Identification of Key Influencing Factors and Correlation Analysis of Self-Neglect Behavior in Elderly Patients with Coronary Heart Disease

Identification of Key Influencing Factors and Correlation Analysis of Self-Neglect Behavior in Elderly Patients with Coronary Heart Disease | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Identification of Key Influencing Factors and Correlation Analysis of Self-Neglect Behavior in Elderly Patients with Coronary Heart Disease Meiqi Liu, Xiaoli Wang, Can Wang, Xingsheng Li, Shiqun Zhou, Lanlan Lou, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7295771/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 6 You are reading this latest preprint version Abstract Objective This study aimed to investigate the influencing factors of self-neglect behavior (SNB) in elderly patients with coronary heart disease (CHD) and provide a basis for clinical intervention. Methods A retrospective analysis was conducted on 400 elderly patients with coronary heart disease who visited our hospital from January 2023 and June 2025.Based on the scores of the Elder Self-Neglect Scale (SESN), the patients were divided into a Low Self-Neglect (LSN) group (n = 179) and a High Self-Neglect (HSN) group (n = 221). Data were collected on the patients' general information, disease-related assessments, psychological evaluations, physical status, cognitive function assessments, and quality of life evaluations. Pearson and Spearman correlation analyses were used to explore the relationship between self-neglect behaviors (SNB) and various factors, while univariate logistic regression analysis was performed to identify the influencing factors of SNB. Results There were no significant differences in age, gender, and education level between the two groups (P > 0.05). However, there was a significant difference in the New York Heart Association (NYHA) functional classification between the two groups ( P < 0.05). The LSN group had significantly higher scores in psychological resilience, optimism, and self-efficacy than the HSN group ( P < 0.05). The LSN group had significantly lower anxiety scores than the HSN group ( P < 0.05). The LSN group also had significantly higher scores in the Fatigue Scale-14, Timed Up and Go (TUG) test, Montreal Cognitive Assessment (MoCA), overall well-being, and social support compared to the HSN group ( P < 0.05). Correlation and logistic regression analyses showed that NYHA functional classification, psychological resilience, optimism, self-efficacy, fatigue, frailty, cognitive function, overall well-being, and social support were independent influencing factors of SNB in elderly patients with CHD. Conclusion SNB in elderly patients with CHD is influenced by multiple factors. Clinical healthcare providers should pay attention to patients’ psychological resilience, anxiety, social support, and cognitive function, and formulate individualized health management plans to improve their health status and quality of life. Clinical trial number not applicable. Elderly coronary heart disease Self-neglect behavior Influencing factors Psychological resilience Cognitive function Cardiac function Highlights Cardiac function classification emerged as an independent predictor of self-neglect behavior (SNB) in elderly coronary heart disease (CHD) patients. Retrospective analysis of 400 elderly CHD patients revealed that worsening cardiac function (assessed via NYHA classification) significantly correlates with increased SNB risk, offering a critical physiological marker for early clinical identification. Psychological resilience, self-efficacy, and optimism serve as core protective factors against SNB. The low-self-neglect group demonstrated significantly higher psychological resilience scores (e.g., coping with chronic illness stressors), self-efficacy, and optimism, alongside lower anxiety levels, highlighting the necessity of integrating psychological interventions into geriatric CHD care protocols. Cognitive function and social support synergistically mitigate SNB risk. Higher Mini-Mental State Examination (MMSE) scores and robust social support were associated with reduced SNB incidence, emphasizing the need for interdisciplinary strategies combining cognitive training and community resource mobilization. Fatigue-frailty-anxiety interplay exacerbates SNB in elderly CHD patients. Strong correlations were observed between SNB and elevated fatigue (via Fatigue Scale-14), frailty (via Tilburg Frailty Indicator, TFI), and anxiety levels, suggesting the urgency of stepwise interventions targeting this triad in clinical practice. A translational framework for precision nursing care, “4P Model”, is proposed. Grounded in empirical findings, the 4P model integrates Physiological monitoring (cardiac function), Psychological resilience-building, Partnerships (social support networks), and Personalized interventions to directly inform clinical pathways for SNB reduction. Background As the global population ages, the incidence of coronary heart disease (CHD) in elderly patients is increasing, posing enormous challenges to public health systems[ 1 ]. Elderly CHD individuals often face complex disease management issues due to physiological decline,increased comorbidities,and heightened disease burdens. Among them, self-neglect behavior (SNB) has emerged as a particularly critical concern[ 2 ].SNB refers to individuals refuse or can't maintain behaviors to satisfy their basic personal needs,including but not limited to neglect of personal hygiene, diet, medication intake, safety, and environmental sanitation[ 3 – 5 ]. Research indicates that SNB is linked to prolonged disease suffering, degraded physiological functions, and heightened psychological stress among elderly CHD patients[ 6 ]. SNB not only leads to a deterioration in patients' health, but also increases hospitalization rates and mortality risks[ 7 – 9 ].Consequently, the identification and intervention of SNB play a vital role in improving patien.t prognosis. SNB in elderly CHD patients and its influencing factors have garnered increasing academic attention. Its correlations with psychological resilience, disease perception, and social support have been identified. However,knowledge gaps remain regarding how these factors interact to influence SNB in this population, and evidence for targeted interventions is scarce. To address this, we conducted a cross-sectional study to explore factors influencing SNB in elderly CHD patients, identify key determinants and their interrelationships, and examine their relative contributions, aiming to inform personalized health management and targeted behavioral interventions. Methods Study population This cross-sectional study analyzed 400 elderly patients who were diagnosed with CHD and presented to the author's institution from January 2023 and June 2025. The inclusion criteria included adherence to established diagnostic standards for CHD[ 10 ], an age of 60 years or older, completion of the Scale of the Elderly Self-Neglect (SESN), comprehensive medical documentation, and a stable mental and cognitive status. The exclusion criteria included patients with respiratory or other infectious diseases, malignant neoplasms, significant dysfunction of major organs, cerebrovascular or peripheral vascular disorders, and autoimmune deficiencies. This study received ethical approval from the institutional review board of the author's hospital (Approval No: 2023120). This study was conducted in compliance with identified data protocols as per the Declaration of Helsinki, thus exempting patients from the requirement for informed consent. Patient grouping Patients were stratified on the basis of the severity of SNB. Those scoring below 20 on the SESN[ 11 ]. were classified into the low self-neglect (LSN) group, comprising 179 participants. Conversely, those with SESN scores of 20 or higher were categorized into the high self-neglect (HSN) group, comprising 221 participants. Data collection and assessment instrument General Information Collection Demographic data, including age, sex, educational level, marital status, occupation, income level, place of residence, smoking history, drinking history, medical history, and family history, were collected. Disease-Related Assessment Instrument (1) Fear of Disease Progression Assessment: The Fear of Progression Questionnaire-Short Form (FoP-Q-SF[ 12 ]. comprises 12 items that are categorized into two dimensions: physiological health (six items) and the society-family context (six items). Responses were measured via a 5-point Likert scale (1–5), with total scores ranging from 12–60. A higher score indicates a more pronounced fear of disease progression.The Cronbach's α coefficient was 0.85. (2) Illness Perception Assessment: The Illness Perception Questionnaire (IPQ)[ 12 ], which consists of nine items rated on a scale from 0–10, was administered to evaluate patients' perceptions of their illness. Higher scores reflect an increased perception of threat from the illness.The Cronbach's α coefficient was 0.78. Psychological Status Assessment Instrument (1) Psychological Resilience Assessment: The Psychological Resilience Scale (PRS)[ 13 ], which consists of 25 items, was employed to assess psychological resilience and encompasses three domains: toughness, optimism, and self-efficacy. Each item was rated on a scale from 0 to 4, with a maximum score of 100. Higher scores denote enhanced psychological resilience.The Cronbach's α coefficient was 0.89. (2) Anxiety and Depression Assessment: The Self-Rating Anxiety Scale (SAS) [ 14 ]was used to assess anxiety levels via a 4-point scoring system. The primary output is the total score, which is derived by multiplying the raw score by 1.25 and truncating it to the nearest integer. A critical cutoff score of 50 indicates elevated anxiety levels.The Cronbach's α coefficient was 0.76. (3) The Self-Rating Depression Scale (SDS)[ 15 ] was also administered, with a threshold score of 53. Higher scores indicate greater severity of depressive symptoms.The Cronbach's α coefficient was 0.79. Assessment of physical condition and cognitive function (1) Fatigue assessment utilized the Fatigue Scale (FS)[ 16 ], which comprises 14 items with binary responses (yes/no) and is scored as 0 or 1 (0 = no, 1 = yes). The total score ranges from 0–14. Higher scores indicate greater levels of chronic fatigue.The Cronbach's α coefficient was 0.82. (2) The frailty assessment used the Tilburg Frailty Indicator (TFI)[ 17 ], which covers physiological, psychological, and social dimensions across 15 items. A total score of 5 or greater indicates the presence of frailty. The Falls Efficacy Scale[ 18 ], which consists of 16 items rated on a 1–4 scale, with a maximum score of 64, was also employed to assess patients' concerns regarding falls during daily activities. Larger scores suggest greater efficacy in preventing falls.The Cronbach's α coefficient was 0.80. (3) The Montreal Cognitive Assessment (MoCA) [ 19 ] was used to evaluate the intellectual status and degree of cognitive deficit of the patients, including 7 items including naming, orientation, and delayed recall, with a total score of 30 points, a cut-off value of 26 points, and a ≥ of 26 points were normal.It has a total score of 30, Lower scores indicate greater cognitive impairment.The Cronbach's α coefficient was 0.81. (4) The overall well-being assessment employed the overall well-being scale (OWBS)[ 20 ], which comprises 18 items across six dimensions. A total score below 48 denotes low subjective well-being, scores between 49 and 72 reflect moderate well-being, and scores between 73 and 120 signify high well-being.The Cronbach's α coefficient was 0.88. (5) Social support assessment utilized the Social Support Assessment Scale (SSAS)[ 21 , 22 ], which incorporates three dimensions, objective support, subjective support, and support utilization, with a total of 10 items and a maximum score of 66. Higher scores represent greater social support.The Cronbach's α coefficient was 0.83. Assessment of Patients' Quality of Life The Short Form Health Survey (SF-36)[ 23 ] was employed to assess the quality of life of patients. It incorporates eight dimensions classified