression and severity.

Clinical Studies Investigating RDW/PLT in COVID-19
RDW/PLT’s function in COVID-19 prognosis has 
been specifically examined in recent clinical studies. As 
an illustration of  its potential as a predictive marker for 
disease severity, a study by Wang et al., 2020 found that 
severe COVID-19 cases had noticeably higher RDW/PLT 
ratios than moderate cases (Wang et al., 2022). Similarly, 
in a retrospective analysis, Kilercik et al., 2021 found that 
in COVID-19 patients admitted to intensive care units, 
high RDW/PLT ratios were associated with unfavorable 
outcomes and severe disease (Kilercik et al., 2021).

Mechanistic Insights and Future Directions
Elucidating the mechanistic underpinnings of  the 
association between elevated RDW/PLT ratios and 
COVID-19 severity remains a critical area for exploration. 
Factors such as the inflammatory milieu, endothelial 
dysfunction, and potential interactions between platelets 
and red blood cells might contribute to alterations in 
RDW/PLT ratios (Henry, Aggarwal, et al., 2020; Lippi 
& Favaloro, 2020). Future research endeavors should 
focus on unravelling these mechanisms and conducting 
prospective trials to validate RDW/PLT as a robust 
prognostic marker in COVID-19.

MATERIALS AND METHODS
Study Participants
Retrospective review of  patient medical records from 
August 1, 2021, to March 1, 2023, at the Third People’s 
Hospital of  Yangzhou and the Affiliated Hospital of  
Xuzhou Medical University was part of  the study. 
Included were patients who had been diagnosed with 
COVID-19 and initially classified as having a moderate 
illness. According to the World Health Organization’s 
interim guidelines, confirmation of  COVID-19 depended 
on positive results from high-throughput sequencing or 
real-time reverse transcription-polymerase chain reaction 
(RT-PCR) assays of  nasal and pharyngeal swab specimens. 
Following admission, patients were observed for at least 
14 days to determine whether severe pneumonia had 
developed.



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Ethical Approval
The Affiliated Hospital of  Xuzhou Medical University’s 
Ethics Committee approved the study protocol (Protocol 
ID: XYFY2022-KL034-01).

Data Collection
Standardized data collection forms were used to gather 
information from electronic medical records about the 
following: demographics (age, gender), comorbidities 
(diabetes, hypertension, coronary heart disease), and 
laboratory parameters (such as White Blood Cell - WBC, 
Lymphocyte - LY, Eosinophil Cell - EOS, Platelet - PLT, 
Mean Platelet Volume - MPV, Red Cell Distribution 
Width - RDW, Red Cell Distribution Width to Platelet 
Count Ratio - RDW/PLT, Aspartate Aminotransferase 
- ALT, Alanine Aminotransferase - ALT, Albumin - 
ALB, Creatinine - CREA, C-reactive protein - CRP, and 
Interleukin-6 - IL-6).
Patients were categorized into the progressive group 
(17 cases) and the stable group (36 cases) based on the 
development of  severe illness within 3 days post-sample 
collection. Patients already categorized as severe at 
admission were excluded from statistical analyses.

Clinical Classification of  COVID-19 Pneumonia
Based on the severity of  their illness, patients with 
COVID-19 pneumonia were divided into various clinical 
groups in this study. A decrease in oxygen saturation, 
aberrant chest imaging, or the manifestation of  
COVID-19 symptoms without dyspnea were among the 
characteristics that classified the condition as mild. People 
who showed signs of  a lower respiratory disease but were 
still able to maintain a sufficient oxygen saturation (SpO2) 
of  ≥94% on room air at sea level were classified as having 
a moderate illness. Individuals classified as having a severe 

illness included those with heart rates under 94%, arterial 
partial pressure of  oxygen to fraction of  inspired oxygen 
(PaO2/FiO2) ratios less than 300 mm Hg, elevated 
respiratory rates greater than 30 breaths per minute, or 
lung infiltrates greater than 50%. These categorizations 
were crucial in distinguishing and describing the different 
levels of  severity among the COVID-19 pneumonia cases 
in this investigation.

