Use of nmlr in a prognostic test kit for endovascular treatment of acute ischemic stroke

Abstract

This invention relates to the field of biomedical technology, providing the application of NMLR in the preparation of a predictive kit for the prognosis of endovascular treatment of acute ischemic stroke. The predictive kit includes reagents for detecting neutrophil, monocyte, and lymphocyte counts, assisting in the prediction of the prognosis of endovascular treatment for acute ischemic stroke. The application of NMLR in the predictive kit for the prognosis of endovascular treatment of acute ischemic stroke can be routinely used for early risk assessment, providing objective evidence for individualized clinical treatment and prognostic management, especially for patients with NMLR > 7.480, to enhance perioperative monitoring and strengthen brain protection and inflammation control strategies to improve prognosis. Furthermore, as a simple and economical laboratory indicator, NMLR is particularly suitable for widespread use in primary hospitals and emergency treatment scenarios.

Description

Technical Field

[0001] This invention belongs to the field of biomedical technology, and in particular relates to the application of NMLR in the preparation of a predictive kit for the prognosis of endovascular treatment of acute ischemic stroke. Background Technology

[0002] Acute ischemic stroke (AIS) is a leading cause of death and disability worldwide, with large vessel occlusion (LVO) accounting for a significant proportion and exhibiting a poor prognosis. Endovascular treatment (EVT) has been proven to be the first-line treatment for LVO patients, significantly improving their prognosis. However, even with successful recanalization, more than half of patients fail to achieve functional independence, and some even experience adverse outcomes such as death. Therefore, early identification of risk factors affecting prognosis is crucial for guiding clinical decision-making and improving patient outcomes.

[0003] The neutrophil-monocyte-to-lymphocyte ratio (NMLR) is a novel inflammatory marker proposed in recent years. It integrates information from neutrophils, monocytes, and lymphocytes, providing a more comprehensive reflection of the body's immune-inflammatory imbalance. Some studies have shown that NMLR is a prognostic indicator for patients after cardiopulmonary resuscitation and for acute myocardial infarction, but its predictive value in patients undergoing endovascular treatment for acute ischemic stroke remains unclear. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention provides the application of NMLR in the preparation of a predictive kit for the prognosis of endovascular treatment of acute ischemic stroke, with the aim of solving the problems mentioned in the background art.

[0005] This invention provides the application of NMLR in the preparation of a predictive kit for the prognosis of endovascular treatment of acute ischemic stroke, the predictive kit assisting in predicting the prognosis of endovascular treatment of acute ischemic stroke.

[0006] Furthermore, the prediction kit includes detection reagents for detecting neutrophil count, monocyte count, and lymphocyte count.

[0007] Furthermore, the formula for calculating NMLR is expressed as follows: NMLR = (neutrophil count + monocyte count) / lymphocyte count.

[0008] Furthermore, the detection reagents include leukocyte differential staining reagent, hemolysin, and diluent.

[0009] Furthermore, the sample detected by the prediction kit is a peripheral venous blood sample.

[0010] Furthermore, the predictive kit assists in predicting the prognosis of endovascular treatment for acute ischemic stroke, including excellent prognosis, good prognosis, death, and ineffective recanalization at 90 days post-treatment.

[0011] Furthermore, an excellent prognosis mRS score is 0-1.

[0012] Furthermore, a good prognosis is indicated by an mRS score of 0-2.

[0013] Furthermore, the mTICI score for ineffective recanalization was 2b-3, and the mRS score was >2.

[0014] This invention offers the following advantages: NMLR, when applied to the preparation of a predictive kit for the prognosis of endovascular treatment of acute ischemic stroke, can be routinely used for early risk assessment, providing objective evidence for individualized clinical treatment and prognostic management. This is particularly beneficial for patients with NMLR > 7.480, enabling enhanced perioperative monitoring and strengthened brain protection and inflammation control strategies to improve prognosis. Furthermore, as a simple and economical laboratory indicator, NMLR possesses significant clinical advantages in emergency screening and early risk stratification, making it particularly suitable for widespread use in primary hospitals and emergency treatment scenarios. Attached Figure Description

[0015] Exemplary embodiments of the present invention can be more fully understood by referring to the following figures: Figure 1 This is the ROC curve of the predicted excellent prognosis in Embodiment 3 of the present invention; Figure 2 This is the ROC curve of a good prognosis predicted in Embodiment 3 of the present invention; Figure 3 This is the ROC curve for predicting mortality in Embodiment 3 of the present invention; Figure 4 This is the ROC curve of the predicted invalid re-application in Embodiment 3 of the present invention. Detailed Implementation

[0016] To make the technical problems to be solved, the technical solutions, and the beneficial effects of the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present invention and are not intended to limit the present invention.

[0017] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains; the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the invention.

[0018] Sample collection and analysis: 1. Research Subjects We retrospectively collected clinical data of AIS patients who underwent EVT at the First Affiliated Hospital of Nanchang University from November 2019 to January 2025. This study was approved by the Ethics Committee of the First Affiliated Hospital of Nanchang University (Ethics No. IIT

[2023] Linlun Shen No. 364).

