Blunted Heart Rate Response Enhances Prognostic Value of Dipyridamole Stress SPECT for Cardiovascular Morbidity and Mortality in All-Comers

Blunted Heart Rate Response Enhances Prognostic Value of Dipyridamole Stress SPECT for Cardiovascular Morbidity and Mortality in All-Comers | 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 Blunted Heart Rate Response Enhances Prognostic Value of Dipyridamole Stress SPECT for Cardiovascular Morbidity and Mortality in All-Comers Alexander Izhaki, Aviram Akuka, Alexey Migranov, Diklah Geva, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8176602/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 10 You are reading this latest preprint version Abstract Background Dipyridamole stress cardiac 99mTc Single Photon Emission Computed Tomography (DS-SPECT) is a common method for detecting myocardial ischemia in selected patients. Blunted heart rate response (BHRR) during pharmacological stress is a known risk factor for mortality and morbidity. With increasing prevalence of referred patients with significant comorbidities, often excluded in studies, an all-comers population was evaluated to better represent the patients undergoing DS-SPECT. This study aimed to determine the prognostic significance of BHRR compared to DS-SPECT imaging results. Methods We conducted an all comer, single-center, retrospective cohort study. All patients subjected to DS-SPECT, years 2014 to 2017, were included. Results Study population consisted of 388 patients, 227 (58.5%) had normal imaging results, and 245 (63.1%) exhibited BHRR. During a mean follow-up of four years, multivariable analysis identified BHRR as the strongest independent predictor of cardiovascular death (HR 8.09, CI: 1.2–11.6, p < 0.05). Patients with abnormal DS-SPECT imaging and BHRR had a nearly fourfold increased risk of adverse cardiovascular events (HR 3.79, CI: 1.06–61.91, p < 0.05). Moreover, individuals demonstrating both abnormal imaging results and BHRR experienced the highest rate of all-cause mortality (HR 2.93, CI: 1.1–7.7, p < 0.01). Overall, BHRR significantly correlated with increased all-cause and cardiovascular mortality. Conclusions In unselected patients referred for DS-SPECT, BHRR was an independent predictor of cardiovascular mortality, stronger than imaging findings. When combined with abnormal imaging results, BHRR significantly improves the prediction value of DS-SPECT for cardiovascular morbidity and all-cause mortality. These findings suggest inclusion of BHRR in DS-SPECT studies. SPECT Dipyridamole ischemic heart disease blunted heart rate response Introduction 99mTc Single Photon Emission Computed Tomography (SPECT) is widely used to assess myocardial ischemia in patients with coronary artery disease (CAD)¹⁻⁶. Pharmacologic stress testing is typically reserved for those unable to exercise, or with left bundle-branch block or paced rhythms¹⁻³, as SPECT retains high sensitivity and specificity⁷⁻¹¹, with demonstrated cost-effectiveness in CAD detection¹²⁻¹⁵. One of the most commonly used agents for pharmacologic stress SPECT is Dipyridamole, an indirect coronary vasodilator¹⁶⁻¹⁷, known to improve diagnostic yield¹⁸⁻¹⁹ while maintaining a strong safety profile²⁰. Although low risk and normal SPECT test results are associated with low probability of major adverse cardiac events (MACE) 7–8,21−22 , in specific higher risk profile populations with comorbidities (especially: diabetes, atrial fibrillation, chronic renal impairment and elderly), a normal test result does not necessarily translate into low mortality and MACE risk 24 – 34 , with contradictory results previously reported for the elderly population 35 – 37 . Moreover, as the incidence of abnormal SPECT tests has progressively decreased, the proportion of these higher risk profile subjects among the testing population continued to grow 38 – 40 , thus potentially negatively influencing the predictive value of test results. Nevertheless, pharmacological stress SPECT also incorporates non-imaging prognostic data. Accumulating evidence have demonstrated that inadequately slower than expected (blunted) heart rate response to vasodilator injection is an independent risk factor for all cause death and cardiovascular mortality, that adds incremental prognostic information to clinical and imaging variables 41 – 47 , even in the presence of normal perfusion test 48 – 49 . The mechanism of Blunted heart rate response (BHRR) is attributed to Cardiac Autonomic Neuropathy (CAN) 44 , 50 – 53 and left ventricular dysfuntion 42 . As mentioned before, the proportion of normal SPECT results is continuously rising 38 – 40 , but alongside the rise in the proportion of tested patients with higher risk profile, the prevalence of atrial fibrillation (AF)/atrial flutter (AFL) and Cardiac Implantable Electronic Devices (CIED), in tested subject is also increasing 54 – 57 . These subgroups of patients were often excluded 10 , 42 , 45 – 46 , 48 in previous studies. Methods Objectives To perform an "all-comers" study characterized by a diverse and contemporary comorbidity profile, reflecting the current patient population undergoing Dipyridamole induced Stress Cardiac SPECT (DS-SPECT). The primary objective is to evaluate the independent prognostic significance of BHRR and its added value when combined with imaging findings, in predicting cardiovascular events and mortality. Study Design and Population This study is a single-center retrospective cohort study. All patients over 18 subjected to Dipyridamole induced cardiac SPECT stress test with no additional exercise, from 2014 to 2017 in our center were included, and followed up until September 2020. All the tests were conducted in the same SPECT camera. Patients' data was acquired from their electronic medical record, coded according to the Ninth Revision of the International Classification of Diseases (ICD-9) and from pretest structured interviews. For all patients, age and gender, including the diagnosis of further chronic comorbidities: CAD, Diabetes Mellitus (DM), Hypertension (HTN), presence of CIED, AF/AFL and End Stage Renal Failure (ESRF, glomerular filtration rate of less than 15 mL/min). This study was approved by the local institutional review board with waiver of informed consent. Imaging test conduction and analysis Imaging was performed using a Infinia Hawkeye 4 camera (GE healthcare), and processing was implemented by GE Xeleris workstation, with eight frames per cardiac cycle and iterative reconstruction with and without CT attenuation correction. A same-day dipyridamole (stress) -rest 99m Tc sestamibi 10/30 mCi protocol was implemented 16 . In case stress images were interpreted as abnormal, additional 30 millicuries 99m Tc sestamibi were reinjected two hours after stress dose injection. Both post-stress and rest images were acquired one-hour post tracer injections. All patients were under caffeine/xantines restriction regiment before the test. Outcomes and Variables All subjects were assigned into four pre-defined DS-SPECT categories: Normal, Reversible (ischemic defects) only, Irreversible (fixed) defects only and Mixed type (both reversible and irreversible defects). Normal test results were defined as no 99m Tc uptake defects and post stress LVEF ≥ 50%. BHRR was defined as heart rate increase of less than 20% than baseline after dipyridamole administration. All patients were followed for the occurrence of two end-point outcome events: all-cause (AC) mortality and cardiovascular (CV) mortality. Events during 60 days after index DS-SPECT date were excluded to avoid test-driven events. It is worth mentioning that patients demonstrating reversible defects were admitted for early revascularization assessment. Mortality was corroborated through the Ministry of Interior records. Information obtained from the patients' medical electronic files included: the diagnosis and dates of CV events (CVE) - cardiovascular death, non-fatal myocardial infarction, stroke, coronary intervention and CIED implantation. Statistical analysis Baseline characteristics were described by means and standard deviations (SD) for continuous variables and percentages for categorical variables. The comparison between different variables was performed using Student’s t-test for continuous variables, and Pearson chi-square for categorical variables. In addition, each variable’s effect on each study outcome was evaluated in a univariate Cox Proportional Hazard model and was tabulated and presented in a forest plot. Multivariable Cox Proportional Hazard regression was run to evaluate the adjusted effect of the variable of interest. The study significance level was set to 5% and no correction for multiple testing was conducted. Subgroup Analysis Subgroup analyses were conducted to evaluate the different characteristics and outcome of the cohort population according to heart rate response (BHRR vs. normal response), the same analysis was conducted on the patient group after excluding patients presenting with atrial fibrillation or implanted pacemakers/implantable defibrillators. Similar subgroup analysis was conducted on the cohort dividing the patients by DS-SPECT results. Declaration of generative AI and AI-assisted technologies in the writing process During the preparation of this work the author used CHATGPT in order to improve grammar. After using this tool, the author reviewed and edited the content as needed and takes full responsibility for the content of the published article. Results Study population Study population comprised of 388 subjects with mean follow-up period lasted 1560 days (4.3 ± 1.5 years). Male comprised 212 (54.6%) of cohort, with 38 (9.8%) of patients after CIED implantation (four with ICD) and 27 (7.0%) with permanent atrial fibrillation/flutter. 227 (58.5%) of total patient population had normal DS-SPECT results, 29 (7.4%) had reversible only defects in the test, 83(21.6%) have shown irreversible defects and 47 (12.1%) have shown mixed results. Two patients could not be assigned to any category. 363 of the patients had LVEF information, post-stress LVEF ≤ 40% was observed in 28 (22.8%) of the 123 patients with numerically determined LVEF values, as post stress LVEF > 45% represents 281(77.4% of the patients with known LVEF) patients. Blunted heart rate response was observed in 245 out of 376 patients with available data (63.1%), constituted a majority in every scan category, 140(61.6%), 15(52%), 56 (67.5%), and 31(66%) of the normal, reversible, fixed and mixed DS-SPECT, respectively. The incidence of any cardiovascular event was 21.9% (85 patients). 90 patients (23.2%) have died during follow up period, as cardiovascular cause of death was confirmed in 20 patients (5.3%). The full population's characteristics and outcomes are detailed in Table 1 . Table 1 Characteristics and Outcomes of study population Variable Cohort (n = 388) Age (years) 73.4±9.6 Males (%) 212 (54.6) Coronary artery disease (%) 200 (51.5) CIED (%) 38 (9.8) Atrial fibrillation/flutter (%) 27 (7.0) Insulin dependent diabetes (%) 29 (7.6) Hypertension (%) 294 (77.6) End Stage Renal Disease (%) 12 (3.1) Pre- test angina (%) 112 (28.9) Basal heart rate (bpm) 69.6 ± 11.8 BHRR (%) 245 (63.1) Normal DSPECT (%) 227 (58.5) Reversible defects in DSPECT (%) 29 (7.4) Fixed only DSPECT (%) 83 (21.6) Mixed DSPECT (%) 47 (12.1) Post stress LVEF > 45% (% n = 363) 281 (77.4) Cardiovascular event (%) 85 (21.9) All cause death (%) 90 (23.2) Cardiovascular death (%) 20 (5.3) Logistic regression analysis Univariate analysis identified atrial fibrillation/flutter, insulin dependent diabetes and elevated basal HR as predictors of CV death. Interestingly, the association between CV death and previously known cardiovascular disease was not statistically significant (Table 2 ). Table 2 Predictors of all Cause and Cardiovascular death, univariate analysis Death Predictor Cardiovascular Death Confidence Interval p value All-cause Mortality Confidence Interval p value Age (year) 1.02 (0.97,1.07) 0.415 1.04 (1.01, 1.06) 0.01 Known coronary artery disease 1.32 (0.55,3.2) 0.535 1.81 (1.18, 2.78) 0.007 Atrial fib/flutter 4.12 (1.35,12.52) 0.013 1.92 (0.99,3.71) 0.052 Insulin dependent diabetes 6.35 (2.13, 18.92) 0.001 3.12 (1.74, 5.58) 45% 0.41 (0.16,1.04) 0.06 0.53 (0.38,0.85) 0.008 Normal DSPECT 0.34 (0.13.0.85) 0.021 0.62 (0.41,0.93) 0.022 Fixed DSPECT 3.2 (1.32,7.72) 0.01 1.85 (1.19,2.88) 0.006 Reversible DSPECT 0 0.997 0.6 (0.22,1.65) 0.324 In multivariable outcome analysis BHRR emerged as an independent predictor of CV death (HR 8.09, CI: 1.2, 11.6, p < 0.05). The combination of abnormal