Statistical Analysis
All statistical analysis was performed on SPSS 26.0 and 
GraphPad Prism 8.0. The formats for descriptive statistics 
are mean ± SD, median (IQR), and n (%). The Chi-square 
test or Fisher’s exact test were used to analyze categorical 
variables, and the student’s t-test or Mann-Whitney 
U-test were used to analyze continuous variables. If  the 
two-sided P value was less than 0.05, it was considered 
statistically significant. Using single-variable logistic 
regression based on the likelihood ratio, risk factors were 
found, and these risk components were then combined to 
create a forest plot. The area under the curve (AUC) was 
used to evaluate discrimination performance.

RESULTS 
Patient Characteristics and Group Classification
The rigorous application of  inclusion criteria yielded 
a cohort of  64 individuals diagnosed with COVID-19. 
Following careful screening, 11 patients were excluded 
due to severe/critical COVID-19 status at admission or 
being below 18 years of  age, resulting in a final study 
population of  53 patients. Among these, a subgroup 
of  17 patients experienced a distressing progression to 
severe pneumonia during their hospital stay, prompting a 
comparative evaluation to discern distinguishing clinical 
features, as shown in Figure 1.

Figure 1: The flow diagram shows the study population enrollment



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Comparison between Stable and Progressive Patients
A thorough comparison of  the clinical and demographic 
traits of  patients who developed severe COVID-19 and 
those who kept their condition stable is shown in Table 1. 
Interestingly, the mean age of  patients in the progressive 
group was 7.88 years ± 14.66 years, which was significantly 
higher than the mean age of  patients in the stable group 
(58.97 years ± 18.94) (P = 0.021). Moreover, individuals 

with underlying coronary heart disease were notably more 
prevalent within the progressive group (41.2%) than in 
the stable group (2.8%) (P = 0.001).
Notably, various laboratory parameters manifested 
pronounced differences between the groups, with 
significantly higher levels of  RDW-SD, RDW/PLT, AST, 
CREA, CRP, and IL-6 observed in the progressive cohort 
(all P < 0.05).

Table 1: Characteristics between the stable and progressive patients
Characteristic Stable group Progressive group P
Gender, n (%)
Male 15 (41.7%) 11 (64.7%) 0.117
Female 21 (58.3%) 6 (35.3%)
Age, years 58.97 ± 18.94 70.88 ± 14.66 0.021
Times of  vaccination
0 19 (52.8%) 8 (47.1%) 0.832
1 6 (16.7%) 4 (23.5%)
2 11 (30.6) 5 (29.4)
Comorbidities, n (%) 
Diabetes 4 (11.1%) 4 (23.5%) 0.443
Hypertension 12 (33.3%) 5 (29.4%) 0.775
Coronary heart disease 1 (2.8%) 7 (41.2%) 0.001
Laboratory findings
WBC (×109/L) 4.57 ± 1.56 4.61 ± 1.81 0.929
LY (×109/L) 1.18 ± 0.53 0.89 ± 0.36 0.051
EOS (×109/L) 0.01 (0.00-0.08) 0.00(0.00-0.00) 0.003
PLT (×109 /L) 146.50 (124.25-193.25) 92.00 (66.50-106.5) 0.000
MPV (fL) 11.59 ± 1.13 11.98 ± 1.08 0.240
RDW-SD 40.58 ± 2.35 42.98 ± 2.15 0.001
RDW/PLT (×10-2) 27.25 (20.43-33.60)  46.80 (38.95-64.95) 0.000
AST (U/L) 21.50 (18.50-34.00) 50.20 (29.80-88.40) 0.000
ALT (U/L) 25.89 ± 21.85 38.25 ± 21.39 0.059
ALB (g/L) 44.11 ± 3.37 38.91 ± 3.81 0.000
CREA (umol/L) 68.50 (61.00-88.00) 90.00 (64-113) 0.038
CRP (mg/ L) 22.92 (9.43-33.07) 58.00 (39.35-91.70) 0.000
IL-6 (pg/ml) 21.85 (13.75-32.85) 81.50 (39.35-115.30) 0.000

Predictors of  Progression from Moderate to Severe 
COVID-19
Univariate logistic regression analysis illuminated several 
potential predictors of  disease progression, unveiling age, 

PLT, RDW-SD, RDW/PLT, AST, ALB, CRP, and IL-6 
as significantly associated with the transition to severe 
COVID-19 pneumonia, as shown in Table 2.
The construction of  a forest plot, which is shown in 

