Subclinical hypothyroidism: a new risk factor for prediction of heart failure with improved ejection fraction

Subclinical hypothyroidism: a new risk factor for prediction of heart failure with improved ejection fraction | 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 Subclinical hypothyroidism: a new risk factor for prediction of heart failure with improved ejection fraction Haiqing Zhou, Qi Wang, Zhiquan Liu, Guohong Wu, Wenqing Zhou, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4904289/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 17 Dec, 2024 Read the published version in Internal and Emergency Medicine → Version 1 posted 4 You are reading this latest preprint version Abstract BACKGROUND Heart failure (HF) with improved ejection fraction (HFimpEF) has gradually attracted widespread attention in recent years for its better clinical prognosis. In this study, we attempted to investigate the relationship between subclinical hypothyroidism (SCH) and HFimpEF. METHODS This study retrospectively collected clinical data on patients with HF with reduced ejection fraction (HFrEF) hospitalized at the First Affiliated Hospital of USTC from March 2015 to September 2023, and divided into two groups as euthyroidism or SCH according to the baseline thyroid function. Then patients were further categorized into HFimpEF (follow-up LVEF > 40% and absolute increase ≥ 10%) and persistent HFrEF based on their LVEF on the echocardiograms during the follow-up period. Afterwards, logistic regression was used to estimate the effect of SCH on HFimpEF. RESULTS A total of 916 patients with HFrEF met the inclusion and exclusion criteria, and 396 patients (43.2%) progressed to HFimpEF status during the follow-up period. Compared with HFrEF patients, the prevalence of SCH is lower in HFimpEF patients (9.3% vs. 14.4%, P = 0.020). Univariate logistic regression analysis indicates that SCH was a potential risk factor for HFimpEF (OR: 0.612 [95% CI 0.403–0.928], P = 0.021). After adjusting for multiple factors in logistic regression, the odds ratios of HFrEF patients with SCH progressing to HFimpEF decreased by 37.8% (OR: 0.622 [95%CI 0.397–0.974], P = 0.038) compared with patients with euthyroidism. CONCLUSIONS This study demonstrated that thyroid function affects the improvement of cardiac function in patients with HFrEF and SCH is an independent risk factor for HFimpEF. HFimpEF HFrEF Subclinical hypothyroidism Thyroid function Figures Figure 1 Figure 2 INTRODUCTION Currently, heart failure (HF) affects more than 64 million people worldwide, the prevalence is expected to increase by 34% in the next few decades[ 1 – 2 ]. Approximately 40% of HF is HF with reduced ejection fraction (HFrEF) in China, which is often associated with progressive ventricular remodeling and dilatation that underlie adverse cardiovascular outcomes [ 3 ]. With the rapid development of drug and device therapy for HF, approximately 20%-50% of HFrEF patients can significantly improve their left ventricular ejection fraction (LVEF) [ 4 ], those with a baseline LVEF ≤ 40%, a ≥ 10 point increase from baseline LVEF, and a second measurement of LVEF > 40% are defined as HF with improved ejection fraction (HFimpEF) [ 5 ].Studies have shown significant reductions in HF readmission rates, cardiovascular mortality and all-cause mortality in patients with HFimpEF [ 6 ]. Consequently, identifying the factors that influence the improvement of LVEF at an early stage is of significant clinical importance for improving the prognosis of HFrEF patients. Thyroid hormones play an important role in the regulation of the cardiovascular system, and the most common type of thyroid dysfunction is subclinical hypothyroidism (SCH), with an estimated prevalence of 3%- 15% in the general population [ 7 ]. Previous studies have shown that SCH can result in left ventricular dysfunction, atherosclerosis, and is significantly associated with the occurrence and progression of HF [ 8 – 9 ]. However, there is a lack of clinical evidence regarding the impact of SCH on the improvement of LVEF among HFrEF patients. This study aims to evaluate the impact of SCH on HFimpEF by retrospectively analyzing the baseline characteristics, thyroid function, and LVEF outcomes of patients with HFrEF. METHODS Study Population This is a single-center, retrospective study, and the study population selected from patients with HFrEF who were first hospitalized for HF at the First Affiliated Hospital of USTC from March 2015 to September 2023, then the follow-up echocardiographic parameters were collected until March 2024. The inclusion criteria were as follows: 1) age ≥ 18 years; 2) HF diagnostic criteria in accordance with “Chinese guidelines for the diagnosis and treatment of heart failure 2024” [ 10 ], baseline LVEF ≤ 40%, N-terminal pro-B-type (NT-pro BNP) ≥ 300 pg/mL; 3) at least 2 comparable echocardiograms (If a patient undergone two more echocardiograms during the follow-up period, the highest LVEF value was included in the analysis). The exclusion criteria were as follows: 1) the interval between two echocardiograms < 3 months; 2) patients with missing or unclassifiable thyroid function data; 3) patients with hyperthyroidism, subclinical hyperthyroidism or hypothyroidism; 4) patients who have undergone thyroid surgery and received amiodarone or thyroid hormone treatment before. This study finally consisted of 916 patients with HFrEF, the flow chart is shown in Fig. 1. The study protocol was in accordance with the tenets of the Declaration of Helsinki and approved by the Hospital Ethics Committee (Approved No. of ethics committee: 2024-RE-268). Clinical and Biochemical Assessments By searching the medical record system of the First Affiliated Hospital of USTC, collected the patients' initial vital signs, medical history, medication and the results of the first laboratory measurements during hospitalization (including thyroid function, hemoglobin, serum creatinine, blood lipids and NT-pro BNP), features with missing data for < 10% of the patients were subjected to multiple imputation. BMI was calculated as weight/height 2 (kg/m 2 ). The serum levels of thyroid hormones and TSH were measured using chemiluminescence, euthyroidism was defined as normal TSH (0.45–4.5 mIU/L), and subclinical hypothyroidism was defined as TSH > 4.5 and < 20 mIU/L with normal FT3 (2.1–5.4 pmol/L) and FT4 (9–25 pmol/L) [ 11 ]. Echocardiographic Examination The echocardiographic parameters investigated included left atrial diameter (LAD), left ventricular end-diastolic diameter (LVEDD), LVESD, left ventricular end-systolic diameter (LVESD), systolic pulmonary artery pressure (SPAP) and LVEF. To assess the relationship between thyroid function and LVEF outcomes, the enrolled HFrEF patients were categorized into 2 groups based on the LVEF values obtained from echocardiography during the follow-up period: those with a baseline LVEF ≤ 40%, a second measurement of LVEF > 40% and 10% increase from baseline LVEF are defined as HFimpEF [ 5 ], then the remaining patients were classified as having persistent HFrEF. Statistical Analysis Continuous variables were presented as median (interquartile range) and were compared using the Mann-Whitney U test. Categorical variables were described as frequency and ratio and were compared using the chi-square test, and the Mann-Whitney U test was used for the comparison of ranked data (NYHA class). Univariable logistic regression analysis was performed to screen potential influencing factors for HFimpEF. Afterwards, multivariable logistic regression models were constructed to validate the independent effect of SCH on HFimpEF. In Model 1, age and gender were adjusted. In Model 2, additional adjustment for LVEF baseline, BMI, LAD, LVEDD, SPAP and NT-pro BNP; medical history and medication use. In Model 3, additional adjustment for coronary heart disease, PCI and diabetes, medication use of ARNI/ACEI/ARB, SGLT2 inhibitors. All analyses were performed using SPSS version 24.0 (IBM Corp., Armonk, NY, USA). A P -value < 0.05 was considered statistically significant. RESULTS Baseline Characteristics of the Study Population A total of 916 patients with HFrEF with data on thyroid function and echocardiography during the follow-up period were included in this study, with a median age of 64 years and 629 patients (68.7%) were male. Of whom 357 patients (39.0%) had coronary heart disease, 313 patients (34.2%) had hypertension, and 177 patients (19.3%) had diabetes. Additionally, 677 individuals (73.9%) were treated with ARNI/ACEI/ARB drugs, 685 (74.8%) with beta-blockers, 146 (15.9%) with SGLT2 inhibitors, and 813 (88.8%) with Antisterone. Patients were classified into the euthyroid group with 804 cases (87.8%) and the SCH group with 112 cases (12.2%) according to their thyroid function. The baseline characteristics of the two groups are shown in Table 1, compared with those with