SPECT associated with BHRR predicted an almost fourfold increase of CVE (HR 3.79, CI: 1.06–61.91, p < 0.05) (Table 3 ). Moreover, further multivariant analysis reveals that BHRR emerged as a significant predictor of both all cause death (HR 2.93, CI: 1.1–7.7, p < 0.05) and CVE (HR 3.43, CI: 1.4–8.3, p 60 days BHRR 8.09∗ (1.06,61.91) 1.11 (0.57,2.16) 0.92 (0.44,1.92) DSPECT – abnormal vs. normal 2.75 (0.94,8.07) 0.77 (0.27,2.20) 0.81 (0.30,2.20) Age 1.03 (0.98,1.08) 1.06∗∗∗ (1.03,1.08) 1.00 (0.97,1.02) male vs. female 0.95 (0.35, 2.58) 1.05 1.10 (0.67, 1.64) (0.68, 1.78) Diabetes: no vs. insulin therapy 3.99∗ (1.23,12.91) 2.72∗∗ (1.43,5.16) 4.64∗∗∗ (2.36,9.11) End stage renal disease 2.71 (0.29,25.06) 6.27∗∗∗ (2.63, 14.95) 2.30 (0.79,6.70) BHRR and abnormal DSPECT° 2.78 (0.89, 8.68) 3.79∗ (1.24, 11.63) *p < 0.05 **p < 0.01 ***p < 0.001 °The interaction between BHRR and DSPECT: CV death outcome interaction was impossible to calculate due to lack of events in each cell of interaction. Table 4 Multivariable analysis by DSPECT status Covariate Normal DSPECT Abnormal DSPECT Dependent variables: Hazard Ratios with 95% Confidence Intervals All-cause death 1st CVE All-cause death 1st CVE HR CI HR CI HR CI HR CI BHRR 1.16 0.6 2.2 0.87 0.4 1.90 2.93∗ 1.1 7.7 3.43∗∗ 1.4 8.3 Age 1.04∗ 1.0 1.1 0.99 0.96 1.03 1.07∗∗∗ 1.0 1.1 1.0 0.97 1.04 Diabetes treated with insulin° 2.8∗ 1.4 5.2 8.5∗∗∗ 2.9 25.1 2.4∗ 1.1 5.3 3.06∗∗ 1.3 7.06 End stage renal disease 4.5∗∗ 2.6 15 2.3 0.62 8.4 11.6∗∗ 2.4 55.6 1.63 0.2 13.1 ∗p < 0.05 ∗∗p < 0.01 ∗∗∗p < 0.001 °Comparing orally treated diabetics vs. non diabetics Subgroup Analysis The subset analyses, as detailed in the supplementary material, revealed similar results to the main dataset, indicating internal consistency of the results. AC and CV death and CVE- were more frequent among BHRR patients, while excluding patients with AF/AFL or CIED did not altered BHRR associations with outcomes (Table S1 -2). Another subgroup analysis, assessing the different clinical descriptors by DS-SPECT categories, found that normal results group, compared to fixed and mixed groups, demonstrated lower CV death (3% vs.11.4% vs. 8.5%, p = 0.04) and all-cause mortality (19.8% vs. 34.1% vs. 27.7%, p = 0.03), as presented in Table S3. The low rates in the reversible group are due to low sample size (n = 29). Discussion This is a unique cohort retrospective study aimed at evaluating association between the BHRR and DS-SPECT imaging results and cardiovascular mortality and morbidity in an all-comers population with significant comorbidities. The study population is characterised by high rates of octogenarians, diabetic patient, patients with atrial fibrillation/flutter and CIED implanted subjects which were often excluded from previous studies 10 , 42 – 48 . Our cohort BHRR rate (64%), was grossly consistent with previous studies 45 – 48 , while the relatively high incidence can be explained by the higher rates of diabetes and older age in our study population. As previously described in the literature, older age and diabetes are known to be associated with Cardiac Autonomous Neuropathy (CAN), which is characterized by chronotropic incompetence (may manifest as BHRR) and a reduced long-term survival rates 50 – 53 . CV mortality among patients with normal DS-SPECT imaging results in our study was low (averaging less than 1% per one year follow-up), in accordance with the known literature 7 – 11 . The relatively higher rate of AC mortality (19.8% at end of follow up period) among the normal DS-SPECT patients can be attributed to the high rates of comorbidities in our study population, whereas sub-optimal (attenuated) “stress” heart rates may also have partially contributed to false–negative results 58 . In our study, BHRR appears to be an independent prominent predictor of cardiovascular death, with 8-fold increase in multivariate analysis, which may align with the known literature 41 – 48 . These findings were further cemented by our subgroup analysis that demonstrated significate increase in CV and AC mortality in patients with BHRR, repeated in further analysis of patients without comorbidities of AF/AFL and CIED. Moreover, the association of BHRR with adverse outcome events includes: reduced post stress LVEF, lower survival rate and a fourfold increase in CVE among patients with abnormal DS-SPECT, demonstrating the incremental prognostic value of BHRR over DS-SPECT imaging test results alone. However, in contrast to a previous study 49 , impact of BHRR on AC and CV death rates among our normal DS-SPECT patients did not reach statistical significance, thus retaining the well-known high negative predictive value of a normal DS-SPECT result. Based on comparable rates of non-fatal MI and revascularizations, in either BHRR presence or absence subsets, Mathur et al. 45 suggested that that BHRR is specifically associated with cardiac death by non-ischemic mechanisms like ventricular arrhythmias, this may explain our results' discrepancy of significant higher CV death rates in patients with BHRR compared with patients with normal HRR, contrary to almost no difference in other CVE. Strengths and Limitations The major strength of the study is by including contemporary, higher risk, all-comer population, moreover, it includes results and data on patients that were previously not included in similar studies. The study also has its strength in its relatively long follow-up period and the assessment of both imaging and BHRR results. The study main limitation is its retrospective nature and its single center design, which may have resulted in selection bias. Furthermore, the study population is relatively small, although population size was satisfactory for reaching statistical significance. Conclusions In conclusion, we have conducted an "all-comers" population cohort study that resembles the contemporary population that is referred for DS-SPECT, which is characterized by older age and high rates of diabetes, AF and CIED. BHRR in DS-SPECT patients was proved to be a useful predictor of CV mortality, and also of AC and CVE in patients with abnormal imaging results. The study findings suggest rethinking the use of nuclear imaging results by themselves, and consider the incorporation of BHRR with test results in order to project a more viable and reliable posttest risk calculation. Abbreviations 99mTc Technetium–99m AC All–Cause (e.g., all–cause mortality) AF Atrial Fibrillation AFL Atrial Flutter BHRR Blunted Heart Rate Response CAD coronary artery disease CAN Cardiac Autonomic Neuropathy CIED Cardiac Implantable Electronic Device CV Cardiovascular CVE Cardiovascular Events DM Diabetes Mellitus DS SPECT –Dipyridamole Stress Single Photon Emission Computed Tomography ESRF End Stage Renal Failure HR Heart Rate HRR Heart Rate Response HTN Hypertension ICD Implantable Cardioverter–Defibrillator ICD 9 –International Classification of Diseases, 9th Revision LVEF Left Ventricular Ejection Fraction MACE Major Adverse Cardiac Events MI Myocardial Infarction SD Standard Deviation Declarations Statement of Ethics: The study was performed in accordance with the Declaration of Helsinki according to the approval of the Institutional Review Board of the Wolfson Medical Center. This study protocol was reviewed and approved by IRB Wolfson. Consent of the participants was waived for this retrospective study. Clinical trial number: not applicable. Conflict of interest: The authors declare that there are no conflicts of interest regarding the publication of this article. Funding Declaration: No funding of any type was received to perform this study Authorship: All author takes responsibility for all aspects of the reliability and freedom from bias of the data presented and their discussed interpretation. All authors contributed to the study conception and design. Data collection and analysis were performed by Alexander Izhaki and Alexey Migranov. The first draft of the manuscript was written by Alexander Izhaki and Aviram Akuka and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript. The authors Diklah Geva and Dina Vorobeichik also contributed by preforming the statistical analysis. The author Ronen Rubinshtein also helped in the wirting proccess, wording and finalizing the manuscript. Data Availability: The data that support the findings of this study are not publicly available due to privacy considerations, but are available from the corresponding author upon reasonable request. Disclosure : The Authors declares that there is no conflict of interest. References Henzlova MJ, Cerqueira MD, Mahmarian JJ, Yao SS. Quality Assurance Committee of the American Society of Nuclear Cardiology. Stress protocols and tracers. J Nucl Cardiol. 2006;13(6):e80–90. Druz RS. Current advances in vasodilator pharmacological stress perfusion imaging. Semin Nucl Med. 2009;39(3):204–9. Hendel RC, Berman DS, Di Carli MF, ACCF/ASNC/ACR/AHA/ASE/SCCT/SCMR, et al. Force, the American Society of Nuclear Cardiology, the American College of Radiology, the American Heart Association, the American Society of Echocardiography, the Society of Cardiovascular Computed Tomography, the Society for Cardiovascular Magnetic Resonance, and the Society of Nuclear Medicine. Circulation. 2009;119(22):e561–87. /SNM 2009 appropriate use criteria for cardiac radionuclide imaging: a report of the American College of Cardiology Foundation Appropriate Use Criteria Task. Knuuti J, Ballo H, Juarez-Orozco LE, et al. The performance of non-invasive tests to rule-in and rule-out significant coronary artery stenosis in patients with stable angina: a meta-analysis focused on post-test disease probability. Eur Heart J. 2018;39(35):3322–30. Gulati M, Levy PD, Mukherjee D, et al. 2021 AHA/ACC/ASE/CHEST/SAEM/SCCT/SCMR Guideline for the Evaluation and Diagnosis of Chest Pain: A Report of the American College of Cardiology/American Heart Association Joint Committee on Clinical Practice Guidelines. Circulation. 2021;144(22):e368–454. Vrints C, Andreotti F, Koskinas KC, et al. 2024 ESC Guidelines for the management of chronic coronary syndromes. Eur Heart J. 2024;45(36):3415–537. Underwood SR, Anagnostopoulos C, Cerqueira M, et al. Myocardial perfusion scintigraphy: the evidence. Eur J Nucl Med Mol Imaging. 2004;31(2):261–91. Marcassa C, Bax JJ, Bengel F, et al. Clinical value, cost-effectiveness, and safety of myocardial perfusion scintigraphy: a position statement. Eur Heart J. 2008;29(4):557–63. Medical Advisory Secretariat. Single photon emission computed tomography for the diagnosis of coronary artery disease: an evidence-based analysis. Ont Health Technol Assess Ser. 2010;10(8):1–64. Cantoni V, Green R, Acampa W, et al. Diagnostic performance of myocardial perfusion imaging with conventional and CZT single-photon emission computed tomography in detecting coronary artery disease: A meta-analysis. J Nucl Cardiol. 2021;28(2):698–715. Driessen RS, van Diemen PA, Raijmakers PG, et al. Functional stress imaging to predict abnormal coronary fractional flow reserve: the PACIFIC 2 study. Eur Heart J. 2022;43(33):3118–28. Underwood SR, Godman B, Salyani S, Ogle JR, Ell PJ. Economics of myocardial perfusion imaging in Europe–the EMPIRE Study. Eur Heart J. 1999;20(2):157–66. Heller GV, Stowers SA, Hendel RC, et al. Clinical value of acute rest technetium-99m tetrofosmin tomographic myocardial perfusion imaging in patients with acute chest pain and nondiagnostic electrocardiograms. J Am Coll Cardiol. 1998;31(5):1011–7. Shaw LJ, Hachamovitch R, Berman DS, et al. The economic consequences of available diagnostic and prognostic strategies for the evaluation of stable angina patients: an observational assessment of the value of precatheterization ischemia. Economics of Noninvasive Diagnosis (END) Multicenter Study Group. J Am Coll Cardiol. 1999;33(3):661–9. Shaw LJ, Heller GV, Travin MI, et al. Cost analysis of diagnostic testing for coronary artery disease in women with stable chest pain. Economics of Noninvasive Diagnosis (END) Study Group. J Nucl Cardiol. 1999;6(6):559–69. Henzlova MJ, Duvall WL, Einstein AJ, Travin MI, Verberne HJ. ASNC imaging guidelines for SPECT nuclear cardiology procedures: Stress, protocols, and tracers. J Nucl Cardiol. 2016;23(3):606–39. Hendel RC, Ramirredy A. Exercise and Pharmacological Stress Testing. Chapter 8. Nuclear Cardiology’ pages109-112. Practical Applications. 