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2. Personalized diagnosis in suspected myocardial infarction.

Author

Neumann, Johannes, Twerenbold, Raphael, Ojeda, Francisco, Aldous, Sally, Allen, Brandon, Apple, Fred, Babel, Hugo, Christenson, Robert, Cullen, Louise, Di Carluccio, Eleonora, Doudesis, Dimitrios, Ekelund, Ulf, Giannitsis, Evangelos, Greenslade, Jaimi, Inoue, Kenji, Jernberg, Tomas, Kavsak, Peter, Keller, Till, Lee, Kuan, Lindahl, Bertil, Lorenz, Thiess, Mahler, Simon, Mills, Nicholas, Mokhtari, Arash, Parsonage, William, Pickering, John, Pemberton, Christopher, Reich, Christoph, Richards, A, Sandoval, Yader, Than, Martin, Toprak, Betül, Troughton, Richard, Worster, Andrew, Zeller, Tanja, Ziegler, Andreas, and Blankenberg, Stefan

Subjects
Acute myocardial infarction, Biomarker, Machine learning, Probability, Super learner, Troponin, Validation, Humans, Angina Pectoris, Biomarkers, Myocardial Infarction, ROC Curve, Troponin I, Troponin T, Clinical Studies as Topic
Abstract

BACKGROUND: In suspected myocardial infarction (MI), guidelines recommend using high-sensitivity cardiac troponin (hs-cTn)-based approaches. These require fixed assay-specific thresholds and timepoints, without directly integrating clinical information. Using machine-learning techniques including hs-cTn and clinical routine variables, we aimed to build a digital tool to directly estimate the individual probability of MI, allowing for numerous hs-cTn assays. METHODS: In 2,575 patients presenting to the emergency department with suspected MI, two ensembles of machine-learning models using single or serial concentrations of six different hs-cTn assays were derived to estimate the individual MI probability (ARTEMIS model). Discriminative performance of the models was assessed using area under the receiver operating characteristic curve (AUC) and logLoss. Model performance was validated in an external cohort with 1688 patients and tested for global generalizability in 13 international cohorts with 23,411 patients. RESULTS: Eleven routinely available variables including age, sex, cardiovascular risk factors, electrocardiography, and hs-cTn were included in the ARTEMIS models. In the validation and generalization cohorts, excellent discriminative performance was confirmed, superior to hs-cTn only. For the serial hs-cTn measurement model, AUC ranged from 0.92 to 0.98. Good calibration was observed. Using a single hs-cTn measurement, the ARTEMIS model allowed direct rule-out of MI with very high and similar safety but up to tripled efficiency compared to the guideline-recommended strategy. CONCLUSION: We developed and validated diagnostic models to accurately estimate the individual probability of MI, which allow for variable hs-cTn use and flexible timing of resampling. Their digital application may provide rapid, safe and efficient personalized patient care. TRIAL REGISTRATION NUMBERS: Data of following cohorts were used for this project: BACC ( www. CLINICALTRIALS: gov ; NCT02355457), stenoCardia ( www. CLINICALTRIALS: gov ; NCT03227159), ADAPT-BSN ( www.australianclinicaltrials.gov.au ; ACTRN12611001069943), IMPACT ( www.australianclinicaltrials.gov.au , ACTRN12611000206921), ADAPT-RCT ( www.anzctr.org.au ; ANZCTR12610000766011), EDACS-RCT ( www.anzctr.org.au ; ANZCTR12613000745741); DROP-ACS ( https://www.umin.ac.jp , UMIN000030668); High-STEACS ( www. CLINICALTRIALS: gov ; NCT01852123), LUND ( www. CLINICALTRIALS: gov ; NCT05484544), RAPID-CPU ( www. CLINICALTRIALS: gov ; NCT03111862), ROMI ( www. CLINICALTRIALS: gov ; NCT01994577), SAMIE ( https://anzctr.org.au ; ACTRN12621000053820), SEIGE and SAFETY ( www. CLINICALTRIALS: gov ; NCT04772157), STOP-CP ( www. CLINICALTRIALS: gov ; NCT02984436), UTROPIA ( www. CLINICALTRIALS: gov ; NCT02060760).

Published
2023

6. Prognostic performance of soluble urokinase plasminogen activator receptor for heart failure or mortality in Western and Asian patients with acute breathlessness

Author

Chew-Harris, Janice, Frampton, Chris, Greer, Charlotte, Appleby, Sarah, Pickering, John W., Kuan, Win Sen, Ibrahim, Irwani, Chan, Siew Pang, Li, Zisheng, Liew, Oi Wah, Adamson, Philip D., Troughton, Richard, Tan, Li Ling, Lin, Weiqin, Ooi, Shirley Beng Suat, Richards, A. Mark, and Pemberton, Christopher J.