euthyroidism, patients in the SCH group had a higher proportion of women ( P =0.01), higher NT-pro BNP values ( P =0.046), and higher SPAP ( P =0.003), a lower median LVEF ( P =0.033) during follow-up, and a lower proportion of patients on ARNI/ACEI/ARB analogs ( P =0.044). No significant differences were observed in baseline LVEF values, other clinical characteristics, or medication treatment status (Table 1). Table 1. Main baseline characteristics of patients according to thyroid functional status Variables Euthyroidism (N =804) SCH (N =112) P value Age (years) 64 (52, 71) 63 (53, 72) 0.546 Females n, (%) 240 (29.9) 47 (42.0) 0.010 BMI (kg/m 2 ) 24.03 (21.61, 26.73) 23.84 (21.61, 26.50) 0.781 Heart rate (beats/min) 81 (71, 96) 80 (68, 90) 0.134 SBP (mmHg) 121 (109, 134) 120 (110, 134) 0.669 DBP (mmHg) 78 (69, 87) 78 (69, 86) 0.668 NYHA class NYHA class III n, (%) 464 (57.7) 63 (56.3) 0.711 NYHA class IV n, (%) 265 (33.0) 39 (34.8) Baseline EF (%) 31 (27, 36) 31 (25, 37) 0.833 Change in EF (%) 10 (3, 20) 8 (3, 18) 0.054 EF MAX (%) 42 (33, 52) 40 (28, 50) 0.033 HFimpEF n, (%) 359 (44.7) 37 (33.0) 0.020 LAD (mm) 48 (43, 53) 50 (44, 55) 0.136 LVEDD (mm) 69 (63, 76) 69 (61, 78) 0.506 LVESD (mm) 59 (53, 65) 58 (51, 68) 0.726 SPAP (mmHg) 43 (32, 54) 46 (37, 60) 0.003 Medical history Coronary heart disease n, (%) 321 (39.9) 36 (32.1) 0.114 Hypertension n, (%) 277 (34.5) 36 (32.1) 0.629 Atrial fibrillation n, (%) 144 (17.9) 27 (24.1) 0.115 PCI n, (%) 55 (6.8) 10 (8.9) 0.420 Diabetes n, (%) 157 (19.5) 20 (17.9) 0.675 Laboratory measurements NT-pro BNP (pg/mL) 2983 (1494, 5803) 3566 (1909, 6968) 0.046 Hemoglobin (g/L) 132 (122, 143) 130 (121, 142) 0.364 Serum creatinine (μmol/mL) 85 (71, 105) 92 (76, 105) 0.099 LDL cholesterol (mmol/L) 2.34 (1.81, 2.83) 2.13 (1.78, 2.86) 0.177 FT3 (pmol/L) 4.37 (3.90, 5.00) 4.26 (3.47, 4.61) < 0.001 FT4 (pmol/L) 14.89 (12.97, 17.15) 14.22 (12.60, 16.68) 0.049 TSH (mIU/L) 1.99 (1.25, 2.81) 5.90 (5.18, 7.48) < 0.001 Medication ARNI /ACEI/ARB n, (%) 603 (75.0) 74 (66.1) 0.044 SGLT2 inhibitors n, (%) 126 (15.7) 20 (17.9) 0.554 Beta-blockers n, (%) 609 (75.7) 76 (67.9) 0.072 Antisterone n, (%) 715 (88.9) 98 (87.5) 0.653 Loop diuretic n, (%) 723 (89.9) 99 (88.4) 0.617 Abbreviations: SCH, subclinical hypothyroidism; BMI, body mass index; SBP, systolic blood pressure; DBP, diastolic blood pressure; NYHA, New York Heart Association; EF, ejection fraction; HFimpEF, heart failure with improved ejection fraction; LAD, left atrial diameter; LVEDD, left ventricular end-diastolic diameter; LVESD, left ventricular end-systolic diameter; SPAP, systolic pulmonary artery pressure; PCI, percutaneous coronary intervention; NT-pro BNP, N-terminal pro-B-type; LDL, low-density lipoprotein; FT3, free triiodothyronine; FT4, free thyroxine; TSH, thyroid-stimulating hormone; ARNI, angiotensin-receptor neprilysin inhibitors; ACEI, angiotensin-converting enzyme inhibitors; ARB, angiotensin receptor blockers; SGLT2, sodium-glucose cotransporter 2. P -values were obtained by using the Mann-Whitney U test for continuous variables and the chi-square test for categorical variables. Potential influencing factor of HFimpEF By collecting the LVEF values during the follow-up period of the enrolled HFrEF patients, a total of 396 (43.2%) patients improved their LVEF to HFimpEF. In comparison with patients with persistent HFrEF, HFimpEF patients had slightly higher baseline LVEF values ( P =0.005), with an improvement in median LVEF values from 32% to 54.0%, whereas the median LVEF only increased by 4% in patients with persistent HFrEF. Table S1 showed that compared with persistent HFrEF patients, HFimpEF patients had a lower prevalence of SCH (9.3% Vs. 14.4%, P =0.020), and were relatively younger ( P =0.026) with higher heart rate ( P =0.023) SBP ( P ＜0.001) and DBP ( P = 0.006) (Table S1). Univariable logistic regression analysis indicated that elevated LAD, LVEDD, LVESD and SPAP ( P all< 0.001), serum creatinine (OR: 0.996, P =0.012), and NT-pro BNP (OR: 0.956, P =0.001) may served as potential risk factors for HFimpEF. In contrast, the use of SGLT2 inhibitors (OR: 1.478, P =0.031) were potential protective factors for HFimpEF (Table S2). Association between SCH and HFimpEF Univariable logistic regression analysis showed that SCH (OR: 0.612 [95% CI 0.403-0.928]) was negatively associated with the progress of HFimpEF (Table S1). After adjusting for age and gender (Model 1), baseline LVEF, BMI, laboratory measurements and echocardiographic parameters (Model 2), medical history and medication (Model 3), SCH was persistently associated with HFimpEF. As shown in Model 3, the probability of HFrEF patients with SCH progressing to HFimpEF decreased by 37.8% (OR: 0.622 [95%CI 0.397-0.974]) compared with patients with euthyroidism (Table 2). Subgroup analysis showed that there was no significant difference in the effect of SCH on HFimpEF among subgroups defined by gender, age, BMI and cardiovascular risk factors (Figure 2). Table 2. Multivariate analysis for SCH and development of HFimpEF Models OR (95%CI) P value Model 1 0.600 (0.394- 0.915) 0.018 Model 2 0.616 (0.394- 0.962) 0.033 Model 3 0.622 (0.397- 0.974) 0.038 Model 1, adjustment for age and gender; Model 2, additional adjustment for LVEF baseline, BMI, LAD, LVEDD, SPAP, NT-pro BNP; Model 3, additional adjustment for coronary heart disease, PCI and diabetes, medication use of ARNI/ACEI/ARB, SGLT2 inhibitors; Abbreviations: HFimpEF, heart failure with improved ejection fraction; SCH, subclinical hypothyroidism; BMI, body mass index; EF, ejection fraction; LAD, left atrial diameter; LVEDD, left ventricular end-diastolic diameter; SPAP, systolic pulmonary artery pressure; NT-pro BNP, N-terminal pro-B-type; PCI, percutaneous coronary intervention; ARNI, angiotensin-receptor neprilysin inhibitors; ACEI, angiotensin-converting enzyme inhibitors; ARB, angiotensin receptor blockers; SGLT2, sodium-glucose cotransporter 2. DISCUSSION The results of this study suggested that SCH is an independent risk factor for the development of HFimpEF. What' s more, the odds ratios of HFrEF patients with SCH progressing to HFimpEF decreased by 37.8% after further adjusting for multiple factors in logistic regression potential confounding factors. Subgroup analysis showed that there was no significant difference in the effect of SCH on HFimpEF among subgroups defined by gender, age, BMI and cardiovascular risk factors. In recent years, there have been significant advancements in the treatment of HFrEF. Some patients may demonstrate an improvement in LVEF due to the pharmacological and device-based therapies, which may lead to improve clinical outcomes [ 12 – 13 ]. This study indicated that after a minimum interval of 3 months, 43.2% of HFrEF patients showed an improvement in their LVEF values. Bermejo et al. demonstrated that compared to HFrEF patients, HFimpEF patients had significantly reduced rates of all-cause mortality (HFrEF: HFimpEF HR = 2.22, 95% CI 1.189–4.186) and hospitalization (HFrEF: HFimpEF HR = 1.388, 95% CI 1.002–1.924) at the 1-year follow-up [ 14 ]. Even compared with HFpEF and HFmrEF patients, HFimpEF can still show better outcomes in adverse HF-related outcomes such as left ventricular assist device implantation, heart transplantation and all-cause mortality [ 15 – 16 ]. Given the favorable clinical prognosis, the clinical and biochemical factors associated with HFimpEF have received increasing attention in recent years. Available data suggested that younger age, female gender, non-ischemic cardiomyopathy, and fewer cardiac comorbidities may be protective factors for LVEF improvements [ 17 – 19 ]. Similarly, our univariate analysis showed that younger age, no history of PCI treatment, smaller cardiac structural changes and SPAP, lower NT-pro BNP and serum creatinine levels, and the use of SGLT2i inhibitors may be associated with improved LVEF, further exploration of HFimpEF-related influencing factors is beneficial for determining prognosis and adjusting treatment plans. The relationship between metabolic disorders and improvement in LVEF has recently attracted increased attention these years. Ye et al. observed that higher BMI was associated with the recovery of LVEF among HFrEF patients (OR 1.75, [95% CI 1.12–2.72]) at the six-months follow-up [ 20 ]. In addition, Yang et al. demonstrated that in a 12-months follow-up, insulin resistance was negatively associated with LVEF recovery in patients without diabetes (OR 0.572, [95% CI 0.385–0.827]), they also observed that higher HbA1c levels were independently and negatively associated with HFimpEF in diabetic patients (HbA1c > 7.1% Vs. ≤6.2%: OR 0.48, [95% CI 0.28–0.81]) [ 21 – 22 ]. In this study, we investigated the effect of thyroid function on LVEF improvement and revealed that the rate of HFimpEF was lower among HFrEF patients with SCH, and the probability decreased by 37.8% after adjusting for multiple