into two primary categories: overall physical health and overall mental health. The specific dimensions include physical functioning, role-physical, bodily pain, general health, vitality, social functioning, role-emotional, mental health, and health transition. Each dimension is scored between 0 and 100, with higher scores indicating superior health status.The Cronbach's α coefficient was 0.89. Statistical analysis Data entry and statistical analyses were conducted via SPSS 29.0 software. Categorical data are presented as [n (%)]. Continuous variables were subjected to the Shapiro‒Wilk test for normality assessment. Nonnormally distributed data were analyzed via the Wilcoxon rank-sum test, with the results reported as the median (25th percentile, 75th percentile). Correlations were assessed using Pearson's correlation (normally distributed continuous variables) or Spearman's rank correlation (non-normal continuous or categorical variables). Logistic regression analysis was performed to identify potential factors associated with SNB, and the results are expressed as odds ratios (ORs) and 95% confidence intervals (CIs). A significance threshold of p < 0.05 was established. Results Comparison of General Data and Clinical Characteristics between Groups Demographic Characteristics No significant differences were found between the LSN and HSN groups in age, sex, education level, marital status, health insurance status, smoking history, alcohol use history, urban residency, or income level (P > 0.05; Table 1 ). Table 1 Comparison of the demographic characteristics between groups Parameter LSN Group (n = 179) HSN Group (n = 221) W/χ² P Age (years) 76(69,82.5) 76(70,83) 18939.000 0.465 Gender (male/female) 91(50.84%)/88(49.16%) 102(46.15%)/119(53.85%) 0.869 0.351 Educational Level (primary school and below/junior high school/high school/university and above) 42(23.46%)/70(39.11%)/33(18.44%)/34(18.99%) 48(21.72%)/87(39.37%)/54(24.43%)/32(14.48%) 2.993 0.393 Marital Status (married/unmarried) 121(67.6%)/58(32.4%) 158(71.49%)/63(28.51%) 0.711 0.399 Medical Insurance (with/without) 169(94.41%) 212(95.93%) 0.501 0.479 Smoking History (yes/no) 56(31.28%) 77(34.84%) 0.564 0.453 Drinking History (yes/no) 79(44.13%) 96(43.44%) 0.019 0.889 Urban Housing (with/without) 145(81.01%) 187(84.62%) 0.913 0.339 Income/Person (2000–5000/5000–10000/10000 or above) 31(17.32%)/105(58.66%)/43(24.02%) 45(20.36%)/119(53.85%)/57(25.79%) 1.015 0.602 Clinical Features No significant differences were found between groups for hypertension, diabetes, hyperlipidemia, disease duration, stable angina, unstable angina, myocardial infarction, chest pain, family history of CHD, PCI history, or surgical treatment history (P > 0.05). However, NYHA functional class distribution differed significantly between groups (P < 0.05; Table 2 ). Table 2 Comparison of the clinical features between groups Parameter LSN Group (n = 179) HSN Group (n = 221) W/χ² P Hypertension (Yes/No) 127(70.95%) 175(79.19%) 3.626 0.057 Diabetes (Yes/No) 78(43.58%) 116(52.49%) 3.146 0.076 Hyperlipidemia (Yes/No) 86(48.04%) 116(52.49%) 0.781 0.377 BMI (kg/m 2 ) 23.66(21.72,26.48) 23.34(21.11,25.39) 21860.500 0.070 Duration of Disease (years) 10(5,12) 10(5,14) 17737.500 0.073 NYHA Functional Classification (Ⅰ/Ⅱ/Ⅲ/Ⅳ) 64(35.75%)/63(35.2%)/43(24.02%)/9(5.03%) 105(47.51%)/76(34.39%)/36(16.29%)/4(1.81%) 9.400 0.024 Stable Angina (Yes/No) 125(69.83%) 162(73.3%) 0.588 0.443 Unstable Angina (Yes/No) 42(23.46%) 49(22.17%) 0.094 0.759 Myocardial Infarction (Yes/No) 12(6.7%) 10(4.52%) 0.903 0.342 Chest Pain (Yes/No) 94(52.51%) 107(48.42%) 0.664 0.415 Family History of CHD (Yes/No) 93(51.96%) 135(61.09%) 3.364 0.067 PCI Treatment History (1/2/3 times or more) 47(26.26%)/100(55.87%)/29(16.2%)/3(1.68%) 65(29.41%)/107(48.42%)/48(21.72%)/1(0.45%) 4.457 0.216 Surgical Treatment History (Yes/No) 114(63.69%) 141(63.8%) 0.001 0.981 Assessment of Fear of Disease Progression No significant differences were found between groups in total FoP-Q-SF scores or its subscales (Physiological Health, Social-Family) (P > 0.05; Table 3 ). Table 3 Comparison of FoP-Q-SF scores between groups Parameter LSN Group (n = 179) HSN Group (n = 221) W P FoP Score 33(29,42) 33(29,38) 20692.000 0.427 Physiological Health 18(16,22) 19(16,22) 19199.500 0.613 society-family 14(11,17) 14(12,16) 20273.500 0.666 Assessment of Illness Perception No significant differences were observed between groups in total IPQ scores or its cognitive, emotional, and understanding dimensions (P > 0.05; Table 4 ). Table 4 Comparison of Illness Perception Scores between Groups Parameter LSN Group (n = 179) HSN Group (n = 221) W P Total IPQ Score 41(36,48) 41(36,45) 20021.000 0.834 Cognition 24(19,30.5) 24(21,28) 19841.500 0.957 Emotion 13(11,15) 12(11,14) 20601.500 0.470 Understanding 4(3,5) 4(3,5) 19820.000 0.972 Assessment of Psychological Resilience The LSN group had significantly higher scores than the HSN group for total psychological resilience, optimism, and self-efficacy (P 0.05; Table 5 ). Table 5 Comparison of Psychological Resilience Scores between Groups Parameter LSN Group (n = 179) HSN Group (n = 221) W P Psychological Resilience 58(40,67) 51(39,65) 22814.000 0.008 Optimism 10(8,12) 9(7,12) 22611.000 0.013 Self-Efficacy 20(14,25) 17(14,22) 22917.500 0.006 Toughness 26(18,32.5) 23(18,29) 21883.500 0.067 Assessment of Anxiety and Depression Anxiety scores were significantly lower in the LSN group compared to the HSN group (P 0.05; Table 6 ). Table 6 Comparison of Anxiety and Depression Scores between Groups Parameter LSN Group (n = 179) HSN Group (n = 221) W P Anxiety 50(48,53) 50(50,52) 17183.000 0.022 Depression 50(47,53) 50(48,52) 19620.500 0.890 Assessment of physical status and cognitive function The LSN group had significantly higher scores than the HSN group for the FS-14, TFI, MoCA, OWBS, and SSRS (P 0.05; Table 7 ). Table 7 Comparison of physical status and cognitive function between groups Parameter LSN Group (n = 179) HSN Group (n = 221) W P Fatigue Scale 14 10(8,11) 10(10,12) 14898.500 < 0.001 TFI 10(7,11) 10(10,12) 17061.500 0.017 Fall Efficacy 9(8,10) 9(8,10) 17758.000 0.070 MoCA 27(25,29.5) 25(23,27) 27705.000 < 0.001 Overall Well-Being 70(66,76.5) 68(65,72) 24240.500 < 0.001 Social Support 40(36,46) 36(32,41) 25203.500 < 0.001 Assessment of quality of life No significant differences were found between groups for any SF-36 domain scores (Physical Functioning, Role-Physical, Bodily Pain, General Health, Vitality, Social Functioning, Role-Emotional, Mental Health, Health Transition) or the total SF-36 score (P > 0.05; Table 8 ). Table 8 Comparison of Quality of Life Scores between Groups Parameter LSN Group (n = 179) HSN Group (n = 221) W P Physical Functioning 40(40,50) 40(40,60) 19664.000 0.918 Role-Physical 50(25,62.5) 50(25,50) 19276.000 0.641 Bodily Pain 62(52,62) 62(42,62) 20425.000 0.564 General Health 40(40,50) 40(40,50) 21563.500 0.108 Vitality 45(35,50) 45(35,50) 19810.500 0.978 Social Functioning 55.56(44.44,66.67) 55.56(44.44,66.67) 21888.500 0.061 Role-Emotional 66.67(33.33,66.67) 66.67(33.33,66.67) 20489.500 0.474 Mental Health 56(44,60) 56(44,60) 20567.000 0.484 Health Transition 25(25,50) 25(25,50) 21023.000 0.195 SF-36 Total Score 433.11(389.77,499.78) 431(387,478.11) 21101.000 0.251 Correlation analysis of factors influencing SNB in elderly patients with CHD Correlation analysis revealed a negative relationship between SNB and factors such as psychological resilience, optimism, self-efficacy, MoCA scores, overall well-being, and social support (P < 0.05). It was positively correlated with cardiac function classification, anxiety scores, Fatigue Scale 14 scores, and TFI scores (P < 0.05) (Table 9 ). Table 9 Correlation analysis of factors influencing SNB in elderly patients with CHD Parameter ρ P Cardiac Function Classification -0.145 0.004 Psychological Resilience -0.132 0.008 Optimism -0.125 0.013 Self-Efficacy -0.137 0.006 Anxiety 0.114 0.022 Fatigue Scale 14 0.217 P < 0.001 TFI 0.119 0.017 MoCA -0.348 P < 0.001 Overall Well-Being -0.195 P < 0.001 Social Support -0.237 P < 0.001 Univariate logistic regression analysis of factors influencing SNB in elderly patients with CHD Univariate logistic regression analysis revealed that cardiac function classification, psychological resilience scores, optimism, self-efficacy, TFI scores and overall well-being were significantly associated with the occurrence of SNB (P 0.05) (Table 10 ). Table 10 Univariate logistic regression analysis of Factors influencing SNB in elderly patients with CHD Parameter Regression Coefficient Standard Error Wald P OR(95%CI) Cardiac Function Classification 0.361 0.120 3.001 0.003 0.697(0.549–0.881) Psychological Resilience -0.018 0.007 -2.625 0.009 0.982(0.968–0.995) Optimism -0.099 0.041 -2.411 0.016 0.906(0.835–0.981) Self-Efficacy -0.050 0.017 -2.900 0.004 0.951(0.919–0.984) Anxiety 0.044 0.029 1.531 0.126 1.045(0.989–1.107) Fatigue Scale 14 0.305 0.056 5.474 4.389 1.357(1.221–1.521) TFI 0.082 0.033 2.465 0.014 1.085(1.017–1.159) MoCA -0.268 0.041 -6.454 1.091 0.765(0.703–0.828) Overall Well-Being -0.044 0.012 -3.562 < 0.001 0.957(0.934–0.980) Social Support -0.056 0.012 -4.799 1.597 0.945(0.923–0.967) Discussion In the context of the aging of the global population, health management for elderly patients with CHD has become a pivotal issue in the public health discourse. This study conducted a comparative analysis of elderly CHD patients with low versus high levels of SNB, examining demographic characteristics, disease attributes, fear of disease progression, illness perception, psychological resilience, anxiety and depression levels, physical and mental health status, quality of life, and SNB determinants. The findings elucidate several critical factors influencing SNB among this population. Notably, while the two groups had no significant differences in most demographic or clinical characteristics, a significant disparity existed in cardiac function classification. This aligns with previous research by Riegel et al[ 24 ], which indicated that attenuated cardiac function restricts physical activity, adversely impacting daily life engagement and subsequently increasing SNB. Patients categorized with better cardiac function are at greater risk for SNB, likely owing to the associated limitations on daily activities and negative effects on mental health, ultimately leading to compromised self-care capabilities.Furthermore, the correlation between cardiac function classification and SNB suggests that clinical interventions should prioritize patient’s cardiac function management and indirectly reduce the occurrence of SNB by improving cardiac function. Furthermore, in this study, the LSN group scored significantly higher on measures of psychological resilience, optimism, and self-efficacy but presented significantly lower anxiety scores than did the HSN group. Higher psychological resilience allows patients to manage the stressors associated with chronic illness effectively. Consequently, they can maintain a positive outlook that mitigates the incidence of SNB. This observation is consistent with a body of literature suggesting that psychological resilience is an important protective factor against SNB in elderly CHD patients.It serves as an intrinsic protective mechanism, assisting patients in sustaining positive emotional states and enhancing their coping strategies when confronting health-related challenges, thereby diminishing SNB. These findings demonstrate that robust psychological resilience is a pivotal determinant of sustained quality of life[ 25 , 26 ].This research emphasizes the importance of cultivating psychological resilience through clinical interventions such as psychological counseling and group therapy,to help patients strengthen their capacity to cope with disease challenges. In addition, compared with the HSN group, the LSN group demonstrated superior performance on the Fatigue Scale 14, TFI, MoCA, overall well-being, and social support measures. This further underscores the significance of both physical and cognitive health in reducing SNB. Low fatigue levels, superior cognitive function, and high levels of overall well-being and social support provide patients with essential