3rd Edition. McGraw Hill Education.2018. Matzer L, Kiat H, Wang FP, Van Train K, Germano G, Friedman J, Berman DS. Pharmacologic stress dual-isotope myocardial perfusion single-photon emission computed tomography. Am Heart J. 1994;128(6 Pt 1):1067–76. Gholoobi A, Ayati N, Baghyari A, Mouhebati M, Atar B, Dabbagh Kakhki VR. Relationship between gated myocardial perfusion SPECT findings and hemodynamic, electrocardiographic, and heart rate changes after Dipyridamole infusion. Int J Cardiovasc Imaging. 2017;33(6):951–6. Lette J, Tatum JL, Fraser S, et al. Safety of dipyridamole testing in 73,806 patients: the Multicenter Dipyridamole Safety Study. J Nucl Cardiol. 1995;2(1):3–17. skander S, Iskandrian AE. Risk assessment using single-photon emission computed tomographic technetium-99m sestamibi imaging. J Am Coll Cardiol. 1998;32(1):57–62. Shaw LJ, Hage FG, Berman DS, Hachamovitch R, Iskandrian A. Prognosis in the era of comparative effectiveness research: where is nuclear cardiology now and where should it be? J Nucl Cardiol. 2012;19(5):1026–43. Hachamovitch R, Hayes S, Friedman JD, et al. Determinants of risk and its temporal variation in patients with normal stress myocardial perfusion scans: what is the warranty period of a normal scan? J Am Coll Cardiol. 2003;41(8):1329–40. Hachamovitch R, Berman DS, Shaw LJ, et al. Incremental prognostic value of myocardial perfusion single photon emission computed tomography for the prediction of cardiac death: differential stratification for risk of cardiac death and myocardial infarction. Circulation. 1998;97(6):535–43. Giri S, Shaw LJ, Murthy DR, et al. Impact of diabetes on the risk stratification using stress single-photon emission computed tomography myocardial perfusion imaging in patients with symptoms suggestive of coronary artery disease. Circulation. 2002;105(1):32–40. Abidov A, Hachamovitch R, Rozanski A, et al. Prognostic implications of atrial fibrillation in patients undergoing myocardial perfusion single-photon emission computed tomography. J Am Coll Cardiol. 2004;44(5):1062–70. Askew JW, Miller TD, Hodge DO, Gibbons RJ. The value of myocardial perfusion single-photon emission computed tomography in screening asymptomatic patients with atrial fibrillation for coronary artery disease. J Am Coll Cardiol. 2007;50(11):1080–5. Al-Mallah MH, Hachamovitch R, Dorbala S, Di Carli MF. Incremental prognostic value of myocardial perfusion imaging in patients referred to stress single-photon emission computed tomography with renal dysfunction. Circ Cardiovasc Imaging. 2009;2(6):429–36. Smit MD, Tio RA, Slart RH, Zijlstra F, Van Gelder IC. Myocardial perfusion imaging does not adequately assess the risk of coronary artery disease in patients with atrial fibrillation. Europace. 2010;12(5):643–8. Murthy VL, Naya M, Foster CR, et al. Improved cardiac risk assessment with noninvasive measures of coronary flow reserve. Circulation. 2011;124(20):2215–24. Nucifora G, Schuijf JD, van Werkhoven JM, et al. Relationship between obstructive coronary artery disease and abnormal stress testing in patients with paroxysmal or persistent atrial fibrillation. Int J Cardiovasc Imaging. 2011;27(6):777–85. Nair SU, Ahlberg AW, Mathur S, Katten DM, Polk DM, Heller GV. The clinical value of single photon emission computed tomography myocardial perfusion imaging in cardiac risk stratification of very elderly patients (≥ 80 years) with suspected coronary artery disease. J Nucl Cardiol. 2012;19(2):244–55. Nudi F, Biondi-Zoccai G, Schillaci O, et al. Prognostic accuracy of myocardial perfusion imaging in octogenarians. J Nucl Cardiol. 2018;25(4):1342–9. Charytan DM, Skali H, Shah NR, et al. Coronary flow reserve is predictive of the risk of cardiovascular death regardless of chronic kidney disease stage. Kidney Int. 2018;93(2):501–9. Wang FP, Amanullah AM, Kiat H, Friedman JD, Berman DS. Diagnostic efficacy of stress technetium 99m-labeled sestamibi myocardial perfusion single-photon emission computed tomography in detection of coronary artery disease among patients over age 80. J Nucl Cardiol. 1995;2(5):380–8. Gentile R, Vitarelli A, Schillaci O, et al. Diagnostic accuracy and prognostic implications of stress testing for coronary artery disease in the elderly. Ital Heart J. 2001;2(7):539–45. Lima RS, De Lorenzo A, Pantoja MR, Siqueira A. Incremental prognostic value of myocardial perfusion 99m-technetium-sestamibi SPECT in the elderly. Int J Cardiol. 2004;93(2–3):137–43. Rozanski A, Gransar H, Hayes SW, et al. Temporal trends in the frequency of inducible myocardial ischemia during cardiac stress testing: 1991 to 2009. J Am Coll Cardiol. 2013;61(10):1054–65. Beller GA. How Should We Interpret the Decrease in Annual Volume of Stress Imaging Tests for Evaluation of Suspected or Known Coronary Artery Disease With Fewer High-Risk Test Results? Circ Cardiovasc Imaging. 2017;10(7):e006702. Al Badarin FJ, Chan PS, Spertus JA, et al. Temporal trends in test utilization and prevalence of ischaemia with positron emission tomography myocardial perfusion imaging. Eur Heart J Cardiovasc Imaging. 2020;21(3):318–25. Lauer MS, Francis GS, Okin PM, Pashkow FJ, Snader CE, Marwick TH. Impaired chronotropic response to exercise stress testing as a predictor of mortality. JAMA. 1999;281(6):524–9. Lee KH, Yoon JK, Lee MG, Lee SH, Lee WR, Kim BT. Dipyridamole myocardial SPECT with low heart rate response indicates cardiac autonomic dysfunction in patients with diabetes. J Nucl Cardiol. 2001;8(2):129–35. Abidov A, Hachamovitch R, Hayes SW, et al. Prognostic impact of hemodynamic response to adenosine in patients older than age 55 years undergoing vasodilator stress myocardial perfusion study. Circulation. 2003;107(23):2894–9. Hage FG, Iskandrian AE. Heart rate response during vasodilator stress myocardial perfusion imaging: Mechanisms and implications. J Nucl Cardiol. 2010;17(4):536–9. Mathur S, Shah AR, Ahlberg AW, Katten DM, Heller GV. Blunted heart rate response as a predictor of cardiac death in patients undergoing vasodilator stress technetium-99m sestamibi gated SPECT myocardial perfusion imaging. J Nucl Cardiol. 2010;17(4):617–24. Gorur GD, Ciftci EA, Kozdag G, et al. Reduced heart rate response to dipyridamole in patients undergoing myocardial perfusion SPECT. Ann Nucl Med. 2012;26(8):609–15. Cortigiani L, Carpeggiani C, Landi P, Raciti M, Bovenzi F, Picano E. Usefulness of Blunted Heart Rate Reserve as an Imaging-Independent Prognostic Predictor During Dipyridamole Stress Echocardiography. Am J Cardiol. 2019;124(6):972–7. Bhatheja R, Francis GS, Pothier CE, Lauer MS. Heart rate response during dipyridamole stress as a predictor of mortality in patients with normal myocardial perfusion and normal electrocardiograms. Am J Cardiol. 2005;95(10):1159–64. Iqbal FM, Al Jaroudi W, Sanam K, et al. Reclassification of cardiovascular risk in patients with normal myocardial perfusion imaging using heart rate response to vasodilator stress. Am J Cardiol. 2013;111(2):190–5. Doulgerakis D, Moyssakis I, Kapelios CJ, et al. Cardiac Autonomic Neuropathy Predicts All-Cause and Cardiovascular Mortality in Patients with End-Stage Renal Failure: A 5-Year Prospective Study. Kidney Int Rep. 2017;2(4):686–94. Ewing DJ, Martyn CN, Young RJ, Clarke BF. The value of cardiovascular autonomic function tests: 10 years experience in diabetes. Diabetes Care. 1985;8(5):491–8. Taskiran M, Fritz-Hansen T, Rasmussen V, Larsson HB, Hilsted J. Decreased myocardial perfusion reserve in diabetic autonomic neuropathy. Diabetes. 2002;51(11):3306–10. de Souza R, Machado L, Azevedo AB, De Lorenzo A. Predictors of abnormal heart rate response to dipyridamole in patients undergoing myocardial perfusion SPECT. Ann Nucl Med. 2011;25(1):7–11. Valzania C, Torbica A, Tarricone R, Leyva F, Boriani G. Implant rates of cardiac implantable electrical devices in Europe: A systematic literature review. Health Policy. 2016;120(1):1–15. Valzania C, Bonfiglioli R, Fallani F, et al. Single-photon cardiac imaging in patients with cardiac implantable electrical devices. J Nucl Cardiol. 2022;29(2):633–41. Krijthe BP, Kunst A, Benjamin EJ, et al. Projections on the number of individuals with atrial fibrillation in the European Union, from 2000 to 2060. Eur Heart J. 2013;34(35):2746–51. Benjamin EJ, Muntner P, Alonso A, American Heart Association Council on Epidemiology and Prevention Statistics Committee and Stroke Statistics Subcommittee, et al. Heart Disease and Stroke Statistics-2019 Update: A Report from the American Heart Association. Circulation. 2019;139(10):e56–528. Gimelli A, Liga R, Coceani M, Quaranta A, Emdin M, Marzullo P. Chronotropic response to vasodilator-stress in patients submitted to myocardial perfusion imaging: impact on the accuracy in detecting coronary stenosis. Eur J Nucl Med Mol Imaging. 2015;42(12):1903–11. Cortigiani L, Carpeggiani C, Landi P, Raciti M, Bovenzi F, Picano E. Prognostic Value of Heart Rate Reserve in Patients with Permanent Atrial Fibrillation during Dipyridamole Stress Echocardiography. Am J Cardiol. 2020;125(11):1661–5. Sharir T, Germano G, Kavanagh PB, et al. Incremental prognostic value of post-stress left ventricular ejection fraction and volume by gated myocardial perfusion single photon emission computed tomography. Circulation. 1999;100(10):1035–42. De Lorenzo A, Lima RS, Siqueira-Filho AG, Pantoja MR. Prevalence and prognostic value of perfusion defects detected by stress technetium-99m sestamibi myocardial perfusion single-photon emission computed tomography in asymptomatic patients with diabetes mellitus and no known coronary artery disease. Am J Cardiol. 2002;90(8):827–32. Additional Declarations No competing interests reported. Supplementary Files DSSPECTWolfsonstudysupplement.docx GRAPHICALABSTRACT1.jpg Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 08 Jan, 2026 Reviews received at journal 05 Jan, 2026 Reviewers agreed at journal 05 Jan, 2026 Reviews received at journal 04 Jan, 2026 Reviewers agreed at journal 02 Jan, 2026 Reviewers invited by journal 11 Dec, 2025 Editor invited by journal 28 Nov, 2025 Editor assigned by journal 27 Nov, 2025 Submission checks completed at journal 27 Nov, 2025 First submitted to journal 21 Nov, 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. 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-8176602","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":559918850,"identity":"febfe5cd-29db-4d49-b571-1db7885f6613","order_by":0,"name":"Alexander Izhaki","email":"","orcid":"","institution":"Edith Wolfson Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Alexander","middleName":"","lastName":"Izhaki","suffix":""},{"id":559918852,"identity":"595181f1-8a8f-465b-b985-f720f7bb9955","order_by":1,"name":"Aviram Akuka","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAw0lEQVRIiWNgGAWjYDACHgZmIMksB2IfeECKFmOwlgRStCQ2gDhEaeHvOWNs8DPHOn1+2OGHQFvs5HQbCGiRONtjnNi7LT134+00A6CWZGOzA4SsOc9jfIB32+HcjbMTQFoOJG4jpEUeqOXg322H0w1np38gTosB0GHJQFsS5KVziLTF8MyxYmPZbemGG6RzCg4kGBDhF7kzyZsl326zlpefnb75w4cKOznC3oe7EKzSgFjlICDfQIrqUTAKRsEoGFEAAHxgRjtm+j9rAAAAAElFTkSuQmCC","orcid":"","institution":"Edith Wolfson Medical Center","correspondingAuthor":true,"prefix":"","firstName":"Aviram","middleName":"","lastName":"Akuka","suffix":""},{"id":559918853,"identity":"650884ed-3620-4037-8c68-d541f45ad0ad","order_by":2,"name":"Alexey Migranov","email":"","orcid":"","institution":"Edith Wolfson Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Alexey","middleName":"","lastName":"Migranov","suffix":""},{"id":559918854,"identity":"578584ec-7fe0-476a-a3c4-22dbd382fcca","order_by":3,"name":"Diklah Geva","email":"","orcid":"","institution":"IntegriStat LTD","correspondingAuthor":false,"prefix":"","firstName":"Diklah","middleName":"","lastName":"Geva","suffix":""},{"id":559918855,"identity":"25a29659-7a12-49f5-b032-31234b132a4b","order_by":4,"name":"Dina Vorobeichik","email":"","orcid":"","institution":"IntegriStat LTD","correspondingAuthor":false,"prefix":"","firstName":"Dina","middleName":"","lastName":"Vorobeichik","suffix":""},{"id":559918856,"identity":"3108724a-fe24-4c8f-a581-6cf23b67e995","order_by":5,"name":"Ronen Rubinshtein","email":"","orcid":"","institution":"Edith Wolfson Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Ronen","middleName":"","lastName":"Rubinshtein","suffix":""}],"badges":[],"createdAt":"2025-11-21 21:08:17","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8176602/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8176602/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":98356021,"identity":"0f8fa041-5df8-4924-81e0-4374e8eb0026","added_by":"auto","created_at":"2025-12-17 00:13:17","extension":"jpg","order_by":0,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":157603,"visible":true,"origin":"","legend":"","description":"","filename":"GRAPHICALABSTRACT1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8176602/v1/7e534744e7edaac28d436db0.jpg"},{"id":98438692,"identity":"8e481221-78af-44b0-9591-2c4833d21db8","added_by":"auto","created_at":"2025-12-17 