Pub Date : 2024-07-26DOI: 10.1101/2024.07.24.24310960
Rajul K. Ranka, Krishan Gupta, Felix Naegele, Alexander J Lu, Shuang Li, Michael Graber, Kaylee N Carter, Anahita Mojiri, Lili Zhang, Arvind Bhimaraj, Li Lai, Keith A Youker, Kaifu Chen, John P Cooke
Heart failure (HF) remains a major cause of morbidity and mortality worldwide, with limited treatment options. Heart transplantation is an end stage option but limited by donor availability. Left-ventricular assist device (LVAD) implantation serves as a bridging strategy for patients awaiting a transplant. Intriguingly, LVAD support (typically for 6-12 months before heart transplantation) is often associated with some level of improvement in cardiac function and histology. In rare cases, LVAD support can improve cardiac function sufficiently to avoid heart transplantation after LVAD removal. The underlying mechanisms of this improvement in cardiac function are not understood. Here, we provide evidence that the improvement in cardiac function post-LVAD is associated with a reduction in fibrosis and an increase in capillary density. This heart failure recovery (HFR) is also associated with an angiogenic cell fate transition. We observed a distinct pro-angiogenic phenotype of cardiac non-myocytes isolated from post-LVAD hearts. Single-nuclei RNA sequencing of pre- and post-LVAD cardiac tissue reveals a fibroblast subtype that undergoes mesenchymal to endothelial transition (MEndoT), potentially facilitating HFR. In a murine model of HFR, lineage tracing studies confirm that MEndoT is associated with the increase in capillary density and perfusion during HFR. In summary, our results support the new concept that HFR is associated with a reduction in interstitial cardiac fibrosis, an increase in capillary density and perfusion, that is due in part to an angiogenic cell fate transition. Our work represents a shift in the conceptual framework regarding mechanisms of HFR, and a new therapeutic avenue for exploration.
{"title":"Recovery from Heart Failure is a Vascular Recovery","authors":"Rajul K. Ranka, Krishan Gupta, Felix Naegele, Alexander J Lu, Shuang Li, Michael Graber, Kaylee N Carter, Anahita Mojiri, Lili Zhang, Arvind Bhimaraj, Li Lai, Keith A Youker, Kaifu Chen, John P Cooke","doi":"10.1101/2024.07.24.24310960","DOIUrl":"https://doi.org/10.1101/2024.07.24.24310960","url":null,"abstract":"Heart failure (HF) remains a major cause of morbidity and mortality worldwide, with limited treatment options. Heart transplantation is an end stage option but limited by donor availability. Left-ventricular assist device (LVAD) implantation serves as a bridging strategy for patients awaiting a transplant. Intriguingly, LVAD support (typically for 6-12 months before heart transplantation) is often associated with some level of improvement in cardiac function and histology. In rare cases, LVAD support can improve cardiac function sufficiently to avoid heart transplantation after LVAD removal. The underlying mechanisms of this improvement in cardiac function are not understood. Here, we provide evidence that the improvement in cardiac function post-LVAD is associated with a reduction in fibrosis and an increase in capillary density. This heart failure recovery (HFR) is also associated with an angiogenic cell fate transition. We observed a distinct pro-angiogenic phenotype of cardiac non-myocytes isolated from post-LVAD hearts. Single-nuclei RNA sequencing of pre- and post-LVAD cardiac tissue reveals a fibroblast subtype that undergoes mesenchymal to endothelial transition (MEndoT), potentially facilitating HFR. In a murine model of HFR, lineage tracing studies confirm that MEndoT is associated with the increase in capillary density and perfusion during HFR. In summary, our results support the new concept that HFR is associated with a reduction in interstitial cardiac fibrosis, an increase in capillary density and perfusion, that is due in part to an angiogenic cell fate transition. Our work represents a shift in the conceptual framework regarding mechanisms of HFR, and a new therapeutic avenue for exploration.","PeriodicalId":501297,"journal":{"name":"medRxiv - Cardiovascular Medicine","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141771903","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-25DOI: 10.1101/2024.07.24.24310950
Jingchunzi Shi, Suyash S. Shringarpure, David Hinds, 23andMe Research Team, Adam Auton, Michael V. Holmes
Background: Lipoprotein(a) (Lp[a]) is a circulating plasma lipoprotein that is emerging as an important independent risk factor for vascular disease. Lp(a) levels are 75-90% heritable, predominantly determined by copy number variation and single nucleotide polymorphisms (SNPs) at the LPA gene. Methods: Using ~370K individuals with serum measurements of Lp(a) in the UK Biobank European cohort, we constructed a genetic risk score (GRS) consisting of 29 SNPs in the vicinity of LPA which explained 68.18% of variation in Lp(a). Using the LPA GRS to instrument Lp(a), we conducted phenome-wide Mendelian randomization analysis (MR-PheWAS) across a spectrum of 489 medically-relevant phenotypes in ~7.3M individuals from the 23andMe, Inc. database, and compared effects to those derived from a GRS for low-density lipoprotein cholesterol (LDL-C) and apolipoprotein B (apoB). Through multivariable MR, we sought to assess the direct causal effect of Lp(a) on cardiovascular disease risks while keeping LDL-C or apoB constant. Results: MR-PheWAS confirmed previously reported Lp(a) causal effects on coronary artery disease (CAD: OR = 1.199, 95% CI = [1.193, 1.205], p-value < 2.23e-308, for every 59.632 nmol/L higher Lp(a) instrumented by the LPA GRS), and revealed additional genetically-predicted effects largely confined to cardiovascular endpoints, including a novel effect for restrictive cardiomyopathy (OR = 1.101, 95% CI = [1.068, 1.134], p-value = 3e-10). We scaled the LPA, LDL-C and apoB GRS such that they each had the same OR for MACE (major adverse cardiovascular events). Using the scaling rubric, similar magnitudes of effect were seen for the three lipid traits for most vascular diseases, with the exception of peripheral artery disease, aortic stenosis and dilated cardiomyopathy, where Lp(a) had larger genetically-predicted effect sizes compared to LDL-C and apoB. Multivariable MR identified Lp(a) to retain a causal effect on MACE while accounting for LDL-C or apoB. To achieve the 25% relative risk reduction in major vascular events, as seen with a 1 mmol/L reduction in LDL-C from statin trials, we anticipate that Lp(a) ought to be reduced by ~ 90 mg/dL (200 nmol/L), highlighting the importance of not only using therapies that have a profound impact on Lp(a) lowering, but also selecting individuals that have high Lp(a) concentrations at baseline. Conclusion: Lp(a) has genetically-predicted causal effects on a broad range of cardiovascular diseases beyond CAD, with minimal effects seen for non-vascular disease.
