Prediction of Heart Failure in Type 2 Diabetes Mellitus Subjects Using Machine Learning: A Cross-Sectional Study

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Alake, Oluboyo Adeola O Oluboyo, Odewusi Odeyinka O. Odewusi This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3971385/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract The concomitance of Type 2 Diabetes Mellitus (T2DM) and heart failure has made scientists investigate ways the onset of heart failure in T2DM can be predicted. Machine learning techniques have been shown to help with the prediction of heart disease and several model algorithms have been affirmed as good. This study aimed at predicting heart failure in T2DM subjects using machine learning techniques. A total of 123 blood samples from 59 healthy subjects without T2DM (controls) and 63 T2DM subjects (tests) were analyzed for biochemical parameters [troponin (TnI), electrolytes, Lactate dehydrogenase (LDH), Aspartate aminotransferase (AST), Alanine transaminase (ALT), AST/ALT ratio, Creatinine phosphokinase (CK-MB), Fasting Blood Sugar (FBS), Cholesterol, Triglyceride, B-Natriuretic peptide (BNP)] using standard procedures. Demographic data and biochemical results were all subjected to machine learning algorithms. The results of ML showed that the Random Forest algorithm is the best model for heart failure prediction with 87% accuracy. SHAP value (impact on model output) among all possible combinations identified glucose (FBG), BNP, Systolic and diastolic blood pressure, and waist circumference as important features in the prediction of heart failure in T2DM. The permutation importance score of the features studied showed systolic BP, BNP, MUAC and troponin I in this order to have the highest positive importance to the prediction of heart failure in T2DM. Height, weight, and waist circumference have small negative importance values meaning they slightly decrease model performance. The study concluded that CK-MB, BNP, and troponin I alone may not be early indicators of heart failure in T2DM subjects. However, subjecting them to ML and combining them with the key features identified would make prediction better. Machine learning Heart Failure Type 2 Diabetes Mellitus Prediction BNP Random Forest Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 INTRODUCTION It is no longer news that there is a surge in the prevalence of diabetes around the world. Over the years, it has also been observed that the most popular type of diabetes among older adults is type 2 diabetes and it is now a menace to global health in this 21st century coupled with its increased popularity among the younger population (WHO, 2021). The global prevalence of T2DM among adults aged 20 to 79 is 537 million (10.5%), and by 2045, it is expected to rise to 783 million (12%), according to the 2021 International Diabetes Federation (IDF) study (Sun et al., 2022 ). In Africa, 24 million individuals live with T2DM in 2021 (Adamu et al., 2023 ). According to projections, this figure will rise by 129% to 55 million by 2045 (Sun et al., 2022 ). The prevalence of Type 2 DM in Nigeria has been reported as 3.9% that is, 3.9 million adults, aged 20–79 years have type 2 diabetes (IDF, 2019). Congestive Heart Failure (CHF), as defined by the American College of Cardiology (ACC) and the American Heart Association (AHA), is "a complex clinical syndrome that results from any structural or functional impairment of ventricular filling or ejection of blood.” CHF is a common disorder worldwide with a high morbidity and mortality rate. With an estimated prevalence of 26 million people worldwide, CHF contributes to increased healthcare costs, reduces functional capacity, and significantly affects quality of life. Diagnosing and effectively treating the disease is imperative to prevent recurrent hospitalizations, decrease morbidity and mortality, and enhance patient outcomes (Heidenreich et al ., 2022). Diabetes has been identified as an important risk factor for Heart Failure (HF), others being age and obesity (Groenewegen et al. , 2020). HF often manifests as the first cardiovascular (CV) event in people with type 2 diabetes (T2D) (Birkeland et al., 2020 ). Even individuals with pre-diabetes, as defined by the criteria of the World Health Organization (WHO) and the American Diabetes Association (ADA), are at a 9–58% greater risk of developing HF (Cai et al., 2021 ). Artificial intelligence (AI), the imitation of human cognition by technology, can guide clinical care and decision-making without human involvement in the process. One sub-field of AI is ML, which allows computers to evaluate data beyond programmatic algorithms, identify patterns within data, map learned patterns to unseen data, and improve the performance of computational tasks beyond human capabilities (Rajkomar et al., 2019 ). In HF, ML has demonstrated its superiority in mortality prediction compared to the benchmark models (Shin et al., 2021 ; König et al. , 2021; Negassa et al., 2021 ; Jing et al., 2020 ). Preventive CV medicine increasingly implements modeling techniques to estimate the individual's absolute risk of a CV event. Modern ML techniques extract useful patterns from large datasets to answer clinical questions and have demonstrated significant promise for risk stratification across various populations (Ross et al. , 2021; Cho et al., 2021 ). ML can help in identifying predictors and relationships between them that may not be identified by traditional models (Ward et al., 2020 ), thus new risk factors may emerge (Nabrdalik et al. , 2023). Recently, several studies have been undertaken on the subject of disease prediction, and some physicians are now using machine-learning models to forecast various diseases (Modern, 2019 ; Kaur & Kumari, 2020; Pradhan et al., 2020 ). So, it is essential to create a diabetes classifier that is practical, reliable, and economical. Most importantly, one that can predict the development of heart failure in diabetic patients. This research will contribute immensely to the body of knowledge specifically the Nigerian health sector and the African health sector at large by predicting and reducing the comorbidity of heart failure in diabetic patients, mortality, and rate of complications of diabetes. Data generated from this study will also be highly instrumental for further studies on predictive model building. METHODOLOGY Study Area This study was carried out in Oba Adejuyigbe General Hospital and Primary Health Care, Okeyinmi, Ado-Ekiti Study Design The study employed a case-control research design. Ethical Approval Ethical approval was