Published
2024
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8. Intracardiac slug

Author

Chan, Wan Yiu Wandy, Troughton, Richard W, and Singh, Harsh

Published
2009

9. Machine Learning for Myocardial Infarction Compared With Guideline-Recommended Diagnostic Pathways

Author

Boeddinghaus, Jasper, Doudesis, Dimitrios, Lopez-Ayala, Pedro, Lee, Kuan Ken, Koechlin, Luca, Wildi, Karin, Nestelberger, Thomas, Borer, Raphael, Miró, Òscar, Martin-Sanchez, F. Javier, Strebel, Ivo, Rubini Giménez, Maria, Keller, Dagmar I., Christ, Michael, Bularga, Anda, Li, Ziwen, Ferry, Amy V., Tuck, Chris, Anand, Atul, Gray, Alasdair, Mills, Nicholas L., Mueller, Christian, Richards, A. Mark, Pemberton, Chris, Troughton, Richard W., Aldous, Sally J., Brown, Anthony F.T., Dalton, Emily, Hammett, Chris, Hawkins, Tracey, O’Kane, Shanen, Parke, Kate, Ryan, Kimberley, Schluter, Jessica, Barker, Stephanie, Blades, Jennifer, Chapman, Andrew R., Fujisawa, Takeshi, Kimenai, Dorien M., McDermott, Michael, Newby, David E., Schulberg, Stacey D., Shah, Anoop S.V., Sorbie, Andrew, Soutar, Grace, Strachan, Fiona E., Taggart, Caelan, Vicencio, Daniel Perez, Wang, Yiqing, Wereski, Ryan, Williams, Kelly, Weir, Christopher J., Berry, Colin, Reid, Alan, Maguire, Donogh, Collinson, Paul O., Sandoval, Yader, Smith, Stephen W., Wussler, Desiree, Muench-Gerber, Tamar, Glaeser, Jonas, Spagnuolo, Carlos, Huré, Gabrielle, Gehrke, Juliane, Puelacher, Christian, Gualandro, Danielle M., Shrestha, Samyut, Kawecki, Damian, Morawiec, Beata, Muzyk, Piotr, Buergler, Franz, Buser, Andreas, Rentsch, Katharina, Twerenbold, Raphael, López, Beatriz, Martinez-Nadal, Gemma, Adrada, Esther Rodriguez, Parenica, Jiri, and von Eckardstein, Arnold

Published
2024
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11. Baseline characteristics of patients in the randomized study to investigate the efficacy and safety of ferric carboxymaltose as treatment for heart failure with iron deficiency: HEART-FID trial

Author

Harrington, Josephine, Mentz, Robert J., Rockhold, Frank W., Garg, Jyotsna, Butler, Javed, De Pasquale, Carmine G., Ezekowitz, Justin A., Lewis, Gregory D., O'Meara, Eileen, Ponikowski, Piotr, Troughton, Richard W., Wong, Yee Weng, Adamczyk, Robert, Blackman, Nicole, and Hernandez, Adrian F.

Published
2023
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14. Baseline characteristics of patients with heart failure with mildly reduced or preserved ejection fraction: The FINEARTS‐HF trial

Author

Solomon, Scott D., primary, Ostrominski, John W., additional, Vaduganathan, Muthiah, additional, Claggett, Brian, additional, Jhund, Pardeep S., additional, Desai, Akshay S., additional, Lam, Carolyn S.P., additional, Pitt, Bertram, additional, Senni, Michele, additional, Shah, Sanjiv J., additional, Voors, Adriaan A., additional, Zannad, Faiez, additional, Abidin, Imran Zainal, additional, Alcocer‐Gamba, Marco Antonio, additional, Atherton, John J., additional, Bauersachs, Johann, additional, Ma, Chang‐Sheng, additional, Chiang, Chern‐En, additional, Chioncel, Ovidiu, additional, Chopra, Vijay, additional, Comin‐Colet, Josep, additional, Filippatos, Gerasimos, additional, Fonseca, Cândida, additional, Gajos, Grzegorz, additional, Goland, Sorel, additional, Goncalvesová, Eva, additional, Kang, Seok‐Min, additional, Katova, Tzvetana, additional, Kosiborod, Mikhail N., additional, Latkovskis, Gustavs, additional, Lee, Alex Pui‐Wai, additional, Linssen, Gerard C.M., additional, Llamas‐Esperón, Guillermo, additional, Mareev, Vyacheslav, additional, Martinez, Felipe A., additional, Melenovský, Vojtěch, additional, Merkely, Béla, additional, Nodari, Savina, additional, Petrie, Mark C., additional, Saldarriaga, Clara Inés, additional, Saraiva, Jose Francisco Kerr, additional, Sato, Naoki, additional, Schou, Morten, additional, Sharma, Kavita, additional, Troughton, Richard, additional, Udell, Jacob A., additional, Ukkonen, Heikki, additional, Vardeny, Orly, additional, Verma, Subodh, additional, von Lewinski, Dirk, additional, Voronkov, Leonid G., additional, Yilmaz, Mehmet Birhan, additional, Zieroth, Shelley, additional, Lay‐Flurrie, James, additional, van Gameren, Ilse, additional, Amarante, Flaviana, additional, Viswanathan, Prabhakar, additional, and McMurray, John J.V., additional

