Impact of mean platelet volume to lymphocyte ratio on short-term clinical outcomes in patients with acute ischemic stroke

doi:10.21203/rs.3.rs-4961116/v1

Background

The Mean platelet volume-to-lymphocyte ratio (MPVLR) is an emerging and cost-effective biomarker that integrates MPV and lymphocytes, reflecting both thrombotic activity and inflammatory responses. Despite its potential, relatively few studies have explored the relationship between MPVLR and the prognosis of acute ischemic stroke (AIS). This study aims to investigate the correlation between MPVLR and short-term clinical outcomes in patients with AIS, providing insights into its prognostic significance.

Method

Data were collected from patients with AIS admitted to the Neurology Department of Beijing Shunyi District Hospital from January 2022 to August 2022. Patients were consecutively included and followed up three months post-symptom onset. The analysis of multivariable logistic regression was used to explore the association of MPVLR with poor functional outcomes. Additionally, a receiver operating characteristic (ROC) curve was analyzed to examine the predictive value of MPVLR.

Results

In this study enrolling 362 AIS patients, the MPVLR was found to be substantially higher in the group with poor outcomes compared to the group with good outcomes (P < 0.05). Patients in the lower tertile group had lower mRS scores (P < 0.05). In addition, previous stroke or TIA, MPVLR, and NIHSS scores at admission were identified as significant predictors of poor outcomes three months after AIS. The ROC curve revealed that the optimal cutoff value for MPVLR to predict poor outcomes at three months was 5.547. And the area under the curve for MPVLR was 0.727 (95% CI: 0.672–0.783), with a sensitivity of 82.2% and a specificity of 52.9%.

Conclusions

Elevated MPVLR values at admission were significantly correlated with short-term poor functional outcomes in AIS patients.

acute ischemic stroke

mean platelet volume to lymphocyte ratio

functional outcomes

Stroke is the leading cause of mortality and disability in China, placing a significant burden on both society and the economy^[1]. Identifying potential biomarkers of poor prognosis and developing effective prevention and treatment strategies are critical.

Platelet activation and inflammatory response are pivotal in the pathogenesis of ischemic stroke^[2–4]. Mean platelet volume (MPV), a key indicator of platelet production, reflects platelet function and activity. Elevated MPV levels have been linked to poor outcomes in treating ischemic stroke ^[5–7] and are considered predictors of stroke recurrence^[8]. However, the relevance between MPV and adverse outcomes remains controversial^[9]. Lymphocytes play a vital role in post-stroke inflammatory response, with studies suggesting that lower lymphocyte counts are correlated with both short and long-term unfavorable prognosis ^{[10, 11]}. MPV-to-lymphocyte ratio (MPVLR) is a recently identified and cost-effective biomarker that has been explored in various diseases, including coronary atherosclerotic heart disease, acute heart failure, and hepatitis^[12–14], but its predictive value in AIS is rarely reported. In this study, we investigated the relationship between MPVLR and the clinical outcomes at three months post-stroke in patients from Beijing Shunyi District Hospital.

2.1 Study population

Data were obtained from Beijing Shunyi District Hospital between January 2022 and August 2022. Participants were consecutively recruited based on the following inclusion criteria: (1) aged over 18 years; (2) admission within 72 hours of symptom onset; (3) diagnosed with AIS based on symptoms, signs, medical history, and diffusion-weighted imaging (DWI); (4) receipt of signed informed consent. Exclusion criteria were: (1) Infection within 2 weeks prior to admission; (2) Pregnancy or within six weeks postpartum; (3) presence of cancer, liver cirrhosis, or severe liver and kidney dysfunction; (4) current use of immunosuppressive medication or steroids; (5) incomplete blood count data at admission; (6) loss to follow-up.

