Heart transplantation nutrition prognosis analysis system for patient with dilated cardiomyopathy

Abstract

The invention provides a heart transplantation nutrition prognosis analysis system for a patient with dilated cardiomyopathy, three factors including prealbumin (PA), total bile acid (TBA) and NRS2002 score are incorporated into the analysis system, a corresponding algorithm is provided, and based on the algorithm, the optimal cutoff value of an undesirable outcome is predicted to be 0.121, the sensitivity is 72.9%, the specificity is 92.9%, and the area under a ROC curve (AUC) is 0.885 (95% CI: 0.802-0.967); when the absolute error of a calibration curve is 0.049, the HL goodness of fit test is equal to 6.134 (P is equal to 0.632 gt, 0.05), the net income threshold probability of DCA is 0.04-0.94, and the threshold probability of CIC is greater than 0.50, the prediction is highly consistent with the actual outcome. Meanwhile, the AUC value of the algorithm is obviously larger than that of other existing prediction methods, the algorithm can serve as a reliable tool for evaluating the postoperative adverse outcome risk of the patient in clinical practice, an important reference basis is provided for optimizing the individualized treatment strategy of the patient to be transplanted and perfecting the organ distribution scheme, and the accuracy and rationality of heart transplantation diagnosis and treatment can be improved.

Description

Technical Field

[0001] This invention belongs to the field of risk prediction technology after heart transplantation, specifically relating to a nutritional prognostic analysis system for heart transplantation in patients with dilated cardiomyopathy. Background Technology

[0002] Dilated cardiomyopathy (DCM) is an abnormal myocardial load characterized by left ventricular or biventricular dilation and systolic dysfunction. Diagnosis requires exclusion of hypertension, valvular heart disease, and coronary artery disease. Specifically, it is defined as a left ventricular end-diastolic diameter exceeding the predicted value by two standard deviations, with a left ventricular ejection fraction <45% or a left ventricular shortening fraction <25%. The etiology of this disease is complex, encompassing gene mutations, infections, autoimmune disorders, toxin exposure, endocrine abnormalities, and perinatal conditions. Epidemiological data shows that the incidence of dilated cardiomyopathy in adults is 1 in 250, with a heart failure rate as high as 59%, accounting for approximately 40% of heart failure patients requiring hospitalization, and even higher at 51% in patients undergoing heart transplantation. Malnutrition occurs in approximately 56% of patients with end-stage heart failure, primarily due to elevated levels of inflammatory factors, intestinal protein loss, intravascular albumin leakage, and abnormal activation of the renin-angiotensin-aldosterone system (RAAS). Existing studies have confirmed that malnutrition is an independent risk factor for death after heart transplantation. Early identification of malnutrition and implementation of standardized nutritional intervention can significantly improve the postoperative prognosis of patients.

[0003] Prealbumin (also known as thyroxine transporter) is a homotetrameric protein with a molecular weight of 55 kDa, mainly synthesized in the liver, choroid plexus, retinal pigment epithelium, and pancreas, and widely present in blood, cerebrospinal fluid, and the eyes. Because its synthesis is dually regulated by the body's nutritional status and inflammatory response, and end-stage heart failure patients commonly experience malnutrition and inflammation, prealbumin is speculated to be a potential indicator of the severity of their condition. Total bile acids are hydroxylated sterols synthesized by the liver from cholesterol. After secretion into the intestine, they undergo biotransformation under the metabolic action of gut microbiota and exert various physiological functions by acting on specific receptors. Recent studies have found that the gut microbiota-total bile acid-cardiovascular receptor axis is involved in the occurrence and progression of heart failure, suggesting that the total bile acid level in heart failure patients may be closely related to their condition. The Nutritional Risk Screening Summary (NRS2002), established in 2002 by Kondrup et al. based on 128 nutrition-related clinical studies, is currently recognized as a scientifically effective nutritional risk screening tool that can accurately identify patients who can benefit from nutritional support. The European Society for Clinical Nutrition and Metabolism (ESPEN) guidelines explicitly recommend the use of NRS2002 for nutritional risk assessment in adult hospitalized patients, and studies have confirmed its effectiveness in nutritional risk screening for patients with heart failure.