Published
2024
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18. Reduction of dietary sodium to less than 100 mmol in heart failure (SODIUM-HF): an international, open-label, randomised, controlled trial

Author

Ezekowitz, Justin, Colin-Ramirez, Eloisa, Ross, Heather, Escobedo, Jorge, Macdonald, Peter, Troughton, Richard, Saldarriaga, Clara, Alemayehu, Wendimagegn, McAlister, Finlay, Arcand, JoAnne, Atherton, John, Doughty, Robert, Gupta, Milan, Howlett, Jonathan, Jaffer, Shahin, Lavoie, Andrea, Lund, Mayanna, Marwick, Thomas, McKelvie, Robert, Moe, Gordon, Pandey, A. Shekhar, Porepa, Liane, Rajda, Miroslaw, Rheault, Haunnah, Singh, Jitendra, Toma, Mustafa, Virani, Sean, Zieroth, Shelley, Ezekowitz, Justin A, McAlister, Finlay A, and Pandey, A Shekhar

Published
2022
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20. Plasma soluble fms‐like tyrosine kinase‐1, placental growth factor, and vascular endothelial growth factor system gene variants as predictors of survival in heart failure.

Author

Paterson, Melinda A., Pilbrow, Anna P., Frampton, Chris M., Cameron, Vicky A., Troughton, Richard W., Pemberton, Chris J., Lund, Mayanna, Devlin, Gerard P., Richards, A. Mark, Doughty, Robert N., and Palmer, Barry R.

Subjects
VASCULAR endothelial growth factors, SINGLE nucleotide polymorphisms, PROPORTIONAL hazards models, PROGNOSIS, GENETIC variation, PLACENTAL growth factor, BRAIN natriuretic factor
Abstract

Aims: Soluble fms‐like tyrosine kinase‐1 (sFlt‐1) and placental growth factor (PlGF), components of the vascular endothelial growth factor (VEGF) system, play key roles in angiogenesis. Reports of elevated plasma levels of sFlt‐1 and PlGF in coronary heart disease and heart failure (HF) led us to investigate their utility, and VEGF system gene single nucleotide polymorphisms (SNPs), as prognostic biomarkers in HF. Methods and results: ELISA assays for sFlt‐1, PlGF and N‐terminal pro‐B‐type natriuretic peptide (NT‐proBNP) were performed on baseline plasma samples from the PEOPLE cohort (n = 890), a study of outcomes among patients after an episode of acute decompensated HF. Eight SNPs potentially associated with sFlt‐1 or PlGF levels were genotyped. sFlt‐1 and PlGF were assayed in 201 subjects from the Canterbury Healthy Volunteers Study (CHVS) matched to PEOPLE participants. All‐cause death was the major endpoint for clinical outcome considered. In PEOPLE participants, mean plasma levels for both sFlt‐1 (125 ± 2.01 pg/ml) and PlGF (17.5 ± 0.21 pg/ml) were higher (both p < 0.044) than in the CHVS cohort (81.2 ± 1.31 pg/ml and 15.5 ± 0.32 pg/ml, respectively). sFlt‐1 was higher in HF with reduced ejection fraction compared to HF with preserved ejection fraction (p = 0.005). The PGF gene SNP rs2268616 was univariately associated with death (p = 0.016), and was also associated with PlGF levels, as was rs2268614 genotype. Cox proportional hazards modelling (n = 695, 246 deaths) showed plasma sFlt‐1, but not PlGF, predicted survival (hazard ratio 6.44, 95% confidence interval 2.57–16.1; p < 0.001) in PEOPLE, independent of age, NT‐proBNP, ischaemic aetiology, diabetic status and beta‐blocker therapy. Conclusions: Plasma sFlt‐1 concentrations have potential as an independent predictor of survival and may be complementary to established prognostic biomarkers in HF. [ABSTRACT FROM AUTHOR]

Published
2024
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21. Implantable Hemodynamic Monitors Improve Survival in Patients With Heart Failure and Reduced Ejection Fraction