2.2 Baseline data collection

The baseline data of enrolled participants were collected through in-person interviews or medical records by trained interviewers. This included demographic and clinical details such as gender, age, body mass index (BMI), smoking and alcohol habits, blood pressure, and medical history, which encompasses diabetes, dyslipidemia, hypertension, coronary heart disease, stroke or TIA, and atrial fibrillation. Additionally, the National Institutes of Health Stroke Scale (NIHSS) score at admission and medications administered during hospital care were recorded, including antihypertensives, antiplatelets, anticoagulants, cholesterol-lowering drugs, hypoglycemic agents, rt-PA for intravenous thrombolysis, and mechanical thrombectomy procedures.

2.3 Sample collection and measurement of MPVLR

Blood samples were collected within 24 hours of participant enrollment. Tests performed included routine blood tests, as well as the measurements of total cholesterol, triglycerides, and fasting blood glucose. The MPVLR was calculated for these samples.

2.4 Outcome assessment

Clinical follow-up was conducted three months after symptom onset, either through outpatient visits or telephone interviews. A poor prognosis was defined as an mRS score of 3–6 at the three-month follow-up.

2.5 Statistical analysis

Patients were split into two groups based on functional outcomes and into three groups based on MPVLR tertiles. The data's normality was verified using the Kolmogorov-Smirnov test. Continuous variables were reported as either mean ± standard deviation or median along with interquartile ranges (IQRs), and categorical variables were detailed by their frequencies and percentages. To compare continuous and categorical variables among groups, the Kruskal-Wallis and Chi-square tests were respectively employed.

Multivariable logistic regression was used to investigate the relationship between MPVLR and adverse clinical outcomes, calculating odds ratios (ORs) and 95% confidence intervals (CIs) in the process. To evaluate MPVLR's prognostic accuracy, receiver operating characteristic (ROC) curves were obtained, and the Youden index was used to establish the best cutoff value along with corresponding sensitivities and specificities. The analyses were performed using SPSS version 22.0 (SPSS Inc., Chicago, IL, USA), with a significance threshold of p-values < 0.05, using a two-sided test.

3.1 Baseline characteristics

The study included 362 AIS patients who were hospitalized in the Neurology Department of Shunyi District Hospital in Beijing from January 2022 to August 2022. The patients had a mean age of 67 years (range 58-74), and the mean MPVLR was 6.05（range 4.68-8.19）. Detailed baseline characteristic data are summarized in Table 1 and Figure 1B. Of the total, 244 patients were categorized in the good outcome group and 118 patients in the poor outcome group. Patients with poor outcomes were typically older, more likely to be female, and had a lower BMI. They also presented with higher NIHSS scores at admission and had a history of stroke or TIA, coronary heart disease, and Atrial fibrillation (P < 0.05). Additionally, these patients had higher levels of neutrophil count, platelet count, FBG, and MPVLR compared to those in the good outcome group. Conversely, their lymphocyte count was significantly lower (all P < 0.05).

Table 1. Baseline characteristics between patients with good and poor functional outcomes