factors, moreover the prevalence of SCH was higher in patients with persistent HFrEF. All of the evidence above suggested an adverse effect of SCH on HFimpEF. The association between SCH and HF has been widely documented, with several studies demonstrating a significant increase in the prevalence of HF, cardiac events and all-cause mortality in patients with SCH [ 23 – 24 ]. The underlying mechanism may be attributed to the impact of hypothyroidism on the structure and function of the heart, as well as cardiac load and lipid metabolism [ 25 – 26 ]. In this study, compared with patients with euthyroidism, patients with SCH had higher baseline values of SPAP and NT-pro BNP, which may be related to the poor improvement of LVEF. Whether to initiate thyroid hormone replacement therapy in patients with SCH combined with HF remains controversial. Some studies have shown that thyroid hormone replacement therapy has no significant effect on cardiovascular outcomes [ 27 – 28 ]. However, a recent multicenter RCT study confirmed that after 24 weeks of treatment with low-dose levothyroxine (L-T4) in patients with SCH and HFrEF, both the 6-min walk test distance ( P < 0.001) and the NYHA classification ( P = 0.033) were significantly improved [ 29 ]. Combined with the confirmation of SCH as an independent risk factor for LVEF improvement in HFrEF patients in this study, suggesting that further studies are needed in the future to implement more precise and stratified management measures for HFrEF patients with SCH with the aim of further improving cardiac function. To the best of our knowledge, this is the first study to demonstrate the association between SCH and HFimpEF. However, as a single-center, retrospective study, there are inherent limitations. Firstly, baseline information were missing in some patients, and secondly, the time to improvement of LVEF varied considerably among different patients, with a relatively long lag in follow-up. However, considering that this article aims to examine the relationship between SCH and HFimpEF, no specific time frame was set for HFimpEF. Thirdly, the patients' enrollment time span varies considerably, and with the updates of HF guidelines, the recommended medication regimens for patients have changed. Accordingly, we adjusted the use of HF-related medications in the multivariate analysis. Finally, only the baseline thyroid function was available for analysis, which may changed during the follow-up period. CONCLUSIONS In conclusion, this study reveals that SCH is an independent risk factor for the development of HFimpEF. Therapies targeted at improving SCH might provide favorable effects on patients with HFrEF. Declarations Acknowledgements None. Author contributions Chen K, Wang Q and Zhou H contributed to the study conception and design. Data collection was performed by Zhou H, Liu Z, Wu G, Zhou W and Yang D. Zhou H analyzed the data and wrote the first draft of the manuscript, Chen K and Wang Q revised the manuscript. All authors read and approved the final manuscript. Funding None. 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Supplementary Files onlinesupplementSCHandHFimpEF.docx Cite Share Download PDF Status: Published Journal Publication published 17 Dec, 2024 Read the published version in Internal and Emergency Medicine → Version 1 posted Reviewers agreed at journal 23 Aug, 2024 Reviewers invited by journal 22 Aug, 2024 Editor assigned by journal 17 Aug, 2024 First submitted to journal 16 Aug, 2024 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. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-4904289","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":343917674,"identity":"15dd4bed-774b-40fe-b068-5c3905a98238","order_by":0,"name":"Haiqing Zhou","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABAUlEQVRIie3PsUrEQBCA4VkCk2bPeiCe8REiByJ4D7PLQdKsYGcKkcDB2kjqgOK9hVgmHGwVW5trEnwBK0khYnKiVsmlFNy/GBiYrxgAm+0vRgBONxHAfZXvdIDuMh9NEOpkPtvjRowh25DVSSjvSR0OCv92abzzy5Np6l0/V/JxHWlQAE380EvYnQm9zNBM75cXgSzXZxqecnZTbnqJQ+rY40hSkxIksCUsFQ7T/QS35OOXROjwYJDwjkx0RyLTzlAg7iBE4eJ0kra/kHICUc6PNEdRDP3iZ4tiw9+upqssqusmJt9fvRRVE/eT71gCPPjZ8p33X8StxhzabDbbP+wT5klTFq3cBFoAAAAASUVORK5CYII=","orcid":"","institution":"The First Affiliated Hospital of USTC: Anhui Provincial Hospital","correspondingAuthor":true,"prefix":"","firstName":"Haiqing","middleName":"","lastName":"Zhou","suffix":""},{"id":343917675,"identity":"0511eeca-9137-4e9e-ac85-86df2bc40cf6","order_by":1,"name":"Qi Wang","email":"","orcid":"","institution":"The First Affiliated Hospital of USTC: Anhui Provincial Hospital","correspondingAuthor":false,"prefix":"","firstName":"Qi","middleName":"","lastName":"Wang","suffix":""},{"id":343917676,"identity":"fd96eda4-35ae-415b-90ca-6ac2626f4674","order_by":2,"name":"Zhiquan Liu","email":"","orcid":"","institution":"The First Affiliated Hospital of USTC: Anhui Provincial Hospital","correspondingAuthor":false,"prefix":"","firstName":"Zhiquan","middleName":"","lastName":"Liu","suffix":""},{"id":343917677,"identity":"e83707e9-f464-40f5-9faa-b8ef6bc77892","order_by":3,"name":"Guohong Wu","email":"","orcid":"","institution":"The First Affiliated Hospital of USTC: Anhui Provincial Hospital","correspondingAuthor":false,"prefix":"","firstName":"Guohong","middleName":"","lastName":"Wu","suffix":""},{"id":343917678,"identity":"e6d34c58-ae8c-4ae9-aa58-42e391218970","order_by":4,"name":"Wenqing Zhou","email":"","orcid":"","institution":"The First Affiliated Hospital of USTC: Anhui Provincial Hospital","correspondingAuthor":false,"prefix":"","firstName":"Wenqing","middleName":"","lastName":"Zhou","suffix":""},{"id":343917679,"identity":"814af9e9-e8b1-48ca-8e2a-fc7421c321e2","order_by":5,"name":"Dongmei Yang","email":"","orcid":"","institution":"The First Affiliated Hospital of USTC: Anhui Provincial Hospital","correspondingAuthor":false,"prefix":"","firstName":"Dongmei","middleName":"","lastName":"Yang","suffix":""},{"id":343917680,"identity":"9b445b21-8890-4a56-9d22-401d88d4b64c","order_by":6,"name":"Kangyu Chen","email":"","orcid":"","institution":"The First Affiliated Hospital of USTC: Anhui Provincial Hospital","correspondingAuthor":false,"prefix":"","firstName":"Kangyu","middleName":"","lastName":"Chen","suffix":""}],"badges":[],"createdAt":"2024-08-13 05:41:53","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4904289/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4904289/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s11739-024-03827-w","type":"published","date":"2024-12-17T15:58:25+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":66739315,"identity":"01354a8c-01d8-48f4-b154-27afdc08f1c4","added_by":"auto","created_at":"2024-10-16 05:31:44","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":111818,"visible":true,"origin":"","legend":"\u003cp\u003eLegend not included with this version.\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e","description":"","filename":"Figure1.flowchat.png","url":"https://assets-eu.researchsquare.com/files/rs-4904289/v1/5eb1ee40951d4332571c5c85.png"},{"id":66739317,"identity":"63473f65-66c9-4af4-8d59-90faac5e395c","added_by":"auto","created_at":"2024-10-16 05:31:44","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":162518,"visible":true,"origin":"","legend":"\u003cp\u003eLegend not included with this version.\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e","description":"","filename":"Figure2.Stratifiedanalysis.png","url":"https://assets-eu.researchsquare.com/files/rs-4904289/v1/6cfd6211dc6698cd70ff8bf9.png"},{"id":72202609,"identity":"316dd522-2fe9-458e-8b03-952d6d654c67","added_by":"auto","created_at":"2024-12-23 16:15:04","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":761038,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4904289/v1/db4d46b3-5d69-47df-b3ec-1fba5001ec50.pdf"},{"id":66739316,"identity":"b1995e3b-5c12-458c-af68-5eaa5be07f29","added_by":"auto","created_at":"2024-10-16 05:31:44","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":22779,"visible":true,"origin":"","legend":"","description":"","filename":"onlinesupplementSCHandHFimpEF.docx","url":"https://assets-eu.researchsquare.com/files/rs-4904289/v1/fc89dcc0e343d6aac2265cc7.docx"}],"financialInterests":"","formattedTitle":"Subclinical hypothyroidism: a new risk factor for prediction of heart failure with improved ejection fraction","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eCurrently, heart failure (HF) affects more than 64\u0026nbsp;million people worldwide, the prevalence is expected to increase by 34% in the next few decades[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Approximately 40% of HF is HF with reduced ejection fraction (HFrEF) in China, which is often associated with progressive ventricular remodeling and dilatation that underlie adverse cardiovascular outcomes [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. With the rapid development of drug and device therapy for HF, approximately 20%-50% of HFrEF patients can significantly improve their left ventricular ejection fraction (LVEF) [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e], those with a baseline LVEF\u0026thinsp;\u0026le;\u0026thinsp;40%, a\u0026thinsp;\u0026ge;\u0026thinsp;10 point increase from baseline LVEF, and a second measurement of LVEF\u0026thinsp;\u0026gt;\u0026thinsp;40% are defined as HF with improved ejection fraction (HFimpEF) [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].Studies have shown significant reductions in HF readmission rates, cardiovascular mortality and all-cause mortality in patients with HFimpEF [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Consequently, identifying the factors that influence the improvement of LVEF at an early stage is of significant clinical importance for improving the prognosis of HFrEF patients.