{"title":"Evaluating genetically-predicted causal effects of lipoprotein(a) in human diseases: a phenome-wide Mendelian randomization study","authors":"Jingchunzi Shi, Suyash S. Shringarpure, David Hinds, 23andMe Research Team, Adam Auton, Michael V. Holmes","doi":"10.1101/2024.07.24.24310950","DOIUrl":"https://doi.org/10.1101/2024.07.24.24310950","url":null,"abstract":"Background: Lipoprotein(a) (Lp[a]) is a circulating plasma lipoprotein that is emerging as an important independent risk factor for vascular disease. Lp(a) levels are 75-90% heritable, predominantly determined by copy number variation and single nucleotide polymorphisms (SNPs) at the LPA gene. Methods: Using ~370K individuals with serum measurements of Lp(a) in the UK Biobank European cohort, we constructed a genetic risk score (GRS) consisting of 29 SNPs in the vicinity of LPA which explained 68.18% of variation in Lp(a). Using the LPA GRS to instrument Lp(a), we conducted phenome-wide Mendelian randomization analysis (MR-PheWAS) across a spectrum of 489 medically-relevant phenotypes in ~7.3M individuals from the 23andMe, Inc. database, and compared effects to those derived from a GRS for low-density lipoprotein cholesterol (LDL-C) and apolipoprotein B (apoB). Through multivariable MR, we sought to assess the direct causal effect of Lp(a) on cardiovascular disease risks while keeping LDL-C or apoB constant. Results: MR-PheWAS confirmed previously reported Lp(a) causal effects on coronary artery disease (CAD: OR = 1.199, 95% CI = [1.193, 1.205], p-value < 2.23e-308, for every 59.632 nmol/L higher Lp(a) instrumented by the LPA GRS), and revealed additional genetically-predicted effects largely confined to cardiovascular endpoints, including a novel effect for restrictive cardiomyopathy (OR = 1.101, 95% CI = [1.068, 1.134], p-value = 3e-10). We scaled the LPA, LDL-C and apoB GRS such that they each had the same OR for MACE (major adverse cardiovascular events). Using the scaling rubric, similar magnitudes of effect were seen for the three lipid traits for most vascular diseases, with the exception of peripheral artery disease, aortic stenosis and dilated cardiomyopathy, where Lp(a) had larger genetically-predicted effect sizes compared to LDL-C and apoB. Multivariable MR identified Lp(a) to retain a causal effect on MACE while accounting for LDL-C or apoB. To achieve the 25% relative risk reduction in major vascular events, as seen with a 1 mmol/L reduction in LDL-C from statin trials, we anticipate that Lp(a) ought to be reduced by ~ 90 mg/dL (200 nmol/L), highlighting the importance of not only using therapies that have a profound impact on Lp(a) lowering, but also selecting individuals that have high Lp(a) concentrations at baseline. Conclusion: Lp(a) has genetically-predicted causal effects on a broad range of cardiovascular diseases beyond CAD, with minimal effects seen for non-vascular disease.","PeriodicalId":501297,"journal":{"name":"medRxiv - Cardiovascular Medicine","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141771904","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-25DOI: 10.1101/2024.07.24.24310961
Fawaz Naeem, Teresa C Leone, Christopher Petucci, Clarissa Shoffler, Ravindra Kodihalli, Tiffany Hidalgo, Cheryl Tow-Keogh, Jessica Y Mancuso, Iphigenia Tzameli, Donald Bennett, John D Groarke, Rachel J. Roth Flach, Daniel J Rader, Daniel P Kelly
Background. Two general phenotypes of heart failure (HF) are recognized: HF with reduced ejection fraction (HFrEF) and with preserved EF (HFpEF). To develop HF disease phenotype-specific approaches to define and guide treatment, distinguishing biomarkers are needed. The goal of this study was to utilize quantitative metabolomics on a large, diverse population to replicate and extend existing knowledge of the plasma metabolic signatures in human HF. Methods. Quantitative, targeted LC/MS plasma metabolomics was conducted on 787 samples collected by the Penn Medicine BioBank from subjects with HFrEF (n=219), HFpEF (n=357), and matched non-failing Controls (n=211). A total of 90 metabolites were analyzed, comprising 28 amino acids, 8 organic acids, and 54 acylcarnitines. 733 of these samples were also processed via an OLINK protein panel for proteomic profiling. Results. Consistent with previous studies, unsaturated forms of medium/long chain acylcarnitines were elevated in the HFrEF group to a greater extent than the HFpEF group compared to Controls. A number of amino acid derivatives, including 1- and 3-methylhistidine, homocitrulline, and symmetric (SDMA) and asymmetric (ADMA) dimethylarginine were elevated in HF, with ADMA elevated uniquely in HFpEF. Plasma branched-chain amino acids (BCAA) were not different across the groups; however, short-chain acylcarnitine species indicative of BCAA catabolism were significantly elevated in both HF groups. The ketone body 3-hydroxybutyrate (3-HBA) and its metabolite C4-OH carnitine were uniquely elevated in the HFrEF group. Linear regression models demonstrated a significant correlation between plasma 3-HBA and NT-proBNP in both forms of HF, stronger in HFrEF. Conclusions. These results identify plasma signatures that are shared as well as potentially distinguish between HFrEF and HFpEF. Metabolite markers for ketogenic metabolic re-programming in extra-cardiac tissues were identified as unique signatures in the HFrEF group, possibly related to the lipolytic action of increased levels of BNP. Future studies will be necessary to further validate these metabolites as HF biosignatures that may guide phenotype-specific therapeutics and provide insight into the systemic metabolic responses to HFpEF and HFrEF.
