Back to Authors

Richards, Mark

https://orcid.org/0000-0002-2023-8177

Mayo Clinic

University of Otago

Citations 5

Protocol for Improving Care by FAster risk-STratification through use of high sensitivity point-of-care troponin in patients presenting with possible acute coronary syndrome in the EmeRgency department (ICare-FASTER): a stepped-wedge cluster randomised qua
Pickering, John W. , Devlin, Gerard, Aldous, Sally, Jaffe, Allan S. , Apple, Fred S. , Kavsak, Peter A. , Cullen, Louise , Lord, Sarah J. , Joyce, Laura R , Frampton, Chris , Than, Martin , Lord, Sarah J , Joyce, Laura , Richards, Arthur M , Than, Martin , Cullen, Louise , Body, Richard , Jaffe, Allan S. , Mills, Nicholas L , Troughton, Richard W. , Peacock, William Frank , Lacey, Cameron James , Richards, Mark , Pitama, Suzanne G

BMJ Open | June 13, 2024 | Volume: 14 | Issue: 6 | Pages: e083752

10.1136/bmjopen-2023-083752 Get It

Introduction Clinical assessment in emergency departments (EDs) for possible acute myocardial infarction (AMI) requires at least one cardiac troponin (cTn) blood test. The turn-around time from blood draw to posting results in the clinical portal for central laboratory analysers is ~1–2 hours. New generation, high-sensitivity, point-of-care cardiac troponin I (POC-cTnI) assays use whole blood on a bedside (or near bedside) analyser that provides a rapid (8 min) result. This may expedite clinical decision-making and reduce length of stay. Our purpose is to determine if utilisation of a POC-cTnI testing reduces ED length of stay. We also aim to establish an optimised implementation process for the amended clinical pathway. Methods and analysis This quality improvement initiative has a pragmatic multihospital stepped-wedge cross-sectional cluster randomised design. Consecutive patients presenting to the ED with symptoms suggestive of possible AMI and having a cTn test will be included. Clusters (comprising one or two hospitals each) will change from their usual-care pathway to an amended pathway using POC-cTnI—the ‘intervention’. The dates of change will be randomised. Changes occur at 1 month intervals, with a minimum 2 month ‘run-in’ period. The intervention pathway will use a POC-cTnI measurement as an alternate to the laboratory-based cTn measurement. Clinical decision-making steps and logic will otherwise remain unchanged. The POC-cTnI is the Siemens (Erlangen Germany) Atellica VTLi high-sensitivity cTnI assay. The primary outcome is ED length of stay. The safety outcome is cardiac death or AMI within 30 days for patients discharged directly from the ED. Ethics and dissemination Ethics approval has been granted by the New Zealand Southern Health and Disability Ethics Committee, reference 21/STH/9. Results will be published in a peer-reviewed journal. Lay and academic presentations will be made. Māori-specific results will be disseminated to Māori stakeholders. Trial registration number ACTRN12619001189112.
Machine Learning to Predict the Likelihood of Acute Myocardial Infarction
Than, Martin , Sandoval, Yader , Shah, Anoop , Apple, Fred S. , Blankenberg, Stefan , Cullen, Louise , Mueller, Christian, Neumann, Franz–Josef , Twerenbold, Raphael , Westermann, Dirk , Beshiri, Agim , Mills, Nicholas L. , Collaborative, On behalf of the MI, George, Peter M., Richards, Mark , Aldous, Sally, Chapman, Andrew R. , Boeddinghaus, Jasper , Huang, Janel, Cullen, Louise , Mills, Nicholas L , Westermann, Dirk , Richards, Arthur M , Than, Martin , Pickering, John W. , Tsanas, Athanasios , Collaborative, On behalf of the MI, Troughton, Richard W. , Anand, Atul , Greenslade, Jaimi , Parsonage, William , Wildi, Karin , Nestelberger, Thomas , Badertscher, Patrick , Du, Shaoqing, Smith, Stephen W. , Sörensen, Nils Arne , Ojeda, Francisco , Boeddinghaus, Jasper , Blankenberg, Stefan , Neumann, Johannes T , Twerenbold, Raphael