Author

Lindenfeld, JoAnn, primary, Costanzo, Maria Rosa, additional, Zile, Michael R., additional, Ducharme, Anique, additional, Troughton, Richard, additional, Maisel, Alan, additional, Mehra, Mandeep R., additional, Paul, Sara, additional, Sears, Samuel F., additional, Smart, Frank, additional, Johnson, Nessa, additional, Henderson, John, additional, Adamson, Philip B., additional, Desai, Akshay S., additional, and Abraham, William T., additional

Published
2024
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22. NT-proBNP for Risk Prediction in Heart Failure: Identification of Optimal Cutoffs Across Body Mass Index Categories

Author

Vergaro, Giuseppe, Gentile, Francesco, Meems, Laura M.G., Aimo, Alberto, Januzzi, James L., Jr., Richards, A. Mark, Lam, Carolyn S.P., Latini, Roberto, Staszewsky, Lidia, Anand, Inder S., Cohn, Jay N., Ueland, Thor, Gullestad, Lars, Aukrust, Pål, Brunner-La Rocca, Hans-Peter, Bayes-Genis, Antoni, Lupón, Josep, Yoshihisa, Akiomi, Takeishi, Yasuchika, Egstrup, Michael, Gustafsson, Ida, Gaggin, Hanna K., Eggers, Kai M., Huber, Kurt, Gamble, Greg D., Ling, Lieng H., Leong, Kui Tong Gerard, Yeo, Poh Shuah Daniel, Ong, Hean Yee, Jaufeerally, Fazlur, Ng, Tze P., Troughton, Richard, Doughty, Robert N., Devlin, Gerry, Lund, Mayanna, Giannoni, Alberto, Passino, Claudio, de Boer, Rudolf A., and Emdin, Michele

Published
2021
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23. Cardiac CRFR1 Expression Is Elevated in Human Heart Failure and Modulated by Genetic Variation and Alternative Splicing

Author

Pilbrow, Anna P, Lewis, Kathy A, Perrin, Marilyn H, Sweet, Wendy E, Moravec, Christine S, Tang, WH Wilson, Huising, Mark O, Troughton, Richard W, and Cameron, Vicky A

Subjects
Pharmacology and Pharmaceutical Sciences, Biomedical and Clinical Sciences, Cardiovascular, Genetics, Heart Disease, Biotechnology, 2.1 Biological and endogenous factors, Aetiology, Adult, Aged, Alternative Splicing, Corticotropin-Releasing Hormone, Female, Genetic Variation, Heart Failure, Humans, Male, Middle Aged, Myocardium, Receptors, Corticotropin-Releasing Hormone, Signal Transduction, Urocortins, Biological Sciences, Agricultural and Veterinary Sciences, Medical and Health Sciences, Endocrinology & Metabolism, Clinical sciences
Abstract

Corticotropin-releasing factor (CRF) and the CRF-related peptides, urocortin (Ucn)-1, Ucn2, and Ucn3 signal through receptors CRFR1 and CRFR2 to restore homeostasis in response to stress. The Ucns exert potent cardioprotective effects and may have clinical utility in heart failure. To explore the activity of this system in the heart, we measured the levels of myocardial gene expression of the CRF/Ucn family of ligands/receptors and investigated genetic variation and alternative splicing of CRFR1 in 110 heart failure patients and 108 heart donors. Using quantitative real-time PCR, we detected CRFR1, CRFR2, CRF, Ucn1, Ucn2, and Ucn3 in all samples. CRFR2α was the most abundant receptor and Ucn3 the most abundant ligand, both in patients and donors. Compared with donors, cardiac expression of CRFR1, CRF, and Ucn3 was higher (P < .001) and CRFR2α lower (P = .012) in patients. In patients and donors, genetic variation within CRFR1, represented by the chromosome 17q21.31 inversion polymorphism, was associated with markedly higher CRFR1 expression (P < .001), making CRFR1 and CRFR2α expression almost equivalent in some patients. A novel, truncated splice variant of CRFR1, designated CRFR1j, was identified and shown to exert a dominant-negative effect on CRFR1 signaling in vitro. The novel variant was expressed in a greater proportion of patients (60%) than donors (3%, P < .001). In summary, cardiac expression of CRFR1, CRF, and Ucn3 genes is elevated in heart failure and may contribute to the activation of the CRF/Ucn system in these patients. A common variant within the CRFR1 gene and a novel CRFR1 splice variant may modulate CRFR1 expression and signaling.