{"title":"Targeted Quantitative Plasma Metabolomics Identifies Metabolite Signatures that Distinguish Heart Failure with Reduced and Preserved Ejection Fraction","authors":"Fawaz Naeem, Teresa C Leone, Christopher Petucci, Clarissa Shoffler, Ravindra Kodihalli, Tiffany Hidalgo, Cheryl Tow-Keogh, Jessica Y Mancuso, Iphigenia Tzameli, Donald Bennett, John D Groarke, Rachel J. Roth Flach, Daniel J Rader, Daniel P Kelly","doi":"10.1101/2024.07.24.24310961","DOIUrl":"https://doi.org/10.1101/2024.07.24.24310961","url":null,"abstract":"Background. Two general phenotypes of heart failure (HF) are recognized: HF with reduced ejection fraction (HFrEF) and with preserved EF (HFpEF). To develop HF disease phenotype-specific approaches to define and guide treatment, distinguishing biomarkers are needed. The goal of this study was to utilize quantitative metabolomics on a large, diverse population to replicate and extend existing knowledge of the plasma metabolic signatures in human HF. Methods. Quantitative, targeted LC/MS plasma metabolomics was conducted on 787 samples collected by the Penn Medicine BioBank from subjects with HFrEF (n=219), HFpEF (n=357), and matched non-failing Controls (n=211). A total of 90 metabolites were analyzed, comprising 28 amino acids, 8 organic acids, and 54 acylcarnitines. 733 of these samples were also processed via an OLINK protein panel for proteomic profiling. Results. Consistent with previous studies, unsaturated forms of medium/long chain acylcarnitines were elevated in the HFrEF group to a greater extent than the HFpEF group compared to Controls. A number of amino acid derivatives, including 1- and 3-methylhistidine, homocitrulline, and symmetric (SDMA) and asymmetric (ADMA) dimethylarginine were elevated in HF, with ADMA elevated uniquely in HFpEF. Plasma branched-chain amino acids (BCAA) were not different across the groups; however, short-chain acylcarnitine species indicative of BCAA catabolism were significantly elevated in both HF groups. The ketone body 3-hydroxybutyrate (3-HBA) and its metabolite C4-OH carnitine were uniquely elevated in the HFrEF group. Linear regression models demonstrated a significant correlation between plasma 3-HBA and NT-proBNP in both forms of HF, stronger in HFrEF. Conclusions. These results identify plasma signatures that are shared as well as potentially distinguish between HFrEF and HFpEF. Metabolite markers for ketogenic metabolic re-programming in extra-cardiac tissues were identified as unique signatures in the HFrEF group, possibly related to the lipolytic action of increased levels of BNP. Future studies will be necessary to further validate these metabolites as HF biosignatures that may guide phenotype-specific therapeutics and provide insight into the systemic metabolic responses to HFpEF and HFrEF.","PeriodicalId":501297,"journal":{"name":"medRxiv - Cardiovascular Medicine","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141771982","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-24DOI: 10.1101/2024.07.21.24302849
Shoshi Shpitzen, Haim Rosen, Ayal Ben-Zvi, Karen Meir, Galina Levin, Amichay Gudgold, Shifra Ben-Dor, Rebecca Haffner, Donna R R Zwas, David Leibowitz, Susan A Slaugenhaupt, Eyal Banin, Rotem Mizrachi, Alexey Obolensky, Robert A Levine, Dan Gilon, Eran Leitersdorf, Idit Tessler, Noga Reshef, Ronen Durst
Background: Mitral Valve Prolapse (MVP) is a prevalent valvular disorder linked to considerable morbidity and mortality, affecting approximately 2.4% of the general population. A prior genome association study linked LTBP2 to this trait. We report a knockout mouse with LTBP2 mutation demonstrating valve phenotype as well as a family with a novel mutation causing MVP Methods: Exome sequencing and segregation analysis were conducted on a large pedigree to identify mutations associated with MVP. Using CRISPR-Cas9 technology, two strains of mice were generated: one with a complete knockout (KO) of the LTBP2 gene and another with a knock-in (KI) mutation corresponding to the putative causative mutation. Echocardiography and histological examinations of valves were performed in the KO and the KI at the age of 6 months. Optical coherence tomography (OCT) and histological examination of the eyes was done at the same time. mRNA qPCR analysis for TGFβ signaling targets (periostin/POSTN, RUNX2, and CTGF) in valve tissues was analyzed. Results: The LTBP2 rs117800773 V1506M mutation exhibited segregation with the MVP trait. LTBP2 KO mice had higher incidence of myxomatous changes by histology (7 of 9 of KO vs. 0 of 7 control animals, p=0.00186) and echocardiography (7 of 9 vs. 0 of 8, p=0.0011). LTBP2 Knock-in mice for the human mutation showed a significantly elevated myxomatous histological phenotype (8 of 8 vs. 0 of 9, p=0.00004) as well as by echocardiography (6 of 8 vs. 0 of 9, p=0.00123). KO mice demonstrated a significant increase in the depth of the anterior chamber as well as reduced visual acuity. LTBP2 KO mice demonstrated overexpression of both TGFβ signaling targets RUNX2 and periostin (P=0.0144 and P=0.001826, respectively). Conclusion: Animal models of LTBP2 KO and KI recapitulate MVP phenotype indicating that LTBP2 mutations are indeed causing myxomatous degeneration. Further, LTBP2 rs117800773 V1506M segregated with MVP in a large pedigree. Our data indicate the importance of LTBP2 in normal mitral valve function and that mutations in the gene care causing myxomatous valve.