emotional and practical resources, alleviating their psychological burdens and consequently abating SNB. The literature highlights the importance of both physical and mental well-being, along with social support, as vital components in the self-management of chronic conditions[ 27 , 28 ].These factors, together with psychological resilience, constitute important resources for elderly CHD patients to face with disease challenges. These factors enhance patients' self-support ability and mitigate psychological stress, contributing to reduced SNB and improved overall health outcomes. The correlation analysis further revealed that psychological resilience, optimism, self-efficacy, MoCA score, overall well-being, and social support are inversely associated with SNB, and higher levels of SNB are correlated with higher levels of cardiac function classification,elevated anxiety, fatigue, and TFI. These findings suggest a need for clinical practices to prioritize the mental health of patients and social support to mitigate SNB. The results of this study resonate with those of prior studies, reaffirming the vital roles of psychological resilience, social support, and cognitive function in the self-management of elderly CHD patients[ 29 , 30 ]. Moreover, fatigue management and frailty prevention are crucial considerations in clinical intervention strategies[ 31 ]. The Kansas City Cardiomyopathy Questionnaire (KCCQ) is a widely used and recognized assessment tool for coronary heart disease patients. The reason for using the SF-36 to assess quality of life in this study is that, as a generic quality-of-life scale, the SF-36 can comprehensively evaluate the physical and psychological health dimensions of CHD patients.This study focused on extensive influencing factors for SNB,rather than solely on the impact of cardiac symptoms on quality of life.Nevertheless,future research could use more disease-specific scales like the KCCQ to explore the relationship between SNB and quality of life more deeply. Nonetheless, this study has several limitations. This was a cross-sectional analysis conducted within a single center, which may introduce selection and information biases, potentially limiting the generalizability of the findings. Future research should encompass larger-scale, multicenter prospective studies to substantiate these results. Conclusions In conclusion, the factors influencing SNB in elderly CHD patients are multifaceted. Among them, cardiac function classification, psychological resilience, cognitive function, overall well-being, and social support are identified as key determinants. Clinical practitioners should prioritize comprehensive assessments of elderly CHD patients,including cardiac function, mental health status, cognitive function, and social support.This study lays a foundation for clinical interventions. It is advocated that healthcare professionals incorporate assessments of these critical factors into routine care for elderly CHD patients and implement tailored interventions, thus lowering SNB incidence and ultimately enhancing patient quality of life. Relevance for clinical practice This study underscores the need to address psychological resilience, anxiety, social support, and cognitive function to prevent SNB in elderly CHD patients. The identification of NYHA functional class as an independent predictor highlights the interplay of physical and psychological factors. Clinicians should incorporate assessments of these domains into routine care and develop personalized interventions. Targeting these key determinants can reduce SNB incidence and enhance the quality of life for this vulnerable population. Abbreviations SNB: Self-neglect behavior CHD: Coronary heart disease SESN: Elderly self-neglect LSN: Low self-neglect HSN: High self-neglect FoP-Q-SF: Fear of Progression Questionnaire-Short Form IPQ: Illness Perception Questionnaire PRS: Psychological Resilience Scale SAS: Self-Rating Anxiety Scale SDS: Self-Rating Depression Scale FS: Fatigue Scale TFI: Tilburg frailty indicator MoCA: Montreal Cognitive Assessment OWBS: Overall Well-Being Scale SSAS: Social Support Assessment Scale OR: odds ratio CI: confidence interval PCI: percutaneous coronary intervention Declarations Funding This work was supported by the National Nature Science Foundation of China (82302219) and the Chongqing Sports Bureau Project (B202496). Contribution of the paper Meiqi Liu (First Author): Conceptualization, Data Curation, Formal Analysis, Investigation, Methodology, Software, Visualization,Writing-Original Draft, Writing-Review& Editing; Xiaoli Wang: Conceptualization, Formal Analysis, Investigation, Methodology, Supervision; Can Wang: Methodology, Supervision, Validation; Can Wang: Data Curation, Investigation, Software; Xingsheng Li: Conceptualization, Methodology, Supervision; Shiqun Zhou: Visualization,Writing-Original Draft, Writing-Review& Editing; Lanlan Lou: Conceptualization, Data Curation, Formal Analysis; Guoxiu Li (Corresponding Author): Conceptualization, Funding Acquisition, Resources, Supervision, Validation, Writing-Original Draft, Writing-Review &Editing. Ethics approval and consent to participate All procedures conducted in studies involving human participants adhered to the ethical standards set forth by the institutional and national research committee, in accordance with the 1964 Helsinki Declaration and its subsequent amendments, or equivalent ethical standards. Due to the retrospective nature of the study, Ethics Committee of the Second Affiliated Hospital of Chongqing Medical University waived the need of obtaining informed consent. Data Availability The datasets generated and analysed during the current study are not publicly available because the data could be used for further research on other topics, but are available from the corresponding author on reasonable request. Consent for publication Not applicable. Competing interests The authors declare that they have no competing interests. References Ambrosini AP, Fishman ES, Damluji AA, Nanna MG. Chronic Coronary Disease in Older Adults. Med Clin North Am. 2024;108(3):581–94. 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Lawton JS, Tamis-Holland JE, Bangalore S, Bates ER, Beckie TM, Bischoff JM, Bittl JA, Cohen MG, DiMaio JM, Don CW, Fremes SE, Gaudino MF, Goldberger ZD, Grant MC, Jaswal JB, Kurlansky PA, Mehran R, Metkus TS Jr., Nnacheta LC, Rao SV, Sellke FW, Sharma G, Yong CM, Zwischenberger BA. 2021 ACC/AHA/SCAI Guideline for Coronary Artery Revascularization: A Report of the American College of Cardiology/American Heart Association Joint Committee on Clinical Practice Guidelines. Circulation. 2022;145:e18–114. Fan Xueli L, Xiaoling Z, Xiaofang Y, Huiping. Correlation between self-perceived burden and disease perception and fear of disease progression in young and middle-aged patients after PCI. Evid Based Nurs. 2024;10:3338–42. Lin Xiaoya O, Hongxia L, Hua Y, Xin. Reliability and validity test of the psychological toughness scale in compulsory drug rehabilitation population. J Nanjing Med Univ (Social Sci Edition). 2017;17:204–7. Guo C, Huang X. Hospital anxiety and depression scale exhibits good consistency but shorter assessment time than Zung self-rating anxiety/depression scale for evaluating anxiety/depression in non-small cell lung cancer. Med (Baltim). 2021;100(8):e24428. Zhao X, Hu T, Qiao G, Li C, Wu M, Yang F, Zhou J. Psychometric Properties of the Smartphone Distraction Scale in Chinese College Students: Validity, Reliability and Influencing Factors. Front Psychiatry. 2022;13:859640. Alkhamees AA, Algubllan LA, Alsughier N, et al. Fatigue Syndrome among Medical Students in Saudi Arabia: A Cross-Sectional Study on Depression and Anxiety. J Pharm Bioallied Sci. 2024;16(Suppl 5):S4623–7. Safarnavadeh M, Salehi L. Psychometric adequacy of the persian adapted version of the tilburg frailty indicator (P-TFI). BMC Geriatr. 2024;24(1):623. Published 2024 Jul 21. Ting HXT, Ho J, Ong PH, Young WR, Soh SLH. Convergent and predictive validity of the activities-specific balance confidence scales and balance recovery confidence scale, with regard to the falls efficacy scale-international: a cross-sectional study. Front Aging. 2025;6:1330612. Published 2025 May 30. Zeng Y, Feng Q, Hesketh T, Christensen K, Vaupel JW. Survival, disabilities in activities of daily living, and physical and cognitive functioning among the oldest-old in China: a cohort study. Lancet (London England). 2017;389(10079):1619–29. Fan J, Chang Y, Li L, et al. The relationship between medical staff burnout and subjective wellbeing: the chain mediating role of psychological capital and perceived social support. Front Public Health. 2024;12:1408006. Published 2024 Jun 21. Xiao Shuiyuan. Theoretical basis and research application of the Social Support Rating Scale. J Clin Psychiatry. 1994; 98–100. Ma Xueer H, Xiaoxuan Z, Kai J, Qianqian R, Shufeng C, Wen. Correlation between social support and self-care ability of rural disabled elderly people. Nurs Res. 2024;38:3561–4. Yang Z, Li W, Tu X, Tang W, Messing S, Duan L, Pan J, Li X, Wan C. Validation and psychometric properties of Chinese version of SF-36 in patients with hypertension, coronary heart diseases, chronic gastritis and peptic ulcer. Int J Clin Pract. 2012;66:991–8. Riegel B, Matus A, Quinn RJ, Gordon D, Thomas G, and Chittams JJJoCF. Self-care Neglect Of Heart Failure Caregivers Before And Early After The Pandemic Began. 2023; 29: 566. Korkmaz Aslan T, Çetin İ. The Relationship Between Psychological Resilience Before Orthopaedic Surgery and Postoperative Pain Level. Orthop Nurs. 2025;44(3):175–83. Liu L, Zhou L, Zhang Q, Zhang, HJZndxxbYxbJoCSUMS. Mediation effect of self-neglect in family resilience and medication adherence in older patients undergoing maintenance hemodialysis. 2023; 48: 1066–75. Zhang Y, Xiao L, Liu Q, et al. The mediating role of social support in self-management and quality of life in patients with liver cirrhosis. Sci Rep. 2025;15(1):4758. Published 2025 Feb 8. Adu FA, Poku CA, Adu AP, Owusu LB. The role of social support and self-management on glycemic control of type 2 diabetes mellitus with complications in Ghana: A cross-sectional study. Health Sci Rep. 2024;7(4):e2054. Published 2024 Apr 21. Lin C, Zhu X, Wang X, et al. The impact of perceived social support on chronic disease self-management among older inpatients in China: The chain-mediating roles of psychological resilience and health empowerment. BMC Geriatr. 2025;25(1):284. Published 2025 Apr 26. Mäki K, Nybo T, Hietanen M, Huovinen A, Marinkovic I, Melkas S. Subjective Cognitive Complaints in Mild Traumatic Brain Injury: Association with Cognitive Test Performance and Protective Psychological Factors. Arch Clin Neuropsychol Published online June 13, 2025. Yu M, Ramachandran HJ, Qian M, Shi Y, Gu L, Wang. WJJoNS. Understanding professionals’ perspectives and experiences of elder self-neglect: A systematic review and meta‐synthesis of qualitative studies. 2022; 54: 24–30. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 10 Oct, 2025 Reviewers invited by journal 10 Oct, 2025 Editor invited by journal 09 Sep, 2025 Editor assigned by journal 20 Aug, 2025 Submission checks completed at journal 20 Aug, 2025 First submitted to journal 20 Aug, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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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-7295771","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":533307653,"identity":"36ff2d86-270b-49e6-b96d-71e42ce51d7a","order_by":0,"name":"Meiqi Liu","email":"","orcid":"","institution":"The First Affiliated Hospital of Chongqing Medical University","correspondingAuthor":false,"prefix":"","firstName":"Meiqi","middleName":"","lastName":"Liu","suffix":""},{"id":533307654,"identity":"9623ae5c-0cf4-45f0-929a-645dc3a0fdcc","order_by":1,"name":"Xiaoli Wang","email":"","orcid":"","institution":"The Second Affiliated Hospital of 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12:09:08","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1529290,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7295771/v1/a7fdc7ed-883e-4d5f-87bd-f1fd02da744d.