Characteristic	Total （n=362）	Good outcome （n=244）	Poor outcome （n=118）	P value
Age, yr-Median (IQR)	67（58-74）	64.5（56-70）	72（66-78）	P＜0.001
Female-No. (%)	116（32%）	69（28.3%）	47（39.8%）	0.027
Body-mass index, kg/m²-Median (IQR)	25.4（23.1-27.68）	25.82（23.55-28.08）	24.77（22.48-27.34）	0.011
Blood pressure, mmHg-Median (IQR)
Systolic	150（137-160）	150（134.5-160）	149（140-158）	0.886
Diastolic	86（79-90）	85（79-90）	87.5（79-90）	0.747
Medical History-no. (%)
Hypertension	275（76%）	179（73.4%）	96（81.4%）	0.095
Diabetes mellitus	130（35.9%）	85（34.8%）	45（38.1%）	0.54
Dyslipidemia	137（37.8%）	83（34%）	54（45.8%）	0.03
Previous stroke or TIA	125（34.5%）	67（27.5%）	58（49.2%）	P＜0.001
Coronary heart disease	83（22.9%）	43（17.6%）	40（33.9%）	P＜0.001
Atrial fibrillation	35（9.7%）	12（4.9%）	23（19.5%）	P＜0.001
Current smoker-no. (%)	169（46.7%）	126（51.6%）	43（36.4%）	0.007
current alcohol drinking .(%)	156（43.1%）	113（46.3%）	43（36.4%）	0.075
NIHSS score at admission,median(IQR)	3（2-7）	3（1-4）	8（5-14）	0.000
Laboratory data, median (IQR)
TC, mmol/L	4.32（3.64-5.19）	4.22（3.64-5.16）	4.48（3.63-5.2）	0.4
TG, mmol/L	1.33（0.93-1.92）	1.36（0.98-1.93）	1.25（0.9-1.87）	0.248
FBG，mmol/L	6.33（5.51-8.63）	6.13（5.49-8.03）	7.21（5.7-9.57）	0.03
HGB (g/L)	141（129-152）	141（130-151）	141（125-152）	0.442
WBC, ×109/L	6.9（5.83-8.36）	6.82（5.83-8.19）	7.23（5.83-8.98）	0.33
Neutrophils, ×109/L	4.45（3.61-6.02）	4.35（3.51-5.54）	4.98（3.84-6.56）	0.004
Lymohocytes, ×109/L	1.66（1.26-2.07）	1.82（1.42-2.21）	1.35（1.01-1.71）	P＜0.001
Monocytes, ×109/L	0.44（0.34-0.56）	0.44（0.35-0.55）	0.44（0.32-0.6）	0.734
PLT, ×109/L	211.5（179-253）	219（188.5-256.5）	198.5（165-241）	P＜0.001
MPV (fl)	10（9.4-10.6）	9.95（9.4-10.6）	10.05（9.4-10.8）	0.179
MPVLR, median（IQR）	6.05（4.68-8.19）	5.48（4.38-7.39）	7.5（5.82-10.4）	P＜0.001
Treatment in hospital, (n%)
Antihypertensive agents	214（59.1%）	143（58.6%）	71（60.2%）	0.777
Antiplatelet agents	343（94.8%）	234（95.9%）	109（92.4%）	0.158
Anticoagulant agents	24（6.6%）	12（4.9%）	12（10.2%）	0.06
Cholesterol-lowering agents	357（98.6%）	242（99.2%）	115（97.5%）	0.188
Hypoglycemic agents	117（32.3%）	83（34%）	34（28.8%）	0.321
rt-PA intravenous thrombolytic	55（14.1%）	37（15.2%）	18（15.3%）	0.982
Mechanical thrombectomy	14（3.9%）	6（2.5%）	8（6.8%）	0.046

Abbreviations: NIHSS=National institutes of health stroke scale；SBP=Systolic blood pressure; DBP=Diastolic blood pressure; MPVLR= Mean platelet volume-to-lymphocyte ratio; FBG= Fasting blood glucose; TC=Total cholesterol; TG=Triglyceride; HGB=hemoglobin; WBC=white blood cell count; PLT=platelet count; MPV=Mean platelet volume.

3.2 Analysis of AIS clinical characteristics by MPVLR tertiles

Based on MPVLR tertiles, patients were divided into three groups: low tertile (MPVLR ≤ 5.10), middle tertile (5.11 ≤ MPVLR ≤ 7.41), and high tertile (MPVLR > 7.42). The rate of poor outcomes increased with higher tertiles: 12.4% in the low tertile group, 34.7% in the middle tertile group, and 50.8% in the high tertile group (Fig 1A). Detailed comparisons across the groups are presented in Table 2 and Figure 2. High-tertile group patients were generally older, less likely to smoke, had lower BMI, and higher NIHSS scores at admission compared to the low-tertile group. Laboratory data revealed that the high tertile group had lower counts of white blood cells, platelets, lymphocytes, and monocytes but a higher MPV. Additionally, a greater percentage of patients in the high tertile group underwent mechanical thrombectomy. Patients in the low tertile group exhibited lower mRS scores compared to those in the other groups (all P < 0.05).