collected from the Ethics Committee, College of Medicine and Health Sciences, Afe Bablola University, Ado Ekiti, Nigeria. Informed consent was obtained from all participants before the commencement of the study Sample Size Determination The sample size (N) was calculated using Fisher’s formula (Safranek, 2018) n=z2p(1−p) / d 2 Where: N = the desired sample size (when the population is greater than 10,000) Z = is a constant given as 1.96 (or more samples at 2.0) which corresponds to the 95% confidence level. p = prevalence (3.9%) (IDF, 2021) q = 1.0 – p d = acceptable error (5%) However, 123 participants were recruited for this study; comprising of 59 apparently healthy subjects without T2DM (controls) and 63 T2DM subjects (tests). Inclusion and Exclusion Criteria The inclusion criteria for this study are non-pregnant and non-lactating women, those who gave their consent, and those within the age range of 20-95 years. The exclusion criteria for this study are pregnant women, nursing mothers, and, those who did not give their consent. Sample Collection and Statistical Analysis 5ml of blood was collected from all subjects into a lithium heparin tube and fluoride oxalate tube via venipuncture. Fasting blood glucose was analyzed immediately. Electrolytes were estimated using an ion-selective electrode (ISE). BNP and Troponin I were determined using Enzyme-Linked Immunosorbent Assay (ELK Biotechnology) according to the manufacturer’s instructions. Lactate dehydrogenase (LDH), Aspartate aminotransferase (AST), Alanine transaminase (ALT), Creatinine phosphokinase (CPK), Fasting blood sugar (FBS), Total Cholesterol, and triglyceride were quantified using the enzymatic rate method following the manufacturer’s direction. Machine Learning Analysis Dataset related to previously published datasets where reported conventional risk factors like age, glycemic parameters, lipid profile, and demographic data were built. However, additional biochemical parameters were added (biomarkers of heart failure inclusive). In this present study, the dataset consists of 123 samples with 34 attributes. Data preprocessing was done by Label encoding. Lemmatization was used to transform the data into a categorical variable and grouping categories was created using factorize to group the Dataset into T2DM patients and non-T2DM patients. The T2DM subject group was Labeled 1 while non-T2DM subjects were labeled 0. Following this, the data were thoroughly checked for missing values as well as incorrect values which impact the quality of the model. To reduce the influence of missing values as well as incorrect values on the model performance the means from the data was applied. Following data preprocessing, various machine learning classification models such as K-nearest neighbors (K-NN), Logistic Regression (LR), Support Vector Machine (SVM), Linear Discriminant Analysis (LDA), Classification and Regression Trees (CART), Naive Bayes (NB), and Random Forest were applied to the dataset and implemented in Python language. To carry out the ML analysis the data was split into training (70%), validation (20%) and test sets (30%). SHAP framework (shap 0.37.0 version) for interpreting additive feature importance in an ensemble Random Forest model. SHAP is a cutting-edge method that explains predictions made by complex ML and DL models (Christoph, 2019). The SHAP values explain the relative contribution of each feature in ML model prediction (Jangili et al ., 2023). To assess the predictive power of these models we have considered the confusion matrix which provides Precision, Accuracy, F1 score and Recall. The “confusion_matrix” function from the Python library “sklearn. metrics”, is used for model evaluation (Pedregosa et al ., 2011). This Python function takes actual and predicted values as inputs to obtain a confusion matrix. RESULTS A total of 123 subjects were recruited in this study: 59 diabetes subjects and 63 non-diabetes subjects. Table 4.1 shows the demographic characteristics of the subjects studied. Table 4.2 shows the accuracy of classification models. Table 4.3 shows the 5-fold cross-validation scores for different machine learning models for predicting heart failure in diabetes patients. Table 4.4 shows the predictive performance of the Random Forest model. Table 4.5 shows the permutation importance scores for features from a Random Forest classifier model predicting heart failure in type 2 diabetes patients. Figure 4.1 shows ROC (Receiver Operating Characteristic) curves for multiple machine learning algorithms. Figure 4.2 shows a confusion matrix showing the performance of a Random Forest classification model for the prediction of heart failure in type 2 diabetes patients. Figure 4.3 shows the ROC and AUC of Random Forest. Figure 4.4 shows the SHAP plot bar () of features that increase and decrease model output. Figure 4.5 shows the bee swarm plot of each feature to visualize the SHAP values. Figure 4.6: Shap plot bar () showing the overall impact of features on model output Table 4.1: Demographic Characteristics of the Subjects Variable Frequency Percent (%) Gender Male Female 11 39 22.00% 78.00% Age (years) <50 51 – 60 61 & above 10 19 21 20.00% 38.00% 42.00% Marital status Married Widowed 7 43 14.00% 86.00% Educational status Tertiary Secondary No formal 35 12 3 70.00% 24.00% 6.00% Occupation Civil servants Entrepreneurs Retired 31 14 5 62.00% 28.00% 10.00% Religion Christian Islam 43 7 86.00% 14.00% Table 4.2 Accuracy of classification models Table 4.3: 5-fold Cross-validation scores for models MODELS MEAN CROSS-VALIDATION SCORE STANDARD DEVIATION Linear Regression 0.825000 0.144482 Linear Discriminant Analysis 0.777500 0.242629 k-nearest neighbor 0.675000 0.256174 Decision Tree 0.732500 0.218103 Naive Bayes 0.842500 0.164526 Support Vector Machine 0.502500 0.222191 Random Forest Classifier 0.837500 0.190312 Table 4.4: Predictive performance of the Random Forest model PRECISION RECALL F1-SCORE SUPPORT CLASS 0 0.83 0.95 0.88 20 CLASS 1 0.93 0.78 0.85 18 OVERALL ACCURACY 0.87 38 MACRO AVG 0.88 0.86 0.87 38 WEIGHTED AVG 0.88 0.87 0.87 38 TABLE 4.5: The permutation importance scores for features from a Random Forest classifier model predicting heart failure in type 2 diabetes patients. DISCUSSION This present study used a multi-marker approach to predict heart failure in T2DM subjects via machine learning techniques. The anthropometric data (age, systolic blood pressure, diastolic blood pressure, weight, height, MUAC, waist circumference) and biochemical data namely fasting blood glucose, CK-MB, Troponin, and BNP were subjected to 18 model algorithms