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Identification of Key Influencing Factors and Correlation Analysis of Self-Neglect Behavior in Elderly Patients with Coronary Heart Disease","fulltext":[{"header":"Highlights","content":"\u003col\u003e\n \u003cli\u003e\u003cstrong\u003eCardiac function classification emerged as an independent predictor of self-neglect behavior (SNB) in elderly coronary heart disease (CHD) patients.\u003c/strong\u003e\u003cbr\u003e\u0026nbsp;Retrospective analysis of 400 elderly CHD patients revealed that worsening cardiac function (assessed via NYHA classification) significantly correlates with increased SNB risk, offering a critical physiological marker for early clinical identification.\u003c/li\u003e\n\u003c/ol\u003e\n\u003col start=\"2\"\u003e\n \u003cli\u003e\u003cstrong\u003ePsychological resilience, self-efficacy, and optimism serve as core protective factors against SNB.\u003c/strong\u003e\u003cbr\u003e\u0026nbsp;The low-self-neglect group demonstrated significantly higher psychological resilience scores (e.g., coping with chronic illness stressors), self-efficacy, and optimism, alongside lower anxiety levels, highlighting the necessity of integrating psychological interventions into geriatric CHD care protocols.\u003c/li\u003e\n\u003c/ol\u003e\n\u003col start=\"3\"\u003e\n \u003cli\u003e\u003cstrong\u003eCognitive function and social support synergistically mitigate SNB risk.\u003c/strong\u003e\u003cbr\u003e\u0026nbsp;Higher Mini-Mental State Examination (MMSE) scores and robust social support were associated with reduced SNB incidence, emphasizing the need for interdisciplinary strategies combining cognitive training and community resource mobilization.\u003c/li\u003e\n\u003c/ol\u003e\n\u003col start=\"4\"\u003e\n \u003cli\u003e\u003cstrong\u003eFatigue-frailty-anxiety interplay exacerbates SNB in elderly CHD patients.\u003cbr\u003e\u0026nbsp;\u003c/strong\u003eStrong correlations were observed between SNB and elevated fatigue (via Fatigue Scale-14), frailty (via Tilburg Frailty Indicator, TFI), and anxiety levels, suggesting the urgency of stepwise interventions targeting this triad in clinical practice.\u003c/li\u003e\n\u003c/ol\u003e\n\u003col start=\"5\"\u003e\n \u003cli\u003e\u003cstrong\u003eA translational framework for precision nursing care, “4P Model”, is proposed.\u003c/strong\u003e\u003cbr\u003e\u0026nbsp;Grounded in empirical findings, the 4P model integrates Physiological monitoring (cardiac function), Psychological resilience-building, Partnerships (social support networks), and Personalized interventions to directly inform clinical pathways for SNB reduction.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Background","content":"\u003cp\u003eAs the global population ages, the incidence of coronary heart disease (CHD) in elderly patients is increasing, posing enormous challenges to public health systems[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Elderly CHD individuals often face complex disease management issues due to physiological decline,increased comorbidities,and heightened disease burdens. Among them, self-neglect behavior (SNB) has emerged as a particularly critical concern[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].SNB refers to individuals refuse or can't maintain behaviors to satisfy their basic personal needs,including but not limited to neglect of personal hygiene, diet, medication intake, safety, and environmental sanitation[\u003cspan additionalcitationids=\"CR4\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Research indicates that SNB is linked to prolonged disease suffering, degraded physiological functions, and heightened psychological stress among elderly CHD patients[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. SNB not only leads to a deterioration in patients' health, but also increases hospitalization rates and mortality risks[\u003cspan additionalcitationids=\"CR8\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].Consequently, the identification and intervention of SNB play a vital role in improving patien.t prognosis. SNB in elderly CHD patients and its influencing factors have garnered increasing academic attention. Its correlations with psychological resilience, disease perception, and social support have been identified. However,knowledge gaps remain regarding how these factors interact to influence SNB in this population, and evidence for targeted interventions is scarce. To address this, we conducted a cross-sectional study to explore factors influencing SNB in elderly CHD patients, identify key determinants and their interrelationships, and examine their relative contributions, aiming to inform personalized health management and targeted behavioral interventions.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStudy population\u003c/h2\u003e\u003cp\u003eThis cross-sectional study analyzed 400 elderly patients who were diagnosed with CHD and presented to the author's institution from January 2023 and June 2025. The inclusion criteria included adherence to established diagnostic standards for CHD[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e], an age of 60 years or older, completion of the Scale of the Elderly Self-Neglect (SESN), comprehensive medical documentation, and a stable mental and cognitive status. The exclusion criteria included patients with respiratory or other infectious diseases, malignant neoplasms, significant dysfunction of major organs, cerebrovascular or peripheral vascular disorders, and autoimmune deficiencies. This study received ethical approval from the institutional review board of the author's hospital (Approval No: 2023120). This study was conducted in compliance with identified data protocols as per the Declaration of Helsinki, thus exempting patients from the requirement for informed consent.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003ePatient grouping\u003c/h3\u003e\n\u003cp\u003ePatients were stratified on the basis of the severity of SNB. Those scoring below 20 on the SESN[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. were classified into the low self-neglect (LSN) group, comprising 179 participants. Conversely, those with SESN scores of 20 or higher were categorized into the high self-neglect (HSN) group, comprising 221 participants.\u003c/p\u003e\n\u003ch3\u003eData collection and assessment instrument\u003c/h3\u003e\n\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003eGeneral Information Collection\u003c/h2\u003e\u003cp\u003eDemographic data, including age, sex, educational level, marital status, occupation, income level, place of residence, smoking history, drinking history, medical history, and family history, were collected.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eDisease-Related Assessment Instrument\u003c/h3\u003e\n\u003cp\u003e(1) Fear of Disease Progression Assessment: The Fear of Progression Questionnaire-Short Form (FoP-Q-SF[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. comprises 12 items that are categorized into two dimensions: physiological health (six items) and the society-family context (six items). Responses were measured via a 5-point Likert scale (1\u0026ndash;5), with total scores ranging from 12\u0026ndash;60. A higher score indicates a more pronounced fear of disease progression.The Cronbach's α coefficient was 0.85.\u003c/p\u003e\u003cp\u003e(2) Illness Perception Assessment: The Illness Perception Questionnaire (IPQ)[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], which consists of nine items rated on a scale from 0\u0026ndash;10, was administered to evaluate patients' perceptions of their illness. Higher scores reflect an increased perception of threat from the illness.The Cronbach's α coefficient was 0.78.\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003ePsychological Status Assessment Instrument\u003c/h2\u003e\u003cp\u003e(1) Psychological Resilience Assessment: The Psychological Resilience Scale (PRS)[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], which consists of 25 items, was employed to assess psychological resilience and encompasses three domains: toughness, optimism, and self-efficacy. Each item was rated on a scale from 0 to 4, with a maximum score of 100. Higher scores denote enhanced psychological resilience.The Cronbach's α coefficient was 0.89.\u003c/p\u003e\u003cp\u003e(2) Anxiety and Depression Assessment: The Self-Rating Anxiety Scale (SAS) [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]was used to assess anxiety levels via a 4-point scoring system. The primary output is the total score, which is derived by multiplying the raw score by 1.25 and truncating it to the nearest integer. A critical cutoff score of 50 indicates elevated anxiety levels.The Cronbach's α coefficient was 0.76.\u003c/p\u003e\u003cp\u003e(3) The Self-Rating Depression Scale (SDS)[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e] was also administered, with a threshold score of 53. Higher scores indicate greater severity of depressive symptoms.The Cronbach's α coefficient was 0.79.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eAssessment of physical condition and cognitive function\u003c/h3\u003e\n\u003cp\u003e(1) Fatigue assessment utilized the Fatigue Scale (FS)[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e], which comprises 14 items with binary responses (yes/no) and is scored as 0 or 1 (0\u0026thinsp;=\u0026thinsp;no, 1\u0026thinsp;=\u0026thinsp;yes). The total score ranges from 0\u0026ndash;14. Higher scores indicate greater levels of chronic fatigue.The Cronbach's α coefficient was 0.82.\u003c/p\u003e\u003cp\u003e(2) The frailty assessment used the Tilburg Frailty Indicator (TFI)[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], which covers physiological, psychological, and social dimensions across 15 items. A total score of 5 or greater indicates the presence of frailty. The Falls Efficacy Scale[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e], which consists of 16 items rated on a 1\u0026ndash;4 scale, with a maximum score of 64, was also employed to assess patients' concerns regarding falls during daily activities. Larger scores suggest greater efficacy in preventing falls.The Cronbach's α coefficient was 0.80.\u003c/p\u003e\u003cp\u003e(3) The Montreal Cognitive Assessment (MoCA) [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e] was used to evaluate the intellectual status and degree of cognitive deficit of the patients, including 7 items including naming, orientation, and delayed recall, with a total score of 30 points, a cut-off value of 26 points, and a\u0026thinsp;\u0026ge;\u0026thinsp;of 26 points were normal.It has a total score of 30, Lower scores indicate greater cognitive impairment.The Cronbach's α coefficient was 0.81.\u003c/p\u003e\u003cp\u003e(4) The overall well-being assessment employed the overall well-being scale (OWBS)[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e], which comprises 18 items across six dimensions. A total score below 48 denotes low subjective well-being, scores between 49 and 72 reflect moderate well-being, and scores between 73 and 120 signify high well-being.The Cronbach's α coefficient was 0.88.\u003c/p\u003e\u003cp\u003e(5) Social support assessment utilized the Social Support Assessment Scale (SSAS)[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e], which incorporates three dimensions, objective support, subjective support, and support utilization, with a total of 10 items and a maximum score of 66. Higher scores represent greater social support.The Cronbach's α coefficient was 0.83.\u003c/p\u003e\n\u003ch3\u003eAssessment of Patients' Quality of Life\u003c/h3\u003e\n\u003cp\u003eThe Short Form Health Survey (SF-36)[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e] was employed to assess the quality of life of patients. It incorporates eight dimensions classified into two primary categories: overall physical health and overall mental health. The specific dimensions include physical functioning, role-physical, bodily pain, general health, vitality, social functioning, role-emotional, mental health, and health transition. Each dimension is scored between 0 and 100, with higher scores indicating superior health status.The Cronbach's α coefficient was 0.89.