{"title":"Characterization of LTBP2 mutation causing Mitral Valve Prolapse","authors":"Shoshi Shpitzen, Haim Rosen, Ayal Ben-Zvi, Karen Meir, Galina Levin, Amichay Gudgold, Shifra Ben-Dor, Rebecca Haffner, Donna R R Zwas, David Leibowitz, Susan A Slaugenhaupt, Eyal Banin, Rotem Mizrachi, Alexey Obolensky, Robert A Levine, Dan Gilon, Eran Leitersdorf, Idit Tessler, Noga Reshef, Ronen Durst","doi":"10.1101/2024.07.21.24302849","DOIUrl":"https://doi.org/10.1101/2024.07.21.24302849","url":null,"abstract":"Background: Mitral Valve Prolapse (MVP) is a prevalent valvular disorder linked to considerable morbidity and mortality, affecting approximately 2.4% of the general population. A prior genome association study linked LTBP2 to this trait. We report a knockout mouse with LTBP2 mutation demonstrating valve phenotype as well as a family with a novel mutation causing MVP Methods: Exome sequencing and segregation analysis were conducted on a large pedigree to identify mutations associated with MVP. Using CRISPR-Cas9 technology, two strains of mice were generated: one with a complete knockout (KO) of the LTBP2 gene and another with a knock-in (KI) mutation corresponding to the putative causative mutation. Echocardiography and histological examinations of valves were performed in the KO and the KI at the age of 6 months. Optical coherence tomography (OCT) and histological examination of the eyes was done at the same time. mRNA qPCR analysis for TGFβ signaling targets (periostin/POSTN, RUNX2, and CTGF) in valve tissues was analyzed. Results: The LTBP2 rs117800773 V1506M mutation exhibited segregation with the MVP trait. LTBP2 KO mice had higher incidence of myxomatous changes by histology (7 of 9 of KO vs. 0 of 7 control animals, p=0.00186) and echocardiography (7 of 9 vs. 0 of 8, p=0.0011). LTBP2 Knock-in mice for the human mutation showed a significantly elevated myxomatous histological phenotype (8 of 8 vs. 0 of 9, p=0.00004) as well as by echocardiography (6 of 8 vs. 0 of 9, p=0.00123). KO mice demonstrated a significant increase in the depth of the anterior chamber as well as reduced visual acuity. LTBP2 KO mice demonstrated overexpression of both TGFβ signaling targets RUNX2 and periostin (P=0.0144 and P=0.001826, respectively). Conclusion: Animal models of LTBP2 KO and KI recapitulate MVP phenotype indicating that LTBP2 mutations are indeed causing myxomatous degeneration. Further, LTBP2 rs117800773 V1506M segregated with MVP in a large pedigree. Our data indicate the importance of LTBP2 in normal mitral valve function and that mutations in the gene care causing myxomatous valve.","PeriodicalId":501297,"journal":{"name":"medRxiv - Cardiovascular Medicine","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141771905","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Background: Fulminant myocarditis (FM) is an acute fatal inflammation disease, but its chronic phase is unclear. A Japanese nationwide registry evaluated the long-term mortality in FM patients using a prognostic nutritional index (PNI). Methods and Results: The retrospective cohort study included patients with clinically suspected or histologically proven FM available for PNI. PNI was assessed on admission and at discharge. We divided patients into two groups based on PNI at discharge (PNI ≤40 or PNI >40) and analyzed the change in PNI and mortality between the groups. Of 323 patients (the median [first-third quartiles] age of this cohort was 50 [37-64] years, and 143 [44%] were female), PNI ≤40 at discharge was in 99 (31%) patients. The median PNI in all patients increased from 41 (36-46) on admission to 43 (39-48) at discharge (P<0.0001). Patients with PNI ≤40 had a lower event-free rate of death or rehospitalization with cardiovascular causes than those with PNI >40 (log-rank P=0.0001). When the PNI at discharge, age, sex, left ventricular ejection fraction, and Barthel index were evaluated in a multivariable Cox regression analysis, the PNI had an independent association with the death or rehospitalization with cardiovascular causes (hazard ratio, 0.95 [95% confidence interval, 0.91-0.99]; P=0.0289). Conclusions: One-third of FM patients with low PNI at discharge had a higher risk of mortality than those with high PNI in the chronic phase. This study provokes clinical insight into the phenotype of chronic inflammation in FM and optimal follow-up management with low PNI.
{"title":"Prognostic Nutritional Index in Risk of Mortality Following Fulminant Myocarditis","authors":"Shunichi Doi, Yuki Ishibashi, Norio Suzuki, Daisuke Miyahara, Yukio Sato, Shingo Kuwata, Keisuke Kida, Masaki Izumo, Kenji Onoue, Koshiro Kanaoka, Yoshihiko Saito, Yoshihiro J Akashi","doi":"10.1101/2024.07.22.24310842","DOIUrl":"https://doi.org/10.1101/2024.07.22.24310842","url":null,"abstract":"Background: Fulminant myocarditis (FM) is an acute fatal inflammation disease, but its chronic phase is unclear. A Japanese nationwide registry evaluated the long-term mortality in FM patients using a prognostic nutritional index (PNI).\u0000Methods and Results: The retrospective cohort study included patients with clinically suspected or histologically proven FM available for PNI. PNI was assessed on admission and at discharge. We divided patients into two groups based on PNI at discharge (PNI ≤40 or PNI >40) and analyzed the change in PNI and mortality between the groups. Of 323 patients (the median [first-third quartiles] age of this cohort was 50 [37-64] years, and 143 [44%] were female), PNI ≤40 at discharge was in 99 (31%) patients. The median PNI in all patients increased from 41 (36-46) on admission to 43 (39-48) at discharge (P<0.0001). Patients with PNI ≤40 had a lower event-free rate of death or rehospitalization with cardiovascular causes than those with PNI >40 (log-rank P=0.0001). When the PNI at discharge, age, sex, left ventricular ejection fraction, and Barthel index were evaluated in a multivariable Cox regression analysis, the PNI had an independent association with the death or rehospitalization with cardiovascular causes (hazard ratio, 0.95 [95% confidence interval, 0.91-0.99]; P=0.0289).\u0000Conclusions: One-third of FM patients with low PNI at discharge had a higher risk of mortality than those with high PNI in the chronic phase. This study provokes clinical insight into the phenotype of chronic inflammation in FM and optimal follow-up management with low PNI.","PeriodicalId":501297,"journal":{"name":"medRxiv - Cardiovascular Medicine","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141771983","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-19DOI: 10.1101/2024.07.18.24310670
Ehsan Vaghefi, Songyang An, Shima Moghadam, Song Yang, Li Xie, Mary K Durbin, Huiyuan Hou, Robert N Weinreb, David Squirrell, Michael V McConnell