and the random forest classifier was identified as the best model to predict heart failure accurately (Accuracy = 87%). Several studies have also reported that a random forest is a useful tool in the identification of important predictors from a mixture of variables, Yuan et al (2019) reported the random forest as the best algorithm that can predict heart failure using four cardiac biomarkers, namely, BNP, sST2, Gal-3, and CK-MB (Yuan et al ., 2019). Random forest was also used to rank the importance of the biomarkers used. Kavitha et al (2021) in their study discovered that random forest (Accuracy = 81%) and hybrid model (random forest and decision tree) are good algorithms for the prediction of heart disease. Jangili et al ., (2023), reported in their study that random forest (Accuracy = 76%) is a good predictor of T2DM, coronary artery diseases, and risk factors for the occurrence of each condition. It's worthy of note that Jangili et al (2023) used age, glycemic parameters, lipid profile, 27 traditional cytokines and 10 metabolic hormones, 3 adipokines, and 6 apo-lipoproteins. Ansari et al (2023), also found random forests as a good model for the prediction of heart disease (Accuracy = 99%) (Ansari et al ., 2023). All these studies and more have identified the random forest classifier model as a good algorithm for predicting heart failure (disease) and this corroborates the result of this study. To classify patients and identify predictors, random forests were employed, which is a novel method that develops numerous decision trees, by which the accuracy of the predictors was tested. The random forest classifier operates by building a set of decision trees. At each node in the trees, a random subset of the predictor variables is randomly selected and considered as split candidates (Yuan et al ., 2019). The dataset was repeatedly divided into subtrees, assessing predictor variables by importance based on the change in the classification error affected by its presence or absence in the subset. Furthermore, the random forests also combine the predictions of multiple decision trees, improving the power of the algorithm (Sylvester et al., 2017). SHAP value (impact on model output) among all possible combinations identified glucose (FBG), BNP, Systolic and diastolic blood pressure, and waist circumference as important features in the prediction of heart failure in T2DM. The permutation importance score of the 12 features studied shows the effect that each feature would have on the performance of the model when reshuffled. Systolic BP, BNP, MUAC, and troponin I in this order have the highest positive importance to the prediction of heart failure in T2DM. Height, weight, and waist circumference have small negative importance values meaning they slightly decrease model performance. This means that the most useful predictor of heart failure based on the RF model in this dataset is systolic blood pressure. There are a few limitations in this study. First, this is a cross-sectional study with a relatively small size that was performed in multi-centers and the generalizability of these results (in another site) is yet to be carried out. Second, this study focused on three cardiac markers (CK-MB, BNP, Troponin I) among the several other cardiac markers (Gal-3, sST2, etc.) and other biomarkers involved in the pathophysiology of HF such as oxidative stress markers, renal salt, and water retention. CONCLUSION The present study is the first to provide a framework for the exploration of the random forest algorithm in the prediction of heart failure. This study provided supporting evidence that with Systolic BP, BNP, MUAC and troponin I, an accurate predictive model for the biochemical prediction of heart failure in T2DM subjects can be built. The random forest algorithm was once again proven to have the ability to provide relevant information about the importance of different biomarkers and anthropometric variables. However, this needs further investigation. Abbreviations FBS – Fasting blood sugar CK-MB – Creatinine Phosphokinase BNP – B natriuretic Peptide sSt2 - soluble suppression of tumorigenesis-2 Gal-3 – Galectin 3 HF – Heart Failure RF – Random Forest MUAC – Mid Upper arm Circumference T2DM – Type 2 Diabetes Mellitus ROC – Receiver Operating Characteristic AUC – Area Under Curve SHAP - BMI – Body Mass Index ML – Machine learning KNN - K-nearest neighbors LR - Logistic Regression SVM - Support Vector Machine LDA - Linear Discriminant Analysis CART - Classification and Regression Trees NB - Naive Bayes Declarations Ethics approval and consent to participate Ethical approval was collected from the Ethics Committee, College of Medicine and Health Sciences, Afe Babalola University, Ado Ekiti, Nigeria. Informed consent was obtained from all participants before the commencement of the study. Consent for publication Not applicable. Availability of data and materials Data available from the corresponding author on reasonable request Competing interests None declared Funding None Author’s contributions All auth Acknowledgments References Adamu, U. G., Mpanya, D., Patel, A., & Tsabedze, N. (2023). Beyond HbA1c cardiovascular protection in type 2 diabetes mellitus. Journal of Endocrinology, Metabolism, and Diabetes of South Africa , 28 (1), 7-13. Ansari, G. A., Bhat, S. S., Ansari, M. D., Ahmad, S., Nazeer, J., & Eljialy, A. E. M. (2023). Performance Evaluation of Machine Learning Techniques (MLT) for Heart Disease Prediction. Computational and Mathematical Methods in Medicine , 2023 . Birkeland, K. I., Bodegard, J., Eriksson, J. W., Norhammar, A., Haller, H., Linssen, G. C., ... & Kadowaki, T. (2020). Heart failure and chronic kidney disease manifestation and mortality risk associations in type 2 diabetes: a large multinational cohort study. Diabetes, obesity and metabolism , 22 (9), 1607-1618. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3971385","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":274281014,"identity":"e05f47a8-7d72-41c6-a07a-9af4d22548d0","order_by":0,"name":"Alake Oluwapelumi A. 