| 1. |
- Neumann, Johannes Tobias, et al.
(författare)
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Personalized diagnosis in suspected myocardial infarction
- 2023
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Ingår i: Clinical Research in Cardiology. - : Springer. - 1861-0684 .- 1861-0692. ; 112, s. 1288-1301
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Tidskriftsartikel (refereegranskat)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.
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| 2. |
- Akhtar, Zubair, et al.
(författare)
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Optimal timing of influenza vaccination among patients with acute myocardial infarction - Findings from the IAMI trial
- 2023
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Ingår i: Vaccine. - : Elsevier. - 0264-410X .- 1873-2518. ; 41:48, s. 7159-7165
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Tidskriftsartikel (refereegranskat)abstract
- Influenza vaccination reduces the risk of adverse cardiovascular events. The IAMI trial randomly assigned 2571 patients with acute myocardial infarction (AMI) to receive influenza vaccine or saline placebo during their index hospital admission. It was conducted at 30 centers in 8 countries from October 1, 2016 to March 1, 2020. In this post-hoc exploratory sub-study, we compare the trial outcomes in patients receiving early season vaccination (n = 1188) and late season vaccination (n = 1344). The primary endpoint was the composite of all-cause death, myocardial infarction (MI), or stent thrombosis at 12 months. The cumulative incidence of the primary and key secondary endpoints by randomized treatment and early or late vaccination was estimated using the Kaplan-Meier method. In the early vaccinated group, the primary composite endpoint occurred in 36 participants (6.0%) assigned to influenza vaccine and 49 (8.4%) assigned to placebo (HR 0.69; 95% CI 0.45 to 1.07), compared to 31 participants (4.7%) assigned to influenza vaccine and 42 (6.2%) assigned to placebo (HR 0.74; 95% CI 0.47 to 1.18) in the late vaccinated group (P = 0.848 for interaction on HR scale at 1 year). We observed similar estimates for the key secondary endpoints of all-cause death and CV death. There was no statistically significant difference in vaccine effectiveness against adverse cardiovascular events by timing of vaccination. The effect of vaccination on all-cause death at one year was more pronounced in the group receiving early vaccination (HR 0.50; 95% CI, 0.29 to 0.86) compared late vaccination group (HR 0.75; 35% CI, 0.40 to 1.40) but there was no statistically significant difference between these groups (Interaction P = 0.335). In conclusion, there is insufficient evidence from the trial to establish whether there is a difference in efficacy between early and late vaccination but regardless of vaccination timing we strongly recommend influenza vaccination in all patients with cardiovascular diseases.
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| 3. |
- Björkelund, Anders, et al.
(författare)
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Machine learning compared with rule‐in/rule‐out algorithms and logistic regression to predict acute myocardial infarction based on troponin T concentrations
- 2021
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Ingår i: Journal of the American College of Emergency Physicians Open. - Hoboken, NJ : John Wiley & Sons. - 2688-1152. ; 2:2
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Tidskriftsartikel (refereegranskat)abstract
- AbstractObjectiveComputerized decision-support tools may improve diagnosis of acute myocardial infarction (AMI) among patients presenting with chest pain at the emergency department (ED). The primary aim was to assess the predictive accuracy of machine learning algorithms based on paired high-sensitivity cardiac troponin T (hs-cTnT) concentrations with varying sampling times, age, and sex in order to rule in or out AMI.MethodsIn this register-based, cross-sectional diagnostic study conducted retrospectively based on 5695 chest pain patients at 2 hospitals in Sweden 2013–2014 we used 5-fold cross-validation 200 times in order to compare the performance of an artificial neural network (ANN) with European guideline-recommended 0/1- and 0/3-hour algorithms for hs-cTnT and with logistic regression without interaction terms. Primary outcome was the size of the intermediate risk group where AMI could not be ruled in or out, while holding the sensitivity (rule-out) and specificity (rule-in) constant across models.ResultsANN and logistic regression had similar (95%) areas under the receiver operating characteristics curve. In patients (n = 4171) where the timing requirements (0/1 or 0/3 hour) for the sampling were met, using ANN led to a relative decrease of 9.2% (95% confidence interval 4.4% to 13.8%; from 24.5% to 22.2% of all tested patients) in the size of the intermediate group compared to the recommended algorithms. By contrast, using logistic regression did not substantially decrease the size of the intermediate group.ConclusionMachine learning algorithms allow for flexibility in sampling and have the potential to improve risk assessment among chest pain patients at the ED.