Published
2016

26. Convalescent Growth Differentiation Factor-15 and Long-Term Outcomes after an Acute Coronary Syndrome.

Author

Greer, Charlotte E., Chew-Harris, Janice, Adamson, Philip D., Pemberton, Chris J., Pickering, John W., Pilbrow, Anna P., Frampton, Chris M., Troughton, Richard W., Doughty, Robert N., and Richardsa, A. Mark

Subjects
ACUTE coronary syndrome, MYOCARDIAL infarction, CORONARY disease, MYOCARDIAL injury, HEART failure
Abstract

Background: Growth differentiation factor-15 (GDF-15) has been shown to be associated with adverse clinical outcomes in patients after an acute coronary syndrome when measured soon after an event. Although dynamic in the acute phase after myocardial injury, GDF-15 has been shown to remain stable during convalescence. In this study, we aimed to assess the value of GDF-15 as a long-term prognostic marker for clinical outcomes when measured in the convalescent phase following an acute coronary syndrome. Methods: GDF-15 concentrations were measured in 1945 patients who were recruited between 2002 and 2009 to the Coronary Disease Cohort Study. For this analysis, follow-up was curtailed at 10 years and association of GDF-15 with all-cause death, cardiovascular death, recurrent myocardial infarction, and heart failure hospitalizations were assessed with multivariate Cox proportional hazard regression analysis. Results: After 10 years of follow-up, there were 648 deaths (348 from cardiovascular causes), 500 admissions for myocardial infarction, and 436 for heart failure. Four-month convalescent GDF-15 demonstrated a robust independent association with all endpoints, which remained after adjustment for Global Registry of Acute Coronary Events score and other convalescent biomarkers. When compared to the lowest quartile of GDF-15 concentrations, those in the highest quartile had a 3-fold increased risk of all-cause death. Conclusions: Convalescent plasma GDF-15 is a strong and independent predictor of 10-year all-cause death, cardiovascular death, recurrent myocardial infarction, and heart failure admission following an acute coronary syndrome. [ABSTRACT FROM AUTHOR]

Published
2024
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28. Derivation and Validation of Thresholds Using Synthetic Data Methods for Single-Test Screening of Emergency Department Patients with Possible Acute Myocardial Infarction Using a Point-of-Care Troponin Assay.

Author

Pickering, John W, Young, Joanna M, George, Peter M, Watson, Antony S, Aldous, Sally J, Verryt, Toby, Troughton, Richard W, Pemberton, Christopher J, Richards, A Mark, Cullen, Louise A, Apple, Fred S, and Than, Martin P

Subjects
MYOCARDIAL infarction, MEDICAL screening, HOSPITAL emergency services, PLASMA products, TROPONIN
Abstract

Background: Single-sample (screening) rule-out of acute myocardial infarction (AMI) with troponin requires derivation of a single-test screening threshold. In data sets with small event numbers, the lowest one or two concentrations of myocardial infarction (MI) patients dictate the threshold. This is not optimal. We aimed to demonstrate a process incorporating both real and synthetic data for deriving such thresholds using a novel pre-production high-precision point-of-care assay. Methods: cTnI concentrations were measured from thawed plasma using the Troponin I Next (TnI-Nx) assay (i-STAT; Abbott) in adults on arrival to the emergency department with symptoms suggestive of AMI. The primary outcome was an AMI or cardiac death within 30 days. We used internal–external validation with synthetic data production based on clinical and demographic data, plus the measured TnI-Nx concentration, to derive and validate decision thresholds for TnI-Nx. The target low-risk threshold was a sensitivity of 99% and a high-risk threshold specificity of >95%. Results: In total, 1356 patients were included, of whom 191 (14.1%) had the primary outcome. A total of 500 synthetic data sets were constructed. The mean low-risk threshold was determined to be 5 ng/L. This categorized 38% (95% CI, 6%–68%) to low-risk with a sensitivity of 99.0% (95% CI, 98.6%–99.5%) and a negative predictive value of 99.4% (95% CI, 97.6%–99.8%). A similarly derived high-risk threshold of 25 ng/L had a specificity of 95.0% (95% CI, 94.8%–95.1%) and a positive predictive value of 74.8% (95% CI, 71.5%–78.0%). Conclusions: With the TnI-Nx assay, we successfully demonstrated an approach using synthetic data generation to derive low-risk thresholds for safe and effective screening. [ABSTRACT FROM AUTHOR]

Published
2024
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32. Circulating erythroferrone has diagnostic utility for acute decompensated heart failure in patients presenting with acute or worsening dyspnea

Author

Appleby, Sarah, primary, Frampton, Chris, additional, Holdaway, Mark, additional, Chew-Harris, Janice, additional, Liew, Oi Wah, additional, Chong, Jenny Pek Ching, additional, Lewis, Lynley, additional, Troughton, Richard, additional, Ooi, Shirley Beng Suat, additional, Kuan, Win Sen, additional, Ibrahim, Irwani, additional, Chan, Siew Pang, additional, Richards, A. Mark, additional, and Pemberton, Christopher J., additional