[0019] Inclusion criteria: ① Age ≥ 18 years; ② Meets the diagnostic criteria for AIS in the Chinese Guidelines for the Diagnosis and Treatment of Acute Ischemic Stroke (2023 Edition), acute ischemic stroke caused by occlusion of large vessels in the anterior or posterior circulation; ③ Received endovascular treatment (with or without intravenous thrombolysis) within 24 hours of onset; ④ Completed routine blood tests before the procedure.

[0020] Exclusion criteria: ① Comorbid severe acute infection, malignant tumor, coagulation dysfunction, autoimmune disease, severe liver and kidney dysfunction, chronic infection and other major diseases; ② Lack of relevant clinical data (such as baseline NIHSS score, imaging examination results, laboratory data, follow-up data, etc.); ③ Pre-onset mRS score > 2 points.

[0021] 2. Data Collection (1) Baseline data: Collect patient age, gender, hypertension, diabetes, atrial fibrillation, and stroke history; (2) Clinical characteristics: Record systolic blood pressure, diastolic blood pressure, NIHSS score, time from onset to admission, time from puncture to reperfusion, and time from admission to puncture at admission; (3) Neuroimaging data: ASPECTS grade, infarct core volume, penumbra volume, mismatch ratio, and affected vascular region (anterior circulation, posterior circulation), modified thrombolysis in cerebral infarction scale (mTICI); (4) Laboratory tests: Complete blood count (white blood cell count, neutrophil count, monocyte count, lymphocyte count) at admission, blood glucose, creatinine, urea, and uric acid at admission; (5) Follow-up data: All patients were followed up by professional medical staff by telephone, SMS, or outpatient clinic after discharge. The follow-up time was 90 days ± 7 days after surgery, and the mRS score was used to assess the patient's prognosis.

[0022] The formula for calculating NMLR is: NMLR = (neutrophil count + monocyte count) / lymphocyte count.

[0023] 3. Outcome Indicators The outcome measures were excellent prognosis (mRS score 0-1) at 90 days postoperatively, good prognosis (mRS score 0-2), death, and ineffective recanalization (mTICI score 2b-3 but mRS score >2 at 90 days postoperatively).

[0024] 4. Grouping criteria Patients were divided into three groups based on the NMLR tertiles: low level (≤4.68), intermediate level (4.69~7.48), and high level (>7.48).

[0025] 5. Statistical methods Statistical analysis was performed using SPSS 26.0 software. Continuous variables conforming to a normal distribution were expressed as mean ± standard deviation. ) indicates that non-normally distributed continuous variables are represented by M(P25,P75), and categorical variables are represented by frequency (%). Comparisons between groups of continuous variables are performed using t-tests or Kruskal-Wallis H tests, while comparisons of categorical variables are performed using... The relationship between non-molecular venous resection (NMLR) and endovascular treatment of acute ischemic attacks (AIS) was investigated using a binary logistic regression model. ROC curves were constructed, and the area under the curve (AUC), 95% confidence interval (95% CI), and Youden index were calculated to determine the optimal cutoff value for NMLR in predicting different prognostic outcomes. A p-value < 0.05 was considered statistically significant.

[0026] Example 1: This retrospective study included 1525 patients diagnosed with acute large vessel occlusive stroke and admitted within 24 hours of onset between November 2019 and January 2025. 54 patients with serious acute infections, malignancies, coagulation disorders, severe liver or kidney dysfunction, chronic infections, or other major diseases were excluded; 355 patients lacked relevant clinical data (such as baseline NIHSS score, imaging results, laboratory data, follow-up data, etc.); 38 patients had a pre-onset mRS score >2; and 2 patients were <18 years old. A total of 1076 patients were ultimately included in the analysis.

[0027] Table 1 shows the baseline data and clinical characteristics of 1076 patients classified according to their NMLR levels at admission. The results showed that 704 patients (65.4%) were male, with an average age of 65.26 years (range 57.0-74.0 years). Based on NMLR levels, patients were divided into a low-level group (n=353), a moderate-level group (n=358), and a high-level group (n=358). There were no statistically significant differences among the three groups in terms of age, sex, history of hypertension, history of atrial fibrillation, systolic blood pressure, diastolic blood pressure, time from puncture to reperfusion, infarct core volume, penumbra volume, mismatch ratio, mTICI score, and stroke etiology (P>0.05). Statistically significant differences were found among the three groups in terms of history of diabetes, stroke history, baseline NIHSS score, time from onset to admission, time from admission to puncture, ASPECTS classification, affected vessel region, blood glucose level at admission, and creatinine level (P<0.05).

[0028] Table 1. Baseline data and clinical characteristics of patients classified according to their NMLR levels at admission.

[0029] Note: In the table, NIHSS: National Institutes of Health Stroke Scale; ASPECTS: Alberta Stroke Program Early CT Score; mTICI: Modified Thrombolysis Grade for Cerebral Infarction.