\u003c/p\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eStatistical analysis\u003c/h2\u003e\u003cp\u003eData entry and statistical analyses were conducted via SPSS 29.0 software. Categorical data are presented as [n (%)]. Continuous variables were subjected to the Shapiro‒Wilk test for normality assessment. Nonnormally distributed data were analyzed via the Wilcoxon rank-sum test, with the results reported as the median (25th percentile, 75th percentile). Correlations were assessed using Pearson's correlation (normally distributed continuous variables) or Spearman's rank correlation (non-normal continuous or categorical variables).\u003c/p\u003e\u003cp\u003eLogistic regression analysis was performed to identify potential factors associated with SNB, and the results are expressed as odds ratios (ORs) and 95% confidence intervals (CIs). A significance threshold of p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was established.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003eComparison of General Data and Clinical Characteristics between Groups\u003c/h2\u003e\u003cdiv id=\"Sec14\" class=\"Section3\"\u003e\u003ch2\u003eDemographic Characteristics\u003c/h2\u003e\u003cp\u003eNo significant differences were found between the LSN and HSN groups in age, sex, education level, marital status, health insurance status, smoking history, alcohol use history, urban residency, or income level (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05; Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eComparison of the demographic characteristics between groups\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eParameter\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLSN Group (n\u0026thinsp;=\u0026thinsp;179)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHSN Group (n\u0026thinsp;=\u0026thinsp;221)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003eW/χ\u0026sup2;\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge (years)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e76(69,82.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e76(70,83)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e18939.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.465\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGender (male/female)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e91(50.84%)/88(49.16%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e102(46.15%)/119(53.85%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.869\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.351\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEducational Level (primary school and below/junior high school/high school/university and above)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e42(23.46%)/70(39.11%)/33(18.44%)/34(18.99%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e48(21.72%)/87(39.37%)/54(24.43%)/32(14.48%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.993\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.393\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMarital Status (married/unmarried)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e121(67.6%)/58(32.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e158(71.49%)/63(28.51%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.711\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.399\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMedical Insurance (with/without)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e169(94.41%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e212(95.93%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.501\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.479\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSmoking History (yes/no)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e56(31.28%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e77(34.84%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.564\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.453\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDrinking History (yes/no)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e79(44.13%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e96(43.44%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.019\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.889\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUrban Housing (with/without)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e145(81.01%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e187(84.62%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.913\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.339\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIncome/Person (2000\u0026ndash;5000/5000\u0026ndash;10000/10000 or above)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e31(17.32%)/105(58.66%)/43(24.02%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e45(20.36%)/119(53.85%)/57(25.79%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.015\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.602\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003eClinical Features\u003c/h2\u003e\u003cp\u003eNo significant differences were found between groups for hypertension, diabetes, hyperlipidemia, disease duration, stable angina, unstable angina, myocardial infarction, chest pain, family history of CHD, PCI history, or surgical treatment history (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05). However, NYHA functional class distribution differed significantly between groups (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05; Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eComparison of the clinical features between groups\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eParameter\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLSN Group (n\u0026thinsp;=\u0026thinsp;179)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHSN Group (n\u0026thinsp;=\u0026thinsp;221)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003eW/χ\u0026sup2;\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHypertension (Yes/No)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e127(70.95%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e175(79.19%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e3.626\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.057\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDiabetes (Yes/No)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e78(43.58%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e116(52.49%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e3.146\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.076\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHyperlipidemia (Yes/No)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e86(48.04%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e116(52.49%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.781\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.377\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBMI (kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e23.66(21.72,26.48)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e23.34(21.11,25.39)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e21860.500\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.070\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDuration of Disease (years)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e10(5,12)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e10(5,14)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e17737.500\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.073\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNYHA Functional Classification\u003c/p\u003e\u003cp\u003e(Ⅰ/Ⅱ/Ⅲ/Ⅳ)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e64(35.75%)/63(35.2%)/43(24.02%)/9(5.03%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e105(47.51%)/76(34.39%)/36(16.29%)/4(1.81%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e9.400\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.024\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eStable Angina (Yes/No)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e125(69.83%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e162(73.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.588\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.443\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUnstable Angina (Yes/No)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e42(23.46%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e49(22.17%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.094\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.759\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMyocardial Infarction (Yes/No)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e12(6.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e10(4.52%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.903\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.342\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eChest Pain (Yes/No)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e94(52.51%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e107(48.42%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.664\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.415\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFamily History of CHD (Yes/No)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e93(51.96%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e135(61.09%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e3.364\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.067\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePCI Treatment History (1/2/3 times or more)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e47(26.26%)/100(55.87%)/29(16.2%)/3(1.68%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e65(29.41%)/107(48.42%)/48(21.72%)/1(0.45%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e4.457\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.216\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSurgical Treatment History (Yes/No)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e114(63.69%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e141(63.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.981\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\u003ch2\u003eAssessment of Fear of Disease Progression\u003c/h2\u003e\u003cp\u003eNo significant differences were found between groups in total FoP-Q-SF scores or its subscales (Physiological Health, Social-Family) (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05; Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eComparison of FoP-Q-SF scores between groups\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eParameter\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLSN Group (n\u0026thinsp;=\u0026thinsp;179)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHSN Group (n\u0026thinsp;=\u0026thinsp;221)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003eW\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFoP Score\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e33(29,42)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e33(29,38)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e20692.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.427\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePhysiological Health\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e18(16,22)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e19(16,22)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e19199.500\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.613\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003esociety-family\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e14(11,17)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e14(12,16)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e20273.500\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.666\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\u003ch2\u003eAssessment of Illness Perception\u003c/h2\u003e\u003cp\u003eNo significant differences were observed between groups in total IPQ scores or its cognitive, emotional, and understanding dimensions (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05; Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eComparison of Illness Perception Scores between Groups\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eParameter\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLSN Group (n\u0026thinsp;=\u0026thinsp;179)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHSN Group (n\u0026thinsp;=\u0026thinsp;221)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003eW\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal IPQ Score\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e41(36,48)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e41(36,45)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e20021.