Published
2024
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36. Combining Circulating MicroRNA and NT-proBNP to Detect and Categorize Heart Failure Subtypes

Author

Wong, Lee Lee, Zou, Ruiyang, Zhou, Lihan, Lim, Jia Yuen, Phua, Dominic C.Y., Liu, Chengcheng, Chong, Jenny P.C., Ng, Jessica Y.X., Liew, Oi Wah, Chan, Siew Pang, Chen, Yei-Tsung, Chan, Michelle M.Y., Yeo, Poh Shuan D., Ng, Tze Pin, Ling, Lieng H., Sim, David, Leong, Kui Toh G., Ong, Hean Y., Jaufeerally, Fazlur, Wong, Raymond, Chai, Ping, Low, Adrian F., Lund, Mayanna, Devlin, Gerry, Troughton, Richard, Cameron, Vicky A., Doughty, Robert N., Lam, Carolyn S.P., Too, Heng Phon, and Richards, Arthur Mark

Published
2019
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37. Ferric Carboxymaltose in Heart Failure with Iron Deficiency

Author

Mentz, Robert J., primary, Garg, Jyotsna, additional, Rockhold, Frank W., additional, Butler, Javed, additional, De Pasquale, Carmine G., additional, Ezekowitz, Justin A., additional, Lewis, Gregory D., additional, O’Meara, Eileen, additional, Ponikowski, Piotr, additional, Troughton, Richard W., additional, Wong, Yee Weng, additional, She, Lilin, additional, Harrington, Josephine, additional, Adamczyk, Robert, additional, Blackman, Nicole, additional, and Hernandez, Adrian F., additional

Published
2023
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38. Plasma Ceramides as Prognostic Biomarkers and Their Arterial and Myocardial Tissue Correlates in Acute Myocardial Infarction

Author

de Carvalho, Leonardo P., Tan, Sock Hwee, Ow, Ghim-Siong, Tang, Zhiqun, Ching, Jianhong, Kovalik, Jean-Paul, Poh, Sock Cheng, Chin, Chee-Tang, Richards, A. Mark, Martinez, Eliana C., Troughton, Richard W., Fong, Alan Yean-Yip, Yan, Bryan P., Seneviratna, Aruni, Sorokin, Vitaly, Summers, Scott A., Kuznetsov, Vladimir A., and Chan, Mark Y.

Published
2018
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39. Prioritizing Candidates of Post-Myocardial Infarction Heart Failure Using Plasma Proteomics and Single-Cell Transcriptomics

Author

Chan, Mark Y., Efthymios, Motakis, Tan, Sock Hwee, Pickering, John W., Troughton, Richard, Pemberton, Christopher, Ho, Hee-Hwa, Prabath, Joseph-Francis, Drum, Chester L., Ling, Lieng Hsi, Soo, Wern-Miin, Chai, Siang-Chew, Fong, Alan, Oon, Yen-Yee, Loh, Joshua P., Lee, Chi-Hang, Foo, Roger SY, Ackers-Johnson, Matthew Andrew, Pilbrow, Anna, and Richards, A. Mark

Published
2020
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43. Personalized diagnosis in suspected myocardial infarction

Author

Neumann , Johannes T, Twerenbold , Raphael, Ojeda, Francisco M, Aldous, Sally J., Allen, Brandon R., Apple, Fred S, Babel, Hugo, Christenson, Robert H., Cullen , Louise, Di Carluccio, Eleonora, Doudesis, Dimitrios, Ekelund, Ulf, Giannitsis, Evangelos, Greenslade, Jaimi H, Inoue, Kenji, Jernberg, Tomas, Kavsak, Peter A, Keller, Till, Lee, Kuan Ken, Lindahl, Bertil, Lorenz, Thiess, Mahler, Simon, Mills, Nicholas L, Mokhtari, Arash, Parsonage, William, Pickering, John W, Pemberton, Christopher J, Reichetzeder, Christoph, Richards, A Mark, Sandoval, Yader, Than , Martin P, Toprak, Betül, Troughton, Richard W, Worster, Andrew, Zeller, Tanja, Ziegler, Andreas, and Blankenberg, Stefan

Subjects
machine learning, troponin, probability, Validation, biomarker, Acute myocardial infarction, super learner
Abstract