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| 4. |
- Chiang, Cho-Han, et al.
(författare)
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Performance of the European Society of Cardiology 0/1-Hour, 0/2-Hour, and 0/3-Hour Algorithms for Rapid Triage of Acute Myocardial Infarction : An International Collaborative Meta-analysis
- 2022
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Ingår i: Annals of Internal Medicine. - 0003-4819. ; 175:1, s. 101-113
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Forskningsöversikt (refereegranskat)abstract
- BACKGROUND: The 2020 European Society of Cardiology (ESC) guidelines recommend using the 0/1-hour and 0/2-hour algorithms over the 0/3-hour algorithm as the first and second choices of high-sensitivity cardiac troponin (hs-cTn)-based strategies for triage of patients with suspected acute myocardial infarction (AMI).PURPOSE: To evaluate the diagnostic accuracies of the ESC 0/1-hour, 0/2-hour, and 0/3-hour algorithms.DATA SOURCES: PubMed, Embase, Cochrane Central Register of Controlled Trials, Web of Science, and Scopus from 1 January 2011 to 31 December 2020. (PROSPERO: CRD42020216479).STUDY SELECTION: Prospective studies that evaluated the ESC 0/1-hour, 0/2-hour, or 0/3-hour algorithms in adult patients presenting with suspected AMI.DATA EXTRACTION: The primary outcome was index AMI. Twenty unique cohorts were identified. Primary data were obtained from investigators of 16 cohorts and aggregate data were extracted from 4 cohorts. Two independent authors assessed each study for methodological quality.DATA SYNTHESIS: A total of 32 studies (20 cohorts) with 30 066 patients were analyzed. The 0/1-hour algorithm had a pooled sensitivity of 99.1% (95% CI, 98.5% to 99.5%) and negative predictive value (NPV) of 99.8% (CI, 99.6% to 99.9%) for ruling out AMI. The 0/2-hour algorithm had a pooled sensitivity of 98.6% (CI, 97.2% to 99.3%) and NPV of 99.6% (CI, 99.4% to 99.8%). The 0/3-hour algorithm had a pooled sensitivity of 93.7% (CI, 87.4% to 97.0%) and NPV of 98.7% (CI, 97.7% to 99.3%). Sensitivity of the 0/3-hour algorithm was attenuated in studies that did not use clinical criteria (GRACE score <140 and pain-free) compared with studies that used clinical criteria (90.2% [CI, 82.9 to 94.6] vs. 98.4% [CI, 88.6 to 99.8]). All 3 algorithms had similar specificities and positive predictive values for ruling in AMI, but heterogeneity across studies was substantial. Diagnostic performance was similar across the hs-cTnT (Elecsys; Roche), hs-cTnI (Architect; Abbott), and hs-cTnI (Centaur/Atellica; Siemens) assays.LIMITATION: Diagnostic accuracy, inclusion and exclusion criteria, and cardiac troponin sampling time varied among studies.CONCLUSION: The ESC 0/1-hour and 0/2-hour algorithms have higher sensitivities and NPVs than the 0/3-hour algorithm for index AMI.PRIMARY FUNDING SOURCE: National Taiwan University Hospital.
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| 5. |
- de Capretz, Pontus Olsson, et al.
