Application of blood nutrition marker based on central nervous system injury prognosis

Abstract

The invention discloses application of a group of blood nutrition markers in prediction of central nervous system (CNS) injury function prognosis. According to the technical scheme, the method is characterized in that serum albumin, total cholesterol (TC) and low density lipoprotein cholesterol (LDL-C) are determined as independent predictive factors of CNS injury prognosis for the first time through retrospective queue research (n = 404), and clinical decision critical values are determined to be 36.35 g / L, 3.60 mmol / L and 2.13 mmol / L respectively. The detection kit developed on the basis of the discovery can objectively and quantitatively evaluate the prognosis risk of the patient within 24 hours of admission, and is obviously superior to that of a traditional scoring system. According to the method, key technical support is provided for precise nutrition intervention and early rehabilitation strategy formulation of the CNS injury.

Description

Technical Field

[0001] This invention relates to the field of biomarker technology, and more specifically, to the application of blood nutritional biomarkers based on the prognosis of central nervous system injury. Background Technology

[0002] Functional prognostic assessment following central nervous system (CNS) injury is a major challenge in clinical medicine. Patients often face a high risk of malnutrition due to the disease itself and its treatment. This is primarily due to vomiting caused by trauma, coma, or increased intracranial pressure, making it difficult for patients to eat. Furthermore, the body is in a hypermetabolic state, with significantly increased energy and protein requirements. Simultaneously, nerve injury is often accompanied by gastrointestinal dysfunction, affecting nutrient absorption. Blood loss, vomiting, or drainage in patients also leads to substantial loss of body fluids and protein. Malnutrition directly impacts nerve repair and overall recovery; therefore, enteral or parenteral nutritional support is necessary to ensure adequate energy and protein intake, providing the material basis for recovery. Current techniques for predicting the prognosis of malnutrition mainly rely on imaging examinations and clinical scoring scales, which have limitations such as high subjectivity and time lag.

[0003] Currently, there is no technical solution to systematically and quantitatively link blood nutritional indicators with the prognosis of CNS damage. Traditional nutritional assessment tools (such as NRS-2002 and the MUST scale) lack specificity for CNS damage and have not established decision thresholds for objective biochemical biomarkers. Summary of the Invention

[0004] The purpose of this invention is to provide the application of blood nutritional biomarkers based on the prognosis of central nervous system injury, and to further confirm the prognostic value of blood nutritional biomarkers in the recovery period of CNS injury.

[0005] The above-mentioned technical objective of this invention is achieved through the following technical solution: the application of a reagent for detecting blood nutritional markers in the preparation of products for predicting the prognosis of central nervous system injury, wherein the blood nutritional marker combination consists of serum albumin, total cholesterol, and low-density lipoprotein cholesterol; wherein, a serum albumin concentration ≥36.35 g / L indicates a good functional prognosis; a total cholesterol concentration ≤3.60 mmol / L indicates a good functional prognosis; and a low-density lipoprotein cholesterol concentration ≤2.13 mmol / L indicates a good functional prognosis; the reagent is used to detect the concentration of the above markers to achieve early and objective assessment of the functional prognosis of patients with central nervous system injury.

[0006] The present invention is further configured such that: serum albumin, total cholesterol and low-density lipoprotein cholesterol are all independent prognostic factors for central nervous system injury (the prognostic assessment criterion is the modified Barthel index mean relative functional gain [mRFG]).

[0007] The present invention is further configured such that: the higher the serum albumin content, the better the prognosis.

[0008] The present invention is further configured such that the higher the total cholesterol and low-density lipoprotein cholesterol content, the worse the prognosis.

[0009] The present invention further provides a product for predicting the prognosis of central nervous system injury, the product comprising reagents for detecting blood nutritional markers, the reagents including the aforementioned serum albumin, total cholesterol and / or low-density lipoprotein cholesterol.

[0010] The present invention is further configured such that the product includes a chip and a reagent kit.

[0011] The present invention is further configured such that the reagent includes an antibody, peptide, aptamer, or compound that specifically binds to the blood nutritional marker.

[0012] In summary, the present invention has the following beneficial effects:

[0013] The core innovation of this invention lies in establishing for the first time the causal relationship between blood nutritional biomarkers and functional prognosis of CNS damage, and providing clinically translatable decision thresholds: serum albumin, total cholesterol, and low-density lipoprotein cholesterol levels were found to be independent predictors of functional prognosis in patients with CNS damage. Serum albumin was identified as a protective factor, while total cholesterol and low-density lipoprotein cholesterol were associated with poorer prognosis. Utilizing these characteristics, the critical values ​​for these biomarkers can be determined, further providing clinicians with more precise guidance for patient management and prognostic assessment. Attached Figure Description

[0014] Figure 1 This is a nonlinear analysis of albumin, total cholesterol, and low-density lipoprotein in the embodiments of the present invention;

[0015] Note: Serum albumin showed a linear positive correlation with prognosis (non-linear P > 0.05), and TC / LDL-C showed a linear negative correlation with prognosis (non-linear P > 0.05), confirming a stable dose-response relationship.