Background. In suspected myocardial infarction (MI), guidelines recommend using high-sensitivity cardiac troponin (hs-cTn)-based approaches. These require fixed assay-specific thresholds and timepoints, without directly integrating clinical information. Using machine-learning techniques including hs-cTn and clinical routine variables, we aimed to build a digital tool to directly estimate the individual probability of MI, allowing for numerous hs-cTn assays.Methods. In 2,575 patients presenting to the emergency department with suspected MI, two ensembles of machine-learning models using single or serial concentrations of six different hs cTn assays were derived to estimate the individual MI probability (ARTEMIS model). Discriminative performance of the models was assessed using area under the receiver operating characteristic curve (AUC) and logLoss. Model performance was validated in an external cohort with 1,688 patients and tested for global generalizability in 13 international cohorts with 23,411 patients.Results. Eleven routinely available variables including age, sex, cardiovascular risk factors, electrocardiography, and hs-cTn were included in the ARTEMIS models. In the validation and generalization cohorts, excellent discriminative performance was confirmed, superior to hs-cTn only. For the serial hs-cTn measurement model, AUC ranged from 0.92-0.98. Good calibration was observed. Using a single hs-cTn measurement, the ARTEMIS model allowed direct rule-out of MI with very high and similar safety but up to tripled efficiency compared to the guideline-recommended strategy.Conclusion. We developed and validated diagnostic models to accurately estimate the individual probability of MI, which allow for variable hs-cTn use and flexible timing of resampling. Their digital application may provide rapid, safe and efficient personalized patient care.

Published
2023

45. An integrated signature of extracellular matrix proteins and a diastolic function imaging parameter predicts post-MI long-term outcomes

Author

Koh, Hiromi W.L., primary, Pilbrow, Anna P., additional, Tan, Sock Hwee, additional, Zhao, Qing, additional, Benke, Peter I., additional, Burla, Bo, additional, Torta, Federico, additional, Pickering, John W., additional, Troughton, Richard, additional, Pemberton, Christopher, additional, Soo, Wern-Miin, additional, Ling, Lieng Hsi, additional, Doughty, Robert N., additional, Choi, Hyungwon, additional, Wenk, Markus R., additional, Richards, A. Mark, additional, and Chan, Mark Y., additional

Published
2023
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46. NT-PROBNP DURING SCREENING IN THE STUDY OF VERICIGUAT IN PARTICIPANTS WITH HEART FAILURE WITH REDUCED EJECTION FRACTION (VICTORIA) TRIAL: INSIGHTS INTO OUTCOMES AND VERICIGUAT

Author

Westerhout, Cynthia M., primary, Zheng, Yinggan, additional, Lund, Lars, additional, Butler, Javed, additional, Troughton, Richard W., additional, Emdin, Michele, additional, Lam, Carolyn S.P., additional, Ponikowski, Piotr, additional, Blaustein, Robert, additional, O'Connor, Christopher M., additional, Roessig, Lothar, additional, Voors, Adriaan, additional, Ezekowitz, Justin A., additional, and Armstrong, Paul Wayne, additional

Published
2023
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47. LONGITUDINAL CHANGES IN N-TERMINAL PRO B-TYPE NATRIURETIC PEPTIDE: ASSOCIATIONS WITH ECHOCARDIOGRAPHIC CHANGES AND OUTCOMES IN HEART FAILURE FROM THE SHOP AND PEOPLE STUDY

Author

Teramoto, Kanako, primary, Tay, Wan Ting, additional, Tromp, Jasper, additional, Ouwerkerk, Wouter, additional, Teng, Tiew-Hwa Katherine, additional, Chandramouli, Chanchal, additional, Liew, Oi Wah, additional, Chong, Jenny, additional, Poppe, Katrina, additional, Lund, Mayanna, additional, Devlin, Gerard P., additional, Troughton, Richard W., additional, Doughty, Rob N., additional, Richards, Mark, additional, and Lam, Carolyn S.P., additional

Published
2023
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48. Prognostic modelling of clinical outcomes after first-time acute coronary syndrome in New Zealand

Author

Earle, Nikki J, primary, Poppe, Katrina K, additional, Rolleston, Anna, additional, Pilbrow, Anna, additional, Aish, Sara, additional, Bradbury, Kathryn, additional, Choi, Yeunhyang, additional, Devlin, Gerry, additional, Gladding, Patrick A, additional, Grey, Corina, additional, Harrison, Wil, additional, Henare, Kimiora, additional, Howson, Joanna, additional, Kerr, Andrew, additional, Lumley, Thomas, additional, Pera, Vijaya, additional, Porter, Graeme, additional, Stewart, Ralph, additional, Troughton, Richard W, additional, Wihongi, Helen, additional, Richards, A Mark, additional, Cameron, Vicky A, additional, Legget, Malcolm E, additional, and Doughty, Robert N, additional