\u003c/p\u003e \u003cp\u003eThyroid hormones play an important role in the regulation of the cardiovascular system, and the most common type of thyroid dysfunction is subclinical hypothyroidism (SCH), with an estimated prevalence of 3%- 15% in the general population [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Previous studies have shown that SCH can result in left ventricular dysfunction, atherosclerosis, and is significantly associated with the occurrence and progression of HF [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. However, there is a lack of clinical evidence regarding the impact of SCH on the improvement of LVEF among HFrEF patients. This study aims to evaluate the impact of SCH on HFimpEF by retrospectively analyzing the baseline characteristics, thyroid function, and LVEF outcomes of patients with HFrEF.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy Population\u003c/h2\u003e \u003cp\u003eThis is a single-center, retrospective study, and the study population selected from patients with HFrEF who were first hospitalized for HF at the First Affiliated Hospital of USTC from March 2015 to September 2023, then the follow-up echocardiographic parameters were collected until March 2024. The inclusion criteria were as follows: 1) age\u0026thinsp;\u0026ge;\u0026thinsp;18 years; 2) HF diagnostic criteria in accordance with \u0026ldquo;Chinese guidelines for the diagnosis and treatment of heart failure 2024\u0026rdquo; [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e], baseline LVEF\u0026thinsp;\u0026le;\u0026thinsp;40%, N-terminal pro-B-type (NT-pro BNP)\u0026thinsp;\u0026ge;\u0026thinsp;300 pg/mL; 3) at least 2 comparable echocardiograms (If a patient undergone two more echocardiograms during the follow-up period, the highest LVEF value was included in the analysis). The exclusion criteria were as follows: 1) the interval between two echocardiograms \u0026lt; 3 months; 2) patients with missing or unclassifiable thyroid function data; 3) patients with hyperthyroidism, subclinical hyperthyroidism or hypothyroidism; 4) patients who have undergone thyroid surgery and received amiodarone or thyroid hormone treatment before. This study finally consisted of 916 patients with HFrEF, the flow chart is shown in Fig.\u0026nbsp;1. The study protocol was in accordance with the tenets of the Declaration of Helsinki and approved by the Hospital Ethics Committee (Approved No. of ethics committee: 2024-RE-268).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eClinical and Biochemical Assessments\u003c/h2\u003e \u003cp\u003eBy searching the medical record system of the First Affiliated Hospital of USTC, collected the patients' initial vital signs, medical history, medication and the results of the first laboratory measurements during hospitalization (including thyroid function, hemoglobin, serum creatinine, blood lipids and NT-pro BNP), features with missing data for \u0026lt;\u0026thinsp;10% of the patients were subjected to multiple imputation. BMI was calculated as weight/height\u003csup\u003e2\u003c/sup\u003e (kg/m\u003csup\u003e2\u003c/sup\u003e). The serum levels of thyroid hormones and TSH were measured using chemiluminescence, euthyroidism was defined as normal TSH (0.45\u0026ndash;4.5 mIU/L), and subclinical hypothyroidism was defined as TSH\u0026thinsp;\u0026gt;\u0026thinsp;4.5 and \u0026lt;\u0026thinsp;20 mIU/L with normal FT3 (2.1\u0026ndash;5.4 pmol/L) and FT4 (9\u0026ndash;25 pmol/L) [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eEchocardiographic Examination\u003c/h2\u003e \u003cp\u003eThe echocardiographic parameters investigated included left atrial diameter (LAD), left ventricular end-diastolic diameter (LVEDD), LVESD, left ventricular end-systolic diameter (LVESD), systolic pulmonary artery pressure (SPAP) and LVEF. To assess the relationship between thyroid function and LVEF outcomes, the enrolled HFrEF patients were categorized into 2 groups based on the LVEF values obtained from echocardiography during the follow-up period: those with a baseline LVEF\u0026thinsp;\u0026le;\u0026thinsp;40%, a second measurement of LVEF\u0026thinsp;\u0026gt;\u0026thinsp;40% and 10% increase from baseline LVEF are defined as HFimpEF [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e], then the remaining patients were classified as having persistent HFrEF.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eContinuous variables were presented as median (interquartile range) and were compared using the Mann-Whitney U test. Categorical variables were described as frequency and ratio and were compared using the chi-square test, and the Mann-Whitney U test was used for the comparison of ranked data (NYHA class). Univariable logistic regression analysis was performed to screen potential influencing factors for HFimpEF. Afterwards, multivariable logistic regression models were constructed to validate the independent effect of SCH on HFimpEF. In Model 1, age and gender were adjusted. In Model 2, additional adjustment for LVEF baseline, BMI, LAD, LVEDD, SPAP and NT-pro BNP; medical history and medication use. In Model 3, additional adjustment for coronary heart disease, PCI and diabetes, medication use of ARNI/ACEI/ARB, SGLT2 inhibitors. All analyses were performed using SPSS version 24.0 (IBM Corp., Armonk, NY, USA). A \u003cem\u003eP\u003c/em\u003e-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"RESULTS","content":"\u003cp\u003e\u003cstrong\u003eBaseline Characteristics of the Study Population\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA total of 916 patients with HFrEF with data on thyroid function and echocardiography\u0026nbsp;during the follow-up period\u0026nbsp;were included in this study, with a median age of 64 years and 629 patients (68.7%) were male. Of whom 357 patients (39.0%) had coronary heart disease, 313 patients (34.2%) had hypertension, and 177 patients (19.3%) had diabetes. Additionally, 677 individuals (73.9%) were treated with ARNI/ACEI/ARB drugs, 685 (74.8%) with beta-blockers, 146 (15.9%) with SGLT2 inhibitors, and 813 (88.8%) with Antisterone.\u003c/p\u003e\n\u003cp\u003ePatients were classified into the euthyroid group with 804 cases (87.8%) and the SCH group with 112 cases (12.2%) according to their thyroid function. The baseline characteristics of the two groups are shown in Table 1, compared with those with euthyroidism, patients in the SCH group had a higher proportion of women (\u003cem\u003eP\u003c/em\u003e=0.01), higher NT-pro BNP values (\u003cem\u003eP\u003c/em\u003e=0.046), and higher SPAP (\u003cem\u003eP\u003c/em\u003e=0.003), a lower median LVEF (\u003cem\u003eP\u003c/em\u003e=0.033) during follow-up, and a lower proportion of patients on ARNI/ACEI/ARB analogs (\u003cem\u003eP\u003c/em\u003e=0.044). No significant differences were observed in baseline LVEF values, other clinical characteristics, or medication treatment status (Table 1).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1. Main baseline characteristics of patients according to thyroid functional status\u003c/strong\u003e\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"652\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.30321592649311%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariables\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.02450229709035%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eEuthyroidism\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;(N =804)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.033690658499236%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eSCH (N =112)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.638591117917304%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eP\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.30321592649311%\" valign=\"top\"\u003e\n \u003cp\u003eAge (years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.02450229709035%\" valign=\"top\"\u003e\n \u003cp\u003e64 (52, 71)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.033690658499236%\" valign=\"top\"\u003e\n \u003cp\u003e63 (53, 72)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.638591117917304%\" valign=\"top\"\u003e\n \u003cp\u003e0.546\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.30321592649311%\" valign=\"top\"\u003e\n \u003cp\u003eFemales n, (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.02450229709035%\" valign=\"top\"\u003e\n \u003cp\u003e240 (29.