Background: There is a growing recognition of the divergence between biological and chronological age, as well as the interaction among cardiovascular, kidney, and metabolic (CKM) diseases, known as CKM syndrome, in shortening both lifespan and healthspan. Detecting indicators of CKM syndrome can prompt lifestyle and risk-factor management to prevent progression to adverse clinical events. In this study, we tested a novel deep-learning model, retinal BioAge, to determine whether it could identify individuals with a higher prevalence of CKM indicators compared to their peers of similar chronological age. Methods: Retinal images and health records were analyzed from both the UK Biobank population health study and the US-based EyePACS 10K dataset of persons living with diabetes. 77,887 retinal images from 44,731 unique participants were used to train the retinal BioAge model. For validation, separate test sets of 10,976 images (5,476 individuals) from UK Biobank and 19,856 retinal images (9,786 individuals) from EyePACS 10K were analyzed. Retinal AgeGap (retinal BioAge — chronological age) was calculated for each participant, and those in the top and bottom retinal AgeGap quartiles were compared for prevalence of abnormal blood pressure, cholesterol, kidney function, and hemoglobin A1c. Results: In UK Biobank, participants in the top retinal AgeGap quartile had significantly higher prevalence of hypertension compared to the bottom quartile (36.3% vs. 29.0%, p<0.001), while the prevalence was similar for elevated non-HDL cholesterol (77.9% vs. 78.4%, p=0.80), impaired kidney function (4.8% vs. 4.2%, p=0.60), and diabetes (3.1% vs. 2.2%, p=0.24). In contrast, EyePACS 10K individuals in the top retinal AgeGap quartile had higher prevalence of elevated non-HDL cholesterol (49.9% vs. 43.0%, p<0.001), impaired kidney function (36.7% vs. 23.1%, p<0.001), suboptimally controlled diabetes (76.5% vs. 60.0%, p<0.001), and diabetic retinopathy (52.9% vs. 8.0%, p<0.001), but not hypertension (53.8% vs. 55.4%, p=0.33). Conclusion: A deep-learning retinal BioAge model identified individuals who had a higher prevalence of underlying indicators of CKM syndrome compared to their peers, particularly in a diverse US dataset of persons living with diabetes.
{"title":"Retinal BioAge Reveals Indicators of Cardiovascular-Kidney-Metabolic Syndrome in US and UK Populations","authors":"Ehsan Vaghefi, Songyang An, Shima Moghadam, Song Yang, Li Xie, Mary K Durbin, Huiyuan Hou, Robert N Weinreb, David Squirrell, Michael V McConnell","doi":"10.1101/2024.07.18.24310670","DOIUrl":"https://doi.org/10.1101/2024.07.18.24310670","url":null,"abstract":"Background: There is a growing recognition of the divergence between biological and chronological age, as well as the interaction among cardiovascular, kidney, and metabolic (CKM) diseases, known as CKM syndrome, in shortening both lifespan and healthspan. Detecting indicators of CKM syndrome can prompt lifestyle and risk-factor management to prevent progression to adverse clinical events. In this study, we tested a novel deep-learning model, retinal BioAge, to determine whether it could identify individuals with a higher prevalence of CKM indicators compared to their peers of similar chronological age. Methods: Retinal images and health records were analyzed from both the UK Biobank population health study and the US-based EyePACS 10K dataset of persons living with diabetes. 77,887 retinal images from 44,731 unique participants were used to train the retinal BioAge model. For validation, separate test sets of 10,976 images (5,476 individuals) from UK Biobank and 19,856 retinal images (9,786 individuals) from EyePACS 10K were analyzed. Retinal AgeGap (retinal BioAge — chronological age) was calculated for each participant, and those in the top and bottom retinal AgeGap quartiles were compared for prevalence of abnormal blood pressure, cholesterol, kidney function, and hemoglobin A1c. Results: In UK Biobank, participants in the top retinal AgeGap quartile had significantly higher prevalence of hypertension compared to the bottom quartile (36.3% vs. 29.0%, p<0.001), while the prevalence was similar for elevated non-HDL cholesterol (77.9% vs. 78.4%, p=0.80), impaired kidney function (4.8% vs. 4.2%, p=0.60), and diabetes (3.1% vs. 2.2%, p=0.24). In contrast, EyePACS 10K individuals in the top retinal AgeGap quartile had higher prevalence of elevated non-HDL cholesterol (49.9% vs. 43.0%, p<0.001), impaired kidney function (36.7% vs. 23.1%, p<0.001), suboptimally controlled diabetes (76.5% vs. 60.0%, p<0.001), and diabetic retinopathy (52.9% vs. 8.0%, p<0.001), but not hypertension (53.8% vs. 55.4%, p=0.33). Conclusion: A deep-learning retinal BioAge model identified individuals who had a higher prevalence of underlying indicators of CKM syndrome compared to their peers, particularly in a diverse US dataset of persons living with diabetes.","PeriodicalId":501297,"journal":{"name":"medRxiv - Cardiovascular Medicine","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141739044","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Background: Recently, radiofrequency catheter ablation (RFCA) has become an important treatment strategy for atrial fibrillation (AF). During this procedure, achieving first-pass pulmonary vein (PV) isolation — PV isolation in which no residual conduction gap remains following initial circumferential lesion is created around the PV — has proven to lead better results in terms of AF recurrence. Although various risk factors for the creation of residual conduction gap have been proposed, the relationship between the transseptal puncture location on fossa ovalis and first-pass PV isolation success rate has not been clarified. Therefore, we investigate the relationship through this investigation. Methods: Overall, 102 consecutive patients who had undergone their first RFCA for AF were included. These patients were divided based on the transseptal puncture location (infero-anterior, infero-posterior, supero-anterior, and supero-posterior), which was confirmed by imaging of three-dimensional structure of the anatomical fossa ovalis creating intracardiac echocardiography. The relationship between transseptal puncture location and the first-pass PV isolation success rate was analyzed. Results: Among all 102 patients, the number of transseptal puncture locations located in infero-anterior, infero-posterior, supero-anterior, and supero-posterior were 26, 61, 6, and 9 respectively. Among these, first-pass PV isolation success rate in the infero-posterior group exhibited the highest 79% (48/61 patients) compared to that in other locations [infero-anterior 61% (16/26 patients), supero-anterior 33% (2/6 patients), and supero-posterior 44% (4/9 patients); P=0.02]. Regarding ablation parameters, although the ablation index was not significantly different between each group (infero-anterior 401.6±7.6, infero-posterior 401.9±5.2, supero-anterior 397.5±4.7, and supero-posterior 398.6±5.3, P = 0.176). The P-vector, which represents insufficient catheter contact, was significantly observed lower frequency in the infero-posterior group (8.6%; P < 0.01) than in the other groups. Conclusion: The transseptal puncture location in PV isolation is an important factor to achieve first-pass PV isolation, and it might affect AF recurrence.