[0016] Figure 2 In this embodiment of the invention, prognostic differences are compared by grouping according to cutoff values;

[0017] Note: When grouped by cutoff value, the differences in mRFG among the serum albumin, TC and LDL-C groups were statistically significant (P < 0.05).

[0018] Figure 3 This is a subgroup analysis of albumin, total cholesterol, and low-density lipoprotein in the embodiments of the present invention;

[0019] Note: In the brain injury and spinal cord injury subgroups, the biomarker effect sizes were highly consistent (I²=0%, P for interaction > 0.05), confirming the generalizability of the results. Detailed Implementation

[0020] The following is in conjunction with the appendix Figure 1-3 The present invention will be described in further detail below.

[0021] Example: Application of blood nutritional biomarkers for prognostic outcomes of central nervous system injury

[0022] 1. Study Design: 404 patients with CNS injuries admitted to a tertiary teaching hospital in China from January 2018 to January 2025 were included. The types of injuries included traumatic brain injury (n=182) and spinal cord injury (n=222).

[0023] 2. Prognostic Assessment: Functional recovery was accurately quantified using the modified Barthel Index Mean Relative Functional Gain (mRFG). The mRFG formula is: mRFG = (Discharge MBI - Admission MBI) / (100 - Admission MBI) × 100%. This formula adjusts for baseline functional status and mitigates the "ceiling effect," where patients with high admission modified Barthel scores have limited potential for measurable improvement compared to those with lower initial scores. mRFG > 0.5 was defined as a good prognosis. Patients were divided into a good prognosis group (n = 71, mRFG > 0.5) and a poor prognosis group (n = 333, mRFG ≤ 0.5).

[0024] 3. Testing method: Fasting venous blood was collected within 24 hours of admission.

[0025] 4. Statistical Analysis: Univariate and multivariate analyses were used to identify independent prognostic factors, including demographic variables, clinical characteristics, complications, and blood biomarkers. Receiver operating characteristic (ROC) curve analysis was used to determine the optimal cutoff values ​​for independent predictors. The reliability and stability of the results were validated using restricted cubic spline (RCS) models, subgroup analyses, and sensitivity analyses.

[0026] 5. Statistical Results: Univariate analysis (Table 1-2) showed that the two groups had similarities in time from injury to hospitalization (Z = -3.201, P = 0.001) and injury type (χ²). 2 = 4.434, P = 0.035), coronary heart disease (χ²) 2Significant differences were found in the following values: (Z = -2.820, P = 0.005), albumin (Z = -2.226, P = 0.026), creatinine (Z = -2.621, P = 0.009), total cholesterol (Z = -4.529, P < 0.001), triglycerides (TG, Z = -2.235, P = 0.025), and low-density lipoprotein (LDL-C, Z = -4.711, P < 0.001).

[0027] The above factors were included in a multivariate analysis (Table 3). After adjusting for other confounding factors, serum albumin (OR = 0.900, P = 0.015), total cholesterol (TC, OR = 2.217, P < 0.001), and low-density lipoprotein cholesterol (OR = 2.442, P < 0.001) were independent predictors of functional prognosis.

[0028] Table 1. Single-factor analysis under general circumstances

[0029]

[0030] Table 2. Univariate analysis of blood parameters

[0031]

[0032] Table 3. Multivariate Logistic Analysis

[0033]

[0034] RCS analysis was used to flexibly model the relationship between albumin, TC, LDL-C, and functional prognosis. RCS analysis showed no significant non-linear relationship between serum albumin, TC, or LDL-C and functional prognosis. See [link to RCS analysis]. Figure 1 .

[0035] ROC curves were used to determine the cutoff values ​​for albumin, total cholesterol (TC), and LDL-C. The area under the curve (AUC) for albumin was 0.586 (95% CI: 0.52, 0.65), with an optimal cutoff value of 36.35 g / L. The AUC for TC was 0.67 (95% CI: 0.60, 0.73), with an optimal cutoff value of 3.60 mmol / L. The AUC for LDL-C was 0.68 (95% CI: 0.61, 0.74), with a cutoff value of 2.13 mmol / L. Furthermore, albumin, TC, and LDL-C were grouped according to these cutoff values, and differences in prognosis between groups were compared. According to cutoff values, there were statistically significant differences in mRFG between the albumin (cutoff value 36.35 g / L, P < 0.01), TC (cutoff value 3.6 mmol / L, P < 0.001), and LDL-C (cutoff value 2.13 mmol / L, P < 0.001) groups. (See attached table). Figure 2 .