[0004] Currently, there are few studies on the association between nutrition-related indicators and heart transplant prognosis. Existing reports mostly use indicators such as albumin, prognostic nutritional index (PNI), albumin-creatinine ratio (ACR), albumin-bilirubin score (ALBI), modified end-stage liver disease model score (MELD-XI), and leukocyte-to-albumin ratio (LAR) to predict heart transplant prognosis. However, no specific studies have been reported on the relationship between nutrition-related indicators and heart transplant prognosis in patients with dilated cardiomyopathy. Summary of the Invention

[0005] This invention addresses the aforementioned technical problems by providing a nutritional prognostic analysis system for heart transplantation in patients with dilated cardiomyopathy. The system aims to analyze the relationship between prealbumin (PA), total bile acids (TBA), and NRS2002 scores with the prognosis of heart transplantation in patients with dilated cardiomyopathy, in order to more accurately assess the nutritional status of patients and provide a theoretical basis for improving clinical treatment strategies and optimizing organ allocation plans.

[0006] This invention, through the detection of data from the survival group and the death group of DCM patients undergoing heart transplantation, found that the lymphocyte count, albumin, prealbumin, and albumin-to-globulin ratio were significantly higher in the survival group than in the death group, while the NRS2002 score and the proportion of patients with nutritional risk were significantly lower in the survival group than in the death group, and all of the above differences were statistically significant (P<0.05).

[0007] Furthermore, a correlation analysis was performed on prealbumin (PA), total bile acids (TBA), and NRS2002 score. The results showed that low PA, high TBA, and high NRS2002 score were independent risk factors for adverse postoperative outcomes in this group of patients. The combined predictive ability of PA, TBA, and NRS2002 score for 1-year postoperative mortality risk was significantly higher than that of the three factors alone.

[0008] Based on the above results, a nutritional prognostic analysis system for heart transplantation patients with dilated cardiomyopathy was constructed using the prealbumin (PA), total bile acid (TBA), and NRS2002 score β values ​​in multivariate logistic regression analysis. This system is named CDHTNPI (Changhai DCM patient Heart Transplantation Nutrition Prognostic Index), and its calculation formula is as follows: .

[0009] Where a represents the prealbumin level (unit: mg / L), b represents the total bile acid level (unit: mg / L), and c represents the NRS2002 score.

[0010] ROC curve analysis showed that the optimal cutoff value for CDHTNPI in predicting adverse outcomes in heart transplant patients was 0.121, corresponding to a sensitivity of 72.9% and a specificity of 92.9%. Predictive ability assessment results showed that the C-index of CDHTNPI was 0.885, indicating good predictive efficacy for adverse outcomes after heart transplantation in patients with dilated cardiomyopathy. Clinical decision curve (DCA) analysis showed that making clinical decisions based on CDHTNPI yielded a net benefit. Clinical impact curve (CIC) analysis showed that when the threshold probability was >0.50, the predicted outcomes of this algorithm were highly consistent with the actual outcomes.

[0011] Compared with other existing nutrition-related prediction methods, CDHTNPI has a significantly better predictive ability for the prognosis of heart transplantation in patients with dilated cardiomyopathy.

[0012] Based on the above analysis, the technical solution to be protected by this invention is as follows:

[0013] In a first aspect, the present invention provides a nutritional prognostic analysis system for heart transplantation in patients with dilated cardiomyopathy, which includes at least an analysis module for analyzing prealbumin (PA), total bile acids (TBA) and NRS2002 scores, and for determining low PA, high TBA and high NRS2002 scores as adverse postoperative outcomes.

[0014] Preferably, the adverse postoperative outcome refers to an increased risk of death one year after surgery, meaning that the present invention mainly predicts the risk of death one year after heart transplantation in patients with dilated cardiomyopathy.

[0015] Further optimization involves the analysis module using the following algorithm to individually assess the 1-year mortality risk in DCM patients after heart transplantation:

[0016]

[0017] Where a represents prealbumin level in mg / L, b represents total bile acid level in mg / L, and c represents NRS2002 score. The cutoff value for CDHTNPI was 0.121, and elevated CDHTNPI was significantly associated with an increased risk of death at 1 year post-surgery.

[0018] Preferably, the nutritional prognostic analysis system for heart transplantation in patients with dilated cardiomyopathy provided by the present invention further includes an input display module for inputting the patient's basic information and the corresponding prealbumin, total bile acid and NRS2002 score values, and displaying the judgment results.

[0019] In a second aspect, the present invention provides the application of a nutritional prognostic analysis system for heart transplantation in patients with dilated cardiomyopathy in predicting the risk of death one year after heart transplantation in patients with dilated cardiomyopathy.

[0020] In a third aspect, the present invention provides a method for nutritional prognostic analysis of heart transplantation in patients with dilated cardiomyopathy, comprising the following steps: inputting the patient's basic information and corresponding prealbumin, total bile acid and NRS2002 score values ​​into the input display module; the calculation module calculates the CDHTNPI value using the following formula; and when the value is greater than the cutoff value of 0.121, it is determined that the patient's risk of death one year after surgery is increased.

[0021] .

[0022] In a fourth aspect, the present invention provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the pre-analysis method as described above.

