Dataset Information

Systematic Review and Meta-Analysis of Diagnostic Accuracy to Identify ST-Segment Elevation Myocardial Infarction on Interpretations of Prehospital Electrocardiograms.

ABSTRACT: Background: The aim of this study was to assess and discuss the diagnostic accuracy of prehospital ECG interpretation through systematic review and meta-analyses. Methods and Results: Relevant literature published up to July 2020 was identified using PubMed. All human studies of prehospital adult patients suspected of ST-segment elevation myocardial infarction in which prehospital electrocardiogram (ECG) interpretation by paramedics or computers was evaluated and reporting all 4 (true-positive, false-positive, false-negative, and true-negative) values were included. Meta-analyses were conducted separately for the diagnostic accuracy of prehospital ECG interpretation by paramedics (Clinical Question [CQ] 1) and computers (CQ2). After screening, 4 studies for CQ1 and 6 studies for CQ2 were finally included in the meta-analysis. Regarding CQ1, the pooled sensitivity and specificity were 95.5% (95% confidence interval [CI] 82.5-99.0%) and 95.8% (95% CI 82.3-99.1%), respectively. Regarding CQ2, the pooled sensitivity and specificity were 85.4% (95% CI 74.1-92.3%) and 95.4% (95% CI 87.3-98.4%), respectively. Conclusions: This meta-analysis suggests that the diagnostic accuracy of paramedic prehospital ECG interpretations is favorable, with high pooled sensitivity and specificity, with an acceptable estimated number of false positives and false negatives. Computer-assisted ECG interpretation showed high pooled specificity with an acceptable estimated number of false positives, whereas the pooled sensitivity was relatively low.

SUBMITTER: Tanaka A

PROVIDER: S-EPMC9257459 | biostudies-literature | 2022 Jul

REPOSITORIES: biostudies-literature

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Systematic Review and Meta-Analysis of Diagnostic Accuracy to Identify ST-Segment Elevation Myocardial Infarction on Interpretations of Prehospital Electrocardiograms.

Tanaka Akihito A Matsuo Kunihiro K Kikuchi Migaku M Kojima Sunao S Hanada Hiroyuki H Mano Toshiaki T Nakashima Takahiro T Hashiba Katsutaka K Yamamoto Takeshi T Yamaguchi Junichi J Nakayama Naoki N Nomura Osamu O Matoba Tetsuya T Tahara Yoshio Y Nonogi Hiroshi H

Circulation reports 20220525 7

Background: The aim of this study was to assess and discuss the diagnostic accuracy of prehospital ECG interpretation through systematic review and meta-analyses. Methods and Results: Relevant literature published up to July 2020 was identified using PubMed. All human studies of prehospital adult patients suspected of ST-segment elevation myocardial infarction in which prehospital electrocardiogram (ECG) interpretation by paramedics or computers was evaluated and repo ...[more]