Circulation | August 16, 2019 | Volume: 140 | Issue: 11 | Pages: 899-909

10.1161/circulationaha.119.041980 Get It

Background: Variations in cardiac troponin concentrations by age, sex, and time between samples in patients with suspected myocardial infarction are not currently accounted for in diagnostic approaches. We aimed to combine these variables through machine learning to improve the assessment of risk for individual patients. Methods: A machine learning algorithm (myocardial-ischemic-injury-index [MI 3 ]) incorporating age, sex, and paired high-sensitivity cardiac troponin I concentrations, was trained on 3013 patients and tested on 7998 patients with suspected myocardial infarction. MI 3 uses gradient boosting to compute a value (0–100) reflecting an individual’s likelihood of a diagnosis of type 1 myocardial infarction and estimates the sensitivity, negative predictive value, specificity and positive predictive value for that individual. Assessment was by calibration and area under the receiver operating characteristic curve. Secondary analysis evaluated example MI 3 thresholds from the training set that identified patients as low risk (99% sensitivity) and high risk (75% positive predictive value), and performance at these thresholds was compared in the test set to the 99th percentile and European Society of Cardiology rule-out pathways. Results: Myocardial infarction occurred in 404 (13.4%) patients in the training set and 849 (10.6%) patients in the test set. MI 3 was well calibrated with a very high area under the receiver operating characteristic curve of 0.963 [0.956–0.971] in the test set and similar performance in early and late presenters. Example MI 3 thresholds identifying low- and high-risk patients in the training set were 1.6 and 49.7, respectively. In the test set, MI 3 values were <1.6 in 69.5% with a negative predictive value of 99.7% (99.5–99.8%) and sensitivity of 97.8% (96.7–98.7%), and were ≥49.7 in 10.6% with a positive predictive value of 71.8% (68.9–75.0%) and specificity of 96.7% (96.3–97.1%). Using these thresholds, MI 3 performed better than the European Society of Cardiology 0/3-hour pathway (sensitivity, 82.5% [74.5–88.8%]; specificity, 92.2% [90.7–93.5%]) and the 99th percentile at any time point (sensitivity, 89.6% [87.4–91.6%]); specificity, 89.3% [88.6–90.0%]). Conclusions: Using machine learning, MI 3 provides an individualized and objective assessment of the likelihood of myocardial infarction, which can be used to identify low- and high-risk patients who may benefit from earlier clinical decisions. Clinical Trial Registration: URL: https://www.anzctr.org.au . Unique identifier: ACTRN12616001441404.
Detectable High-Sensitivity Cardiac Troponin within the Population Reference Interval Conveys High 5-Year Cardiovascular Risk: An Observational Study
Than, Martin , Aldous, Sally, Troughton, Richard W. , Pemberton, Christopher J, Richards, Mark , Frampton, Christopher , Florkowski, Christopher M , Bailey, Samantha, Young, Joanna M. , Cullen, Louise , Greenslade, Jaimi , Parsonage, William , Jaffe, Allan S. , Pickering, John W. , Cullen, Louise , Pemberton, Christopher J, George, Peter Myles , Everett, Brendan M. , Peacock, William Frank , Jaffe, Allan S. , Troughton, Richard W , Richards, Arthur M , Than, Martin