[0023] The beneficial protections and effects of this invention are as follows:

[0024] The nutritional prognostic analysis system for heart transplantation in patients with dilated cardiomyopathy provided by this invention incorporates three factors: prealbumin (PA), total bile acids (TBA), and NRS2002 score. A corresponding algorithm is provided, and based on this algorithm, the optimal cutoff value for predicting adverse outcomes is 0.121, with a sensitivity of 72.9%, specificity of 92.9%, and an area under the ROC curve (AUC) of 0.885 (95% CI: 0.802–0.967). A Norman diagram of the model was plotted, the absolute error of the calibration curve was 0.049, and the HL goodness-of-fit test was performed. =6.134 (P=0.632>0.05), DCA net benefit threshold probability 0.04-0.94, CIC threshold probability >0.50, the prediction is highly consistent with the actual outcome.

[0025] Meanwhile, the algorithm's AUC value is significantly higher than other existing prediction methods, making it a reliable tool for assessing the risk of adverse postoperative outcomes in clinical practice. It provides important reference for optimizing individualized treatment strategies for transplant patients (such as preoperative nutritional intervention) and improving organ allocation plans, thus helping to improve the accuracy and rationality of heart transplant diagnosis and treatment. Attached Figure Description

[0026] Figure 1 A flowchart of the participants in this invention's research is shown.

[0027] Figure 2 The correlation analysis of PA, TBA, and NRS2002 is shown.

[0028] Figure 3 The comparison of ROC curves for the independent prediction models PA, TBA, and NRS2002 is shown.

[0029] Figure 4 The ROC curve analysis of the CDHTNPI prediction model is shown.

[0030] Figure 5 The nomogram analysis of the CDHTNPI prediction model is shown.

[0031] Figure 6 The calibration curve analysis of the CDHTNPI prediction model is shown.

[0032] Figure 7 The DCA analysis of the CDHTNPI prediction model is shown.

[0033] Figure 8 The CIC analysis of the CDHTNPI prediction model is shown.

[0034] Figure 9 The ROC curves of the CDHTNPI prediction model are compared with those of other analytical methods. Detailed Implementation

[0035] The following embodiments and experimental examples further illustrate the present invention and should not be construed as limiting the invention. The embodiments do not include a detailed description of conventional methods, which are well known to those skilled in the art and described in numerous publications.

[0036] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as are familiar to those skilled in the art. Furthermore, any methods and materials similar to or equivalent to those described herein may be applied to this invention, and the preferred embodiments and materials described in the specific implementation are for illustrative purposes only.

[0037] Unless otherwise specified, the experimental methods described in the following examples are generally performed under standard conditions or as recommended by the manufacturer.

[0038] This invention explores a novel, simple, and efficient prognostic algorithm for patients with dilated cardiomyopathy undergoing heart transplantation, providing a reference for their surgical prognosis assessment.

[0039] Clinical data of 92 patients with dilated cardiomyopathy who underwent heart transplantation at Shanghai Changhai Hospital from January 2017 to December 2022 were retrospectively collected. After inclusion according to the inclusion and exclusion criteria, 8 patients were lost to follow-up, and the remaining 84 patients were divided into a survival group (n=70) and a death group (n=14) according to the 1-year postoperative outcome. Differences in demographic and clinical data between the two groups were compared. A novel nutritional prognostic algorithm for heart transplantation patients with dilated cardiomyopathy was established by combining prealbumin, total bile acids, and NRS2002 scores through logistic regression analysis. Receiver operating characteristic (ROC) curves were plotted to determine the optimal cutoff value, sensitivity, and specificity, and evaluated using calibration curves, HL goodness-of-fit tests, decision curve analysis (DCA), and clinical impact curves (CIC). The ROC curves were also compared with predictive methods such as prognostic nutritional index (PNI), albumin-to-creatinine ratio (ACR), albumin-to-bilirubin score (ALBI), and Model for End-Stage Liver Disease (MELD) score.

[0040] The results showed no statistically significant differences in data between patients lost to follow-up and those who completed follow-up (P>0.05). Among the 84 heart transplant patients who completed follow-up, the survival group had significantly higher levels of prealbumin, albumin, lymphocytes, and albumin / globulin ratio than the death group, while the proportion of patients with NRS2002 scores and nutritional risks was significantly lower in the survival group than in the death group (P<0.05). The optimal cutoff value for predicting adverse outcomes using this prognostic algorithm was 0.121, with a sensitivity of 72.9%, a specificity of 92.9%, and an area under the ROC curve (AUC) of 0.885 (95% CI: 0.802–0.967). A Norman plot of the algorithm model was plotted; the absolute error of the calibration curve was 0.049, and the HL goodness-of-fit test was performed. =6.134 (P=0.632>0.05), DCA net benefit threshold probability is 0.04-0.94, and CIC threshold probability is >0.50. The prediction is highly consistent with the actual outcome; at the same time, its AUC is greater than other prediction methods.