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.033690658499236%\" valign=\"top\"\u003e\n \u003cp\u003e47 (42.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.638591117917304%\" valign=\"top\"\u003e\n \u003cp\u003e0.010\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.30321592649311%\" valign=\"top\"\u003e\n \u003cp\u003eBMI (kg/m\u003csup\u003e2\u003c/sup\u003e)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.02450229709035%\" valign=\"top\"\u003e\n \u003cp\u003e24.03 (21.61, 26.73)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.033690658499236%\" valign=\"top\"\u003e\n \u003cp\u003e23.84 (21.61, 26.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.638591117917304%\" valign=\"top\"\u003e\n \u003cp\u003e0.781\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.30321592649311%\" valign=\"top\"\u003e\n \u003cp\u003eHeart rate (beats/min)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.02450229709035%\" valign=\"top\"\u003e\n \u003cp\u003e81 (71, 96)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.033690658499236%\" valign=\"top\"\u003e\n \u003cp\u003e80 (68, 90)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.638591117917304%\" valign=\"top\"\u003e\n \u003cp\u003e0.134\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.30321592649311%\" valign=\"top\"\u003e\n \u003cp\u003eSBP (mmHg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.02450229709035%\" valign=\"top\"\u003e\n \u003cp\u003e121 (109, 134)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.033690658499236%\" valign=\"top\"\u003e\n \u003cp\u003e120 (110, 134)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.638591117917304%\" valign=\"top\"\u003e\n \u003cp\u003e0.669\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.30321592649311%\" valign=\"top\"\u003e\n \u003cp\u003eDBP (mmHg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.02450229709035%\" valign=\"top\"\u003e\n \u003cp\u003e78 (69, 87)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.033690658499236%\" valign=\"top\"\u003e\n \u003cp\u003e78 (69, 86)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.638591117917304%\" valign=\"top\"\u003e\n \u003cp\u003e0.668\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eNYHA class\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.30321592649311%\" valign=\"top\"\u003e\n \u003cp\u003eNYHA class III n, (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.02450229709035%\" valign=\"top\"\u003e\n \u003cp\u003e464 (57.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.033690658499236%\" valign=\"top\"\u003e\n \u003cp\u003e63 (56.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.638591117917304%\" rowspan=\"2\"\u003e\n \u003cp\u003e0.711\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.82149046793761%\" valign=\"top\"\u003e\n \u003cp\u003eNYHA class IV n, (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"31.7157712305026%\" valign=\"top\"\u003e\n \u003cp\u003e265 (33.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.462738301559792%\" valign=\"top\"\u003e\n \u003cp\u003e39 (34.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.30321592649311%\" valign=\"top\"\u003e\n \u003cp\u003eBaseline EF (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.02450229709035%\" valign=\"top\"\u003e\n \u003cp\u003e31 (27, 36)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.033690658499236%\" valign=\"top\"\u003e\n \u003cp\u003e31 (25, 37)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.638591117917304%\" valign=\"top\"\u003e\n \u003cp\u003e0.833\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.30321592649311%\" valign=\"top\"\u003e\n \u003cp\u003eChange in EF (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.02450229709035%\" valign=\"top\"\u003e\n \u003cp\u003e10 (3, 20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.033690658499236%\" valign=\"top\"\u003e\n \u003cp\u003e8 (3, 18)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.638591117917304%\" valign=\"top\"\u003e\n \u003cp\u003e0.054\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.30321592649311%\" valign=\"top\"\u003e\n \u003cp\u003eEF MAX (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.02450229709035%\" valign=\"top\"\u003e\n \u003cp\u003e42 (33, 52)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.033690658499236%\" valign=\"top\"\u003e\n \u003cp\u003e40 (28, 50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.638591117917304%\" valign=\"top\"\u003e\n \u003cp\u003e0.033\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.30321592649311%\" valign=\"top\"\u003e\n \u003cp\u003eHFimpEF n, (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.02450229709035%\" valign=\"top\"\u003e\n \u003cp\u003e359 (44.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.033690658499236%\" valign=\"top\"\u003e\n \u003cp\u003e37 (33.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.638591117917304%\" valign=\"top\"\u003e\n \u003cp\u003e0.020\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.30321592649311%\" valign=\"top\"\u003e\n \u003cp\u003eLAD (mm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.02450229709035%\" valign=\"top\"\u003e\n \u003cp\u003e48 (43, 53)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.033690658499236%\" valign=\"top\"\u003e\n \u003cp\u003e50 (44, 55)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.638591117917304%\" valign=\"top\"\u003e\n \u003cp\u003e0.136\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.30321592649311%\" valign=\"top\"\u003e\n \u003cp\u003eLVEDD (mm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.02450229709035%\" valign=\"top\"\u003e\n \u003cp\u003e69 (63, 76)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.033690658499236%\" valign=\"top\"\u003e\n \u003cp\u003e69 (61, 78)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.638591117917304%\" valign=\"top\"\u003e\n \u003cp\u003e0.506\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.30321592649311%\" valign=\"top\"\u003e\n \u003cp\u003eLVESD (mm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.02450229709035%\" valign=\"top\"\u003e\n \u003cp\u003e59 (53, 65)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.033690658499236%\" valign=\"top\"\u003e\n \u003cp\u003e58 (51, 68)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.638591117917304%\" valign=\"top\"\u003e\n \u003cp\u003e0.726\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.30321592649311%\" valign=\"top\"\u003e\n \u003cp\u003eSPAP (mmHg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.02450229709035%\" valign=\"top\"\u003e\n \u003cp\u003e43 (32, 54)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.033690658499236%\" valign=\"top\"\u003e\n \u003cp\u003e46 (37, 60)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.638591117917304%\" valign=\"top\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eMedical history\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.30321592649311%\" valign=\"top\"\u003e\n \u003cp\u003eCoronary heart disease n, (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.02450229709035%\" valign=\"top\"\u003e\n \u003cp\u003e321 (39.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.033690658499236%\" valign=\"top\"\u003e\n \u003cp\u003e36 (32.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.638591117917304%\" valign=\"top\"\u003e\n \u003cp\u003e0.114\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.30321592649311%\" valign=\"top\"\u003e\n \u003cp\u003eHypertension n, (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.02450229709035%\" valign=\"top\"\u003e\n \u003cp\u003e277 (34.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.033690658499236%\" valign=\"top\"\u003e\n \u003cp\u003e36 (32.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.638591117917304%\" valign=\"top\"\u003e\n \u003cp\u003e0.629\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.30321592649311%\" valign=\"top\"\u003e\n \u003cp\u003eAtrial fibrillation n, (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.02450229709035%\" valign=\"top\"\u003e\n \u003cp\u003e144 (17.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.033690658499236%\" valign=\"top\"\u003e\n \u003cp\u003e27 (24.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.638591117917304%\" valign=\"top\"\u003e\n \u003cp\u003e0.115\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.30321592649311%\" valign=\"top\"\u003e\n \u003cp\u003ePCI n, (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.02450229709035%\" valign=\"top\"\u003e\n \u003cp\u003e55 (6.