{"title":"Impact of transseptal puncture location on the fossa ovalis on first-pass pulmonary vein isolation","authors":"Kohei Matsunaga, Tadashi Hoshiyama, Shozo Kaneko, Hitoshi Sumi, Hisanori Kanazawa, Yuta Tsurusaki, Yuichiro Tsuruta, Masanobu Ishii, Shinsuke Hanatani, Hiroki Usuku, Eiichiro Yamamoto, Yasuhiro Izumiya, Kenichi Tsujita","doi":"10.1101/2024.07.18.24310668","DOIUrl":"https://doi.org/10.1101/2024.07.18.24310668","url":null,"abstract":"Background: Recently, radiofrequency catheter ablation (RFCA) has become an important treatment strategy for atrial fibrillation (AF). During this procedure, achieving first-pass pulmonary vein (PV) isolation — PV isolation in which no residual conduction gap remains following initial circumferential lesion is created around the PV — has proven to lead better results in terms of AF recurrence. Although various risk factors for the creation of residual conduction gap have been proposed, the relationship between the transseptal puncture location on fossa ovalis and first-pass PV isolation success rate has not been clarified. Therefore, we investigate the relationship through this investigation.\u0000Methods: Overall, 102 consecutive patients who had undergone their first RFCA for AF were included. These patients were divided based on the transseptal puncture location (infero-anterior, infero-posterior, supero-anterior, and supero-posterior), which was confirmed by imaging of three-dimensional structure of the anatomical fossa ovalis creating intracardiac echocardiography. The relationship between transseptal puncture location and the first-pass PV isolation success rate was analyzed.\u0000Results: Among all 102 patients, the number of transseptal puncture locations located in infero-anterior, infero-posterior, supero-anterior, and supero-posterior were 26, 61, 6, and 9 respectively. Among these, first-pass PV isolation success rate in the infero-posterior group exhibited the highest 79% (48/61 patients) compared to that in other locations [infero-anterior 61% (16/26 patients), supero-anterior 33% (2/6 patients), and supero-posterior 44% (4/9 patients); P=0.02]. Regarding ablation parameters, although the ablation index was not significantly different between each group (infero-anterior 401.6±7.6, infero-posterior 401.9±5.2, supero-anterior 397.5±4.7, and supero-posterior 398.6±5.3, P = 0.176). The P-vector, which represents insufficient catheter contact, was significantly observed lower frequency in the infero-posterior group (8.6%; P < 0.01) than in the other groups.\u0000Conclusion: The transseptal puncture location in PV isolation is an important factor to achieve first-pass PV isolation, and it might affect AF recurrence.","PeriodicalId":501297,"journal":{"name":"medRxiv - Cardiovascular Medicine","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141738773","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-19DOI: 10.1101/2024.07.18.24310539
Rebecca Fisher, Nick S. Nurmohamed, Edward A. Fisher, Melissa Aquino, James P. Earls, James K Min, Chen Gurevitz, Waqas Malick, Robert Peters, Sascha N Goonewardena, Robert S. Rosenson
BACKGROUND: Lipoprotein(a) [Lp(a)] is an inherited risk factor for cardiovascular disease that is accompanied by a more severe coronary artery disease (CAD) phenotype and a higher risk for events. The objective of this study is to clarify the association between Lp(a) and coronary plaque characteristics in asymptomatic patients. METHODS: 373 consecutive asymptomatic patients were evaluated for primary prevention of CAD. Artificial intelligence quantitative coronary CTA (AI-QCT) was used to investigate the relationship between Lp(a) and coronary plaque characteristics. Multivariable linear regression adjusted for CAD risk factors (age, sex, race, diabetes, smoking), statin use, and body mass index were used to analyze associations between the Lp(a) (by quintile), high sensitivity C-reactive protein (hsCRP), coronary artery calcium (CAC) score, and AI-QCT findings. AI-QCT findings were defined as low-density non-calcified plaque volume (LD-NCPV). RESULTS: The mean age was 56.2±8.9 years, 71.6% were male, and 54.2% were taking statin therapy. Median LDL-C was 103(72,136)mg/dL, median Lp(a) was 31(11, 89)nmol/L, median Lp(a) corrected LDL-C was 101(64, 131)mg/dL. Median hsCRP levels were 0.8(0.4, 1.8)mg/L. Median CAC levels were 6.0(0.0,110.0). There was no association between Lp(a) concentrations and CAC(P=0.281). After adjustment for CAD risk factors, every quintile of Lp(a) increase was associated with a 0.4% increase in LD-NCPV(P=0.039). The inclusion of hsCRP to the models had no significant effect on LD-NCPV. CONCLUSIONS: Higher Lp(a) concentrations in asymptomatic patients are significantly associated with increased low-density non-calcified plaque volume.