[0041] The specific research process is as follows:

[0042] I. Research Methods

[0043] 1. Research Design

[0044] This retrospective cohort study employed a cohort design, including patients with dilated cardiomyopathy (DCM) who underwent heart transplantation at Shanghai Changhai Hospital between 2017 and 2022. Follow-up was conducted via telephone and outpatient visits. Patients were grouped and analyzed based on their 1-year postoperative survival outcomes. (Flowchart available). Figure 1 .

[0045] 2. Research Subjects

[0046] 2.1 Source and Inclusion: Clinical data of DCM patients who underwent heart transplantation at Shanghai Changhai Hospital from January 2017 to December 2022 were retrospectively collected, including demographic characteristics (sex, age, body mass index, etc.), clinical diagnosis, laboratory test results and nutritional status assessment. Initially, 92 cases were included.

[0047] 2.2 Inclusion criteria: (1) Age 18-80 years, diagnosed with DCM and undergoing heart transplantation; (2) Preoperative blood routine, liver and kidney function, cardiac ultrasound and other examinations; (3) Complete medical records.

[0048] 2.3 Exclusion criteria: (1) Patients with combined immunodeficiency, malignant tumors, or hematological diseases; (2) Patients who have received combined organ transplants such as heart-lung or heart-kidney transplants; (3) Patients with severe mental disorders (such as schizophrenia, major depressive disorder, etc.); (4) Pregnant or lactating women.

[0049] 3. Grouping strategy

[0050] Clinical outcomes of enrolled patients were tracked one year post-surgery through a combination of telephone follow-up and outpatient follow-up. Patients who completed the follow-up were divided into a survival group and a death group. Grouping process and sample size changes: Initially, 92 patients were included. After 8 patients were lost to follow-up, the remaining 84 patients were included in the final analysis (survival group n=70, death group n=14).

[0051] 4. Observation indicators and data collection

[0052] 4.1 Demographic characteristics: Record gender, age, height, weight, and body mass index (BMI).

[0053] 4.2 Auxiliary examination results: Extract the most recent preoperative test data, including complete blood count (hemoglobin Hb, red blood cell count RBC, white blood cell count WBC, platelet count PLT, lymphocyte count L), liver and kidney function (albumin ALB, globulin GLB, total protein TP, prealbumin PA, total bilirubin TBIL, total bile acid TBA, alanine aminotransferase ALT, aspartate aminotransferase AST, lactate dehydrogenase LDH, alkaline phosphatase ALP, gamma-glutamyl transferase GGT, creatinine Cr, urea, sodium Na, potassium K, chloride Cl) and left ventricular ejection fraction (EF); (3) Nutritional risk score: the most recent preoperative NRS2002 score; (4) Observation endpoint: clinical outcome 1 year after heart transplantation, including survival and death. (5) Predictive methods: Prognostic Nutrition Index (PNI), Albumin-Cretin Ratio (ACR), Albumin-Bilirubin Score (ALBI), Modified End-Stage Liver Disease Model Score (MELD-XI), and Leukocyte-Albumin Ratio (LAR).

[0054] 4.3 Nutritional Risk Screening: Collect the most recent NRS2002 score before surgery. NRS2002 total score (0-7 points) = disease severity score (0-3 points) + nutritional status impairment score (0-3 points) + age score (0-1 points). A total score ≥3 points indicates that the patient has nutritional risk and requires nutritional support; a total score <3 points indicates that the patient does not have nutritional risk and should be rescreened one week later.

[0055] 4.4 Observation endpoint: Clinical outcome (survival / death) 1 year postoperatively.

[0056] 4.5 Prediction methods and formulas: (1) Prognostic Nutrition Index (PNI) = albumin + 5 × lymphocyte count; (2) Albumin-creatinine ratio (ACR) = albumin / creatinine; (3) Albumin-bilirubin score (ALBI) = 0.66 × lg bilirubin - 0.085 × albumin; (4) Modified end-stage liver disease model score (MELD-XI) = 5.11 × ln bilirubin + 11.76 × ln creatinine + 9.44; (5) Leukocyte-albumin ratio (LAR) = leukocytes / albumin.

[0057] 5. Statistical methods

[0058] Data statistics were performed using the professional statistical software R 4.3.2.

[0059] 5.1 Descriptive analysis: Normally distributed continuous data are described by mean ± standard deviation, non-normally distributed data are described by median (interquartile range), and categorical data are described by count (percentage).