Table 2: Univariate logistic regression analysis independent high-risk factors for severity of  COVID-19 patients
Variables OR (95%CI) P value
Age 1.05 (1.00-1.09) 0.029
EO 0.00 (0.00-455.76) 0.349
PLT 0.94 (0.90-0.97) <0.001
RDW-SD 1.05 (1.02-1.08) 0.004
RDW/PLT 1.21 (1.08-1.36) <0.001
AST 1.04 (1.02-1.07) 0.002



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Figure 2, further underscored the prominence of  RDW/
PLT, IL-6, CRP, RDW-SD, age, and AST as prominent 
predictors in delineating disease severity.

Predictive Value of  RDW/PLT
Intriguingly, receiver operating characteristic (ROC) curve 
analysis highlighted the remarkable predictive capacity 

of  RDW/PLT in forecasting the risk of  progression in 
COVID-19 patients. With an impressive area under the 
curve (AUC) of  0.925 (95% CI 0.858–0.991), RDW/PLT 
emerged as the most robust single parameter. Utilizing a cut-
off  value of  0.355, RDW/PLT showcased a high sensitivity 
of  94.12% and specificity of  80.56% in predicting the risk 
of  progression, which is shown in Figure 3.

ALB 0.68 (0.54-0.84) <0.001
CREA 1.02 (1.00-1.04) 0.052
CRP 1.06 (1.03-1.10) <0.001
IL-6 1.07 (1.03-1.12) <0.001

Figure 2: Forest plot

Figure 3: ROC curve for the prediction of  developing severe COVID-19 pneumonia

Interpretation and Implications
These findings underscore the clinical relevance of  
specific hematological and demographic markers in 
predicting the trajectory of  COVID-19 pneumonia. 
Notably, the identification of  RDW/PLT as a robust 
predictor of  disease progression signifies its potential 
utility as an early prognostic marker, allowing for prompt 
interventions and focused clinical management.

DISCUSSION
According to the study’s findings, the Red Cell 
Distribution Width to Platelet Ratio (RDW/PLT) may 
prove to be a useful biomarker for determining when 
COVID-19 pneumonia will progress from a moderate to 
a severe stage (Alballa & Al-Turaiki, 2021; Ghahramani et 
al., 2020; Yamada et al., 2020). Since elevated RDW/PLT 
values have been associated with disease progression, 



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physicians may be able to use them as a preemptive 
measure to identify patients who are more likely to 
develop severe illness in the future (Alnor et al., 2020; 
Gong et al., 2021). Early detection could result in targeted 
therapy, attentive observation, and intervention strategies 
that could enhance patient outcomes (Bonetti et al., 2020).
The study’s findings indicate that the Red Cell 
Distribution Width to Platelet Ratio (RDW/PLT) may be 
a valuable biomarker for predicting how COVID-19 will 
progress. Numerous studies have reported a relationship 
between RDW and disease severity for a range of  medical 
conditions, including cancer, pulmonary disorders, and 
cardiovascular diseases (Foy et al., 2020b). RDW is a 
measure of  the heterogeneity in red blood cell size that 
is caused by oxidative stress, inflammatory reactions, 
and decreased erythropoiesis. Within the framework of  
COVID-19, the noted increase in RDW could be linked 
to the inflammatory reaction and subsequent cytokine 
storm, which could lead to modifications in red blood 
cell properties (Liu et al., 2020; Pongpirul et al., 2020). 
Furthermore, the correlation between RDW/PLT and 
the severity of  the COVID-19 virus is consistent with 
decreased platelet counts, which are frequently observed 
in cases of  severe viral infections (Ponti et al., 2020).
This study’s findings align with previous investigations 
highlighting the role of  RDW and platelet count as 
markers of  systemic inflammation and hematological 
abnormalities (C. Wang et al., 2020). Elevated RDW 
has consistently been linked to adverse outcomes in 
diverse medical conditions, including cardiovascular 
and respiratory disorders (Yuan et al., 2020). Similarly, 
alterations in platelet count have been associated with 
inflammatory responses and endothelial dysfunction (Li 
et al., 2020). This study contributes by emphasizing the 
utility of  the composite RDW/PLT ratio as a potential 
biomarker, specifically within the context of  COVID-19 
pneumonia (Ballaz et al., 2021).
A plausible underlying mechanism for the observed 
association involves the systemic inflammation and 
oxidative stress triggered by SARS-CoV-2 infection (Shiri 
et al., 2021). The virus-induced inflammatory response 
might lead to hematological changes, affecting red cell 
distribution and platelet activation (Khosravi et al., 2021). 
The RDW/PLT ratio could capture these underlying 
pathophysiological processes, serving as an indicator 
of  disease severity (X. Wang et al., 2020). Furthermore, 
leveraging the RDW/PLT ratio as a predictive tool may 
contribute to personalized approaches to managing 
COVID-19.
Table 1 and Table 2 in the current study elucidate 
demographic, clinical, and laboratory characteristics 
associated with the progression of  COVID-19 
pneumonia. Similar analyses in previous studies have often 
highlighted age, comorbidities, and specific laboratory 
parameters, such as inflammatory markers (e.g., CRP, IL-
6), as crucial predictors of  disease severity (Tjendra et al., 
2020). However, the current study emphasizes the RDW/
PLT ratio, which might have been less extensively in prior 