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.033690658499236%\" valign=\"top\"\u003e\n \u003cp\u003e10 (8.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.638591117917304%\" valign=\"top\"\u003e\n \u003cp\u003e0.420\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.30321592649311%\" valign=\"top\"\u003e\n \u003cp\u003eDiabetes n, (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.02450229709035%\" valign=\"top\"\u003e\n \u003cp\u003e157 (19.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.033690658499236%\" valign=\"top\"\u003e\n \u003cp\u003e20 (17.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.638591117917304%\" valign=\"top\"\u003e\n \u003cp\u003e0.675\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eLaboratory measurements\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.30321592649311%\" valign=\"top\"\u003e\n \u003cp\u003eNT-pro BNP (pg/mL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.02450229709035%\" valign=\"top\"\u003e\n \u003cp\u003e2983 (1494, 5803)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.033690658499236%\" valign=\"top\"\u003e\n \u003cp\u003e3566 (1909, 6968)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.638591117917304%\" valign=\"top\"\u003e\n \u003cp\u003e0.046\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.30321592649311%\" valign=\"top\"\u003e\n \u003cp\u003eHemoglobin (g/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.02450229709035%\" valign=\"top\"\u003e\n \u003cp\u003e132 (122, 143)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.033690658499236%\" valign=\"top\"\u003e\n \u003cp\u003e130 (121, 142)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.638591117917304%\" valign=\"top\"\u003e\n \u003cp\u003e0.364\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.30321592649311%\" valign=\"top\"\u003e\n \u003cp\u003eSerum creatinine (\u0026mu;mol/mL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.02450229709035%\" valign=\"top\"\u003e\n \u003cp\u003e85 (71, 105)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.033690658499236%\" valign=\"top\"\u003e\n \u003cp\u003e92 (76, 105)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.638591117917304%\" valign=\"top\"\u003e\n \u003cp\u003e0.099\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.30321592649311%\" valign=\"top\"\u003e\n \u003cp\u003eLDL cholesterol (mmol/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.02450229709035%\" valign=\"top\"\u003e\n \u003cp\u003e2.34 (1.81, 2.83)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.033690658499236%\" valign=\"top\"\u003e\n \u003cp\u003e2.13 (1.78, 2.86)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.638591117917304%\" valign=\"top\"\u003e\n \u003cp\u003e0.177\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.30321592649311%\" valign=\"top\"\u003e\n \u003cp\u003eFT3 (pmol/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.02450229709035%\" valign=\"top\"\u003e\n \u003cp\u003e4.37 (3.90, 5.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.033690658499236%\" valign=\"top\"\u003e\n \u003cp\u003e4.26 (3.47, 4.61)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.638591117917304%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.30321592649311%\" valign=\"top\"\u003e\n \u003cp\u003eFT4 (pmol/L)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.02450229709035%\" valign=\"top\"\u003e\n \u003cp\u003e14.89 (12.97, 17.15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.033690658499236%\" valign=\"top\"\u003e\n \u003cp\u003e14.22 (12.60, 16.68)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.638591117917304%\" valign=\"top\"\u003e\n \u003cp\u003e0.049\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.30321592649311%\" valign=\"top\"\u003e\n \u003cp\u003eTSH (mIU/L)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.02450229709035%\" valign=\"top\"\u003e\n \u003cp\u003e1.99 (1.25, 2.81)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.033690658499236%\" valign=\"top\"\u003e\n \u003cp\u003e5.90 (5.18, 7.48)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.638591117917304%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eMedication\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.30321592649311%\" valign=\"top\"\u003e\n \u003cp\u003eARNI /ACEI/ARB n, (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.02450229709035%\" valign=\"top\"\u003e\n \u003cp\u003e603 (75.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.033690658499236%\" valign=\"top\"\u003e\n \u003cp\u003e74 (66.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.638591117917304%\" valign=\"top\"\u003e\n \u003cp\u003e0.044\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.30321592649311%\" valign=\"top\"\u003e\n \u003cp\u003eSGLT2 inhibitors n, (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.02450229709035%\" valign=\"top\"\u003e\n \u003cp\u003e126 (15.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.033690658499236%\" valign=\"top\"\u003e\n \u003cp\u003e20 (17.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.638591117917304%\" valign=\"top\"\u003e\n \u003cp\u003e0.554\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.30321592649311%\" valign=\"top\"\u003e\n \u003cp\u003eBeta-blockers n, (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.02450229709035%\" valign=\"top\"\u003e\n \u003cp\u003e609 (75.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.033690658499236%\" valign=\"top\"\u003e\n \u003cp\u003e76 (67.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.638591117917304%\" valign=\"top\"\u003e\n \u003cp\u003e0.072\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.30321592649311%\" valign=\"top\"\u003e\n \u003cp\u003eAntisterone n, (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.02450229709035%\" valign=\"top\"\u003e\n \u003cp\u003e715 (88.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.033690658499236%\" valign=\"top\"\u003e\n \u003cp\u003e98 (87.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.638591117917304%\" valign=\"top\"\u003e\n \u003cp\u003e0.653\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.30321592649311%\" valign=\"top\"\u003e\n \u003cp\u003eLoop diuretic n, (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.02450229709035%\" valign=\"top\"\u003e\n \u003cp\u003e723 (89.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.033690658499236%\" valign=\"top\"\u003e\n \u003cp\u003e99 (88.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.638591117917304%\" valign=\"top\"\u003e\n \u003cp\u003e0.617\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003eAbbreviations:\u0026nbsp;\u003c/strong\u003eSCH, subclinical hypothyroidism; BMI, body mass index; SBP, systolic blood pressure; DBP, diastolic blood pressure; NYHA, New York Heart Association; EF, ejection fraction; HFimpEF, heart failure with improved ejection fraction; LAD, left atrial diameter; LVEDD, left ventricular end-diastolic diameter; LVESD, left ventricular end-systolic diameter; SPAP, systolic pulmonary artery pressure; PCI, percutaneous coronary intervention; NT-pro BNP, N-terminal pro-B-type; LDL, low-density lipoprotein; FT3, free triiodothyronine; FT4, free thyroxine; TSH, thyroid-stimulating hormone; ARNI, angiotensin-receptor neprilysin inhibitors; ACEI, angiotensin-converting enzyme inhibitors; ARB, angiotensin receptor blockers; SGLT2, sodium-glucose cotransporter 2.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eP\u003c/em\u003e-values were obtained by using the Mann-Whitney U test for continuous variables and the chi-square test for categorical variables.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePotential influencing factor of HFimpEF\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBy collecting the LVEF values during the follow-up period of the enrolled HFrEF patients, a total of 396 (43.2%) patients improved their LVEF to HFimpEF. In comparison with patients with persistent HFrEF, HFimpEF patients had slightly higher baseline LVEF values (\u003cem\u003eP\u003c/em\u003e=0.005), with an improvement in median LVEF values from 32% to 54.0%, whereas the median LVEF only increased by 4% in patients with persistent HFrEF. Table S1 showed that compared with persistent HFrEF patients, HFimpEF patients had a lower prevalence of SCH (9.3% Vs. 14.4%, \u003cem\u003eP\u003c/em\u003e=0.020), and were relatively younger (\u003cem\u003eP\u003c/em\u003e=0.026) with higher heart rate (\u003cem\u003eP\u003c/em\u003e=0.023) SBP (\u003cem\u003eP\u003c/em\u003e＜0.001) and DBP (\u003cem\u003eP\u003c/em\u003e= 0.006) (Table S1).\u003c/p\u003e\n\u003cp\u003eUnivariable logistic regression analysis indicated that elevated LAD, LVEDD, LVESD and SPAP (\u003cem\u003eP\u003c/em\u003e all\u0026lt; 0.001), serum creatinine (OR: 0.996, \u003cem\u003eP\u003c/em\u003e=0.012), and NT-pro BNP (OR: 0.956, \u003cem\u003eP\u003c/em\u003e=0.001) may served as potential risk factors for HFimpEF. In contrast, the use of SGLT2 inhibitors (OR: 1.478, \u003cem\u003eP\u003c/em\u003e=0.031) were potential protective factors for HFimpEF (Table S2).