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Odewusi","email":"","orcid":"","institution":"Afe Babalola University","correspondingAuthor":false,"prefix":"","firstName":"Odewusi","middleName":"Odeyinka O.","lastName":"Odewusi","suffix":""}],"badges":[],"createdAt":"2024-02-20 02:31:48","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3971385/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3971385/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":51538992,"identity":"c6579f06-6ae1-4cbb-ab90-fdf340a7f31c","added_by":"auto","created_at":"2024-02-23 10:37:50","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":907971,"visible":true,"origin":"","legend":"\u003cp\u003eFIGURE 4.1: ROC (Receiver Operating Characteristic) curves for multiple machine learning algorithms\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-3971385/v1/cbf8f034137fd208b283a66c.png"},{"id":51538411,"identity":"c61f091a-3dd3-4936-bcbe-8d72a86d4f27","added_by":"auto","created_at":"2024-02-23 10:29:50","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":78489,"visible":true,"origin":"","legend":"\u003cp\u003eFIGURE 4.2: A confusion matrix showing the performance of a Random Forest classification model for the prediction of heart failure in type 2 diabetes patients.\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-3971385/v1/78b8cc160a1cacd5bab70ac9.png"},{"id":51538412,"identity":"56e1cd7a-d911-4454-a796-c822fc54ad4c","added_by":"auto","created_at":"2024-02-23 10:29:50","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":165040,"visible":true,"origin":"","legend":"\u003cp\u003eFIGURE 4.3: ROC \u0026amp; AUC of Random Forest Classifier\u003c/p\u003e","description":"","filename":"floatimage7.png","url":"https://assets-eu.researchsquare.com/files/rs-3971385/v1/58b3276a7245628f475611c4.png"},{"id":51538413,"identity":"ef0b6762-8413-4a57-b96d-c501717b8c6d","added_by":"auto","created_at":"2024-02-23 10:29:50","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":592875,"visible":true,"origin":"","legend":"\u003cp\u003eFIGURE 4.4: SHAP plot bar () showing features that increase and decrease model output\u003c/p\u003e","description":"","filename":"floatimage8.png","url":"https://assets-eu.researchsquare.com/files/rs-3971385/v1/775f1c9d52d183b30bcad102.png"},{"id":51538416,"identity":"c7b0dbc9-e5da-42ce-8629-bf276065fb39","added_by":"auto","created_at":"2024-02-23 10:29:50","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":699324,"visible":true,"origin":"","legend":"\u003cp\u003eFIGURE 4.5: The bee swarm plot to visualize the SHAP values for each feature\u003c/p\u003e","description":"","filename":"floatimage9.png","url":"https://assets-eu.researchsquare.com/files/rs-3971385/v1/c27b0b5c6cc3723af6fb0c36.png"},{"id":51538415,"identity":"d5770ba5-fa1a-4328-bbc1-57a9a69d393c","added_by":"auto","created_at":"2024-02-23 10:29:50","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":661131,"visible":true,"origin":"","legend":"\u003cp\u003eFIGURE 4.6: Shap plot bar () showing the overall impact of features on model output\u003c/p\u003e","description":"","filename":"floatimage10.png","url":"https://assets-eu.researchsquare.com/files/rs-3971385/v1/edde656a3394a5eadcbd313d.png"},{"id":51699709,"identity":"bd3216d1-3ac4-494b-a666-2beeeaf88d4c","added_by":"auto","created_at":"2024-02-27 13:54:06","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2300719,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3971385/v1/4aae0d21-f804-4bcb-946d-0bf844ad4ed0.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Prediction of Heart Failure in Type 2 Diabetes Mellitus Subjects Using Machine Learning: A Cross-Sectional Study","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eIt is no longer news that there is a surge in the prevalence of diabetes around the world. Over the years, it has also been observed that the most popular type of diabetes among older adults is type 2 diabetes and it is now a menace to global health in this 21st century coupled with its increased popularity among the younger population (WHO, 2021). The global prevalence of T2DM among adults aged 20 to 79 is 537\u0026nbsp;million (10.5%), and by 2045, it is expected to rise to 783\u0026nbsp;million (12%), according to the 2021 International Diabetes Federation (IDF) study (Sun et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). In Africa, 24\u0026nbsp;million individuals live with T2DM in 2021 (Adamu et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). According to projections, this figure will rise by 129% to 55\u0026nbsp;million by 2045 (Sun et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The prevalence of Type 2 DM in Nigeria has been reported as 3.9% that is, 3.9\u0026nbsp;million adults, aged 20\u0026ndash;79 years have type 2 diabetes (IDF, 2019).\u003c/p\u003e \u003cp\u003eCongestive Heart Failure (CHF), as defined by the American College of Cardiology (ACC) and the American Heart Association (AHA), is \"a complex clinical syndrome that results from any structural or functional impairment of ventricular filling or ejection of blood.\u0026rdquo; CHF is a common disorder worldwide with a high morbidity and mortality rate. With an estimated prevalence of 26\u0026nbsp;million people worldwide, CHF contributes to increased healthcare costs, reduces functional capacity, and significantly affects quality of life. Diagnosing and effectively treating the disease is imperative to prevent recurrent hospitalizations, decrease morbidity and mortality, and enhance patient outcomes (Heidenreich \u003cem\u003eet al\u003c/em\u003e., 2022). Diabetes has been identified as an important risk factor for Heart Failure (HF), others being age and obesity (Groenewegen \u003cem\u003eet al.\u003c/em\u003e, 2020). HF often manifests as the first cardiovascular (CV) event in people with type 2 diabetes (T2D) (Birkeland et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Even individuals with pre-diabetes, as defined by the criteria of the World Health Organization (WHO) and the American Diabetes Association (ADA), are at a 9\u0026ndash;58% greater risk of developing HF (Cai et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eArtificial intelligence (AI), the imitation of human cognition by technology, can guide clinical care and decision-making without human involvement in the process. One sub-field of AI is ML, which allows computers to evaluate data beyond programmatic algorithms, identify patterns within data, map learned patterns to unseen data, and improve the performance of computational tasks beyond human capabilities (Rajkomar et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). In HF, ML has demonstrated its superiority in mortality prediction compared to the benchmark models (Shin et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; K\u0026ouml;nig \u003cem\u003eet al.\u003c/em\u003e, 2021; Negassa et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Jing et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Preventive CV medicine increasingly implements modeling techniques to estimate the individual's absolute risk of a CV event. Modern ML techniques extract useful patterns from large datasets to answer clinical questions and have demonstrated significant promise for risk stratification across various populations (Ross \u003cem\u003eet al.