16:59:51","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":73102,"visible":true,"origin":"","legend":"","description":"","filename":"DSSPECTstudymanuscriptAviramAkuka.docx","url":"https://assets-eu.researchsquare.com/files/rs-8176602/v1/53052ab8fec3bca971693bee.docx"},{"id":98356024,"identity":"5ab4dd19-c382-4264-a35a-164091fc6a70","added_by":"auto","created_at":"2025-12-17 00:13:17","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":46352,"visible":true,"origin":"","legend":"","description":"","filename":"DSSPECTstudytablesAviramAkukaCopy.docx","url":"https://assets-eu.researchsquare.com/files/rs-8176602/v1/374c67b03dd6fcc522c57ed9.docx"},{"id":98356020,"identity":"75dd1fd3-7196-4e21-9737-fb01eec72606","added_by":"auto","created_at":"2025-12-17 00:13:17","extension":"json","order_by":3,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":8154,"visible":true,"origin":"","legend":"","description":"","filename":"4d91ee0ad27b41bca7c99f1cbb120ae9.json","url":"https://assets-eu.researchsquare.com/files/rs-8176602/v1/5286b995bdb8883407618368.json"},{"id":98439445,"identity":"78a129ef-b2f3-4364-b667-2658a6144d57","added_by":"auto","created_at":"2025-12-17 17:01:52","extension":"docx","order_by":4,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":26248,"visible":true,"origin":"","legend":"","description":"","filename":"DSSPECTWolfsonstudysupplement.docx","url":"https://assets-eu.researchsquare.com/files/rs-8176602/v1/bc42d8a1a47b3879e9b975f3.docx"},{"id":98438899,"identity":"c30308ec-3899-447b-ad6a-79c6a2ba3eea","added_by":"auto","created_at":"2025-12-17 17:00:23","extension":"xml","order_by":5,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":163836,"visible":true,"origin":"","legend":"","description":"","filename":"4d91ee0ad27b41bca7c99f1cbb120ae91enriched.xml","url":"https://assets-eu.researchsquare.com/files/rs-8176602/v1/6913662d77972238640cf4d3.xml"},{"id":98356031,"identity":"005c3d71-fd3e-41f2-a5e0-3ceab9bc2dcd","added_by":"auto","created_at":"2025-12-17 00:13:17","extension":"jpg","order_by":6,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":157603,"visible":true,"origin":"","legend":"","description":"","filename":"GRAPHICALABSTRACT1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8176602/v1/c1202514e178473afb7252df.jpg"},{"id":98439213,"identity":"f41916a8-4033-4630-a755-3d5bcb95f460","added_by":"auto","created_at":"2025-12-17 17:01:28","extension":"png","order_by":7,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":51258,"visible":true,"origin":"","legend":"","description":"","filename":"OnlineGRAPHICALABSTRACT1.png","url":"https://assets-eu.researchsquare.com/files/rs-8176602/v1/6090a25f66423a9b10823329.png"},{"id":98356027,"identity":"a73533b7-8d24-43cb-a72d-b153a876191e","added_by":"auto","created_at":"2025-12-17 00:13:17","extension":"xml","order_by":8,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":159135,"visible":true,"origin":"","legend":"","description":"","filename":"4d91ee0ad27b41bca7c99f1cbb120ae91structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-8176602/v1/99c14635b899a2862332fae4.xml"},{"id":98356030,"identity":"8bc818bd-314a-42df-b406-34aedcc7d126","added_by":"auto","created_at":"2025-12-17 00:13:17","extension":"html","order_by":9,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":176497,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8176602/v1/92469ea9ab91ab2c4fc25531.html"},{"id":98774993,"identity":"a970c3f9-a02e-4bcf-886f-291d8d438faa","added_by":"auto","created_at":"2025-12-22 12:17:48","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1003644,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8176602/v1/8bd66b57-4e89-41af-bde2-ce9828b60bf7.pdf"},{"id":98440104,"identity":"42f985dd-9336-4f47-b5af-372102538430","added_by":"auto","created_at":"2025-12-17 17:03:18","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":26248,"visible":true,"origin":"","legend":"","description":"","filename":"DSSPECTWolfsonstudysupplement.docx","url":"https://assets-eu.researchsquare.com/files/rs-8176602/v1/31be52ba7000df31c4dd6707.docx"},{"id":98356025,"identity":"039765e4-e6c5-40f8-a4be-ecdd13b8fae1","added_by":"auto","created_at":"2025-12-17 00:13:17","extension":"jpg","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":157603,"visible":true,"origin":"","legend":"","description":"","filename":"GRAPHICALABSTRACT1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8176602/v1/870d7e2b1791d9d8b4e811fd.jpg"}],"financialInterests":"No competing interests reported.","formattedTitle":"Blunted Heart Rate Response Enhances Prognostic Value of Dipyridamole Stress SPECT for Cardiovascular Morbidity and Mortality in All-Comers","fulltext":[{"header":"Introduction","content":"\u003cp\u003e99mTc Single Photon Emission Computed Tomography (SPECT) is widely used to assess myocardial ischemia in patients with coronary artery disease (CAD)\u0026sup1;⁻⁶. Pharmacologic stress testing is typically reserved for those unable to exercise, or with left bundle-branch block or paced rhythms\u0026sup1;⁻\u0026sup3;, as SPECT retains high sensitivity and specificity⁷⁻\u0026sup1;\u0026sup1;, with demonstrated cost-effectiveness in CAD detection\u0026sup1;\u0026sup2;⁻\u0026sup1;⁵. One of the most commonly used agents for pharmacologic stress SPECT is Dipyridamole, an indirect coronary vasodilator\u0026sup1;⁶⁻\u0026sup1;⁷, known to improve diagnostic yield\u0026sup1;⁸⁻\u0026sup1;⁹ while maintaining a strong safety profile\u0026sup2;⁰.\u003c/p\u003e \u003cp\u003eAlthough low risk and normal SPECT test results are associated with low probability of major adverse cardiac events (MACE) \u003csup\u003e7\u0026ndash;8,21\u0026minus;22\u003c/sup\u003e, in specific higher risk profile populations with comorbidities (especially: diabetes, atrial fibrillation, chronic renal impairment and elderly), a normal test result does not necessarily translate into low mortality and MACE risk\u003csup\u003e\u003cspan additionalcitationids=\"CR25 CR26 CR27 CR28 CR29 CR30 CR31 CR32 CR33\" citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e, with contradictory results previously reported for the elderly population\u003csup\u003e\u003cspan additionalcitationids=\"CR36\" citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e. Moreover, as the incidence of abnormal SPECT tests has progressively decreased, the proportion of these higher risk profile subjects among the testing population continued to grow\u003csup\u003e\u003cspan additionalcitationids=\"CR39\" citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e, thus potentially negatively influencing the predictive value of test results.\u003c/p\u003e \u003cp\u003eNevertheless, pharmacological stress SPECT also incorporates non-imaging prognostic data. Accumulating evidence have demonstrated that inadequately slower than expected (blunted) heart rate response to vasodilator injection is an independent risk factor for all cause death and cardiovascular mortality, that adds incremental prognostic information to clinical and imaging variables\u003csup\u003e\u003cspan additionalcitationids=\"CR42 CR43 CR44 CR45 CR46\" citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u003c/sup\u003e, even in the presence of normal perfusion test\u003csup\u003e\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u003c/sup\u003e. The mechanism of Blunted heart rate response (BHRR) is attributed to Cardiac Autonomic Neuropathy (CAN)\u003csup\u003e\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e,\u003cspan additionalcitationids=\"CR51 CR52\" citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e\u003c/sup\u003e and left ventricular dysfuntion\u003csup\u003e\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eAs mentioned before, the proportion of normal SPECT results is continuously rising\u003csup\u003e\u003cspan additionalcitationids=\"CR39\" citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e, but alongside the rise in the proportion of tested patients with higher risk profile, the prevalence of atrial fibrillation (AF)/atrial flutter (AFL) and Cardiac Implantable Electronic Devices (CIED), in tested subject is also increasing\u003csup\u003e\u003cspan additionalcitationids=\"CR55 CR56\" citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e\u003c/sup\u003e. These subgroups of patients were often excluded\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e,\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e,\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e,\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e in previous studies.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eObjectives\u003c/h2\u003e \u003cp\u003eTo perform an \"all-comers\" study characterized by a diverse and contemporary comorbidity profile, reflecting the current patient population undergoing Dipyridamole induced Stress Cardiac SPECT (DS-SPECT). The primary objective is to evaluate the independent prognostic significance of BHRR and its added value when combined with imaging findings, in predicting cardiovascular events and mortality.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eStudy Design and Population\u003c/h3\u003e\n\u003cp\u003eThis study is a single-center retrospective cohort study. All patients over 18 subjected to Dipyridamole induced cardiac SPECT stress test with no additional exercise, from 2014 to 2017 in our center were included, and followed up until September 2020. All the tests were conducted in the same SPECT camera.\u003c/p\u003e \u003cp\u003ePatients' data was acquired from their electronic medical record, coded according to the Ninth Revision of the International Classification of Diseases (ICD-9) and from pretest structured interviews. For all patients, age and gender, including the diagnosis of further chronic comorbidities: CAD, Diabetes Mellitus (DM), Hypertension (HTN), presence of CIED, AF/AFL and End Stage Renal Failure (ESRF, glomerular filtration rate of less than 15 mL/min).\u003c/p\u003e \u003cp\u003e This study was approved by the local institutional review board with waiver of informed consent.\u003c/p\u003e\n\u003ch3\u003eImaging test conduction and analysis\u003c/h3\u003e\n\u003cp\u003eImaging was performed using a Infinia Hawkeye 4 camera (GE healthcare), and processing was implemented by GE Xeleris workstation, with eight frames per cardiac cycle and iterative reconstruction with and without CT attenuation correction.\u003c/p\u003e \u003cp\u003eA same-day dipyridamole (stress) -rest \u003csup\u003e99m\u003c/sup\u003eTc sestamibi 10/30 mCi protocol was implemented\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. In case stress images were interpreted as abnormal, additional 30 millicuries \u003csup\u003e99m\u003c/sup\u003eTc sestamibi were reinjected two hours after stress dose injection. Both post-stress and rest images were acquired one-hour post tracer injections.\u003c/p\u003e \u003cp\u003eAll patients were under caffeine/xantines restriction regiment before the test.\u003c/p\u003e\n\u003ch3\u003eOutcomes and Variables\u003c/h3\u003e\n\u003cp\u003eAll subjects were assigned into four pre-defined DS-SPECT categories: Normal, Reversible (ischemic defects) only, Irreversible (fixed) defects only and Mixed type (both reversible and irreversible defects). Normal test results were defined as no \u003csup\u003e99m\u003c/sup\u003eTc uptake defects and post stress LVEF\u0026thinsp;\u0026ge;\u0026thinsp;50%. BHRR was defined as heart rate increase of less than 20% than baseline after dipyridamole administration.\u003c/p\u003e \u003cp\u003eAll patients were followed for the occurrence of two end-point outcome events: all-cause (AC) mortality and cardiovascular (CV) mortality. Events during 60 days after index DS-SPECT date were excluded to avoid test-driven events. It is worth mentioning that patients demonstrating reversible defects were admitted for early revascularization assessment.\u003c/p\u003e \u003cp\u003eMortality was corroborated through the Ministry of Interior records. Information obtained from the patients' medical electronic files included: the diagnosis and dates of CV events (CVE) - cardiovascular death, non-fatal myocardial infarction, stroke, coronary intervention and CIED implantation.