{"title":"Lipoprotein(a) is Associated with Increased Low-Density Plaque Volume","authors":"Rebecca Fisher, Nick S. Nurmohamed, Edward A. Fisher, Melissa Aquino, James P. Earls, James K Min, Chen Gurevitz, Waqas Malick, Robert Peters, Sascha N Goonewardena, Robert S. Rosenson","doi":"10.1101/2024.07.18.24310539","DOIUrl":"https://doi.org/10.1101/2024.07.18.24310539","url":null,"abstract":"BACKGROUND: Lipoprotein(a) [Lp(a)] is an inherited risk factor for cardiovascular disease that is accompanied by a more severe coronary artery disease (CAD) phenotype and a higher risk for events. The objective of this study is to clarify the association between Lp(a) and coronary plaque characteristics in asymptomatic patients. METHODS: 373 consecutive asymptomatic patients were evaluated for primary prevention of CAD. Artificial intelligence quantitative coronary CTA (AI-QCT) was used to investigate the relationship between Lp(a) and coronary plaque characteristics. Multivariable linear regression adjusted for CAD risk factors (age, sex, race, diabetes, smoking), statin use, and body mass index were used to analyze associations between the Lp(a) (by quintile), high sensitivity C-reactive protein (hsCRP), coronary artery calcium (CAC) score, and AI-QCT findings. AI-QCT findings were defined as low-density non-calcified plaque volume (LD-NCPV). RESULTS: The mean age was 56.2±8.9 years, 71.6% were male, and 54.2% were taking statin therapy. Median LDL-C was 103(72,136)mg/dL, median Lp(a) was 31(11, 89)nmol/L, median Lp(a) corrected LDL-C was 101(64, 131)mg/dL. Median hsCRP levels were 0.8(0.4, 1.8)mg/L. Median CAC levels were 6.0(0.0,110.0). There was no association between Lp(a) concentrations and CAC(P=0.281). After adjustment for CAD risk factors, every quintile of Lp(a) increase was associated with a 0.4% increase in LD-NCPV(P=0.039). The inclusion of hsCRP to the models had no significant effect on LD-NCPV. CONCLUSIONS: Higher Lp(a) concentrations in asymptomatic patients are significantly associated with increased low-density non-calcified plaque volume.","PeriodicalId":501297,"journal":{"name":"medRxiv - Cardiovascular Medicine","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141738774","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-19DOI: 10.1101/2024.07.19.24310709
Mohammadreza Naderian, Marwan E. Hamed, Ali A. Vaseem, Kristjan Norland, Ozan Dikilitas, Azin Teymourzadeh, Kent R. Bailey, Iftikhar J. Kullo
Background: The MI-GENES clinical trial (NCT01936675), in which participants at intermediate risk of coronary heart disease (CHD) were randomized to receive a Framingham risk score (FRSg, n=103), or an integrated risk score (IRSg, n=104) that additionally included a polygenic risk score (PRS), demonstrated that after 6 months, participants randomized to IRSg had higher statin initiation and lower low-density lipoprotein cholesterol (LDL-C). Objectives: In a post hoc 10-year follow-up analysis of the MI-GENES trial, we investigated whether disclosure of a PRS for CHD was associated with a reduction in adverse cardiovascular events. Methods: Participants were followed from randomization beginning in October 2013 until September 2023 to ascertain adverse cardiovascular events, testing for CHD, and changes in risk factors, by blinded review of electronic health records. The primary outcome was the time from randomization to the occurrence of the first major adverse cardiovascular event (MACE), defined as cardiovascular death, non-fatal myocardial infarction, coronary revascularization, and non-fatal stroke. Statistical analyses were conducted using Cox proportional hazards regression and linear mixed-effects models. Results: We followed all 203 participants who completed the MI-GENES trial, 100 in FRSg and 103 in IRSg (mean age at the end of follow-up: 68.2+-5.2, 48% male). During a median follow-up of 9.5 years, 9 MACEs occurred in FRSg and 2 in IRSg (hazard ratio (HR), 0.20; 95% confidence interval (CI), 0.04 to 0.94; P=0.042). In FRSg, 47 (47%) underwent at least one test for CHD, compared to 30 (29%) in IRSg (HR, 0.51; 95% CI, 0.32 to 0.81; P=0.004). IRSg participants had a longer duration of statin therapy during the first four years post-randomization and a greater reduction in LDL-C for up to 3 years post-randomization. No significant differences between the two groups were observed for hemoglobin A1C, systolic and diastolic blood pressures, weight, and smoking cessation rate during follow-up. Conclusions: The disclosure of an IRS that included a PRS to individuals at intermediate risk for CHD was associated with a lower incidence of MACE after a decade of follow-up, likely due to a higher rate of initiation and longer duration of statin therapy, leading to lower LDL-C levels.
{"title":"Effect of disclosing a polygenic risk score for coronary heart disease on adverse cardiovascular events: 10-year follow-up of the MI-GENES randomized clinical trial","authors":"Mohammadreza Naderian, Marwan E. Hamed, Ali A. Vaseem, Kristjan Norland, Ozan Dikilitas, Azin Teymourzadeh, Kent R. Bailey, Iftikhar J. Kullo","doi":"10.1101/2024.07.19.24310709","DOIUrl":"https://doi.org/10.1101/2024.07.19.24310709","url":null,"abstract":"Background: The MI-GENES clinical trial (NCT01936675), in which participants at intermediate risk of coronary heart disease (CHD) were randomized to receive a Framingham risk score (FRSg, n=103), or an integrated risk score (IRSg, n=104) that additionally included a polygenic risk score (PRS), demonstrated that after 6 months, participants randomized to IRSg had higher statin initiation and lower low-density lipoprotein cholesterol (LDL-C).\u0000Objectives: In a post hoc 10-year follow-up analysis of the MI-GENES trial, we investigated whether disclosure of a PRS for CHD was associated with a reduction in adverse cardiovascular events. Methods: Participants were followed from randomization beginning in October 2013 until September 2023 to ascertain adverse cardiovascular events, testing for CHD, and changes in risk factors, by blinded review of electronic health records. The primary outcome was the time from randomization to the occurrence of the first major adverse cardiovascular event (MACE), defined as cardiovascular death, non-fatal myocardial infarction, coronary revascularization, and non-fatal stroke. Statistical analyses were conducted using Cox proportional hazards regression and linear mixed-effects models.\u0000Results: We followed all 203 participants who completed the MI-GENES trial, 100 in FRSg and 103 in IRSg (mean age at the end of follow-up: 68.2+-5.2, 48% male). During a median follow-up of 9.5 years, 9 MACEs occurred in FRSg and 2 in IRSg (hazard ratio (HR), 0.20; 95% confidence interval (CI), 0.04 to 0.94; P=0.042). In FRSg, 47 (47%) underwent at least one test for CHD, compared to 30 (29%) in IRSg (HR, 0.51; 95% CI, 0.32 to 0.81; P=0.004). IRSg participants had a longer duration of statin therapy during the first four years post-randomization and a greater reduction in LDL-C for up to 3 years post-randomization. No significant differences between the two groups were observed for hemoglobin A1C, systolic and diastolic blood pressures, weight, and smoking cessation rate during follow-up.\u0000Conclusions: The disclosure of an IRS that included a PRS to individuals at intermediate risk for CHD was associated with a lower incidence of MACE after a decade of follow-up, likely due to a higher rate of initiation and longer duration of statin therapy, leading to lower LDL-C levels.","PeriodicalId":501297,"journal":{"name":"medRxiv - Cardiovascular Medicine","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141738772","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-12DOI: 10.1101/2024.07.10.24310247