\u003c/em\u003e, 2021; Cho et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). ML can help in identifying predictors and relationships between them that may not be identified by traditional models (Ward et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), thus new risk factors may emerge (Nabrdalik \u003cem\u003eet al.\u003c/em\u003e, 2023).\u003c/p\u003e \u003cp\u003eRecently, several studies have been undertaken on the subject of disease prediction, and some physicians are now using machine-learning models to forecast various diseases (Modern, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Kaur \u0026amp; Kumari, 2020; Pradhan et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). So, it is essential to create a diabetes classifier that is practical, reliable, and economical. Most importantly, one that can predict the development of heart failure in diabetic patients. This research will contribute immensely to the body of knowledge specifically the Nigerian health sector and the African health sector at large by predicting and reducing the comorbidity of heart failure in diabetic patients, mortality, and rate of complications of diabetes. Data generated from this study will also be highly instrumental for further studies on predictive model building.\u003c/p\u003e"},{"header":"METHODOLOGY","content":"\u003cp\u003e\u003cstrong\u003eStudy Area\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was carried out in Oba Adejuyigbe General Hospital and Primary Health Care, Okeyinmi, Ado-Ekiti\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStudy Design\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study employed a case-control research design.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical Approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEthical approval was collected from the Ethics Committee, College of Medicine and Health Sciences, Afe Bablola University, Ado Ekiti, Nigeria. Informed consent was obtained from all participants before the commencement of the study\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSample Size Determination\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe sample size (N) was calculated using Fisher\u0026rsquo;s formula (Safranek, 2018)\u0026nbsp;\u003c/p\u003e\n\u003cp\u003en=z2p(1\u0026minus;p) / d\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003eWhere: N = the desired sample size (when the population is greater than 10,000)\u003c/p\u003e\n\u003cp\u003eZ = is a constant given as 1.96 (or more samples at 2.0) which corresponds to the 95% confidence level.\u003c/p\u003e\n\u003cp\u003ep = prevalence (3.9%) (IDF, 2021)\u003c/p\u003e\n\u003cp\u003eq = 1.0 \u0026ndash; p\u003c/p\u003e\n\u003cp\u003ed = acceptable error (5%)\u003c/p\u003e\n\u003cp\u003e\u003cimg 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\" width=\"408\" height=\"364\"\u003e\u003c/p\u003e\n\u003cp\u003eHowever, 123 participants were recruited for this study; comprising of 59 apparently healthy subjects without T2DM (controls) and 63 T2DM subjects (tests).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInclusion and Exclusion Criteria\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe inclusion criteria for this study are non-pregnant and non-lactating women, those who gave their consent, and those within the age range of 20-95 years. The exclusion criteria for this study are pregnant women, nursing mothers, and, those who did not give their consent.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSample\u003c/strong\u003e \u003cstrong\u003eCollection and Statistical Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e5ml of blood was collected from all subjects into a lithium heparin tube and fluoride oxalate tube via venipuncture. Fasting blood glucose was analyzed immediately. Electrolytes were estimated using an ion-selective electrode (ISE). BNP and Troponin I were determined using Enzyme-Linked Immunosorbent Assay (ELK Biotechnology) according to the manufacturer\u0026rsquo;s instructions. Lactate dehydrogenase (LDH), Aspartate aminotransferase (AST), Alanine transaminase (ALT), Creatinine phosphokinase (CPK), Fasting blood sugar (FBS), Total Cholesterol, and triglyceride were quantified using the enzymatic rate method following the manufacturer\u0026rsquo;s direction.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMachine Learning Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDataset related to previously published datasets where reported conventional risk factors like age, glycemic parameters, lipid profile, and demographic data were built. However, additional biochemical parameters were added (biomarkers of heart failure inclusive). In this present study, the dataset consists of 123 samples with 34 attributes. Data preprocessing was done by Label encoding. Lemmatization was used to transform the data into a categorical variable and grouping categories was created using factorize to group the Dataset into T2DM patients and non-T2DM\u0026nbsp;patients. The T2DM subject group was Labeled 1 while non-T2DM subjects were labeled 0. Following this, the data were thoroughly checked for missing values as well as incorrect values which impact the quality of the model. To reduce the influence of missing values as well as incorrect values on the model performance the means from the data was applied.\u003c/p\u003e\n\u003cp\u003eFollowing data preprocessing, various machine learning classification models such as K-nearest neighbors (K-NN), Logistic Regression (LR), Support Vector Machine (SVM), Linear Discriminant Analysis (LDA), Classification and Regression Trees (CART), Naive Bayes (NB), and Random Forest were applied to the dataset and implemented in Python language. To carry out the ML analysis the data was split into training (70%), validation (20%) and test sets (30%). SHAP framework (shap 0.37.0 version) for interpreting additive feature importance in an ensemble Random Forest model. SHAP is a cutting-edge method that explains predictions made by complex ML and DL models (Christoph, 2019). The SHAP values explain the relative contribution of each feature in ML model prediction (Jangili \u003cem\u003eet al\u003c/em\u003e., 2023). To assess the predictive power of these models we have considered the confusion matrix which provides Precision, Accuracy, F1 score and Recall. The \u0026ldquo;confusion_matrix\u0026rdquo; function from the Python library \u0026ldquo;sklearn. metrics\u0026rdquo;, is used for model evaluation (Pedregosa \u003cem\u003eet al\u003c/em\u003e., 2011). This Python function takes actual and predicted values as inputs to obtain a confusion matrix.