\u003c/p\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eBaseline characteristics were described by means and standard deviations (SD) for continuous variables and percentages for categorical variables. The comparison between different variables was performed using Student\u0026rsquo;s t-test for continuous variables, and Pearson chi-square for categorical variables. In addition, each variable\u0026rsquo;s effect on each study outcome was evaluated in a univariate Cox Proportional Hazard model and was tabulated and presented in a forest plot. Multivariable Cox Proportional Hazard regression was run to evaluate the adjusted effect of the variable of interest.\u003c/p\u003e \u003cp\u003eThe study significance level was set to 5% and no correction for multiple testing was conducted.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eSubgroup Analysis\u003c/h2\u003e \u003cp\u003eSubgroup analyses were conducted to evaluate the different characteristics and outcome of the cohort population according to heart rate response (BHRR vs. normal response), the same analysis was conducted on the patient group after excluding patients presenting with atrial fibrillation or implanted pacemakers/implantable defibrillators. Similar subgroup analysis was conducted on the cohort dividing the patients by DS-SPECT results.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eDeclaration of generative AI and AI-assisted technologies in the writing process\u003c/h3\u003e\n\u003cp\u003eDuring the preparation of this work the author used CHATGPT in order to improve grammar. After using this tool, the author reviewed and edited the content as needed and takes full responsibility for the content of the published article.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eStudy population\u003c/h2\u003e \u003cp\u003eStudy population comprised of 388 subjects with mean follow-up period lasted 1560 days (4.3\u0026thinsp;\u0026plusmn;\u0026thinsp;1.5 years). Male comprised 212 (54.6%) of cohort, with 38 (9.8%) of patients after CIED implantation (four with ICD) and 27 (7.0%) with permanent atrial fibrillation/flutter. 227 (58.5%) of total patient population had normal DS-SPECT results, 29 (7.4%) had reversible only defects in the test, 83(21.6%) have shown irreversible defects and 47 (12.1%) have shown mixed results. Two patients could not be assigned to any category. 363 of the patients had LVEF information, post-stress LVEF\u0026thinsp;\u0026le;\u0026thinsp;40% was observed in 28 (22.8%) of the 123 patients with numerically determined LVEF values, as post stress LVEF\u0026thinsp;\u0026gt;\u0026thinsp;45% represents 281(77.4% of the patients with known LVEF) patients.\u003c/p\u003e \u003cp\u003eBlunted heart rate response was observed in 245 out of 376 patients with available data (63.1%), constituted a majority in every scan category, 140(61.6%), 15(52%), 56 (67.5%), and 31(66%) of the normal, reversible, fixed and mixed DS-SPECT, respectively.\u003c/p\u003e \u003cp\u003eThe incidence of any cardiovascular event was 21.9% (85 patients). 90 patients (23.2%) have died during follow up period, as cardiovascular cause of death was confirmed in 20 patients (5.3%). The full population's characteristics and outcomes are detailed in 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\u003eCharacteristics and Outcomes of study population\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCohort (n\u0026thinsp;=\u0026thinsp;388)\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=\"left\" colname=\"c2\"\u003e \u003cp\u003e73.4\u0026plusmn;9.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMales (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e212 (54.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCoronary artery disease (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e200 (51.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCIED (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e38 (9.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAtrial fibrillation/flutter (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e27 (7.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInsulin dependent diabetes (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e29 (7.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypertension (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e294 (77.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEnd Stage Renal Disease (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12 (3.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePre- test angina (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e112 (28.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBasal heart rate (bpm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e69.6 \u0026plusmn; 11.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBHRR (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e245 (63.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNormal DSPECT (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e227 (58.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eReversible defects in DSPECT (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e29 (7.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFixed only DSPECT (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e83 (21.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMixed DSPECT (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e47 (12.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePost stress LVEF\u0026thinsp;\u0026gt;\u0026thinsp;45% (% n\u0026thinsp;=\u0026thinsp;363)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e281 (77.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCardiovascular event (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e85 (21.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAll cause death (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e90 (23.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCardiovascular death (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20 (5.3)\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=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eLogistic regression analysis\u003c/h2\u003e \u003cp\u003eUnivariate analysis identified atrial fibrillation/flutter, insulin dependent diabetes and elevated basal HR as predictors of CV death. Interestingly, the association between CV death and previously known cardiovascular disease was not statistically significant (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\u003ePredictors of all Cause and Cardiovascular death, univariate analysis\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=\"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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDeath\u003c/p\u003e \u003cp\u003ePredictor\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eCardiovascular Death\u003c/p\u003e \u003cp\u003eConfidence Interval p value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eAll-cause Mortality\u003c/p\u003e \u003cp\u003eConfidence Interval p value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge (year)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.02 (0.97,1.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.415\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.04 (1.01, 1.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eKnown coronary artery disease\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.32 (0.55,3.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.535\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.81 (1.18, 2.78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.007\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAtrial fib/flutter\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.12 (1.35,12.52)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.92 (0.99,3.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.052\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eInsulin dependent diabetes\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.35 (2.13, 18.92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.12 (1.74, 5.58)\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\u003e\u003cb\u003eBasal heart rate\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.03 (1.0,1.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.053\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.0 (0.98,1.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.869\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBHRR\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11.18 (1.5,83.54)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.41(1.43,4.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePost stress LVEF\u0026thinsp;\u0026gt;\u0026thinsp;45%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.41 (0.16,1.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.53 (0.38,0.85)\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\u003e\u003cb\u003eNormal DSPECT\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.34 (0.13.0.85)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.62 (0.41,0.93)\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\u003e\u003cb\u003eFixed DSPECT\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.2 (1.32,7.72)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.85 (1.19,2.88)\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\u003e\u003cb\u003eReversible DSPECT\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.997\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.6 (0.22,1.65)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.324\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eIn multivariable outcome analysis BHRR emerged as an independent predictor of CV death (HR 8.09, CI: 1.2, 11.6, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). The combination of abnormal SPECT associated with BHRR predicted an almost fourfold increase of CVE (HR 3.79, CI: 1.06\u0026ndash;61.91, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Moreover, further multivariant analysis reveals that BHRR emerged as a significant predictor of both all cause death (HR 2.93, CI: 1.1\u0026ndash;7.7, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) and CVE (HR 3.43, CI: 1.4\u0026ndash;8.3, p\u0026thinsp;\u0026lt;\u0026thinsp;0.005) among the abnormal DS-SPECT patients, but not in patients with normal imaging results (Table \u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\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\u003eMultivariate Cohort Outcomes Analysis\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\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=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCV death\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAC death\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1st CVE at \u0026gt;\u0026thinsp;60 days\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBHRR\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.09\u0026lowast;\u003c/p\u003e \u003cp\u003e(1.06,61.91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.11\u003c/p\u003e \u003cp\u003e(0.57,2.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.92\u003c/p\u003e \u003cp\u003e(0.44,1.92)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDSPECT \u0026ndash; abnormal vs. normal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.75\u003c/p\u003e \u003cp\u003e(0.94,8.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.77\u003c/p\u003e \u003cp\u003e(0.27,2.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.81\u003c/p\u003e \u003cp\u003e(0.30,2.20)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.03\u003c/p\u003e \u003cp\u003e(0.98,1.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.06\u0026lowast;\u0026lowast;\u0026lowast;\u003c/p\u003e \u003cp\u003e(1.03,1.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003cp\u003e(0.97,1.02)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003emale vs. female\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.95\u003c/p\u003e \u003cp\u003e(0.35, 2.58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.67, 1.64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.68, 1.78)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDiabetes: no vs. insulin therapy\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.99\u0026lowast;\u003c/p\u003e \u003cp\u003e(1.23,12.91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.72\u0026lowast;\u0026lowast;\u003c/p\u003e \u003cp\u003e(1.43,5.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.64\u0026lowast;\u0026lowast;\u0026lowast;\u003c/p\u003e \u003cp\u003e(2.36,9.11)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEnd stage renal disease\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.71\u003c/p\u003e \u003cp\u003e(0.29,25.