(författare)
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Machine learning for early prediction of acute myocardial infarction or death in acute chest pain patients using electrocardiogram and blood tests at presentation
- 2023
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Ingår i: BMC Medical Informatics and Decision Making. - London : BioMed Central (BMC). - 1472-6947. ; 23:1, s. 1-10
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Tidskriftsartikel (refereegranskat)abstract
- Aims: In the present study, we aimed to evaluate the performance of machine learning (ML) models for identification of acute myocardial infarction (AMI) or death within 30 days among emergency department (ED) chest pain patients. Methods and results: Using data from 9519 consecutive ED chest pain patients, we created ML models based on logistic regression or artificial neural networks. Model inputs included sex, age, ECG and the first blood tests at patient presentation: High sensitivity TnT (hs-cTnT), glucose, creatinine, and hemoglobin. For a safe rule-out, the models were adapted to achieve a sensitivity > 99% and a negative predictive value (NPV) > 99.5% for 30-day AMI/death. For rule-in, we set the models to achieve a specificity > 90% and a positive predictive value (PPV) of > 70%. The models were also compared with the 0 h arm of the European Society of Cardiology algorithm (ESC 0 h); An initial hs-cTnT < 5 ng/L for rule-out and ≥ 52 ng/L for rule-in. A convolutional neural network was the best model and identified 55% of the patients for rule-out and 5.3% for rule-in, while maintaining the required sensitivity, specificity, NPV and PPV levels. ESC 0 h failed to reach these performance levels. Discussion: An ML model based on age, sex, ECG and blood tests at ED arrival can identify six out of ten chest pain patients for safe early rule-out or rule-in with no need for serial blood tests. Future studies should attempt to improve these ML models further, e.g. by including additional input data. © 2023, The Author(s).
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| 6. |
- Engström, Agnes, et al.
(författare)
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Direct Comparison of the European Society of Cardiology 0/1-Hour Vs. 0/2-Hour Algorithms in Patients with Acute Chest Pain
- 2024
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Ingår i: Journal of Emergency Medicine. - 0736-4679. ; 66:6, s. 651-659
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Tidskriftsartikel (refereegranskat)abstract
- Background: The recent guidelines from the European Society of Cardiology recommends using high-sensitivity cardiac troponin (hs-cTn) in either 0/1-h or 0/2-h algorithms to identify or rule out acute myocardial infarction (AMI). Several studies have reported good diagnostic accuracy with both algorithms, but few have compared the algorithms directly. Objective: We aimed to compare the diagnostic accuracy of the algorithms head-to-head, in the same patients. Methods: This was a secondary analysis of data from a prospective observational study; 1167 consecutive patients presenting with chest pain to the emergency department at Skåne University Hospital (Lund, Sweden) were enrolled. Only patients with a hs-cTnT sample at presentation AND after 1 AND 2 h were included in the analysis. We compared sensitivity, specificity, and negative (NPV) and positive predictive value (PPV). The primary outcome was index visit AMI. Results: A total of 710 patients were included, of whom 56 (7.9%) had AMI. Both algorithms had a sensitivity of 98.2% and an NPV of 99.8% for ruling out AMI, but the 0/2-h algorithm ruled out significantly more patients (69.3% vs. 66.2%, p < 0.001). For rule-in, the 0/2-h algorithm had higher PPV (73.4% vs. 65.2%) and slightly better specificity (97.4% vs. 96.3%, p = 0.016) than the 0/1-h algorithm. Conclusion: Both algorithms had good diagnostic accuracy, with a slight advantage for the 0/2-h algorithm. Which algorithm to implement may thus depend on practical issues such as the ability to exploit the theoretical time saved with the 0/1-h algorithm. Further studies comparing the algorithms in combination with electrocardiography, history, or risk scores are needed.
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| 7. |
- Eriksson, David, et al.