\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cp\u003eA total of 123 subjects were recruited in this study: 59 diabetes subjects and 63 non-diabetes subjects. Table 4.1 shows the demographic characteristics of the subjects studied. Table 4.2 shows the accuracy of classification models. Table 4.3 shows the 5-fold cross-validation scores for different machine learning models for predicting heart failure in diabetes patients. Table 4.4 shows the predictive performance of the Random Forest model. Table 4.5 shows the permutation importance scores for features from a Random Forest classifier model predicting heart failure in type 2 diabetes patients.\u003c/p\u003e\n\u003cp\u003eFigure 4.1 shows ROC (Receiver Operating Characteristic) curves for multiple machine learning algorithms. Figure 4.2 shows a confusion matrix showing the performance of a Random Forest classification model for the prediction of heart failure in type 2 diabetes patients. Figure 4.3 shows the ROC \u0026nbsp; and AUC of Random Forest. Figure 4.4 shows the SHAP plot bar () of features that increase and decrease model output. Figure 4.5 shows the bee swarm plot of each feature to visualize the SHAP values. Figure 4.6: Shap plot bar () showing the overall impact of features on model output\u003c/p\u003e\n\u003cp\u003eTable 4.1: Demographic Characteristics of the Subjects\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.667396061269145%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.474835886214443%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eFrequency\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"44.85776805251641%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePercent (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.667396061269145%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eGender\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003cp\u003eFemale\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.474835886214443%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003cp\u003e39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"44.85776805251641%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e22.00%\u003c/p\u003e\n \u003cp\u003e78.00%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.667396061269145%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge (years)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026lt;50\u003c/p\u003e\n \u003cp\u003e51 \u0026ndash; 60\u003c/p\u003e\n \u003cp\u003e61 \u0026amp; above\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.474835886214443%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"44.85776805251641%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e20.00%\u003c/p\u003e\n \u003cp\u003e38.00%\u003c/p\u003e\n \u003cp\u003e42.00%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.667396061269145%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMarital status\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eMarried\u003c/p\u003e\n \u003cp\u003eWidowed\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.474835886214443%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003cp\u003e43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"44.85776805251641%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e14.00%\u003c/p\u003e\n \u003cp\u003e86.00%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.667396061269145%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eEducational status\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eTertiary\u003c/p\u003e\n \u003cp\u003eSecondary\u003c/p\u003e\n \u003cp\u003eNo formal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.474835886214443%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e35\u003c/p\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"44.85776805251641%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e70.00%\u003c/p\u003e\n \u003cp\u003e24.00%\u003c/p\u003e\n \u003cp\u003e6.00%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.667396061269145%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eOccupation\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eCivil\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eservants\u003c/p\u003e\n \u003cp\u003eEntrepreneurs\u003c/p\u003e\n \u003cp\u003eRetired\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.474835886214443%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"44.85776805251641%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e62.00%\u003c/p\u003e\n \u003cp\u003e28.00%\u003c/p\u003e\n \u003cp\u003e10.00%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.667396061269145%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eReligion\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eChristian\u003c/p\u003e\n \u003cp\u003eIslam\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.474835886214443%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e43\u003c/p\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"44.85776805251641%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e86.00%\u003c/p\u003e\n \u003cp\u003e14.00%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 4.2 Accuracy of classification models\u003c/p\u003e\n\u003cp\u003e\u003cimg width=\"624\" src=\"data:image/jpeg;base64,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\" alt=\"image\" height=\"452\"\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 4.3: 5-fold Cross-validation scores for models\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMODELS\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMEAN CROSS-VALIDATION SCORE\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSTANDARD DEVIATION\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003eLinear Regression\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e0.825000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e0.144482\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003eLinear Discriminant Analysis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e0.777500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e0.242629\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003ek-nearest neighbor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e0.675000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e0.256174\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003eDecision Tree\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e0.732500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e0.218103\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003eNaive