Xiarepati Tieliwaerdi, Abulikemu Abuduweili, Saleh Saleh, Erasmus Mutabi, Michael A Rosenberg, Emerson Liu
Background/Aim: Despite extensive research in other medical fields, the capabilities of ChatGPT-4 in clinical decision support within cardiac electrophysiology (EP) remain largely unexplored. This study aims to enhance ChatGPT- 4`s domain-specific expertise by employing the Retrieval-Augmented Generation (RAG) approach, which integrates up-to-date, evidence-based knowledge into ChatGPT-4`s foundational database. Additionally, we plan to explore the use of commonly used automatic evaluation metrics in natural language processing, such as BERTScore, BLEURT, and cosine similarity, alongside human evaluation, to develop a semi-automatic framework. This aims to reduce dependency on exhaustive human evaluations, addressing the need for efficient and scalable assessment tools in medical decision-making, given the rapid adoption of ChatGPT-4 by the public. Method: We analyzed five atrial fibrillation (Afib) cases and seven cardiac implantable electronic device (CIED) infection cases curated from PubMed case reports. We conducted a total of 120 experiments for Afib and 168 for CIED cases, testing each case across four temperature settings (0, 0.5, 1, 1.2) and three seed settings (1, 2, 3). ChatGPT-4`s performance was assessed under two modes: the Retrieval-Augmented Generation (RAG) mode and the Cold Turkey mode, which queries ChatGPT without external knowledge via RAG. For Afib cases, ChatGPT was asked to determine rate, rhythm, and anticoagulation options, and provide reasoning for each. For CIED cases, ChatGPT is asked to determine the presence of device infections. Accuracy metrics evaluated the determination component, while reasoning was assessed by human evaluation, BERTScore, BLEURT, and cosine similarity. A mixed effects analysis was used to compare the performance under both models across varying seeds and temperatures. Spearman`s rank correlation was used to explore the relationship between automatic metrics and human evaluation. Results: In this study, 120 experiments for Afib and 168 for CIED were conducted. There is no significant difference between the RAG mode and the Cold Turkey mode across various metrics including determination accuracy, reasoning similarity, and human evaluation scores, although RAG achieved higher cosine similarity scores in Afib cases (0.82 vs. 0.75) and better accuracy in CIED cases (0.70 vs. 0.66), though these differences were not statistically significant due to the small sample size. Our mixed effects analysis revealed no significant effects of temperature or method interactions, indicating stable performance across these variables. Moreover, while no individual evaluation metric, such as BERTScore, BLEURT or cosine similarity, showed a high correlation with human evaluations. However, the ACC-Sim metric, which averages accuracy and cosine similarity, exhibits the highest correlation with human evaluation, with Spearman`s ρ at 0.86 and a P value < 0.001, indicating a significant ordinal correlation between AC
{"title":"Exploring the Potential of ChatGPT-4 for Clinical Decision Support in Cardiac Electrophysiology and Its Semi-Automatic Evaluation Metrics","authors":"Xiarepati Tieliwaerdi, Abulikemu Abuduweili, Saleh Saleh, Erasmus Mutabi, Michael A Rosenberg, Emerson Liu","doi":"10.1101/2024.07.10.24310247","DOIUrl":"https://doi.org/10.1101/2024.07.10.24310247","url":null,"abstract":"Background/Aim: Despite extensive research in other medical fields, the capabilities of ChatGPT-4 in clinical decision support within cardiac electrophysiology (EP) remain largely unexplored. This study aims to enhance ChatGPT- 4`s domain-specific expertise by employing the Retrieval-Augmented Generation (RAG) approach, which integrates up-to-date, evidence-based knowledge into ChatGPT-4`s foundational database. Additionally, we plan to explore the use of commonly used automatic evaluation metrics in natural language processing, such as BERTScore, BLEURT, and cosine similarity, alongside human evaluation, to develop a semi-automatic framework. This aims to reduce dependency on exhaustive human evaluations, addressing the need for efficient and scalable assessment tools in medical decision-making, given the rapid adoption of ChatGPT-4 by the public. Method: We analyzed five atrial fibrillation (Afib) cases and seven cardiac implantable electronic device (CIED) infection cases curated from PubMed case reports. We conducted a total of 120 experiments for Afib and 168 for CIED cases, testing each case across four temperature settings (0, 0.5, 1, 1.2) and three seed settings (1, 2, 3). ChatGPT-4`s performance was assessed under two modes: the Retrieval-Augmented Generation (RAG) mode and the Cold Turkey mode, which queries ChatGPT without external knowledge via RAG. For Afib cases, ChatGPT was asked to determine rate, rhythm, and anticoagulation options, and provide reasoning for each. For CIED cases, ChatGPT is asked to determine the presence of device infections. Accuracy metrics evaluated the determination component, while reasoning was assessed by human evaluation, BERTScore, BLEURT, and cosine similarity. A mixed effects analysis was used to compare the performance under both models across varying seeds and temperatures. Spearman`s rank correlation was used to explore the relationship between automatic metrics and human evaluation. Results: In this study, 120 experiments for Afib and 168 for CIED were conducted. There is no significant difference between the RAG mode and the Cold Turkey mode across various metrics including determination accuracy, reasoning similarity, and human evaluation scores, although RAG achieved higher cosine similarity scores in Afib cases (0.82 vs. 0.75) and better accuracy in CIED cases (0.70 vs. 0.66), though these differences were not statistically significant due to the small sample size. Our mixed effects analysis revealed no significant effects of temperature or method interactions, indicating stable performance across these variables. Moreover, while no individual evaluation metric, such as BERTScore, BLEURT or cosine similarity, showed a high correlation with human evaluations. However, the ACC-Sim metric, which averages accuracy and cosine similarity, exhibits the highest correlation with human evaluation, with Spearman`s ρ at 0.86 and a P value < 0.001, indicating a significant ordinal correlation between AC","PeriodicalId":501297,"journal":{"name":"medRxiv - Cardiovascular Medicine","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141612310","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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