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.834\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCognition\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e24(19,30.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e24(21,28)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e19841.500\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.957\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEmotion\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e13(11,15)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e12(11,14)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e20601.500\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.470\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUnderstanding\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4(3,5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4(3,5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e19820.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.972\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\u003ch2\u003eAssessment of Psychological Resilience\u003c/h2\u003e\u003cp\u003eThe LSN group had significantly higher scores than the HSN group for total psychological resilience, optimism, and self-efficacy (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). No significant difference was found for tenacity (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05; Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eComparison of Psychological Resilience Scores between Groups\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eParameter\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLSN Group (n\u0026thinsp;=\u0026thinsp;179)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHSN Group (n\u0026thinsp;=\u0026thinsp;221)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003eW\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePsychological Resilience\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e58(40,67)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e51(39,65)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e22814.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.008\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOptimism\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e10(8,12)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e9(7,12)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e22611.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.013\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSelf-Efficacy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e20(14,25)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e17(14,22)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e22917.500\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.006\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eToughness\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e26(18,32.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e23(18,29)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e21883.500\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.067\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec19\" class=\"Section2\"\u003e\u003ch2\u003eAssessment of Anxiety and Depression\u003c/h2\u003e\u003cp\u003eAnxiety scores were significantly lower in the LSN group compared to the HSN group (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Depression scores did not differ significantly between groups (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05; Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eComparison of Anxiety and Depression Scores between Groups\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eParameter\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLSN Group (n\u0026thinsp;=\u0026thinsp;179)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHSN Group (n\u0026thinsp;=\u0026thinsp;221)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003eW\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAnxiety\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e50(48,53)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e50(50,52)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e17183.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.022\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDepression\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e50(47,53)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e50(48,52)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e19620.500\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.890\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec20\" class=\"Section2\"\u003e\u003ch2\u003eAssessment of physical status and cognitive function\u003c/h2\u003e\u003cp\u003eThe LSN group had significantly higher scores than the HSN group for the FS-14, TFI, MoCA, OWBS, and SSRS (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001 for all except TFI P\u0026thinsp;=\u0026thinsp;0.017). No significant difference was found for FES scores (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05; Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eComparison of physical status and cognitive function between groups\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eParameter\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLSN Group (n\u0026thinsp;=\u0026thinsp;179)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHSN Group (n\u0026thinsp;=\u0026thinsp;221)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003eW\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFatigue Scale 14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e10(8,11)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e10(10,12)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e14898.500\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTFI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e10(7,11)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e10(10,12)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e17061.500\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.017\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFall Efficacy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e9(8,10)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e9(8,10)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e17758.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.070\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMoCA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e27(25,29.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e25(23,27)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e27705.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOverall Well-Being\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e70(66,76.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e68(65,72)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e24240.500\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSocial Support\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e40(36,46)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e36(32,41)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e25203.500\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec21\" class=\"Section2\"\u003e\u003ch2\u003eAssessment of quality of life\u003c/h2\u003e\u003cp\u003eNo significant differences were found between groups for any SF-36 domain scores (Physical Functioning, Role-Physical, Bodily Pain, General Health, Vitality, Social Functioning, Role-Emotional, Mental Health, Health Transition) or the total SF-36 score (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05; Table\u0026nbsp;\u003cspan refid=\"Tab8\" class=\"InternalRef\"\u003e8\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab8\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 8\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eComparison of Quality of Life Scores between Groups\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eParameter\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLSN Group (n\u0026thinsp;=\u0026thinsp;179)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHSN Group (n\u0026thinsp;=\u0026thinsp;221)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003eW\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePhysical Functioning\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e40(40,50)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e40(40,60)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e19664.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.918\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRole-Physical\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e50(25,62.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e50(25,50)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e19276.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.641\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBodily Pain\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e62(52,62)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e62(42,62)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e20425.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.564\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGeneral Health\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e40(40,50)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e40(40,50)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e21563.500\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.108\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVitality\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e45(35,50)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e45(35,50)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e19810.500\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.978\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSocial Functioning\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e55.56(44.44,66.67)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e55.56(44.44,66.67)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e21888.500\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.061\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRole-Emotional\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e66.67(33.33,66.67)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e66.67(33.33,66.67)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e20489.500\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.474\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMental Health\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e56(44,60)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e56(44,60)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e20567.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.484\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHealth Transition\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e25(25,50)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e25(25,50)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e21023.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.195\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSF-36 Total Score\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e433.11(389.77,499.78)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e431(387,478.11)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e21101.