[0060] 5.2 Intergroup comparisons: Independent samples t-test was used for normally distributed continuous data, Mann-Whitney U test was used for non-normally distributed data, and chi-square test was used for categorical data.

[0061] 5.3 Correlation and Collinearity: Pearson correlation analysis was used for continuous variables and Spearman rank correlation analysis was used for categorical variables. Variance inflation factor was used to evaluate collinearity analysis.

[0062] 5.4 Predictive efficacy analysis: Receiver operating characteristic (ROC) curves were plotted, and the area under the curve (AUC), optimal cutoff value, sensitivity, and specificity were calculated. The model's calibration was assessed using calibration curves and the Hosmer-Lemeshow goodness-of-fit test. The clinical applicability of the model was evaluated using decision curve analysis (DCA) and clinical impact curve (CIC). The AUC was compared with prediction methods such as PNI, ACR, ALBI, and MELD-XI.

[0063] II. Results

[0064] 1. Comparison of follow-up completion status and baseline characteristics between groups after heart transplantation:

[0065] Based on pre-defined inclusion and exclusion criteria, this retrospective study included 92 patients with dilated cardiomyopathy (DCM) who underwent heart transplantation at Shanghai Changhai Hospital between January 2017 and December 2022. Patients were divided into a follow-up completion group (n=84) and a loss-to-follow-up group (n=8) based on their completion of the 1-year follow-up. The average age of patients in the follow-up completion group was 47.9 ± 13.1 years, with 75 males (89.3%) and 9 females (10.7%). The average age of patients in the loss-to-follow-up group was 49.0 ± 13.9 years, with 6 males (75.0%) and 2 females (25.0%). Comparison of demographic data (sex, age, etc.) and clinical characteristics between the groups showed no statistically significant difference (P>0.05), indicating that the loss-to-follow-up event did not significantly bias the baseline representativeness of the sample. Specific results are shown in Table 1 below. Table 1. Comparison of baseline data between the survival and death groups.

[0066]

[0067]

[0068] Note: Body Mass Index (BMI); Hemoglobin (Hb); Red Blood Cells (RBC); White Blood Cells (WBC); Platelets (PLT); Lymphocytes (L); Albumin (ALB); Globulin (GLB); Albumin-to-Globulin Ratio (AGR); Total Protein (TP); Prealbumin (PA); Total Bilirubin (TBIL); Total Bile Acids (TBA); Alanine Aminotransferase (ALT); Aspartate Aminotransferase (AST); Lactate Dehydrogenase (LDH); Alkaline Phosphatase (ALP); Gamma-Glutamate Transferase (GGT); Creatinine (Cr); Ejection Fraction (EF).

[0069] 2. Comparison of demographic data and clinical characteristics between the survival group and the death group

[0070] Eighty-four patients with dilated cardiomyopathy who underwent heart transplantation and completed follow-up were divided into a survival group (n=70) and a death group (n=14) based on their clinical outcomes one year post-transplantation (Table 2). The average age of patients in the survival group was 47.9 ± 13.9 years, with 64 males (91.4%) and 6 females (8.6%). The average age of patients in the death group was 48.1 ± 8.2 years, with 11 males (78.6%) and 3 females (21.4%).

[0071] Intergroup comparisons showed that the survival group had significantly higher lymphocyte counts, albumin levels, prealbumin levels, and albumin-to-globulin ratio than the death group, specifically: lymphocyte count 1.6±0.8 vs 1.1±0.5; albumin 38.0 (36.0, 42.0) vs 34.5 (32.5, 40.8); prealbumin 221.0±72.2 vs 162.4±65.3; and albumin-to-globulin ratio 1.5 (1.3, 1.6) vs 1.3 (1.2, 1.3). Conversely, the survival group had significantly lower NRS2002 scores and a significantly lower proportion of patients at nutritional risk than the death group, specifically: NRS2002 score 1.0 (1.0, 3.0) vs 3.5 (1.0, 6.0); and a proportion of patients at nutritional risk 18 (25.7%) vs 8 (57.1%). All these differences were statistically significant (P<0.05).

[0072] In addition, there were no statistically significant differences between the two groups in terms of age, height, weight, BMI, hemoglobin, red blood cells, white blood cells, platelets, globulin, total protein, total bilirubin, total bile acids, alanine aminotransferase, aspartate aminotransferase, lactate dehydrogenase, alkaline phosphatase, gamma-glutamyl transferase, creatinine, urea, sodium, potassium, chloride, left ventricular ejection fraction, and gender composition (p>0.05).

[0073] Table 2. Comparison of baseline characteristics of heart transplant patients in the survival and death groups.