Table2. Demographic and clinical characteristics according to MPVLR tertiles

	Low tertile (n=121)	Middle tertile (n=121)	High tertile (n=120)
Variable	≤5.10	5.11-7.41	≥7.42	P value
Age, yr-Median (IQR)	63（56-71）b	66（57-73）b	70（63-75）a	P＜0.001
Female-No. (%)	38（31.4%）	41（33.9%）	37（30.8%）	0.864
Body-mass index, kg/m²-Median (IQR)	25.95（23.88-28.09）a	25.95（22.68-28.33）	24.63（22.96-27.04）b	0.034
Blood pressure, mmHg-Median (IQR)
Systolic	150（133-160）	150（140-160）	145.5（138.5-159）	0.893
Diastolic	83（78-90）	89（80-90）	86（79-90）	0.649
Medical History-no. (%)
Hypertension	90（74.4%）	94（77.7%）	91（75.8%）	0.834
Diabetes mellitus	49（40.5%）	39（32.2%）	42（35%）	0.395
Dyslipidemia	47（38.8%）	45（37.2%）	45（37.5%）	0.718
Previous stroke or TIA	33（27.3%）	47（38.8%）	45（37.5%）	0.117
Coronary heart disease	26（21.5%）	30（24.8%）	27（22.5%）	0.822
Atrial fibrillation	9（7.4%）	16（13.2%）	10（8.3%）	0.261
Current smoker-no. (%)	68（56.2%）a	60（49.6%）a	41（34.2%）b	0.002
current alcohol drinking .(%)	53（43.8%）	57（47.1%）	46（38.3%）	0.381
NIHSS score at admission,median(IQR)	3（1-5）b	3（2-6）	5（2-12）a	P＜0.001
Laboratory data, median (IQR)
TC, mmol/L	4.41（3.79-5.46）a	4.34（3.75-5.26）	4.16（3.41-4.9）b	0.036
TG, mmol/L	1.49（1.16-2.19）a	1.26（0.92-1.87）b	1.16（0.85-1.65）b	P＜0.001
FBG，mmol/L	6.74（5.72-8.55）	6.11（5.53-8.37）	6.15（5.31-9.16）	0.515
HGB (g/L)	142（131-153）	141（129-151）	140（124-151）	0.352
WBC, ×109/L	7.87（6.63-9.15）a	6.59（5.81-7.96）b	6.3（5.19-7.79）b	P＜0.001
Neutrophils, ×109/L	4.62（3.69-5.79）	4.32（3.6-5.83）	4.51（3.56-6.05）	0.632
Lymohocytes, ×109/L	2.27（2.05-2.72）a	1.66（1.51-1.8）b	1.13（0.95-1.26）c	0.000
Monocytes, ×109/L	0.46（0.39-0.6）a	0.44（0.34-0.53）a	0.4（0.29-0.52）b	P＜0.001
PLT, ×109/L	242（206-281）a	212（187-248）b	188.5（159.5-221）c	P＜0.001
MPV (fl)	9.7（9-10.3）b	10.1（9.6-10.7）a	10.1（9.7-11）a	P＜0.001
MPVLR, median（IQR）	4.27（3.63-4.67）c	6.21（5.67-6.77）b	9.14（8.3-11.6）a	0.000
Treatment in hospital, (n%)
Antihypertensive agents	73（60.3%）	72（59.5%）	69（57.5%）	0.900
Antiplatelet agents	114（94.2%）	113（93.4%）	116（96.7%）	0.495
Anticoagulant agents	6（5.0%）	10（8.3%）	8（6.7%）	0.586
Cholesterol-lowering agents	119（98.3%）	120（99.2%）	118（98.3%）	0.814
Hypoglycemic agents	48（39.7%）a	30（24.8%）b	39（32.5%）	0.047
rt-PA intravenous thrombolytic	20（16.5%）	14（11.6%）	21（17.5%）	0.388
Mechanical thrombectomy	2（1.7%）b	3（2.5%）	9（7.5%）a	0.039
mRS score at 3 month	0（0-1）b	2（1-3）a	3（1-4）a	P＜0.001