[0036] Stratified analysis was performed based on gender and injury type to assess potential effect correction factors. Figure 3 In each subgroup, albumin, TC, and LDL-C were consistent with the risk estimates for functional prognosis (all P > 0.05), indicating that the results for each sample were stable and generalizable.

[0037] In summary, serum albumin, total cholesterol (TC), and LDL-C levels are independent predictors of functional prognosis in patients with CNS impairment. Serum albumin is a protective factor, while TC and LDL-C are associated with poorer prognosis. Cutoff values ​​for these biomarkers can provide clinicians with more precise guidance for patient management and prognostic assessment.

[0038] Confirmatory trials were conducted on the serum albumin, TC, and LDL-C levels, which were identified as independent predictors of functional prognosis in patients with CNS injury.

[0039] 1. Reanalyze the outcome variable (mRFG) as a continuous variable. Use an appropriate linear regression model to reassess its relationship with key biomarkers.

[0040] The results showed that the associations between the core biomarkers albumin, total cholesterol, low-density lipoprotein, and outcome were consistent with the binary classification analysis. This confirms that the effect of this biomarker reflects a meaningful biological gradient, rather than depending solely on a specific binary classification threshold.

[0041] Table 4. Validation by linear regression analysis

[0042]

[0043] 2. Internal validation based on Bootstrap resampling method

[0044] The bootstrap method generates a large number (e.g., 1000) of simulated samples by repeatedly sampling the original sample with replacement, and then reconstructs the model based on these simulated samples to obtain empirical distributions of key statistics (such as regression coefficients, prediction accuracy, etc.). This validation process performed the bootstrap resampling procedure (repeated 1000 times). Key model parameters were re-estimated in each bootstrap sample to generate empirical distributions. The results show that the bootstrap distributions of the estimates of the major biomarker effects are tightly clustered, indicating that the estimation results are stable.

[0045] The OR values ​​and confidence intervals derived using the Bootstrap procedure remain statistically significant (excluding zero) and are similar to or more conservative than standard intervals. This provides a high degree of confidence in the accuracy and reliability of the reported effect sizes.

[0046] Table 5. Bootstrap Method Verification

[0047]

[0048] This specific embodiment is merely an explanation of the present invention and is not intended to limit the invention. After reading this specification, those skilled in the art can make modifications to this embodiment without contributing any inventive step, but such modifications are protected by patent law as long as they are within the scope of the claims of the present invention.

Claims

1. Use of a reagent for detecting a blood nutritional marker in the manufacture of a product for predicting the prognosis of an injury to the central nervous system, characterized in that: The blood nutrition marker combination consists of serum albumin, total cholesterol and low density lipoprotein cholesterol; wherein, serum albumin concentration ≥ 36.35 g / L indicates good functional prognosis; total cholesterol concentration ≤ 3.60 mmol / L indicates good functional prognosis; low density lipoprotein cholesterol concentration ≤ 2.13 mmol / L indicates good functional prognosis; the reagent is used for detecting the concentration of the above markers to realize early and objective evaluation of the functional prognosis of patients with central nervous system injury.

2. Use of the reagent for detecting a blood nutritional marker according to claim 1 for the manufacture of a product for predicting the prognosis of an injury to the central nervous system, characterized in that: The serum albumin, total cholesterol and low density lipoprotein cholesterol are all independent factors for the functional prognosis of central nervous system injury.

3. Use of the reagent for detecting a blood trophic marker according to claim 2 for the preparation of a product for predicting the prognosis of an injury to the central nervous system, characterized in that: The higher the serum albumin content is, the better the prognosis is.

4. Use of the reagent for detecting a blood nutritional marker according to claim 2 for the manufacture of a product for predicting the prognosis of a central nervous system injury, characterized in that: The higher the total cholesterol and low density lipoprotein cholesterol content is, the worse the prognosis is.

5. A product for predicting the prognosis of a central nervous system injury, characterized by: The product comprises a reagent for detecting blood nutrition markers, and the reagent comprises serum albumin, total cholesterol and / or low density lipoprotein cholesterol as described in claim 1.

6. A product for predicting the prognosis of a central nervous system injury according to claim 5, characterized by: The product comprises a chip or a kit.

7. Use of blood nutritional markers for prognosis of central nervous system injury according to claim 1, characterized in that: The reagent comprises an antibody, a peptide, an aptamer or a compound specifically combined with the blood nutrition markers.

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