[0074]

[0075]

[0076] Body Mass Index (BMI); Hemoglobin (Hb); Red Blood Cells (RBC); White Blood Cells (WBC); Platelets (PLT); Lymphocytes (L); Albumin (ALB); Globulin (GLB); Albumin-to-Globulin Ratio (AGR); Total Protein (TP); Prealbumin (PA); Total Bilirubin (TBIL); Total Bile Acids (TBA); Alanine Aminotransferase (ALT); Aspartate Aminotransferase (AST); Lactate Dehydrogenase (LDH); Alkaline Phosphatase (ALP); Gamma-Glutamate Transferase (GGT); Creatinine (Cr); Ejection Fraction (EF).

[0077] 3. Predictive value of prealbumin, total bile acids, and NRS2002 score for heart transplantation prognosis in DCM patients.

[0078] Correlation analysis of prealbumin (PA), total bile acids (TBA), and NRS2002 score showed no significant correlation between PA and TBA, or between TBA and NRS2002 score (P>0.05), but a low negative correlation between PA and NRS2002 score (r=-0.31, P<0.05). Figure 2 ).

[0079] With clinical outcome as the dependent variable, the three independent variables, PA, TBA and NRS2002 scores, were tested for collinearity. The results showed that the variance inflation factor (VIF) of all three variables was <10, indicating that only weak collinearity existed among the variables (Table 3).

[0080] Table 3 Correlation analysis of PA, TBA and NRS2002

[0081]

[0082] After excluding the effects of strong correlation and strong collinearity, PA, TBA, and NRS2002 scores were included in a multivariate logistic regression model to predict poor prognosis after heart transplantation in patients with dilated cardiomyopathy. Results showed that low PA (β=-0.02, OR=0.98, 95%CI: 0.97-1.00, P=0.023), high TBA (β=0.07, OR=1.07, 95%CI: 1.02-1.13, P=0.005), and high NRS2002 score (β=0.45, OR=1.57, 95%CI: 1.07-2.39, P=0.025) were independent risk factors for poor postoperative outcomes in these patients (Table 4).

[0083] Table 4 Logistic regression analysis of PA, TBA, and NRS2002

[0084]

[0085] The ROC curve shows that the AUC of the prediction model combining PA, TBA, and NRS2002 scores is 0.885 (95% CI: 0.802–0.967), while the AUCs of PA, TBA, and NRS2002 scores predicted individually are 0.780 (95% CI: 0.662–0.918), 0.664 (95% CI: 0.494–0.835), and 0.718 (95% CI: 0.565–0.872), respectively, all lower than the combined prediction model. Figure 3 ).

[0086] 4. Construction of a novel nutritional prognostic algorithm for heart transplantation in patients with dilated cardiomyopathy

[0087] Based on the prealbumin (PA), total bile acid (TBA), and NRS2002 score β values ​​in multivariate logistic regression analysis, this invention constructs a novel nutritional prognostic algorithm for the prognosis of heart transplantation in patients with dilated cardiomyopathy, named CDHTNPI (Changhai DCM patient Heart Transplantation Nutrition Prognostic Index). The calculation formula is as follows: ,

[0088] Where a represents prealbumin level (unit: mg / L), b represents total bile acid level (unit: mg / L), and c represents NRS2002 score.

[0089] ROC curve analysis showed that the optimal cutoff value for CDHTNPI in predicting poor prognosis in heart transplant patients was 0.121, corresponding to a sensitivity of 72.9% and a specificity of 92.9%. Figure 4 To facilitate clinical application, this study also presents the algorithm in the form of a visual Norman diagram. Figure 5 ).

[0090] 5. Evaluation of the predictive ability of the prognostic algorithm CDHTNPI

[0091] Multivariate logistic regression analysis showed that the C-index of CDHTNPI was 0.885, indicating good predictive efficacy for adverse outcomes after heart transplantation in patients with dilated cardiomyopathy (Table 4). Calibration curve analysis showed that the absolute error between the predicted and actual outcomes was 0.049, indicating strong consistency between the two. Figure 6 The Hosmer-Lemeshow goodness-of-fit test results were χ²=6.134, P=0.632>0.05, indicating that the model passed the goodness-of-fit test, the difference between the predicted values ​​and the true values ​​was not statistically significant, and the fitting effect was ideal (Table 5).

[0092] Table 5 HL fit analysis of the CDHTNPI model

[0093] χ² df P 6.134 8 0.632

[0094] Clinical decision curve (DCA) analysis shows that when the threshold probability is in the range of 0.04–0.94, making clinical decisions based on CDHTNPI can yield a net benefit. Figure 7 Clinical impact curve (CIC) analysis showed that when the threshold probability > 0.50, the algorithm's predicted outcome highly matched the actual outcome. Figure 8 ).