Clinical Chemistry | May 14, 2018 | Volume: 64 | Issue: 7 | Pages: 1044-1053

10.1373/clinchem.2017.285700 Get It

AbstractBACKGROUNDIncreased cardiac troponin I or T detected by high-sensitivity assays (hs-cTnI or hs-cTnT) confers an increased risk of adverse prognosis. We determined whether patients presenting with putatively normal, detectable cTn concentrations [&gt; limit of detection and &lt; upper reference limit (URL)] have increased risk of major adverse cardiovascular events (MACE) or all-cause mortality.METHODSA prospective 5-year follow-up of patients recruited in the emergency department with possible acute coronary syndrome (ACS) and cTn concentrations measured with hs-cTnI (Abbott) and hs-cTnT (Roche) assays. Cox regression models were generated with adjustment for covariates in those without MACE on presentation. Hazard ratios (HRs) for hs-cTn were calculated relative to the HRs at the median concentration.RESULTSOf 1113 patients, 836 were without presentation MACE. Of these, 138 incurred a MACE and 169 died during a median 5.8-year follow-up. HRs for MACE at the URLs were 2.3 (95% CI, 1.7–3.2) for hs-cTnI and 1.8 (95% CI, 1.3–2.4) for hs-cTnT. Corresponding HRs for mortality were 1.7 (95% CI, 1.2–2.2) for hs-cTnI and 2.3 (95 % CI, 1.7–3.1) for hs-cTnT. The HR for MACE increased with increasing hs-cTn concentration similarly for both assays, but the HR for mortality increased at approximately twice the rate for hs-cTnT than hs-cTnI. Patients with hs-cTnI ≥10 ng/L or hs-cTnT ≥16 ng/L had the same percentage of MACE at 5-year follow-up (33%) as patients with presentation MACE.CONCLUSIONSMany patients with ACS ruled out and putatively normal but detectable hs-cTnI concentrations are at similar long-term risk as those with MACE. hs-cTnT concentrations are more strongly associated with 5-year mortality than hs-cTnI.
ICare-ACS (Improving Care Processes for Patients With Suspected Acute Coronary Syndrome)
Than, Martin , Pickering, John W. , Dryden, Jeremy M., Lord, Sally J., Aldous, Sally, Allan, Kate , Ardagh, Michael, Bonning, John , Callender, Rosie, Chapman, Laura R.E., Christiansen, J., Cromhout, Andre P.J., Cullen, Louise , Deely, Joanne M., Devlin, Gerard, Ferrier, Katherine, Florkowski, Christopher M , Frampton, Christopher , George, Peter M., Hamilton, Gregory J. , Jaffe, Allan S. , Makower, R M, Matthews, Timothy James , Parsonage, William , Pelt, Niels C van, Poynton, Louise, Richards, Mark , Scott, Anthony, Simmonds, Mark, Smyth, David, Thomas, Oliver P., To, Andrew, Toit, Stephen A. Du, Troughton, Richard W. , Yates, Kim , Lord, Sarah J. , Cullen, Louise , Aitken, Stuart A. , Chapman, Laura , Jaffe, Allan S. , Kerr, Andrew Jensen , Larkin, Gregory Luke , Peacock, William Frank , Peckler, Brad , Toit, Stephen Du , Troughton, Richard W , Lord, Sarah J , Richards, Arthur M , Than, Martin

Circulation | November 15, 2017 | Volume: 137 | Issue: 4 | Pages: 354-363

10.1161/circulationaha.117.031984 Get It

Background: Efforts to safely reduce length of stay for emergency department patients with symptoms suggestive of acute coronary syndrome (ACS) have had mixed success. Few system-wide efforts affecting multiple hospital emergency departments have ever been evaluated. We evaluated the effectiveness of a nationwide implementation of clinical pathways for potential ACS in disparate hospitals. Methods: This was a multicenter pragmatic stepped-wedge before-and-after trial in 7 New Zealand acute care hospitals with 31 332 patients investigated for suspected ACS with serial troponin measurements. The implementation was a clinical pathway for the assessment of patients with suspected ACS that included a clinical pathway document in paper or electronic format, structured risk stratification, specified time points for electrocardiographic and serial troponin testing within 3 hours of arrival, and directions for combining risk stratification and electrocardiographic and troponin testing in an accelerated diagnostic protocol. Implementation was monitored for >4 months and compared with usual care over the preceding 6 months. The main outcome measure was the odds of discharge within 6 hours of presentation Results: There were 11 529 participants in the preimplementation phase (range, 284–3465) and 19 803 in the postimplementation phase (range, 395–5039). Overall, the mean 6-hour discharge rate increased from 8.3% (range, 2.7%–37.7%) to 18.4% (6.8%–43.8%). The odds of being discharged within 6 hours increased after clinical pathway implementation. The odds ratio was 2.4 (95% confidence interval, 2.3–2.6). In patients without ACS, the median length of hospital stays decreased by 2.9 hours (95% confidence interval, 2.4–3.4). For patients discharged within 6 hours, there was no change in 30-day major adverse cardiac event rates (0.52% versus 0.44%; P =0.96). In these patients, no adverse event occurred when clinical pathways were correctly followed. Conclusions: Implementation of clinical pathways for suspected ACS reduced the length of stay and increased the proportions of patients safely discharged within 6 hours. Clinical Trial Registration: URL: https://www.anzctr.org.au/ (Australian and New Zealand Clinical Trials Registry). Unique identifier: ACTRN12617000381381.