Note: There are significant differences between different letter annotations (a, b, c).

Abbreviations: NIHSS=National institutes of health stroke scale； mRS=modified Rankin Scale；SBP=Systolic blood pressure; DBP=Diastolic blood pressure; MPVLR= Mean platelet volume-to-lymphocyte ratio; FBG= Fasting blood glucose; TC=Total cholesterol; TG=Triglyceride; HGB=hemoglobin; WBC=white blood cell count; PLT=platelet count; MPV=Mean platelet volume.

3.3 The link between MPVLR and poor outcomes at 3 months after AIS

Univariate and multivariate logistic regression models were employed to examine the associations between MPVLR and poor outcomes three months post-AIS. Univariate analysis indicated significant associations: OR for poor outcomes in the middle tertile group versus the low tertile group was 3.757 (95% CI: 1.946–7.251; P < 0.001), and for the high tertile group versus the low tertile group, it was 7.306 (95% CI: 3.820–13.973; P < 0.001). Given that MPVLR combines both MPV and lymphocyte count, it was used as a single composite variable in the analysis, excluding separate adjustments for MPV and lymphocyte counts. The multivariate logistic regression, adjusted for statistically significant variables (p values <0.05) from the univariate analysis except for MPV and lymphocyte counts, revealed that MPVLR remained significantly associated with poor outcomes. The adjusted OR for the middle tertile group versus the low tertile group was 3.210 (95% CI: 1.440-7.155; P < 0.004), and for the high tertile group versus the low tertile group, it was 4.606 (95% CI: 1.971-10.765; P < 0.001). Additionally, a history of stroke or TIA, and NIHSS score at admission were significantly linked to poor outcomes at three months post-AIS (Table 3).

Table3. Univariate and multivariate logistic regression analysis of outcomes

	Univariate analysis		Multivariate analysis
	OR (95% CI)	P value	OR (95% CI)	P value
Age, yr-Median (IQR)	1.609（1.044-1.903）	P＜0.001
Female-No. (%)	1.679（1.058-2.665）	0.028
Body-mass index, kg/m²-Median (IQR)	0.923（0.867-0.982）	0.011
Blood pressure, mmHg-Median (IQR)
Systolic	1.000（0.989-1.012）	0.959
Diastolic	0.997（0.979-1.015）	0.746
Medical History-no. (%)
Hypertension	0.631（0.367-1.087）	0.097
Diabetes mellitus	0.867（0.550-1.367）	0.540
Dyslipidemia	1.036（0.867-1.237）	0.698
Previous stroke or TIA	0.392（0.248-0.619）	P＜0.001	0.401（0.218-0.740）	0.003
Coronary heart disease	0.417（0.252-0.690）	P＜0.001
Atrial fibrillation	0.214（0.102-0.447）	P＜0.001
Current smoker-no. (%)	1.862（1.186-2.924）	0.007
current alcohol drinking .(%)	1.505（0.958-2.363）	0.076
NIHSS score at admission,median(IQR)	1.373（1.275-1.479）	P＜0.001	1.341（1.236-1.455）	P＜0.001
Laboratory data, median (IQR)
TC, mmol/L	1.050（0.872-1.265）	0.607
TG, mmol/L	1.021（0.866-1.204）	0.804
FBG，mmol/L	1.043（0.982-1.107）	0.170
HGB (g/L)	0.992（0.981-1.004）	0.181
WBC, ×109/L	1.053（0.949-1.168）	0.329
Neutrophils, ×109/L	1.011（0.966-1.058）	0.642
Lymohocytes, ×109/L	0.218（0.134-0.353）	P＜0.001
Monocytes, ×109/L	0.988（0.747-1.307）	0.932
PLT, ×109/L	0.993（0.989-0.997）	P＜0.001
MPV (fl)	1.184（0.952-1.473）	0.129
MPVLR tertile
Low tertile	Reference		Reference
Middle tertil	3.757（1.946-7.251）	P＜0.001	3.210（1.440-7.155）	0.004
high tertil	7.306（3.820-13.973）	P＜0.001	4.606（1.971-10.765）	P＜0.001
Treatment in hospital, (n%)
Antihypertensive agents	0.937（0.599-1.467）	0.777
Antiplatelet agents	1.932（0.763-4.891）	0.165
Anticoagulant agents	0.457（0.199-1.050）	0.065
Cholesterol-lowering agents	3.157（0.520-19.152）	0.211
Hypoglycemic agents	1.274（0.789-2.055）	0.322
rt-PA intravenous thrombolytic	0.993（0.539-1.831）	0.982
Mechanical thrombectomy	0.347（0.117-1.023）	0.055