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.27\u0026lowast;\u0026lowast;\u0026lowast;\u003c/p\u003e \u003cp\u003e(2.63, 14.95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.30\u003c/p\u003e \u003cp\u003e(0.79,6.70)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBHRR and abnormal DSPECT\u0026deg;\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.78\u003c/p\u003e \u003cp\u003e(0.89, 8.68)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.79\u0026lowast;\u003c/p\u003e \u003cp\u003e(1.24, 11.63)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e*p\u0026thinsp;\u0026lt;\u0026thinsp;0.05\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e**p\u0026thinsp;\u0026lt;\u0026thinsp;0.01\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e***p\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e\u0026deg;The interaction between BHRR and DSPECT: CV death outcome interaction was impossible to calculate due to lack of events in each cell of interaction.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\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\u003eMultivariable analysis by DSPECT status\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"13\"\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=\"left\" 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 \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eCovariate\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"6\" nameend=\"c7\" namest=\"c2\"\u003e \u003cp\u003eNormal DSPECT\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"6\" nameend=\"c13\" namest=\"c8\"\u003e \u003cp\u003eAbnormal DSPECT\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"12\" nameend=\"c13\" namest=\"c2\"\u003e \u003cp\u003eDependent variables: Hazard Ratios with 95% Confidence Intervals\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eAll-cause death\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003e1st CVE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c10\" namest=\"c8\"\u003e \u003cp\u003eAll-cause death\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c13\" namest=\"c11\"\u003e \u003cp\u003e1st CVE\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eCI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eHR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eCI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eHR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003eCI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003eHR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e \u003cp\u003eCI\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBHRR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e2.93\u0026lowast;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e7.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e3.43\u0026lowast;\u0026lowast;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e1.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e8.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.04\u0026lowast;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1.07\u0026lowast;\u0026lowast;\u0026lowast;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e1.04\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiabetes treated with insulin\u0026deg;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.8\u0026lowast;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e8.5\u0026lowast;\u0026lowast;\u0026lowast;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e25.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e2.4\u0026lowast;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e5.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e3.06\u0026lowast;\u0026lowast;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e1.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e7.06\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEnd stage renal disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4.5\u0026lowast;\u0026lowast;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e8.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e11.6\u0026lowast;\u0026lowast;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e2.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e55.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e1.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e13.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"13\"\u003e\u0026lowast;p\u0026thinsp;\u0026lt;\u0026thinsp;0.05\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"13\"\u003e\u0026lowast;\u0026lowast;p\u0026thinsp;\u0026lt;\u0026thinsp;0.01\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"13\"\u003e\u0026lowast;\u0026lowast;\u0026lowast;p\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"13\"\u003e\u0026deg;Comparing orally treated diabetics vs. non diabetics\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eSubgroup Analysis\u003c/h2\u003e \u003cp\u003eThe subset analyses, as detailed in the supplementary material, revealed similar results to the main dataset, indicating internal consistency of the results. AC and CV death and CVE- were more frequent among BHRR patients, while excluding patients with AF/AFL or CIED did not altered BHRR associations with outcomes (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e-2). Another subgroup analysis, assessing the different clinical descriptors by DS-SPECT categories, found that normal results group, compared to fixed and mixed groups, demonstrated lower CV death (3% vs.11.4% vs. 8.5%, p\u0026thinsp;=\u0026thinsp;0.04) and all-cause mortality (19.8% vs. 34.1% vs. 27.7%, p\u0026thinsp;=\u0026thinsp;0.03), as presented in Table S3. The low rates in the reversible group are due to low sample size (n\u0026thinsp;=\u0026thinsp;29).\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis is a unique cohort retrospective study aimed at evaluating association between the BHRR and DS-SPECT imaging results and cardiovascular mortality and morbidity in an all-comers population with significant comorbidities. The study population is characterised by high rates of octogenarians, diabetic patient, patients with atrial fibrillation/flutter and CIED implanted subjects which were often excluded from previous studies\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan additionalcitationids=\"CR43 CR44 CR45 CR46 CR47\" citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e. Our cohort BHRR rate (64%), was grossly consistent with previous studies\u003csup\u003e\u003cspan additionalcitationids=\"CR46 CR47\" citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e, while the relatively high incidence can be explained by the higher rates of diabetes and older age in our study population. As previously described in the literature, older age and diabetes are known to be associated with Cardiac Autonomous Neuropathy (CAN), which is characterized by chronotropic incompetence (may manifest as BHRR) and a reduced long-term survival rates\u003csup\u003e\u003cspan additionalcitationids=\"CR51 CR52\" citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eCV mortality among patients with normal DS-SPECT imaging results in our study was low (averaging less than 1% per one year follow-up), in accordance with the known literature\u003csup\u003e\u003cspan additionalcitationids=\"CR8 CR9 CR10\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. The relatively higher rate of AC mortality (19.8% at end of follow up period) among the normal DS-SPECT patients can be attributed to the high rates of comorbidities in our study population, whereas sub-optimal (attenuated) \u0026ldquo;stress\u0026rdquo; heart rates may also have partially contributed to false\u0026ndash;negative results\u003csup\u003e\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIn our study, BHRR appears to be an independent prominent predictor of cardiovascular death, with 8-fold increase in multivariate analysis, which may align with the known literature\u003csup\u003e\u003cspan additionalcitationids=\"CR42 CR43 CR44 CR45 CR46 CR47\" citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e. These findings were further cemented by our subgroup analysis that demonstrated significate increase in CV and AC mortality in patients with BHRR, repeated in further analysis of patients without comorbidities of AF/AFL and CIED.\u003c/p\u003e \u003cp\u003eMoreover, the association of BHRR with adverse outcome events includes: reduced post stress LVEF, lower survival rate and a fourfold increase in CVE among patients with abnormal DS-SPECT, demonstrating the incremental prognostic value of BHRR over DS-SPECT imaging test results alone. However, in contrast to a previous study\u003csup\u003e\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u003c/sup\u003e, impact of BHRR on AC and CV death rates among our normal DS-SPECT patients did not reach statistical significance, thus retaining the well-known high negative predictive value of a normal DS-SPECT result. Based on comparable rates of non-fatal MI and revascularizations, in either BHRR presence or absence subsets, Mathur et al.\u003csup\u003e45\u003c/sup\u003e suggested that that BHRR is specifically associated with cardiac death by non-ischemic mechanisms like ventricular arrhythmias, this may explain our results' discrepancy of significant higher CV death rates in patients with BHRR compared with patients with normal HRR, contrary to almost no difference in other CVE.\u003c/p\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eStrengths and Limitations\u003c/h2\u003e \u003cp\u003eThe major strength of the study is by including contemporary, higher risk, all-comer population, moreover, it includes results and data on patients that were previously not included in similar studies. The study also has its strength in its relatively long follow-up period and the assessment of both imaging and BHRR results.\u003c/p\u003e \u003cp\u003eThe study main limitation is its retrospective nature and its single center design, which may have resulted in selection bias. Furthermore, the study population is relatively small, although population size was satisfactory for reaching statistical significance.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusions","content":"\u003cp\u003eIn conclusion, we have conducted an \"all-comers\" population cohort study that resembles the contemporary population that is referred for DS-SPECT, which is characterized by older age and high rates of diabetes, AF and CIED. BHRR in DS-SPECT patients was proved to be a useful predictor of CV mortality, and also of AC and CVE in patients with abnormal imaging results. The study findings suggest rethinking the use of nuclear imaging results by themselves, and consider the incorporation of BHRR with test results in order to project a more viable and reliable posttest risk calculation.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003e99mTc\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eTechnetium\u0026ndash;99m\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eAC\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAll\u0026ndash;Cause (e.g., all\u0026ndash;cause mortality)\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eAF\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAtrial Fibrillation\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eAFL\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAtrial Flutter\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eBHRR\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eBlunted Heart Rate Response\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eCAD\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ecoronary artery disease\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eCAN\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCardiac Autonomic Neuropathy\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eCIED\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCardiac Implantable Electronic Device\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eCV\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCardiovascular\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eCVE\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCardiovascular Events\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eDM\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eDiabetes Mellitus\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eDS\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003e \u003cb\u003eSPECT\u003c/b\u003e\u0026ndash;Dipyridamole Stress Single Photon Emission Computed Tomography\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eESRF\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eEnd Stage Renal Failure\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eHR\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eHeart Rate\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eHRR\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eHeart Rate Response\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eHTN\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eHypertension\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eICD\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eImplantable Cardioverter\u0026ndash;Defibrillator\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eICD\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003e \u003cb\u003e9\u003c/b\u003e\u0026ndash;International Classification of Diseases, 9th Revision\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eLVEF\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eLeft Ventricular Ejection Fraction\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eMACE\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eMajor Adverse Cardiac Events\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eMI\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eMyocardial Infarction\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eSD\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eStandard Deviation\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eStatement of Ethics:\u0026nbsp;\u003c/strong\u003eThe study was performed in accordance with the Declaration of Helsinki according to the approval of the Institutional Review Board of the Wolfson Medical Center. This study protocol was reviewed and approved by IRB Wolfson. Consent of the participants was waived for this retrospective study.