PMID: 35860351

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Project description:ImportanceChallenges to improving ST-segment elevation myocardial infarction (STEMI) care are formidable in low- to middle-income countries because of several system-level factors.ObjectiveTo examine access to reperfusion and percutaneous coronary intervention (PCI) during STEMI using a hub-and-spoke model.Design, setting, and participantsThis multicenter, prospective, observational study of a quality improvement program studied 2420 patients 20 years or older with symptoms or signs consistent with STEMI at primary care clinics, small hospitals, and PCI hospitals in the southern state of Tamil Nadu in India. Data were collected from the 4 clusters before implementation of the program (preimplementation data). We required a minimum of 12 weeks for the preimplementation data with the period extending from August 7, 2012, through January 5, 2013. The program was then implemented in a sequential manner across the 4 clusters, and data were collected in the same manner (postimplementation data) from June 12, 2013, through June 24, 2014, for a mean 32-week period.ExposuresCreation of an integrated, regional quality improvement program that linked the 35 spoke health care centers to the 4 large PCI hub hospitals and leveraged recent developments in public health insurance schemes, emergency medical services, and health information technology.Main outcomes and measuresPrimary outcomes focused on the proportion of patients undergoing reperfusion, timely reperfusion, and postfibrinolysis angiography and PCI. Secondary outcomes were in-hospital and 1-year mortality.ResultsA total of 2420 patients with STEMI (2034 men [84.0%] and 386 women [16.0%]; mean [SD] age, 54.7 [12.2] years) (898 in the preimplementation phase and 1522 in the postimplementation phase) were enrolled, with 1053 patients (43.5%) from the spoke health care centers. Missing data were common for systolic blood pressure (213 [8.8%]), heart rate (223 [9.2%]), and anterior MI location (279 [11.5%]). Overall reperfusion use and times to reperfusion were similar (795 [88.5%] vs 1372 [90.1%]; P = .21). Coronary angiography (314 [35.0%] vs 925 [60.8%]; P < .001) and PCI (265 [29.5%] vs 707 [46.5%]; P < .001) were more commonly performed during the postimplementation phase. In-hospital mortality was not different (52 [5.8%] vs 85 [5.6%]; P = .83), but 1-year mortality was lower in the postimplementation phase (134 [17.6%] vs 179 [14.2%]; P = .04), and this difference remained consistent after multivariable adjustment (adjusted odds ratio, 0.76; 95% CI, 0.58-0.98; P = .04).Conclusions and relevanceA hub-and-spoke model in South India improved STEMI care through greater use of PCI and may improve 1-year mortality. This model may serve as an example for developing STEMI systems of care in other low- to middle-income countries.

Project description:Background Prehospital activation of the cardiac catheter laboratory is associated with significant improvements in ST-segment-elevation myocardial infarction (STEMI) performance measures. However, there are equivocal data, particularly within Australia, regarding its influence on mortality. We assessed the association of prehospital activation on performance measures and mortality in patients with STEMI treated with primary percutaneous coronary intervention from the Queensland Cardiac Outcomes Registry (QCOR). Methods and Results Consecutive ambulance-transported patients with STEMI treated with primary percutaneous coronary intervention were analyzed from January 1, 2017 to December 31, 2020 from the QCOR. The total and direct effects of prehospital activation on the primary outcomes (30-day and 1-year cardiovascular mortality) were estimated using logistic regression analyses. Secondary outcomes were STEMI performance measures. Among 2498 patients (mean age: 62.2±12.4 years; 79.2% male), 73% underwent prehospital activation. Median door-to-balloon time (34 minutes [26-46] versus 86 minutes [68-113]; P<0.001), first-electrocardiograph-to-balloon time (83.5 minutes [72-98] versus 109 minutes [81-139]; P<0.001), and proportion of patients meeting STEMI targets (door-to-balloon <60 minutes 90% versus 16%; P<0.001), electrocardiograph-to-balloon time <90 minutes (62% versus 33%; P<0.001) were significantly improved with prehospital activation. Prehospital activation was associated with significantly lower 30-day (1.6% versus 6.6%; P<0.001) and 1-year cardiovascular mortality (2.9% versus 9.5%; P<0.001). After adjustment, no prehospital activation was strongly associated with increased 30-day (odds ratio [OR], 3.6 [95% CI, 2.2-6.0], P<0.001) and 1-year cardiovascular mortality (OR, 3.0 [95% CI, 2.0-4.6]; P<0.001). Conclusions Prehospital activation of cardiac catheterization laboratory for primary percutaneous coronary intervention was associated with significantly shorter time to reperfusion, achievement of STEMI performance measures, and lower 30-day and 1-year cardiovascular mortality.

Dataset Information

Systematic Review and Meta-Analysis of Diagnostic Accuracy to Identify ST-Segment Elevation Myocardial Infarction on Interpretations of Prehospital Electrocardiograms.

Publications

Systematic Review and Meta-Analysis of Diagnostic Accuracy to Identify ST-Segment Elevation Myocardial Infarction on Interpretations of Prehospital Electrocardiograms.

Similar Datasets

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