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAssociation between SCH and HFimpEF\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eUnivariable logistic regression analysis showed that SCH (OR: 0.612 [95% CI 0.403-0.928]) was negatively associated with the progress of HFimpEF (Table S1). After adjusting for age and gender (Model 1), baseline LVEF, BMI, laboratory measurements and echocardiographic parameters (Model 2), medical history and medication (Model 3), SCH was persistently associated with HFimpEF. As shown in Model 3, the probability of HFrEF patients with SCH progressing to HFimpEF decreased by 37.8% (OR: 0.622 [95%CI 0.397-0.974]) compared with patients with euthyroidism (Table 2). Subgroup analysis showed that there was no significant difference in the effect of SCH on HFimpEF among subgroups defined by gender, age, BMI and cardiovascular risk factors (Figure 2).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2. Multivariate analysis for SCH and development of HFimpEF\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.250457038391225%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eModels\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"46.61791590493601%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eOR (95%CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.13162705667276%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eP\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.250457038391225%\" valign=\"top\"\u003e\n \u003cp\u003eModel 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"46.61791590493601%\" valign=\"top\"\u003e\n \u003cp\u003e0.600 (0.394- 0.915)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.13162705667276%\" valign=\"top\"\u003e\n \u003cp\u003e0.018\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.250457038391225%\" valign=\"top\"\u003e\n \u003cp\u003eModel 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"46.61791590493601%\" valign=\"top\"\u003e\n \u003cp\u003e0.616 (0.394- 0.962)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.13162705667276%\" valign=\"top\"\u003e\n \u003cp\u003e0.033\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.250457038391225%\" valign=\"top\"\u003e\n \u003cp\u003eModel 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"46.61791590493601%\" valign=\"top\"\u003e\n \u003cp\u003e0.622 (0.397- 0.974)\u0026nbsp; \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.13162705667276%\" valign=\"top\"\u003e\n \u003cp\u003e0.038\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eModel 1,\u003c/strong\u003e adjustment for age and\u0026nbsp;gender;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eModel 2,\u0026nbsp;\u003c/strong\u003eadditional adjustment for LVEF baseline, BMI, LAD, LVEDD, SPAP, NT-pro BNP;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eModel 3,\u0026nbsp;\u003c/strong\u003eadditional adjustment for coronary heart disease, PCI and diabetes, medication use of ARNI/ACEI/ARB, SGLT2 inhibitors;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAbbreviations:\u0026nbsp;\u003c/strong\u003eHFimpEF, heart failure with improved ejection fraction; SCH, subclinical hypothyroidism; BMI, body mass index; EF, ejection fraction; LAD, left atrial diameter; LVEDD, left ventricular end-diastolic diameter; SPAP, systolic pulmonary artery pressure; NT-pro BNP, N-terminal pro-B-type; PCI, percutaneous coronary intervention; ARNI, angiotensin-receptor neprilysin inhibitors; ACEI, angiotensin-converting enzyme inhibitors; ARB, angiotensin receptor blockers; SGLT2, sodium-glucose cotransporter 2.\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eThe results of this study suggested that SCH is an independent risk factor for the development of HFimpEF. What' s more, the odds ratios of HFrEF patients with SCH progressing to HFimpEF decreased by 37.8% after further adjusting for multiple factors in logistic regression potential confounding factors. Subgroup analysis showed that there was no significant difference in the effect of SCH on HFimpEF among subgroups defined by gender, age, BMI and cardiovascular risk factors.\u003c/p\u003e \u003cp\u003eIn recent years, there have been significant advancements in the treatment of HFrEF. Some patients may demonstrate an improvement in LVEF due to the pharmacological and device-based therapies, which may lead to improve clinical outcomes [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. This study indicated that after a minimum interval of 3 months, 43.2% of HFrEF patients showed an improvement in their LVEF values. Bermejo et al. demonstrated that compared to HFrEF patients, HFimpEF patients had significantly reduced rates of all-cause mortality (HFrEF: HFimpEF HR\u0026thinsp;=\u0026thinsp;2.22, 95% CI 1.189\u0026ndash;4.186) and hospitalization (HFrEF: HFimpEF HR\u0026thinsp;=\u0026thinsp;1.388, 95% CI 1.002\u0026ndash;1.924) at the 1-year follow-up [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Even compared with HFpEF and HFmrEF patients, HFimpEF can still show better outcomes in adverse HF-related outcomes such as left ventricular assist device implantation, heart transplantation and all-cause mortality [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eGiven the favorable clinical prognosis, the clinical and biochemical factors associated with HFimpEF have received increasing attention in recent years. Available data suggested that younger age, female gender, non-ischemic cardiomyopathy, and fewer cardiac comorbidities may be protective factors for LVEF improvements [\u003cspan additionalcitationids=\"CR18\" citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Similarly, our univariate analysis showed that younger age, no history of PCI treatment, smaller cardiac structural changes and SPAP, lower NT-pro BNP and serum creatinine levels, and the use of SGLT2i inhibitors may be associated with improved LVEF, further exploration of HFimpEF-related influencing factors is beneficial for determining prognosis and adjusting treatment plans.\u003c/p\u003e \u003cp\u003eThe relationship between metabolic disorders and improvement in LVEF has recently attracted increased attention these years. Ye et al. observed that higher BMI was associated with the recovery of LVEF among HFrEF patients (OR 1.75, [95% CI 1.12\u0026ndash;2.72]) at the six-months follow-up [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. In addition, Yang et al. demonstrated that in a 12-months follow-up, insulin resistance was negatively associated with LVEF recovery in patients without diabetes (OR 0.572, [95% CI 0.385\u0026ndash;0.827]), they also observed that higher HbA1c levels were independently and negatively associated with HFimpEF in diabetic patients (HbA1c\u0026thinsp;\u0026gt;\u0026thinsp;7.1% Vs. \u0026le;6.2%: OR 0.48, [95% CI 0.28\u0026ndash;0.81]) [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. In this study, we investigated the effect of thyroid function on LVEF improvement and revealed that the rate of HFimpEF was lower among HFrEF patients with SCH, and the probability decreased by 37.8% after adjusting for multiple factors, moreover the prevalence of SCH was higher in patients with persistent HFrEF. All of the evidence above suggested an adverse effect of SCH on HFimpEF.\u003c/p\u003e \u003cp\u003eThe association between SCH and HF has been widely documented, with several studies demonstrating a significant increase in the prevalence of HF, cardiac events and all-cause mortality in patients with SCH [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. The underlying mechanism may be attributed to the impact of hypothyroidism on the structure and function of the heart, as well as cardiac load and lipid metabolism [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. In this study, compared with patients with euthyroidism, patients with SCH had higher baseline values of SPAP and NT-pro BNP, which may be related to the poor improvement of LVEF.\u003c/p\u003e \u003cp\u003eWhether to initiate thyroid hormone replacement therapy in patients with SCH combined with HF remains controversial. Some studies have shown that thyroid hormone replacement therapy has no significant effect on cardiovascular outcomes [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. However, a recent multicenter RCT study confirmed that after 24 weeks of treatment with low-dose levothyroxine (L-T4) in patients with SCH and HFrEF, both the 6-min walk test distance (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and the NYHA classification (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.033) were significantly improved [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Combined with the confirmation of SCH as an independent risk factor for LVEF improvement in HFrEF patients in this study, suggesting that further studies are needed in the future to implement more precise and stratified management measures for HFrEF patients with SCH with the aim of further improving cardiac function.