Published
2023
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49. Titration of medications and outcomes in multi‐ethnic heart failure cohorts (with reduced ejection fraction) from Singapore and New Zealand

Author

Teng, Tiew‐Hwa Katherine, primary, Tay, Wan Ting, additional, Ouwerkerk, Wouter, additional, Tromp, Jasper, additional, Richards, A. Mark, additional, Gamble, Greg, additional, Greene, Stephen J., additional, Yiu, Kai‐Hang, additional, Poppe, Katrina, additional, Ling, Lieng Hsi, additional, Lund, Mayanna, additional, Sim, David, additional, Devlin, Gerard, additional, Loh, Seet Yoong, additional, Troughton, Richard, additional, Ren, Qing‐wen, additional, Jaufeerally, Fazlur, additional, Lee, Shao Guang Sheldon, additional, Tan, Ru San, additional, Soon, Dinna Kar Nee, additional, Leong, Gerald, additional, Ong, Hean Yee, additional, Yeo, Daniel P.S., additional, Lam, Carolyn S.P., additional, and Doughty, Rob N., additional

Published
2023
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50. Personalized diagnosis in suspected myocardial infarction

Author

Neumann, Johannes Tobias, Twerenbold, Raphael, Ojeda, Francisco, Aldous, Sally, Allen, Brandon, Apple, Fred M., Babel, Hugo, Christenson, Robert, Cullen, Louise, Di Carluccio, Eleonora, Doudesis, Dimitrios, Ekelund, Ulf M., Giannitsis, Evangelos, Greenslade, Jaimi, Inoue, Kenji, Jernberg, Tomas, Kavsak, Peter, Keller, Till, Lee, Kuan Ken, Lindahl, Bertil, Lorenz, Thiess, Mahler, Simon, Mills, Nicholas, Mokhtari, Arash, Parsonage, William, Pickering, John, Pemberton, Christopher, Reich, Christoph, Richards, A. Mark, Sandoval, Yader, Than, Martin A., Toprak, Betül, Troughton, Richard, Worster, Andrew, Zeller, Tanja, Ziegler, Andreas, Blankenberg, Stefan, Neumann, Johannes Tobias, Twerenbold, Raphael, Ojeda, Francisco, Aldous, Sally, Allen, Brandon, Apple, Fred M., Babel, Hugo, Christenson, Robert, Cullen, Louise, Di Carluccio, Eleonora, Doudesis, Dimitrios, Ekelund, Ulf M., Giannitsis, Evangelos, Greenslade, Jaimi, Inoue, Kenji, Jernberg, Tomas, Kavsak, Peter, Keller, Till, Lee, Kuan Ken, Lindahl, Bertil, Lorenz, Thiess, Mahler, Simon, Mills, Nicholas, Mokhtari, Arash, Parsonage, William, Pickering, John, Pemberton, Christopher, Reich, Christoph, Richards, A. Mark, Sandoval, Yader, Than, Martin A., Toprak, Betül, Troughton, Richard, Worster, Andrew, Zeller, Tanja, Ziegler, Andreas, and Blankenberg, Stefan

Abstract

Background: In suspected myocardial infarction (MI), guidelines recommend using high-sensitivity cardiac troponin (hscTn)- based approaches. These require fixed assay-specific thresholds and timepoints, without directly integrating clinical information. Using machine-learning techniques including hs-cTn and clinical routine variables, we aimed to build a digital tool to directly estimate the individual probability of MI, allowing for numerous hs-cTn assays. Methods: In 2,575 patients presenting to the emergency department with suspected MI, two ensembles of machine-learning models using single or serial concentrations of six different hs-cTn assays were derived to estimate the individual MI probability ( ARTEMIS model). Discriminative performance of the models was assessed using area under the receiver operating characteristic curve (AUC) and logLoss. Model performance was validated in an external cohort with 1688 patients and tested for global generalizability in 13 international cohorts with 23,411 patients. Results: Eleven routinely available variables including age, sex, cardiovascular risk factors, electrocardiography, and hs-cTn were included in the ARTEMIS models. In the validation and generalization cohorts, excellent discriminative performance was confirmed, superior to hs-cTn only. For the serial hs-cTn measurement model, AUC ranged from 0.92 to 0.98. Good calibration was observed. Using a single hs-cTn measurement, the ARTEMIS model allowed direct rule-out of MI with very high and similar safety but up to tripled efficiency compared to the guideline- recommended strategy. Conclusion We developed and validated diagnostic models to accurately estimate the individual probability of MI, which allow for variable hs-cTn use and flexible timing of resampling. Their digital application may provide rapid, safe and efficient personalized patient care.

Published
2023
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