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.251\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec22\" class=\"Section2\"\u003e\u003ch2\u003eCorrelation analysis of factors influencing SNB in elderly patients with CHD\u003c/h2\u003e\u003cp\u003eCorrelation analysis revealed a negative relationship between SNB and factors such as psychological resilience, optimism, self-efficacy, MoCA scores, overall well-being, and social support (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). It was positively correlated with cardiac function classification, anxiety scores, Fatigue Scale 14 scores, and TFI scores (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Table\u0026nbsp;\u003cspan refid=\"Tab9\" class=\"InternalRef\"\u003e9\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab9\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 9\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eCorrelation analysis of factors influencing SNB in elderly patients with CHD\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eParameter\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eρ\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCardiac Function Classification\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-0.145\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.004\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePsychological Resilience\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-0.132\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.008\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOptimism\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-0.125\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.013\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSelf-Efficacy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-0.137\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.006\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAnxiety\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.114\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.022\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFatigue Scale 14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.217\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTFI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.119\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.017\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMoCA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-0.348\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOverall Well-Being\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-0.195\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSocial Support\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-0.237\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cdiv id=\"Sec23\" class=\"Section3\"\u003e\u003ch2\u003eUnivariate logistic regression analysis of factors influencing SNB in elderly patients with CHD\u003c/h2\u003e\u003cp\u003eUnivariate logistic regression analysis revealed that cardiac function classification, psychological resilience scores, optimism, self-efficacy, TFI scores and overall well-being were significantly associated with the occurrence of SNB (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Anxiety scores, Fatigue Scale 14 scores, MoCA scores and social support were not significantly different (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05) (Table\u0026nbsp;\u003cspan refid=\"Tab10\" class=\"InternalRef\"\u003e10\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab10\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 10\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eUnivariate logistic regression analysis of Factors influencing SNB in elderly patients with CHD\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eParameter\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRegression Coefficient\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eStandard Error\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eWald\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eOR(95%CI)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCardiac Function Classification\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.361\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.120\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e3.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.003\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.697(0.549\u0026ndash;0.881)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePsychological Resilience\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-0.018\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.007\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-2.625\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.009\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.982(0.968\u0026ndash;0.995)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOptimism\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-0.099\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.041\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-2.411\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.016\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.906(0.835\u0026ndash;0.981)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSelf-Efficacy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-0.050\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.017\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-2.900\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.004\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.951(0.919\u0026ndash;0.984)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAnxiety\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.044\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.029\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.531\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.126\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.045(0.989\u0026ndash;1.107)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFatigue Scale 14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.305\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.056\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e5.474\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e4.389\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.357(1.221\u0026ndash;1.521)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTFI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.082\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.033\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.465\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.014\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.085(1.017\u0026ndash;1.159)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMoCA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-0.268\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.041\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-6.454\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.091\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.765(0.703\u0026ndash;0.828)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOverall Well-Being\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-0.044\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.012\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-3.562\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.957(0.934\u0026ndash;0.980)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSocial Support\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-0.056\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.012\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-4.799\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.597\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.945(0.923\u0026ndash;0.967)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn the context of the aging of the global population, health management for elderly patients with CHD has become a pivotal issue in the public health discourse. This study conducted a comparative analysis of elderly CHD patients with low versus high levels of SNB, examining demographic characteristics, disease attributes, fear of disease progression, illness perception, psychological resilience, anxiety and depression levels, physical and mental health status, quality of life, and SNB determinants. The findings elucidate several critical factors influencing SNB among this population.\u003c/p\u003e\u003cp\u003eNotably, while the two groups had no significant differences in most demographic or clinical characteristics, a significant disparity existed in cardiac function classification. This aligns with previous research by Riegel et al[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e], which indicated that attenuated cardiac function restricts physical activity, adversely impacting daily life engagement and subsequently increasing SNB. Patients categorized with better cardiac function are at greater risk for SNB, likely owing to the associated limitations on daily activities and negative effects on mental health, ultimately leading to compromised self-care capabilities.Furthermore, the correlation between cardiac function classification and SNB suggests that clinical interventions should prioritize patient\u0026rsquo;s cardiac function management and indirectly reduce the occurrence of SNB by improving cardiac function.\u003c/p\u003e\u003cp\u003eFurthermore, in this study, the LSN group scored significantly higher on measures of psychological resilience, optimism, and self-efficacy but presented significantly lower anxiety scores than did the HSN group. Higher psychological resilience allows patients to manage the stressors associated with chronic illness effectively. Consequently, they can maintain a positive outlook that mitigates the incidence of SNB. This observation is consistent with a body of literature suggesting that psychological resilience is an important protective factor against SNB in elderly CHD patients.It serves as an intrinsic protective mechanism, assisting patients in sustaining positive emotional states and enhancing their coping strategies when confronting health-related challenges, thereby diminishing SNB. These findings demonstrate that robust psychological resilience is a pivotal determinant of sustained quality of life[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e].This research emphasizes the importance of cultivating psychological resilience through clinical interventions such as psychological counseling and group therapy,to help patients strengthen their capacity to cope with disease challenges.\u003c/p\u003e\u003cp\u003eIn addition, compared with the HSN group, the LSN group demonstrated superior performance on the Fatigue Scale 14, TFI, MoCA, overall well-being, and social support measures. This further underscores the significance of both physical and cognitive health in reducing SNB. Low fatigue levels, superior cognitive function, and high levels of overall well-being and social support provide patients with essential emotional and practical resources, alleviating their psychological burdens and consequently abating SNB. The literature highlights the importance of both physical and mental well-being, along with social support, as vital components in the self-management of chronic conditions[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e].These factors, together with psychological resilience, constitute important resources for elderly CHD patients to face with disease challenges. These factors enhance patients' self-support ability and mitigate psychological stress, contributing to reduced SNB and improved overall health outcomes.