[0095] 6. Comparison of the prognostic algorithm CDHTNPI with other prediction methods

[0096] ROC curves were plotted to compare the predictive efficacy of CDHTNPI with other reported predictive methods. The results showed that the AUC of CDHTNPI was 0.885 (0.802-0.967), significantly higher than other predictive methods, including the nutritional prognostic index (AUC=0.729, 95% CI: 0.581-0.876), albumin-creatinine ratio (AUC=0.614, 95% CI: 0.421-0.806), albumin-bilirubin score (AUC=0.703, 95% CI: 0.530-0.875), modified end-stage liver disease model score (AUC=0.624, 95% CI: 0.437-0.810), and leukocyte-to-albumin ratio (AUC=0.595, 95% CI: 0.410-0.781). The above results suggest that CDHTNPI has a better predictive ability for the prognosis of heart transplantation in patients with dilated cardiomyopathy than other existing nutrition-related predictive methods. Figure 9 ).

[0097] III. Discussion of Results

[0098] This study innovatively explored the predictive value of combined PA, TBA, and NRS2002 scores for adverse outcomes after heart transplantation in patients with dilated cardiomyopathy (DCM), and constructed a novel nutritional prognostic algorithm, CDHTNPI, for heart transplantation in DCM patients. Key results showed that low PA, high TBA, and high NRS2002 scores were independent risk factors for adverse outcomes after heart transplantation in DCM patients, and elevated CDHTNPI was significantly associated with an increased risk of death at 1 year post-transplantation.

[0099] The CDHTNPI integrates three clinically readily available indicators: PA, TBA, and NRS2002 score. Its predictive power (C-index = 0.885) is significantly superior to existing predictive tools (such as prognostic nutritional index, albumin-creatinine ratio, albumin-bilirubin score, etc.). According to clinical decision criteria (C-index > 0.70 indicates that the model has clinical application value), CDHTNPI has important clinical significance in the individualized assessment of the 1-year mortality risk after heart transplantation in patients with diabetic cerebral palsy (DCM), and can provide a practical tool for clinical diagnosis and prognostic assessment.

[0100] This study is the first to focus on the association between protein glycoprotein (PA) and heart transplantation prognosis, showing that low PA is a risk factor for adverse postoperative outcomes. Existing research has largely focused on patients with end-stage heart failure, finding that the incidence of low PA (serum level <150 mg / L) ranges from 23.9% to 36.0%, consistent with the 25.0% incidence in this study. As a negative acute-phase protein synthesized by the liver, the decrease in PA levels is closely related to a shift in the priority of liver protein synthesis under inflammatory stress (from negative acute-phase proteins to positive acute-phase proteins, such as CRP). Furthermore, PA's short half-life and independence from intestinal protein loss allow it to more accurately reflect the patient's true nutritional status and the effectiveness of nutritional support. End-stage diabetic cerebral palsy (DCM) patients often experience high inflammation and reduced food intake due to intestinal congestion, which may be the main cause of low PA, suggesting that PA can serve as a sensitive indicator for assessing the patient's nutritional-inflammatory status and prognosis.

[0101] Based on the "gut microbiota-bile acid-cardiovascular receptor axis" theory, abnormal TBA metabolism plays an important role in cardiovascular disease. Hydrophobic bile acids (such as lithocholic acid) can induce myocardial hypertrophy and apoptosis, while hydrophilic bile acids (such as ursodeoxycholic acid) have cardioprotective effects. Furthermore, the gut microbiota metabolite trimethylamine oxide (TMAO) can exacerbate heart failure by inducing myocardial hypertrophy and mitochondrial dysfunction. Abnormally elevated TBA levels may further worsen myocardial damage by synergistically activating inflammatory pathways through TMAO. In this study, high TBA levels were associated with adverse postoperative outcomes, supporting TBA as a potential biomarker for prognostic assessment in heart transplantation.

[0102] This study used the NRS2002 score and found that the preoperative nutritional risk rate was as high as 31%, and patients with high scores had a significantly increased risk of postoperative mortality, consistent with the conclusion that "increased nutritional risk exacerbates postoperative mortality after heart transplantation." The NRI, developed in 1991 by the Veterans Affairs Parenteral Nutrition Research Collaboration Group, is used to evaluate the nutritional status of patients before clinical thoracic surgery, assessing serum albumin concentration and percentage weight loss. However, the NRI cannot identify patients with weight deviations due to recent dietary changes or edema, while the NRS2002 score incorporates both disease severity and nutritional status, making it more suitable for DCM patients with severe heart failure (accompanied by gastrointestinal edema and reduced food intake).