Bayes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e0.842500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e0.164526\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003eSupport Vector Machine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e0.502500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e0.222191\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003eRandom Forest Classifier\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e0.837500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e0.190312\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4.4: Predictive performance of the Random Forest model\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003ePRECISION\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003eRECALL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003eF1-SCORE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003eSUPPORT\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003eCLASS 0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003e0.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003e0.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003e0.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003eCLASS 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003e0.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003e0.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003e0.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003eOVERALL ACCURACY\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003e0.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003e38\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003eMACRO AVG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003e0.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003e0.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003e0.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003e38\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003eWEIGHTED AVG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003e0.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003e0.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003e0.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003e38\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTABLE 4.5: The permutation importance scores for features from a Random Forest classifier model predicting heart failure in type 2 diabetes patients.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cimg 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\" alt=\"image\" width=\"635\" height=\"460\"\u003e\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eThis present study used a multi-marker approach to predict heart failure in T2DM subjects via machine learning techniques. The anthropometric data (age, systolic blood pressure, diastolic blood pressure, weight, height, MUAC, waist circumference) and biochemical data namely fasting blood glucose, CK-MB, Troponin, and BNP were subjected to 18 model algorithms and the random forest classifier was identified as the best model to predict heart failure accurately (Accuracy = 87%). Several studies have also reported that a random forest is a useful \u0026nbsp;tool in the identification of important predictors from a mixture of variables,\u003c/p\u003e\n\u003cp\u003eYuan \u003cem\u003eet al\u003c/em\u003e (2019) reported the random forest as the best algorithm that can predict heart failure using four cardiac biomarkers, namely, BNP, sST2, Gal-3, and CK-MB (Yuan \u003cem\u003eet al\u003c/em\u003e., 2019). Random forest was also used to rank the importance of the biomarkers used. \u0026nbsp;Kavitha \u003cem\u003eet al\u0026nbsp;\u003c/em\u003e(2021) in their study discovered that random forest (Accuracy = 81%) and hybrid model (random forest and decision tree) are good algorithms for the prediction of heart disease. Jangili \u003cem\u003eet al\u003c/em\u003e., (2023), reported in their study that random forest (Accuracy = 76%) is a good predictor of T2DM, coronary artery diseases, and risk factors for the occurrence of each condition. It\u0026apos;s worthy of note that Jangili \u003cem\u003eet al\u003c/em\u003e (2023) used age, glycemic parameters, lipid profile, 27 traditional cytokines and 10 metabolic hormones, 3 adipokines, and 6 apo-lipoproteins. Ansari \u003cem\u003eet al\u003c/em\u003e (2023), also found random forests as a good model for the prediction of heart disease (Accuracy = 99%) (Ansari \u003cem\u003eet al\u003c/em\u003e., 2023). All these studies and more have identified the random forest classifier model as a good algorithm for predicting heart failure (disease) and this corroborates the result of this study.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTo classify patients and identify predictors, random forests were employed, which is a novel method that develops numerous decision trees, by which the accuracy of the predictors was tested. The random forest classifier operates by building a set of decision trees. At each node in the trees, a random subset of the predictor variables is randomly selected and considered as split candidates (Yuan \u003cem\u003eet al\u003c/em\u003e., 2019). The dataset was repeatedly divided into subtrees, assessing predictor variables by importance based on the change in the classification error affected by its presence or absence in the subset. Furthermore, the random forests also combine the predictions of multiple decision trees, improving the power of the algorithm (Sylvester \u003cem\u003eet al.,\u0026nbsp;\u003c/em\u003e2017).\u003c/p\u003e\n\u003cp\u003eSHAP value (impact on model output) among all possible combinations identified glucose (FBG), BNP, Systolic and diastolic blood pressure, and waist circumference as important features in the prediction of heart failure in T2DM. The permutation importance score of the 12 features studied shows the effect that each feature would have on the performance of the model when reshuffled. Systolic BP, BNP, MUAC, and troponin I in this order have the highest positive importance to the prediction of heart failure in T2DM. Height, weight, and waist circumference have small negative importance values meaning they slightly decrease model performance. This means that the most useful predictor of heart failure based on the RF model in this dataset is systolic blood pressure.