Note: Multivariate analysis : Adjusted for age, sex, BMI，previous stroke or TIA，history of Coronary heart disease, atrial fibrillation, smoking status, NIHSS score at admission, MPVLR and Mechanical thrombectomy.

Abbreviations: NIHSS=National institutes of health stroke scale；mRS=modified Rankin Scale；SBP=Systolic blood pressure; DBP=Diastolic blood pressure; MPVLR=Mean platelet volume-to-lymphocyte ratio; FBG=Fasting blood glucose; TC=Total cholesterol; TG=Triglyceride; HGB=hemoglobin; WBC=white blood cell count; PLT=platelet count; MPV=Mean platelet volume.

3.4 Association between MPVLR and poor functional outcomes

The ROC curve analysis was conducted to evaluate MPVLR's ability to predict poor outcomes at three months post-AIS. As depicted in Figure 3, the area under the curve for MPVLR was 0.727 (95% CI: 0.672–0.783), indicating that the accuracy of the prediction is moderate predictive. The ideal cutoff value determined was 5.547, and the sensitivity and specificity of forecasting poor outcomes were 82.2% and 52.9%, respectively (Figure 3).

In this study, our findings indicate that an elevated MPVLR at admission is significantly associated with adverse functional outcomes in AIS patients after three months follow-up. MPV is recognized as a marker to assess platelet size, where larger platelets exhibit greater enzymatic and metabolic activity than their smaller counterparts, leading to increased prothrombotic effects ^[15]. They are also known to express and secrete a range of critical mediators involved in coagulation, inflammation, and atherosclerosis, including adhesive proteins (thrombospondin and fibrinogen), growth factors (transforming growth factor-β and platelet-derived growth factor), mitogenic and chemotactic factors (coagulation factors V and XI and platelet factor 4), and cytokine-like factors (CD40 ligand and interleukin-1)^[16]. This evidence underscores the potential of higher MPV to increase thrombosis risk and exacerbate stroke severity. Inflammation is a well-documented contributor to the pathogenesis of stroke ^{[17, 18]}. Lymphocytes play a protective role against atherosclerosis and contribute to mechanisms in the ischemic brain^{[19, 20]}. A decreased lymphocyte count, which is commonly observed in stroke patients, could signify a compromised immune response. By integrating MPV and lymphocyte counts, MPVLR serves as a novel biomarker for assessing thrombosis and inflammation. While previous research has predominantly focused on the link between MPVLR and poor outcomes in cardiovascular diseases ^{[13, 14, 21]}. In recent years, literature has increasingly focused on the prognostic implications of MPVLR in AIS. Chen et al. observed that the MPVLR measurements taken at admission and between 18–24 hours post-intravenous thrombolysis were independently linked to poor clinical outcomes in AIS patients ^[22]. Similarly, a prospective observational study highlighted MPVLR as a significant predictor of unfavorable functional outcomes one year after receiving intravenous thrombolysis for AIS^[23]. These studies primarily explore the association between MPVLR and AIS prognosis following intravenous thrombolysis, suggesting a recurring theme in acute stroke management. However, a broader application of MPVLR was explored in a study enrolling 315 patients with first-time AIS, which found a positive correlation between admission MPVLR and stroke severity, identifying it as an independent indicator of short-term poor prognosis following AIS^[24]. Our findings align with this broader perspective, confirming that elevated MPVLR correlates with unfavorable clinical outcomes at 3 months. Despite these correlations, the underlying mechanisms linking MPVLR with poor stroke prognosis remain elusive, and ongoing research is essential to unravel these mechanisms further.