[0103] This study also observed that the preoperative albumin level in the survival group was significantly higher than that in the death group, consistent with previous findings. End-stage heart failure patients experience decreased albumin levels due to persistent inflammation, liver and kidney dysfunction, protein-losing enteropathy, and hemodilution; low albumin is a risk factor for poor prognosis in heart transplantation. Kato et al. further confirmed that patients with preoperative albumin ≥3.5 g / dL had a significantly lower 1-year mortality rate post-surgery, and for every 1 g / dL increase in albumin, the risk of death decreased by 54%, suggesting that albumin can serve as a supplementary assessment indicator for CDHTNPI.

[0104] This study did not find any association between age, BMI, or sex and post-heart transplant mortality, which differs from some previous studies and may be related to the small sample size (84 cases). Regarding age, the International Heart and Lung Transplantation Society registry study showed that both advanced and underage recipient age increased post-operative mortality, and advanced donor age was also a risk factor, but donor-recipient age differences had no significant impact. Regarding weight, organ transplant registry data suggested that a BMI >30 kg / m² or too low increased post-operative mortality, and excessive weight loss (>10%) while waiting for transplantation may also increase risk, while pre-transplant weight loss surgery may improve prognosis. Regarding sex, existing studies generally believe that recipient sex does not affect prognosis, but donor-recipient sex mismatch may increase risk due to immune rejection or organ size differences.

[0105] Due to the severe shortage of heart transplant donors and the high complexity of surgical procedures, data shows that on average, each medical institution can only perform about 19 heart transplant surgeries per year, which limits the sample size for related studies. Against this backdrop, this study has the following limitations: the sample size is relatively limited, which may affect the stability of the statistical analysis and the extrapolation of the conclusions; the included variables are not comprehensive enough, failing to include donor-related information (such as donor age, heart weight, ischemia time, etc.), while donor factors are important variables affecting the prognosis of heart transplantation.

[0106] Four conclusions

[0107] The novel cardiac transplant nutritional prognostic system (CDHTNPI) developed in this invention demonstrates significantly superior efficacy compared to other existing predictive methods (such as the prognostic nutritional index and albumin-creatinine ratio) in predicting the prognosis of patients with dilated cardiomyopathy one year after heart transplantation. This algorithm can serve as a reliable tool in clinical practice for assessing the risk of adverse postoperative outcomes, providing important reference for optimizing individualized treatment strategies for transplant-bound patients (such as preoperative nutritional intervention) and improving organ allocation plans, thus contributing to enhancing the accuracy and rationality of cardiac transplantation diagnosis and treatment.

[0108] The undescribed parts of this invention are the same as or implemented using existing technology. The applicant declares that this invention is illustrated through the above embodiments, but the invention is not limited to the above detailed methods, i.e., it does not mean that the invention must rely on the above detailed methods to be implemented. Those skilled in the art should understand that any improvements to this invention, equivalent substitutions of raw materials for the product of this invention, additions of auxiliary components, and selection of specific methods all fall within the protection and disclosure scope of this invention.

Claims

1. A nutritional prognostic analysis system for heart transplant patients with dilated cardiomyopathy, characterized in that, The analysis module analyzes prealbumin (PA), total bile acids (TBA), and NRS2002 scores, and identifies low PA, high TBA, and high NRS2002 scores as adverse postoperative outcomes.

2. The nutritional prognostic analysis system for heart transplant patients with dilated cardiomyopathy according to claim 1, characterized in that, The adverse postoperative outcome refers to an increased risk of death within 1 year postoperatively.

3. The nutritional prognostic analysis system for heart transplantation in patients with dilated cardiomyopathy according to claim 1, characterized in that, The analysis module uses the following algorithm to individually assess the 1-year mortality risk of DCM patients after heart transplantation:

4. Among them, a represents the prealbumin level in mg / L, b represents the total bile acid level in mg / L, and c represents the NRS2002 score.

5. The nutritional prognostic analysis system for heart transplant patients with dilated cardiomyopathy according to claim 1, characterized in that, The cutoff value for CDHTNPI is 0.

121.

6. The nutritional prognostic analysis system for heart transplantation in patients with dilated cardiomyopathy according to claim 1, characterized in that, It also includes an input display module, which is used to input the patient's basic information and the corresponding prealbumin, total bile acid and NRS2002 score values, and to display the judgment results.

7. The application of the nutritional prognostic analysis system for heart transplantation in patients with dilated cardiomyopathy as described in any one of claims 1 to 5 in predicting the risk of death 1 year after heart transplantation in patients with dilated cardiomyopathy.

8. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it performs the functions of the system as described in any one of claims 1 to 6.

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