(författare)
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Diagnostic Accuracy of History and Physical Examination for Predicting Major Adverse Cardiac Events Within 30 Days in Patients With Acute Chest Pain
- 2020
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Ingår i: Journal of Emergency Medicine. - : Elsevier BV. - 0736-4679. ; 58:1, s. 1-10
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: The cornerstones in the assessment of emergency department (ED) patients with suspected acute coronary syndrome (ACS) are patient history and physical examination, electrocardiogram, and cardiac troponins. Although there are several prior studies on this subject, they have in some cases produced inconsistent results.OBJECTIVE: The aim of this study was to evaluate the diagnostic and prognostic accuracy of elements of patient history and the physical examination in ED chest pain patients for predicting major adverse cardiac events (MACE) within 30 days.METHODS: This was a prospective observational study that included 1167 ED patients with nontraumatic chest pain. We collected clinical data during the initial ED assessment of the patients. Our primaryoutcome was 30-day MACE.RESULTS: Pain radiating to both arms increased the probability of 30-day MACE (positive likelihood ratio [LR+] 2.7), whereas episodic chest pain lasting seconds (LR+ 0.0) and >24 h (LR+ 0.1) markedly decreased the risk. In the physical examination, pulmonary rales (LR+ 3.0) increased the risk of 30-day MACE, while pain reproduced by palpation (LR+ 0.3) decreased the risk. Among cardiac risk factors, a history of diabetes (LR+ 3.0) and peripheral arterial disease (LR+ 2.7) were the most predictive factors.CONCLUSIONS: No clinical findings reliably ruled in 30-day MACE, whereas episodic chest pain lasting seconds and pain lasting more than 24 h markedly decreased the risk of 30-day MACE. Consequently, these two findings can be adjuncts in ruling out 30-day MACE.
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| 8. |
- Fröbert, Ole, 1964-, et al.
(författare)
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Clinical Impact of Influenza Vaccination after ST- and Non-ST-segment elevation Myocardial Infarction Insights from the IAMI trial
- 2023
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Ingår i: American Heart Journal. - : Elsevier. - 0002-8703 .- 1097-6744. ; 255, s. 82-89
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Influenza vaccination early after myocardial infarction (MI) improves prognosis but vaccine effectiveness may differ dependent on type of MI.METHODS: A total of 2571 participants were prospectively enrolled in the IAMI trial and randomly assigned to receive in-hospital inactivated influenza vaccine or saline placebo. The trial was conducted at 30 centers in 8 countries from October 1, 2016 to March 1, 2020. Here we report vaccine effectiveness in the 2467 participants with ST-segment elevation MI (STEMI, n=1348) or non-ST-segment elevation MI (NSTEMI, n=1119). The primary endpoint was the composite of all-cause death, MI, or stent thrombosis at 12 months. Cumulative incidence of the primary and key secondary endpoints by randomized treatment and NSTEMI/STEMI was estimated using the Kaplan-Meier method. Treatment effects were evaluated with formal interaction testing to assess for effect modification.RESULTS: Baseline risk was higher in participants with NSTEMI. In the NSTEMI group the primary endpoint occurred in 6.5% of participants assigned to influenza vaccine and 10.5% assigned to placebo (hazard ratio [HR], 0.60; 95% CI, 0.39-0.91), compared to 4.1% assigned to influenza vaccine and 4.5% assigned to placebo in the STEMI group (HR, 0.90; 95% CI, 0.54-1.50, P=0.237 for interaction). Similar findings were seen for the key secondary endpoints of all-cause death and cardiovascular death. The Kaplan-Meier risk difference in all-cause death at 1 year was more pronounced in participants with NSTEMI (NSTEMI: HR, 0.47; 95% CI 0.28-0.80, STEMI: HR, 0.86; 95% CI, 0.43-1.70, interaction P=0.028).CONCLUSIONS: The beneficial effect of influenza vaccination on adverse cardiovascular events may be enhanced in patients with NSTEMI compared to those with STEMI.
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| 9. |
- Fröbert, Ole, 1964-, et al.