\u0026nbsp;Clinical trial number: not applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest:\u0026nbsp;\u003c/strong\u003eThe authors declare that there are no conflicts of interest regarding the publication of this article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding Declaration:\u0026nbsp;\u003c/strong\u003eNo funding of any type was received to perform this study\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthorship:\u003c/strong\u003e All author takes responsibility for all aspects of the reliability and freedom from bias of the data presented and their discussed interpretation. All authors contributed to the study conception and design. Data collection and analysis were performed by Alexander Izhaki\u003csup\u003e\u0026nbsp;\u003c/sup\u003eand\u0026nbsp;Alexey Migranov. The first draft of the manuscript was written by\u0026nbsp;Alexander Izhaki and\u0026nbsp;Aviram Akuka and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.\u0026nbsp;The authors Diklah Geva\u0026nbsp;and\u0026nbsp;Dina Vorobeichik\u003csup\u003e\u0026nbsp;\u003c/sup\u003ealso contributed by preforming the statistical analysis. The author Ronen Rubinshtein also helped in the wirting proccess, wording and finalizing the manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability:\u003c/strong\u003e The data that support the findings of this study are not publicly available due to privacy considerations, but are available from the corresponding author upon reasonable request.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDisclosure\u003c/strong\u003e\u003cstrong\u003e:\u003c/strong\u003e The Authors declares that there is no conflict of interest.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eHenzlova MJ, Cerqueira MD, Mahmarian JJ, Yao SS. Quality Assurance Committee of the American Society of Nuclear Cardiology. Stress protocols and tracers. J Nucl Cardiol. 2006;13(6):e80\u0026ndash;90.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDruz RS. Current advances in vasodilator pharmacological stress perfusion imaging. Semin Nucl Med. 2009;39(3):204\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHendel RC, Berman DS, Di Carli MF, ACCF/ASNC/ACR/AHA/ASE/SCCT/SCMR, et al. Force, the American Society of Nuclear Cardiology, the American College of Radiology, the American Heart Association, the American Society of Echocardiography, the Society of Cardiovascular Computed Tomography, the Society for Cardiovascular Magnetic Resonance, and the Society of Nuclear Medicine. Circulation. 2009;119(22):e561\u0026ndash;87. /SNM 2009 appropriate use criteria for cardiac radionuclide imaging: a report of the American College of Cardiology Foundation Appropriate Use Criteria Task.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKnuuti J, Ballo H, Juarez-Orozco LE, et al. The performance of non-invasive tests to rule-in and rule-out significant coronary artery stenosis in patients with stable angina: a meta-analysis focused on post-test disease probability. Eur Heart J. 2018;39(35):3322\u0026ndash;30.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGulati M, Levy PD, Mukherjee D, et al. 2021 AHA/ACC/ASE/CHEST/SAEM/SCCT/SCMR Guideline for the Evaluation and Diagnosis of Chest Pain: A Report of the American College of Cardiology/American Heart Association Joint Committee on Clinical Practice Guidelines. Circulation. 2021;144(22):e368\u0026ndash;454.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVrints C, Andreotti F, Koskinas KC, et al. 2024 ESC Guidelines for the management of chronic coronary syndromes. Eur Heart J. 2024;45(36):3415\u0026ndash;537.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eUnderwood SR, Anagnostopoulos C, Cerqueira M, et al. Myocardial perfusion scintigraphy: the evidence. Eur J Nucl Med Mol Imaging. 2004;31(2):261\u0026ndash;91.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMarcassa C, Bax JJ, Bengel F, et al. Clinical value, cost-effectiveness, and safety of myocardial perfusion scintigraphy: a position statement. Eur Heart J. 2008;29(4):557\u0026ndash;63.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMedical Advisory Secretariat. Single photon emission computed tomography for the diagnosis of coronary artery disease: an evidence-based analysis. Ont Health Technol Assess Ser. 2010;10(8):1\u0026ndash;64.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCantoni V, Green R, Acampa W, et al. Diagnostic performance of myocardial perfusion imaging with conventional and CZT single-photon emission computed tomography in detecting coronary artery disease: A meta-analysis. J Nucl Cardiol. 2021;28(2):698\u0026ndash;715.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDriessen RS, van Diemen PA, Raijmakers PG, et al. Functional stress imaging to predict abnormal coronary fractional flow reserve: the PACIFIC 2 study. Eur Heart J. 2022;43(33):3118\u0026ndash;28.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eUnderwood SR, Godman B, Salyani S, Ogle JR, Ell PJ. Economics of myocardial perfusion imaging in Europe\u0026ndash;the EMPIRE Study. Eur Heart J. 1999;20(2):157\u0026ndash;66.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHeller GV, Stowers SA, Hendel RC, et al. Clinical value of acute rest technetium-99m tetrofosmin tomographic myocardial perfusion imaging in patients with acute chest pain and nondiagnostic electrocardiograms. J Am Coll Cardiol. 1998;31(5):1011\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShaw LJ, Hachamovitch R, Berman DS, et al. The economic consequences of available diagnostic and prognostic strategies for the evaluation of stable angina patients: an observational assessment of the value of precatheterization ischemia. Economics of Noninvasive Diagnosis (END) Multicenter Study Group. J Am Coll Cardiol. 1999;33(3):661\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShaw LJ, Heller GV, Travin MI, et al. Cost analysis of diagnostic testing for coronary artery disease in women with stable chest pain. Economics of Noninvasive Diagnosis (END) Study Group. J Nucl Cardiol. 1999;6(6):559\u0026ndash;69.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHenzlova MJ, Duvall WL, Einstein AJ, Travin MI, Verberne HJ. ASNC imaging guidelines for SPECT nuclear cardiology procedures: Stress, protocols, and tracers. J Nucl Cardiol. 2016;23(3):606\u0026ndash;39.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHendel RC, Ramirredy A. Exercise and Pharmacological Stress Testing. Chapter 8. Nuclear Cardiology\u0026rsquo; pages109-112. Practical Applications. 3rd Edition. McGraw Hill Education.2018.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMatzer L, Kiat H, Wang FP, Van Train K, Germano G, Friedman J, Berman DS. Pharmacologic stress dual-isotope myocardial perfusion single-photon emission computed tomography. Am Heart J. 1994;128(6 Pt 1):1067\u0026ndash;76.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGholoobi A, Ayati N, Baghyari A, Mouhebati M, Atar B, Dabbagh Kakhki VR. Relationship between gated myocardial perfusion SPECT findings and hemodynamic, electrocardiographic, and heart rate changes after Dipyridamole infusion. Int J Cardiovasc Imaging. 2017;33(6):951\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLette J, Tatum JL, Fraser S, et al. Safety of dipyridamole testing in 73,806 patients: the Multicenter Dipyridamole Safety Study. J Nucl Cardiol. 1995;2(1):3\u0026ndash;17.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eskander S, Iskandrian AE. Risk assessment using single-photon emission computed tomographic technetium-99m sestamibi imaging. J Am Coll Cardiol. 1998;32(1):57\u0026ndash;62.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShaw LJ, Hage FG, Berman DS, Hachamovitch R, Iskandrian A. Prognosis in the era of comparative effectiveness research: where is nuclear cardiology now and where should it be? J Nucl Cardiol. 2012;19(5):1026\u0026ndash;43.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHachamovitch R, Hayes S, Friedman JD, et al. Determinants of risk and its temporal variation in patients with normal stress myocardial perfusion scans: what is the warranty period of a normal scan? J Am Coll Cardiol. 2003;41(8):1329\u0026ndash;40.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHachamovitch R, Berman DS, Shaw LJ, et al. Incremental prognostic value of myocardial perfusion single photon emission computed tomography for the prediction of cardiac death: differential stratification for risk of cardiac death and myocardial infarction. Circulation. 1998;97(6):535\u0026ndash;43.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGiri S, Shaw LJ, Murthy DR, et al. Impact of diabetes on the risk stratification using stress single-photon emission computed tomography myocardial perfusion imaging in patients with symptoms suggestive of coronary artery disease. Circulation. 2002;105(1):32\u0026ndash;40.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAbidov A, Hachamovitch R, Rozanski A, et al. Prognostic implications of atrial fibrillation in patients undergoing myocardial perfusion single-photon emission computed tomography. J Am Coll Cardiol. 2004;44(5):1062\u0026ndash;70.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAskew JW, Miller TD, Hodge DO, Gibbons RJ. The value of myocardial perfusion single-photon emission computed tomography in screening asymptomatic patients with atrial fibrillation for coronary artery disease. J Am Coll Cardiol. 2007;50(11):1080\u0026ndash;5.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAl-Mallah MH, Hachamovitch R, Dorbala S, Di Carli MF. Incremental prognostic value of myocardial perfusion imaging in patients referred to stress single-photon emission computed tomography with renal dysfunction. Circ Cardiovasc Imaging. 2009;2(6):429\u0026ndash;36.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSmit MD, Tio RA, Slart RH, Zijlstra F, Van Gelder IC. Myocardial perfusion imaging does not adequately assess the risk of coronary artery disease in patients with atrial fibrillation. Europace. 2010;12(5):643\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMurthy VL, Naya M, Foster CR, et al. Improved cardiac risk assessment with noninvasive measures of coronary flow reserve. Circulation. 2011;124(20):2215\u0026ndash;24.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNucifora G, Schuijf JD, van Werkhoven JM, et al. Relationship between obstructive coronary artery disease and abnormal stress testing in patients with paroxysmal or persistent atrial fibrillation. Int J Cardiovasc Imaging. 2011;27(6):777\u0026ndash;85.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNair SU, Ahlberg AW, Mathur S, Katten DM, Polk DM, Heller GV. The clinical value of single photon emission computed tomography myocardial perfusion imaging in cardiac risk stratification of very elderly patients (\u0026ge;\u0026thinsp;80 years) with suspected coronary artery disease. J Nucl Cardiol. 2012;19(2):244\u0026ndash;55.