This study has several limitations. First, it’s a single-center study with a limited sample size. Secondly, the analysis was based on baseline MPVLR measurements only, without considering the potential insights from dynamic changes in MPVLR over time. Thirdly, we did not account for different etiologies of AIS, which might influence the relationship between MPVLR and stroke outcomes. Future studies should explore the impacts of various stroke etiologies on MPVLR values. Additionally, as all participants were Chinese, the applicability of our findings to other races and ethnicities may be limited. To enhance the understanding of MPVLR's role in stroke prognosis and to confirm its predictive value, further research involving larger, more diverse populations and longitudinal assessments is needed.

Our study demonstrates that MPVLR is significantly associated with short-term poor functional outcomes in patients after AIS onset. MPVLR measured at admission serves as a potential biomarker for outcome assessment and could be considered a therapeutic target in stroke management. Specifically, when MPVLR is equal to or exceeds 5.56, the risk of poor prognosis notably increases, suggesting its utility in clinical decision-making processes.

NIHSS

National institutes of health stroke scale

mRS

modified Rankin Scale༛SBP = Systolic blood pressure

DBP

Diastolic blood pressure

MPVLR

Mean platelet volume-to-lymphocyte ratio

FBG

Fasting blood glucose

TC

Total cholesterol

TG

Triglyceride

HGB

hemoglobin

WBC

white blood cell count

PLT

platelet count

MPV

Mean platelet volume.

Ethics approval and consent to participate

The study was approved by the ethics committee of Beijing Shunyi District Hospital (Beijing, China). Written consents were obtained from all participants or their legal representatives.

Conflict of interest statement

The authors declare that there is no conflict of interest.

Funding

No funding was received.

Author Contribution

Kai Feng，Ying Peng conceived and designed the present study. Ying Peng and Hui Wang contributed to the manuscript drafting. Ying Peng，Hui Wang, and Yuan Zhao performed the statistics analysis. Ying Peng，Liuxi Chen and Yakun Wu contributed to data collection. All authors have read and approved the final manuscript.

Acknowledgements

We thank all the physicians and nurses in the neurology department and all the participants in the present study.

Data availability statement

Data are available to researchers upon request for purposes of reproducing the results or replicating the procedure by directly contacting the corresponding author.

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No competing interests reported.

Impact of mean platelet volume to lymphocyte ratio on short-term clinical outcomes in patients with acute ischemic stroke

Status:

Version 1

Abstract

Background

Method

Results

Conclusions

Figures

1. Introduction

2. Methods

2.1 Study population

2.2 Baseline data collection

2.3 Sample collection and measurement of MPVLR

2.4 Outcome assessment

2.5 Statistical analysis

3. Results

4. Discussion

Conclusions

Abbreviations

Declarations

Ethics approval and consent to participate

Conflict of interest statement

Funding

Author Contribution

Acknowledgements

Data availability statement

References

Additional Declarations

Status:

Version 1