\u003c/p\u003e\u003cp\u003eThe correlation analysis further revealed that psychological resilience, optimism, self-efficacy, MoCA score, overall well-being, and social support are inversely associated with SNB, and higher levels of SNB are correlated with higher levels of cardiac function classification,elevated anxiety, fatigue, and TFI. These findings suggest a need for clinical practices to prioritize the mental health of patients and social support to mitigate SNB. The results of this study resonate with those of prior studies, reaffirming the vital roles of psychological resilience, social support, and cognitive function in the self-management of elderly CHD patients[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Moreover, fatigue management and frailty prevention are crucial considerations in clinical intervention strategies[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe Kansas City Cardiomyopathy Questionnaire (KCCQ) is a widely used and recognized assessment tool for coronary heart disease patients. The reason for using the SF-36 to assess quality of life in this study is that, as a generic quality-of-life scale, the SF-36 can comprehensively evaluate the physical and psychological health dimensions of CHD patients.This study focused on extensive influencing factors for SNB,rather than solely on the impact of cardiac symptoms on quality of life.Nevertheless,future research could use more disease-specific scales like the KCCQ to explore the relationship between SNB and quality of life more deeply.\u003c/p\u003e\u003cp\u003eNonetheless, this study has several limitations. This was a cross-sectional analysis conducted within a single center, which may introduce selection and information biases, potentially limiting the generalizability of the findings. Future research should encompass larger-scale, multicenter prospective studies to substantiate these results.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eIn conclusion, the factors influencing SNB in elderly CHD patients are multifaceted. Among them, cardiac function classification, psychological resilience, cognitive function, overall well-being, and social support are identified as key determinants. Clinical practitioners should prioritize comprehensive assessments of elderly CHD patients,including cardiac function, mental health status, cognitive function, and social support.This study lays a foundation for clinical interventions. It is advocated that healthcare professionals incorporate assessments of these critical factors into routine care for elderly CHD patients and implement tailored interventions, thus lowering SNB incidence and ultimately enhancing patient quality of life.\u003c/p\u003e\u003cdiv id=\"Sec26\" class=\"Section2\"\u003e\u003ch2\u003eRelevance for clinical practice\u003c/h2\u003e\u003cp\u003eThis study underscores the need to address psychological resilience, anxiety, social support, and cognitive function to prevent SNB in elderly CHD patients. The identification of NYHA functional class as an independent predictor highlights the interplay of physical and psychological factors. Clinicians should incorporate assessments of these domains into routine care and develop personalized interventions. Targeting these key determinants can reduce SNB incidence and enhance the quality of life for this vulnerable population.\u003c/p\u003e\u003c/div\u003e"},{"header":"Abbreviations","content":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003eSNB:\u003c/em\u003e\u003c/strong\u003e Self-neglect behavior\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eCHD:\u003c/em\u003e\u003c/strong\u003e Coronary heart disease\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eSESN:\u003c/em\u003e\u003c/strong\u003e Elderly self-neglect\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eLSN:\u003c/em\u003e\u003c/strong\u003e Low self-neglect\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eHSN:\u0026nbsp;\u003c/em\u003e\u003c/strong\u003eHigh self-neglect\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eFoP-Q-SF:\u003c/em\u003e\u003c/strong\u003e Fear of Progression Questionnaire-Short Form\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eIPQ:\u003c/em\u003e\u003c/strong\u003e Illness Perception Questionnaire\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003ePRS:\u003c/em\u003e\u003c/strong\u003e Psychological Resilience Scale\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eSAS:\u003c/em\u003e\u003c/strong\u003e Self-Rating Anxiety Scale\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eSDS:\u0026nbsp;\u003c/em\u003e\u003c/strong\u003eSelf-Rating Depression Scale\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eFS:\u003c/em\u003e\u003c/strong\u003e Fatigue Scale\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eTFI:\u0026nbsp;\u003c/em\u003e\u003c/strong\u003eTilburg frailty indicator\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eMoCA:\u0026nbsp;\u003c/em\u003e\u003c/strong\u003eMontreal Cognitive Assessment\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eOWBS:\u0026nbsp;\u003c/em\u003e\u003c/strong\u003eOverall Well-Being Scale\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eSSAS:\u0026nbsp;\u003c/em\u003e\u003c/strong\u003eSocial Support Assessment Scale\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eOR:\u0026nbsp;\u003c/em\u003e\u003c/strong\u003eodds ratio\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eCI:\u0026nbsp;\u003c/em\u003e\u003c/strong\u003econfidence interval\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003ePCI:\u0026nbsp;\u003c/em\u003e\u003c/strong\u003epercutaneous coronary intervention\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the National Nature Science Foundation of China (82302219) and the Chongqing Sports Bureau Project (B202496).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eContribution of the paper\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMeiqi Liu (First Author): Conceptualization, Data Curation, Formal Analysis, Investigation, Methodology, Software, Visualization,Writing-Original Draft, Writing-Review\u0026amp; Editing;\u003c/p\u003e\n\u003cp\u003eXiaoli Wang: Conceptualization, Formal Analysis, Investigation, Methodology, Supervision;\u003c/p\u003e\n\u003cp\u003eCan Wang: Methodology, Supervision, Validation;\u003c/p\u003e\n\u003cp\u003eCan Wang: Data Curation, Investigation, Software;\u003c/p\u003e\n\u003cp\u003eXingsheng Li: Conceptualization, Methodology, Supervision;\u003c/p\u003e\n\u003cp\u003eShiqun Zhou: Visualization,Writing-Original Draft, Writing-Review\u0026amp; Editing;\u003c/p\u003e\n\u003cp\u003eLanlan Lou: Conceptualization, Data Curation, Formal Analysis;\u003c/p\u003e\n\u003cp\u003eGuoxiu Li (Corresponding Author): Conceptualization, Funding Acquisition, Resources, Supervision, Validation, Writing-Original Draft, Writing-Review \u0026amp;Editing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll procedures conducted in studies involving human participants adhered to the ethical standards set forth by the institutional and national research committee, in accordance with the 1964\u0026nbsp;Helsinki Declaration and its subsequent amendments, or equivalent ethical standards. Due to the retrospective nature of the study, Ethics Committee of the Second Affiliated Hospital of Chongqing Medical University waived the need of obtaining informed consent.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated and analysed during the current study are not publicly available because the data could be used for further research on other topics, but are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAmbrosini AP, Fishman ES, Damluji AA, Nanna MG. 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Understanding professionals\u0026rsquo; perspectives and experiences of elder self-neglect: A systematic review and meta‐synthesis of qualitative studies. 2022; 54: 24\u0026ndash;30.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"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":"bmc-geriatrics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bgtc","sideBox":"Learn more about [BMC Geriatrics](http://bmcgeriatr.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bgtc/default.aspx","title":"BMC Geriatrics","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Elderly coronary heart disease, Self-neglect behavior, Influencing factors, Psychological resilience, Cognitive function, Cardiac function","lastPublishedDoi":"10.21203/rs.3.rs-7295771/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7295771/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eObjective\u003c/h2\u003e\u003cp\u003eThis study aimed to investigate the influencing factors of self-neglect behavior (SNB) in elderly patients with coronary heart disease (CHD) and provide a basis for clinical intervention.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eA retrospective analysis was conducted on 400 elderly patients with coronary heart disease who visited our hospital from January 2023 and June 2025.Based on the scores of the Elder Self-Neglect Scale (SESN), the patients were divided into a Low Self-Neglect (LSN) group (n\u0026thinsp;=\u0026thinsp;179) and a High Self-Neglect (HSN) group (n\u0026thinsp;=\u0026thinsp;221). Data were collected on the patients' general information, disease-related assessments, psychological evaluations, physical status, cognitive function assessments, and quality of life evaluations. Pearson and Spearman correlation analyses were used to explore the relationship between self-neglect behaviors (SNB) and various factors, while univariate logistic regression analysis was performed to identify the influencing factors of SNB.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eThere were no significant differences in age, gender, and education level between the two groups (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05). However, there was a significant difference in the New York Heart Association (NYHA) functional classification between the two groups (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). The LSN group had significantly higher scores in psychological resilience, optimism, and self-efficacy than the HSN group (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). The LSN group had significantly lower anxiety scores than the HSN group (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). The LSN group also had significantly higher scores in the Fatigue Scale-14, Timed Up and Go (TUG) test, Montreal Cognitive Assessment (MoCA), overall well-being, and social support compared to the HSN group (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Correlation and logistic regression analyses showed that NYHA functional classification, psychological resilience, optimism, self-efficacy, fatigue, frailty, cognitive function, overall well-being, and social support were independent influencing factors of SNB in elderly patients with CHD.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e\u003cp\u003eSNB in elderly patients with CHD is influenced by multiple factors. Clinical healthcare providers should pay attention to patients\u0026rsquo; psychological resilience, anxiety, social support, and cognitive function, and formulate individualized health management plans to improve their health status and quality of life.\u003c/p\u003e\u003ch2\u003eClinical trial number\u003c/h2\u003e\u003cp\u003enot applicable.\u003c/p\u003e","manuscriptTitle":"Identification of Key Influencing Factors and Correlation Analysis of Self-Neglect Behavior in Elderly Patients with Coronary Heart Disease","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-23 11:45:02","doi":"10.21203/rs.3.rs-7295771/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"223566483528515123675301285589782401728","date":"2025-10-10T06:47:41+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-10-10T06:05:59+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-09-09T11:37:25+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-08-20T11:30:37+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-08-20T06:49:39+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Geriatrics","date":"2025-08-20T06:46:32+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-geriatrics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bgtc","sideBox":"Learn more about [BMC Geriatrics](http://bmcgeriatr.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bgtc/default.aspx","title":"BMC Geriatrics","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"a5a144e6-4037-4cfc-90f2-6b913b7a107c","owner":[],"postedDate":"October 23rd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2025-10-23T11:45:02+00:00","versionOfRecord":[],"versionCreatedAt":"2025-10-23 11:45:02","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7295771","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7295771","identity":"rs-7295771","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}