\u003c/p\u003e \u003cp\u003eTo the best of our knowledge, this is the first study to demonstrate the association between SCH and HFimpEF. However, as a single-center, retrospective study, there are inherent limitations. Firstly, baseline information were missing in some patients, and secondly, the time to improvement of LVEF varied considerably among different patients, with a relatively long lag in follow-up. However, considering that this article aims to examine the relationship between SCH and HFimpEF, no specific time frame was set for HFimpEF. Thirdly, the patients' enrollment time span varies considerably, and with the updates of HF guidelines, the recommended medication regimens for patients have changed. Accordingly, we adjusted the use of HF-related medications in the multivariate analysis. Finally, only the baseline thyroid function was available for analysis, which may changed during the follow-up period.\u003c/p\u003e"},{"header":"CONCLUSIONS","content":"\u003cp\u003eIn conclusion, this study reveals that SCH is an independent risk factor for the development of HFimpEF. Therapies targeted at improving SCH might provide favorable effects on patients with HFrEF.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNone.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eChen K, Wang Q and Zhou H contributed to the study conception and design. Data collection was performed by Zhou H, Liu Z, Wu G, Zhou W and Yang D. Zhou H analyzed the data and wrote the first draft of the manuscript, Chen K and Wang Q revised the manuscript. All authors read and approved the final manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNone.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data analyzed during the presented study are available upon reasonable request from the corresponding author.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of interest\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have no conflicts of interest to disclose.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eMaddox TM, Januzzi JL Jr, Allen LA, Breathett K, Brouse S, Butler J et al (2024) 2024 ACC Expert Consensus Decision Pathway for Treatment of Heart Failure With Reduced Ejection Fraction: A Report of the American College of Cardiology Solution Set Oversight Committee. J Am Coll Cardiol 83(15), 1444\u0026ndash;1488. https://doi.org/10.1016/j.jacc.2023.12.024.\u003c/li\u003e\n \u003cli\u003eSavarese G, Becher PM, Lund LH, Seferovic P, Rosano GMC, Coats AJS (2023) Global burden of heart failure: a comprehensive and updated review of epidemiology. Cardiovasc Res 118(17), 3272\u0026ndash;3287. https://doi.org/10.1093/cvr/cvac013.\u003c/li\u003e\n \u003cli\u003eHao G, Wang X, Chen Z, Zhang L, Zhang Y, Wei B, Zheng C,\u0026nbsp;et al (2020)\u0026nbsp;China Hypertension Survey Investigators. Prevalence of heart failure and left ventricular dysfunction in China: the China Hypertension Survey, 2012-2015. Eur J Heart Fail\u0026nbsp;\u003cem\u003e21\u003c/em\u003e(11), 1329\u0026ndash;1337. https://doi.org/10.1002/ejhf.1629.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eWilcox JE, Fang JC, Margulies KB, Mann DL (2020) Heart\u0026nbsp;Failure With Recovered Left\u0026nbsp;Ventricular Ejection Fraction: JACC Scientific Expert Panel. J Am Coll Cardiol\u0026nbsp;\u003cem\u003e76\u003c/em\u003e(6), 719\u0026ndash;734. https://doi.org/10.1016/j.jacc.2020.05.075.\u003c/li\u003e\n \u003cli\u003eBozkurt B, Coats AJS, Tsutsui H, Abdelhamid CM, Adamopoulos S, Albert N\u0026nbsp;et al (2021)\u0026nbsp;Universal definition and classification of heart failure: a report of the Heart Failure Society of America, Heart Failure Association of the European Society of Cardiology, Japanese Heart Failure Society and Writing Committee of the Universal Definition of Heart Failure: Endorsed by the Canadian Heart Failure Society, Heart Failure Association of India, Cardiac Society of Australia and New Zealand, and Chinese Heart Failure Association. 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Cell Rep Med \u003cem\u003e5\u003c/em\u003e(4), 101473. https://doi.org/10.1016/j.xcrm.2024.101473. \u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"internal-and-emergency-medicine","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"iaem","sideBox":"Learn more about [Internal and Emergency Medicine](http://link.springer.com/journal/11739)","snPcode":"11739","submissionUrl":"https://www.editorialmanager.com/iaem/default.aspx","title":"Internal and Emergency Medicine","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"HFimpEF, HFrEF, Subclinical hypothyroidism, Thyroid function","lastPublishedDoi":"10.21203/rs.3.rs-4904289/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4904289/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBACKGROUND\u003c/h2\u003e \u003cp\u003eHeart failure (HF) with improved ejection fraction (HFimpEF) has gradually attracted widespread attention in recent years for its better clinical prognosis. In this study, we attempted to investigate the relationship between subclinical hypothyroidism (SCH) and HFimpEF.\u003c/p\u003e\u003ch2\u003eMETHODS\u003c/h2\u003e \u003cp\u003eThis study retrospectively collected clinical data on patients with HF with reduced ejection fraction (HFrEF) hospitalized at the First Affiliated Hospital of USTC from March 2015 to September 2023, and divided into two groups as euthyroidism or SCH according to the baseline thyroid function. Then patients were further categorized into HFimpEF (follow-up LVEF\u0026thinsp;\u0026gt;\u0026thinsp;40% and absolute increase\u0026thinsp;\u0026ge;\u0026thinsp;10%) and persistent HFrEF based on their LVEF on the echocardiograms during the follow-up period. Afterwards, logistic regression was used to estimate the effect of SCH on HFimpEF.\u003c/p\u003e\u003ch2\u003eRESULTS\u003c/h2\u003e \u003cp\u003e A total of 916 patients with HFrEF met the inclusion and exclusion criteria, and 396 patients (43.2%) progressed to HFimpEF status during the follow-up period. Compared with HFrEF patients, the prevalence of SCH is lower in HFimpEF patients (9.3% vs. 14.4%, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.020). Univariate logistic regression analysis indicates that SCH was a potential risk factor for HFimpEF (OR: 0.612 [95% CI 0.403\u0026ndash;0.928], \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.021). After adjusting for multiple factors in logistic regression, the odds ratios of HFrEF patients with SCH progressing to HFimpEF decreased by 37.8% (OR: 0.622 [95%CI 0.397\u0026ndash;0.974], \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.038) compared with patients with euthyroidism.\u003c/p\u003e\u003ch2\u003eCONCLUSIONS\u003c/h2\u003e \u003cp\u003eThis study demonstrated that thyroid function affects the improvement of cardiac function in patients with HFrEF and SCH is an independent risk factor for HFimpEF.\u003c/p\u003e","manuscriptTitle":"Subclinical hypothyroidism: a new risk factor for prediction of heart failure with improved ejection fraction","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-10-16 05:31:39","doi":"10.21203/rs.3.rs-4904289/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"","date":"2024-08-23T17:36:17+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-08-23T00:58:15+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-08-17T11:39:41+00:00","index":"","fulltext":""},{"type":"submitted","content":"Internal and Emergency Medicine","date":"2024-08-16T07:55:37+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"internal-and-emergency-medicine","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"iaem","sideBox":"Learn more about [Internal and Emergency Medicine](http://link.springer.com/journal/11739)","snPcode":"11739","submissionUrl":"https://www.editorialmanager.com/iaem/default.aspx","title":"Internal and Emergency Medicine","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"1b7c8613-7fea-42d2-a1d7-d928ba9af24c","owner":[],"postedDate":"October 16th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-12-23T16:08:56+00:00","versionOfRecord":{"articleIdentity":"rs-4904289","link":"https://doi.org/10.1007/s11739-024-03827-w","journal":{"identity":"internal-and-emergency-medicine","isVorOnly":false,"title":"Internal and Emergency Medicine"},"publishedOn":"2024-12-17 15:58:25","publishedOnDateReadable":"December 17th, 2024"},"versionCreatedAt":"2024-10-16 05:31:39","video":"","vorDoi":"10.1007/s11739-024-03827-w","vorDoiUrl":"https://doi.org/10.1007/s11739-024-03827-w","workflowStages":[]},"version":"v1","identity":"rs-4904289","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4904289","identity":"rs-4904289","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}