literature for COVID-19 severity prediction.
Figure 2, displaying a forest plot of  predictors, echoes 
findings from previous studies, often revealing multiple 
factors associated with disease severity. Previous 
studies have reported diverse predictors, ranging from 
inflammatory markers to specific clinical parameters, 
consistently emphasizing the multifactorial nature of  
disease progression (Krintus et al., 2014).
Figure 3 exhibits ROC curve analysis, demonstrating 
the predictive performance of  individual parameters 
for severe COVID-19 pneumonia. Prior research 
often presents ROC analyses assessing the diagnostic 
or predictive accuracy of  various markers, with AUC 
values serving as indicators of  predictive strength. 
In comparison to previous studies, the current study 
highlights the RDW/PLT ratio as a potential strong 
predictor for disease progression (Cai et al., 2019).
The study highlights the potential of  this readily available 
and cost-effective measure to aid risk classification and 
guide clinical decision-making (Henry, De Oliveira, et al., 
2020). However, validation of  these findings, exploring 
underlying mechanisms, and assessing the RDW/PLT 
ratio’s value in larger patient cohorts necessitate further 
investigation. The prospective application of  the RDW/
PLT ratio in clinical practice holds promise for enhancing 
patient outcomes in COVID-19 pneumonia.

CONCLUSION
This study concludes that elevated RDW/PLT values 
are linked to the advancement of  illness, indicating the 
practicality of  utilizing this readily available parameter 
in clinical settings. Identifying patients at higher risk of  
developing severe illness early on could facilitate timely 
interventions, enhanced surveillance, and more effective 
allocation of  healthcare resources. It provides initial 
evidence supporting the potential of  the RDW/PLT ratio 
as a prognostic biomarker in predicting the progression 
of  COVID-19 pneumonia from moderate to severe 
stages.

STRENGTHS AND LIMITATIONS
The strength of  this study is that it investigates RDW/
PLT as a potential predictor for COVID-19 pneumonia 
progression using robust statistical analyses. Clear 
inclusion criteria and focus on moderate COVID-19 
cases enhance specificity.
The limitations are retrospective design and small, single-
center sample size, which may introduce biases and limit 
generalizability. Unaccounted confounding factors and 
the need for prospective validation in larger cohorts pose 
limitations.

Acknowledgements
Conception and design of  the study: Suming Zhang. 
Acquisition of  data: Suming Zhang, Pengfei Liu, Salwa 
Mohammad Imran. Analysis and interpretation of  data: 
Suming Zhang. Drafting the article: Salwa Mohammad 
Imran, Wafa Mohammad. Revising it critically for 



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important intellectual content: Suming Zhang, Salwa 
Mohammad Imran. Final approval of  the version to be 
submitted: All authors contributed to the final version. 
Suming Zhang takes responsibility for the paper as a 
whole.

Funding
This work was supported by the Wu Jieping Medical 
Foundation’s special fund for clinical research under 
Grant (320.6750.2021-08-3) and the Xuzhou Youth 
Science and Technology Talent Project under Grant 
(KC2204).

Declaration of  Interest
The authors report that there are no competing interests 
to declare. 

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