\u003c/p\u003e\n\u003cp\u003eThere are a few limitations in this study. First, this is a cross-sectional study with a relatively small size that was performed in multi-centers and the generalizability of these results (in another site) is yet to be carried out. Second, this study focused on three cardiac markers (CK-MB, BNP, Troponin I) among the several other cardiac markers (Gal-3, sST2, etc.) and other biomarkers involved in the pathophysiology of HF such as oxidative stress markers, renal salt, and water retention.\u0026nbsp;\u003c/p\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003eThe present study is the first to provide a framework for the exploration of the random forest algorithm in the prediction of heart failure. This study provided supporting evidence that with Systolic BP, BNP, MUAC and troponin I, an accurate predictive model for the biochemical prediction of heart failure in T2DM subjects can be built. The random forest algorithm was once again proven to have the ability to provide relevant information about the importance of different biomarkers and anthropometric variables. However, this needs further investigation.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eFBS \u0026ndash; Fasting blood sugar\u003c/p\u003e\n\u003cp\u003eCK-MB \u0026ndash; Creatinine Phosphokinase\u003c/p\u003e\n\u003cp\u003eBNP \u0026ndash; B natriuretic Peptide\u003c/p\u003e\n\u003cp\u003esSt2 - soluble suppression of tumorigenesis-2\u003c/p\u003e\n\u003cp\u003eGal-3 \u0026ndash; Galectin 3\u003c/p\u003e\n\u003cp\u003eHF \u0026ndash; Heart Failure\u003c/p\u003e\n\u003cp\u003eRF \u0026ndash; Random Forest\u003c/p\u003e\n\u003cp\u003eMUAC \u0026ndash; Mid Upper arm Circumference\u003c/p\u003e\n\u003cp\u003eT2DM \u0026ndash; Type 2 Diabetes Mellitus\u003c/p\u003e\n\u003cp\u003eROC \u0026ndash; Receiver Operating Characteristic\u003c/p\u003e\n\u003cp\u003eAUC \u0026ndash; Area Under Curve\u003c/p\u003e\n\u003cp\u003eSHAP -\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eBMI \u0026ndash; Body Mass Index\u003c/p\u003e\n\u003cp\u003eML \u0026ndash; Machine learning\u003c/p\u003e\n\u003cp\u003eKNN - K-nearest neighbors\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eLR - Logistic Regression\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSVM - Support Vector Machine \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eLDA - Linear Discriminant Analysis\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCART - Classification and Regression Trees\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNB - Naive Bayes\u0026nbsp;\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEthical approval was collected from the Ethics Committee, College of Medicine and Health Sciences, Afe Babalola University, Ado Ekiti, Nigeria. Informed consent was obtained from all participants before the commencement of the study.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData available from the corresponding author on reasonable request\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNone declared\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNone\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor\u0026rsquo;s contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAll auth\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eAdamu, U. 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(2013). 2013 ACCF/AHA guideline for the management of heart failure: a report of the American College of Cardiology Foundation/American Heart Association Task Force on Practice Guidelines. \u003cem\u003eJournal of the American college of cardiology\u003c/em\u003e, \u003cem\u003e62\u003c/em\u003e(16), e147-e239.\u003c/li\u003e\n \u003cli\u003eYuan, H., Fan, X. S., Jin, Y., He, J. X., Gui, Y., Song, L. Y., ... \u0026amp; Chen, W. (2019). Development of heart failure risk prediction models based on a multi-marker approach using random forest algorithms. \u003cem\u003eChinese medical journal\u003c/em\u003e, \u003cem\u003e132\u003c/em\u003e(07), 819-826.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Machine learning, Heart Failure, Type 2 Diabetes Mellitus, Prediction, BNP, Random Forest","lastPublishedDoi":"10.21203/rs.3.rs-3971385/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3971385/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe concomitance of Type 2 Diabetes Mellitus (T2DM) and heart failure has made scientists investigate ways the onset of heart failure in T2DM can be predicted. Machine learning techniques have been shown to help with the prediction of heart disease and several model algorithms have been affirmed as good. This study aimed at predicting heart failure in T2DM subjects using machine learning techniques. A total of 123 blood samples from 59 healthy subjects without T2DM (controls) and 63 T2DM subjects (tests) were analyzed for biochemical parameters [troponin (TnI), electrolytes, Lactate dehydrogenase (LDH), Aspartate aminotransferase (AST), Alanine transaminase (ALT), AST/ALT ratio, Creatinine phosphokinase (CK-MB), Fasting Blood Sugar (FBS), Cholesterol, Triglyceride, B-Natriuretic peptide (BNP)] using standard procedures. Demographic data and biochemical results were all subjected to machine learning algorithms. The results of ML showed that the Random Forest algorithm is the best model for heart failure prediction with 87% accuracy. SHAP value (impact on model output) among all possible combinations identified glucose (FBG), BNP, Systolic and diastolic blood pressure, and waist circumference as important features in the prediction of heart failure in T2DM. The permutation importance score of the features studied showed systolic BP, BNP, MUAC and troponin I in this order to have the highest positive importance to the prediction of heart failure in T2DM. Height, weight, and waist circumference have small negative importance values meaning they slightly decrease model performance. The study concluded that CK-MB, BNP, and troponin I alone may not be early indicators of heart failure in T2DM subjects. However, subjecting them to ML and combining them with the key features identified would make prediction better.\u003c/p\u003e","manuscriptTitle":"Prediction of Heart Failure in Type 2 Diabetes Mellitus Subjects Using Machine Learning: A Cross-Sectional Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-02-23 10:29:45","doi":"10.21203/rs.3.rs-3971385/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"aac7ad36-5654-4dcd-ae42-a2794572ab02","owner":[],"postedDate":"February 23rd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-02-27T13:53:44+00:00","versionOfRecord":[],"versionCreatedAt":"2024-02-23 10:29:45","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3971385","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3971385","identity":"rs-3971385","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}