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNudi F, Biondi-Zoccai G, Schillaci O, et al. Prognostic accuracy of myocardial perfusion imaging in octogenarians. J Nucl Cardiol. 2018;25(4):1342\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCharytan DM, Skali H, Shah NR, et al. Coronary flow reserve is predictive of the risk of cardiovascular death regardless of chronic kidney disease stage. Kidney Int. 2018;93(2):501\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang FP, Amanullah AM, Kiat H, Friedman JD, Berman DS. Diagnostic efficacy of stress technetium 99m-labeled sestamibi myocardial perfusion single-photon emission computed tomography in detection of coronary artery disease among patients over age 80. J Nucl Cardiol. 1995;2(5):380\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGentile R, Vitarelli A, Schillaci O, et al. Diagnostic accuracy and prognostic implications of stress testing for coronary artery disease in the elderly. Ital Heart J. 2001;2(7):539\u0026ndash;45.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLima RS, De Lorenzo A, Pantoja MR, Siqueira A. Incremental prognostic value of myocardial perfusion 99m-technetium-sestamibi SPECT in the elderly. Int J Cardiol. 2004;93(2\u0026ndash;3):137\u0026ndash;43.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRozanski A, Gransar H, Hayes SW, et al. Temporal trends in the frequency of inducible myocardial ischemia during cardiac stress testing: 1991 to 2009. J Am Coll Cardiol. 2013;61(10):1054\u0026ndash;65.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBeller GA. How Should We Interpret the Decrease in Annual Volume of Stress Imaging Tests for Evaluation of Suspected or Known Coronary Artery Disease With Fewer High-Risk Test Results? Circ Cardiovasc Imaging. 2017;10(7):e006702.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAl Badarin FJ, Chan PS, Spertus JA, et al. Temporal trends in test utilization and prevalence of ischaemia with positron emission tomography myocardial perfusion imaging. Eur Heart J Cardiovasc Imaging. 2020;21(3):318\u0026ndash;25.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLauer MS, Francis GS, Okin PM, Pashkow FJ, Snader CE, Marwick TH. Impaired chronotropic response to exercise stress testing as a predictor of mortality. JAMA. 1999;281(6):524\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLee KH, Yoon JK, Lee MG, Lee SH, Lee WR, Kim BT. Dipyridamole myocardial SPECT with low heart rate response indicates cardiac autonomic dysfunction in patients with diabetes. J Nucl Cardiol. 2001;8(2):129\u0026ndash;35.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAbidov A, Hachamovitch R, Hayes SW, et al. Prognostic impact of hemodynamic response to adenosine in patients older than age 55 years undergoing vasodilator stress myocardial perfusion study. Circulation. 2003;107(23):2894\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHage FG, Iskandrian AE. Heart rate response during vasodilator stress myocardial perfusion imaging: Mechanisms and implications. J Nucl Cardiol. 2010;17(4):536\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMathur S, Shah AR, Ahlberg AW, Katten DM, Heller GV. Blunted heart rate response as a predictor of cardiac death in patients undergoing vasodilator stress technetium-99m sestamibi gated SPECT myocardial perfusion imaging. J Nucl Cardiol. 2010;17(4):617\u0026ndash;24.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGorur GD, Ciftci EA, Kozdag G, et al. Reduced heart rate response to dipyridamole in patients undergoing myocardial perfusion SPECT. Ann Nucl Med. 2012;26(8):609\u0026ndash;15.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCortigiani L, Carpeggiani C, Landi P, Raciti M, Bovenzi F, Picano E. Usefulness of Blunted Heart Rate Reserve as an Imaging-Independent Prognostic Predictor During Dipyridamole Stress Echocardiography. Am J Cardiol. 2019;124(6):972\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBhatheja R, Francis GS, Pothier CE, Lauer MS. Heart rate response during dipyridamole stress as a predictor of mortality in patients with normal myocardial perfusion and normal electrocardiograms. Am J Cardiol. 2005;95(10):1159\u0026ndash;64.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIqbal FM, Al Jaroudi W, Sanam K, et al. Reclassification of cardiovascular risk in patients with normal myocardial perfusion imaging using heart rate response to vasodilator stress. Am J Cardiol. 2013;111(2):190\u0026ndash;5.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDoulgerakis D, Moyssakis I, Kapelios CJ, et al. Cardiac Autonomic Neuropathy Predicts All-Cause and Cardiovascular Mortality in Patients with End-Stage Renal Failure: A 5-Year Prospective Study. Kidney Int Rep. 2017;2(4):686\u0026ndash;94.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEwing DJ, Martyn CN, Young RJ, Clarke BF. The value of cardiovascular autonomic function tests: 10 years experience in diabetes. Diabetes Care. 1985;8(5):491\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTaskiran M, Fritz-Hansen T, Rasmussen V, Larsson HB, Hilsted J. Decreased myocardial perfusion reserve in diabetic autonomic neuropathy. Diabetes. 2002;51(11):3306\u0026ndash;10.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ede Souza R, Machado L, Azevedo AB, De Lorenzo A. Predictors of abnormal heart rate response to dipyridamole in patients undergoing myocardial perfusion SPECT. Ann Nucl Med. 2011;25(1):7\u0026ndash;11.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eValzania C, Torbica A, Tarricone R, Leyva F, Boriani G. Implant rates of cardiac implantable electrical devices in Europe: A systematic literature review. Health Policy. 2016;120(1):1\u0026ndash;15.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eValzania C, Bonfiglioli R, Fallani F, et al. Single-photon cardiac imaging in patients with cardiac implantable electrical devices. J Nucl Cardiol. 2022;29(2):633\u0026ndash;41.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKrijthe BP, Kunst A, Benjamin EJ, et al. Projections on the number of individuals with atrial fibrillation in the European Union, from 2000 to 2060. Eur Heart J. 2013;34(35):2746\u0026ndash;51.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBenjamin EJ, Muntner P, Alonso A, American Heart Association Council on Epidemiology and Prevention Statistics Committee and Stroke Statistics Subcommittee, et al. Heart Disease and Stroke Statistics-2019 Update: A Report from the American Heart Association. Circulation. 2019;139(10):e56\u0026ndash;528.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGimelli A, Liga R, Coceani M, Quaranta A, Emdin M, Marzullo P. Chronotropic response to vasodilator-stress in patients submitted to myocardial perfusion imaging: impact on the accuracy in detecting coronary stenosis. Eur J Nucl Med Mol Imaging. 2015;42(12):1903\u0026ndash;11.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCortigiani L, Carpeggiani C, Landi P, Raciti M, Bovenzi F, Picano E. Prognostic Value of Heart Rate Reserve in Patients with Permanent Atrial Fibrillation during Dipyridamole Stress Echocardiography. Am J Cardiol. 2020;125(11):1661\u0026ndash;5.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSharir T, Germano G, Kavanagh PB, et al. Incremental prognostic value of post-stress left ventricular ejection fraction and volume by gated myocardial perfusion single photon emission computed tomography. Circulation. 1999;100(10):1035\u0026ndash;42.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDe Lorenzo A, Lima RS, Siqueira-Filho AG, Pantoja MR. Prevalence and prognostic value of perfusion defects detected by stress technetium-99m sestamibi myocardial perfusion single-photon emission computed tomography in asymptomatic patients with diabetes mellitus and no known coronary artery disease. Am J Cardiol. 2002;90(8):827\u0026ndash;32.\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-cardiovascular-disorders","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcar","sideBox":"Learn more about [BMC Cardiovascular Disorders](http://bmccardiovascdisord.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcar/default.aspx","title":"BMC Cardiovascular Disorders","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"SPECT, Dipyridamole, ischemic heart disease, blunted heart rate response","lastPublishedDoi":"10.21203/rs.3.rs-8176602/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8176602/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cb\u003eBackground\u003c/b\u003e\u003c/p\u003e \u003cp\u003eDipyridamole stress cardiac 99mTc Single Photon Emission Computed Tomography (DS-SPECT) is a common method for detecting myocardial ischemia in selected patients. Blunted heart rate response (BHRR) during pharmacological stress is a known risk factor for mortality and morbidity. With increasing prevalence of referred patients with significant comorbidities, often excluded in studies, an all-comers population was evaluated to better represent the patients undergoing DS-SPECT. This study aimed to determine the prognostic significance of BHRR compared to DS-SPECT imaging results.\u003c/p\u003e\u003cp\u003e\u003cb\u003eMethods\u003c/b\u003e\u003c/p\u003e \u003cp\u003eWe conducted an all comer, single-center, retrospective cohort study. All patients subjected to DS-SPECT, years 2014 to 2017, were included.\u003c/p\u003e\u003cp\u003e\u003cb\u003eResults\u003c/b\u003e\u003c/p\u003e \u003cp\u003eStudy population consisted of 388 patients, 227 (58.5%) had normal imaging results, and 245 (63.1%) exhibited BHRR. During a mean follow-up of four years, multivariable analysis identified BHRR as the strongest independent predictor of cardiovascular death (HR 8.09, CI: 1.2\u0026ndash;11.6, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Patients with abnormal DS-SPECT imaging and BHRR had a nearly fourfold increased risk of adverse cardiovascular events (HR 3.79, CI: 1.06\u0026ndash;61.91, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Moreover, individuals demonstrating both abnormal imaging results and BHRR experienced the highest rate of all-cause mortality (HR 2.93, CI: 1.1\u0026ndash;7.7, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01). Overall, BHRR significantly correlated with increased all-cause and cardiovascular mortality.\u003c/p\u003e\u003cp\u003e\u003cb\u003eConclusions\u003c/b\u003e\u003c/p\u003e \u003cp\u003eIn unselected patients referred for DS-SPECT, BHRR was an independent predictor of cardiovascular mortality, stronger than imaging findings. When combined with abnormal imaging results, BHRR significantly improves the prediction value of DS-SPECT for cardiovascular morbidity and all-cause mortality. These findings suggest inclusion of BHRR in DS-SPECT studies.\u003c/p\u003e","manuscriptTitle":"Blunted Heart Rate Response Enhances Prognostic Value of Dipyridamole Stress SPECT for Cardiovascular Morbidity and Mortality in All-Comers","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-17 00:13:10","doi":"10.21203/rs.3.rs-8176602/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-01-08T05:38:02+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-05T16:18:04+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"286132604056162589344847290020313119952","date":"2026-01-05T16:07:35+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-04T05:36:10+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"287055596651930458674218370801130483202","date":"2026-01-02T11:59:03+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-12-11T05:28:00+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-11-28T06:02:25+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-11-27T13:26:59+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-11-27T13:25:13+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Cardiovascular Disorders","date":"2025-11-21T21:06:16+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-cardiovascular-disorders","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcar","sideBox":"Learn more about [BMC Cardiovascular Disorders](http://bmccardiovascdisord.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcar/default.aspx","title":"BMC Cardiovascular Disorders","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"26365947-8944-4b94-a2ce-6c3cea15863f","owner":[],"postedDate":"December 17th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-23T20:08:39+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-17 00:13:10","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8176602","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8176602","identity":"rs-8176602","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}