(författare)
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Influenza Vaccination after Myocardial Infarction : A Randomized, Double-Blind, Placebo-Controlled, Multicenter Trial
- 2021
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Ingår i: Circulation. - : Lippincott Williams & Wilkins. - 0009-7322 .- 1524-4539. ; 144:18, s. 1476-1484
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Tidskriftsartikel (refereegranskat)abstract
- Background: Observational and small randomized studies suggest that influenza vaccine may reduce future cardiovascular events in patients with cardiovascular disease.Methods: We conducted an investigator-initiated, randomized, double-blind trial to compare inactivated influenza vaccine with saline placebo administered shortly after myocardial infarction (MI) (99.7% of patients) or high-risk stable coronary heart disease (0.3%). The primary endpoint was the composite of all-cause death, MI, or stent thrombosis at 12 months. A hierarchical testing strategy was used for the key secondary endpoints: all-cause death, cardiovascular death, MI, and stent thrombosis.Results: Due to the Covid-19 pandemic, the data safety and monitoring board decided to halt the trial before attaining the prespecified sample size. Between October 1, 2016, and March 1, 2020, 2571 participants were randomized at 30 centers across eight countries; 1290 assigned to influenza vaccine and 1281 to placebo. Over the 12-month follow-up, the primary outcome occurred in 67 participants (5.3%) assigned influenza vaccine and 91 participants (7.2%) assigned placebo (hazard ratio, 0.72; 95% confidence interval, 0.52 to 0.99; P=0.040). Rates of all-cause death were 2.9% and 4.9% (hazard ratio, 0.59; 0.39 to 0.89; P=0.010), of cardiovascular death 2.7% and 4.5%, (hazard ratio, 0.59; 0.39 to 0.90; P=0.014), and of MI 2.0% and 2.4% (hazard ratio, 0.86; 0.50 to 1.46, P=0.57) in the influenza vaccine and placebo groups, respectively. Conclusions: Influenza vaccination early after an MI or in high-risk coronary heart disease resulted in a lower risk of a composite of all-cause death, MI, or stent thrombosis, as well as a lower risk of all-cause death and cardiovascular death at 12 months compared with placebo.Clinical Trial Registration: URL: http://www.clinicaltrials.gov Unique identifier: NCT02831608.
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| 10. |
- Gilje, Patrik, et al.
(författare)
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A Single High-Sensitivity Cardiac Troponin T Strategy for Ruling Out Myocardial Infarction
- 2024
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Ingår i: Emergency Medicine International. - : Hindawi Publishing Corporation. - 2090-2840 .- 2090-2859. ; 2024
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Tidskriftsartikel (refereegranskat)abstract
- Background. Ruling out acute myocardial infarction (AMI) in the emergency department (ED) is challenging. Studies have shown that a high-sensitivity cardiac troponin T (hs-cTnT) <5 ng/L or <6 ng/L at presentation (0 h) can be used to rule out AMI. The objective of this study was to identify whether an even higher hs-cTnT threshold can be used for a safe rule out of AMI in the ED. Methods. The derivation cohort consisted of 24,973 ED patients with a primary complaint of chest pain. In this cohort, we identified the highest concentration of 0 h hs-cTnT that corresponded to a negative predictive value (NPV) of ≥99.5% for the primary endpoint of AMI/all-cause death within 30 days and the secondary endpoint of all-cause death within one year. The results were validated in two cohorts consisting of 132,021 and 1167 ED chest pain patients. Results. The 0 h hs-cTnT threshold corresponding to a NPV of ≥99.5% for the primary endpoint was <9 ng/L (NPV: 99.6% and 95% CI: 99.5-99.7). This cutoff provided a sensitivity of 96.2% (95% CI: 95.2-97.1) and identified 59.7% of the patients as low risk compared to 35.8% and 43.9% with a 0 h hs-cTnT <5 ng/L and <6 ng/L, respectively. The results were similar in the validation cohorts and seemed to perform even better in patients where the 0 h hs-cTnT was measured >3 h after symptom onset and in those with a nonischemic ECG and nonhigh risk history. Conclusions. A 0 h hs-cTnT cutoff of <9 ng/L safely rules out AMI/death within 30 days in a majority of chest pain patients and is a more effective strategy than the currently recommended <5 ng/L and <6 ng/L cutoffs. This trial is registered with NCT03421873.
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