[0030] Prognostic outcomes showed that NMLR levels were significantly correlated with patient prognosis. The excellent prognosis rates for the low-level, intermediate-level, and high-level groups were 42.3%, 32.0%, and 22.1%, respectively; the good prognosis rates were 52.4%, 41.8%, and 32.4%, respectively; the recanalization failure rates were 44.2%, 55.4%, and 67.1%, respectively; and the mortality rates were 19.8%, 26.5%, and 39.4%, respectively. The low-level group had the highest excellent prognosis rate (42.3%) and good prognosis rate (52.4%), while the high-level group had the highest mortality rate (39.4%) and recanalization failure rate (67.1%). All differences between the groups were statistically significant (P<0.001).

[0031] Example 2: Table 2 shows the results of multivariate logistic regression analysis of excellent prognosis, good prognosis, death, and ineffective recanalization. The results showed that, with NMLR as a continuous variable, multivariate logistic regression analysis, after correction 1 (age, sex), correction 2 (variables with P < 0.05 in univariate analysis), and correction 3 (age, sex, and variables with P < 0.05 in univariate analysis), all showed that elevated NMLR levels were negatively correlated with excellent and good prognosis, and positively correlated with death and ineffective recanalization (all P < 0.001).

[0032] Multivariate logistic regression analysis was performed using NMLR grouping as the categorical variable and the low-level group as the reference. Adjusted for 3, compared with the low-level group, the odds ratios (ORs) for excellent outcomes in the intermediate-level and high-level groups were 0.632 (95% CI: 0.454–0.880) and 0.413 (95% CI: 0.289–0.591), respectively; for good outcomes, 0.616 (95% CI: 0.444–0.855) and 0.468 (95% CI: 0.333–0.660), respectively; for death, 1.646 (95% CI: 1.119–2.422) and 2.431 (95% CI: 1.668–3.541), respectively; and for ineffective recanalization, 1.683 (95% CI: 1.190–2.382) and 2.454 (95% CI: 1.711–3.521), respectively.

[0033] Table 2. Multivariate logistic regression analysis of excellent prognosis, good prognosis, death, and ineffective recanalization.

[0034] Example 3: Table 3 shows the predictive power of NMLR for different prognoses, and the ROC analysis is as follows: Figures 1-4 As shown, the results indicated that the AUC for NMLR predicting excellent prognosis was 0.615 (95% CI: 0.580-0.651), with an optimal cutoff of 8.4, a sensitivity of 40.8%, and a specificity of 76.0%; the AUC for predicting good prognosis was 0.598 (95% CI: 0.564-0.632), with an optimal cutoff of 9.2, a sensitivity of 31.4%, and a specificity of 83.7%; the AUC for predicting death was 0.624 (95% CI: 0.586-0.661), with an optimal cutoff of 8.1, a sensitivity of 43.3%, and a specificity of 75.7%; and the AUC for predicting ineffective recanalization was 0.610 (95% CI: 0.575-0.645), with an optimal cutoff of 8.4, a sensitivity of 35.3%, and a specificity of 81.3%.

[0035] Table 3 Predictive ability of NMLR for different prognoses

[0036] Based on Examples 1-3, it was concluded that patients in the high NMLR group had higher baseline NIHSS scores and lower ASPECTS grades, suggesting an intrinsic association between NMLR and stroke severity at onset. Multivariate logistic regression analysis further showed that, after adjusting for confounding factors such as age, sex, baseline medical history, imaging parameters, and admission blood glucose, NMLR > 7.480 independently predicted a lower rate of good prognosis, a higher risk of ineffective recanalization, and a higher risk of death; that is, the higher the NMLR level, the greater the risk of adverse outcomes. Finally, ROC analysis showed that the AUC for NMLR predicting different prognoses ranged from 0.598 to 0.624, suggesting that NMLR has a certain prognostic predictive ability and can serve as a supplement to existing prognostic assessment systems.

[0037] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. Use of NMLR in the manufacture of a prognostic test kit for endovascular treatment of acute ischemic stroke, characterized in that: The predictive kit helps predict the prognosis of endovascular treatment for acute ischemic stroke.

2. The application as described in claim 1, characterized in that: The predictive kit includes detection reagents for detecting neutrophil count, monocyte count, and lymphocyte count.

3. The application as described in claim 2, characterized in that: The formula for calculating NMLR is expressed as follows: NMLR = (neutrophil count + monocyte count) / lymphocyte count.

4. The application as described in claim 3, characterized in that: The testing reagents include leukocyte differential staining reagent, hemolysin, and diluent.

5. The application as described in claim 4, characterized in that: The predictive kit detects peripheral venous blood samples.

6. The application as described in claim 5, characterized in that: The predictive kit helps predict the outcomes of endovascular treatment for acute ischemic stroke, including excellent prognosis, good prognosis, death, and ineffective recanalization at 90 days post-treatment.

7. The application as described in claim 6, characterized in that: An excellent prognosis is indicated by an mRS score of 0-1.

8. The application as described in claim 7, characterized in that: A good prognosis is indicated by an mRS score of 0-2.

9. The application as described in claim 8, characterized in that: The mTICI score for ineffective recanalization is 2b-3, and the mRS score is >2.

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