Dataset Information

Electrocardiogram ST-Segment Morphology Delineation Method Using Orthogonal Transformations.

ABSTRACT: Differentiation between ischaemic and non-ischaemic transient ST segment events of long term ambulatory electrocardiograms is a persisting weakness in present ischaemia detection systems. Traditional ST segment level measuring is not a sufficiently precise technique due to the single point of measurement and severe noise which is often present. We developed a robust noise resistant orthogonal-transformation based delineation method, which allows tracing the shape of transient ST segment morphology changes from the entire ST segment in terms of diagnostic and morphologic feature-vector time series, and also allows further analysis. For these purposes, we developed a new Legendre Polynomials based Transformation (LPT) of ST segment. Its basis functions have similar shapes to typical transient changes of ST segment morphology categories during myocardial ischaemia (level, slope and scooping), thus providing direct insight into the types of time domain morphology changes through the LPT feature-vector space. We also generated new Karhunen and Lo ève Transformation (KLT) ST segment basis functions using a robust covariance matrix constructed from the ST segment pattern vectors derived from the Long Term ST Database (LTST DB). As for the delineation of significant transient ischaemic and non-ischaemic ST segment episodes, we present a study on the representation of transient ST segment morphology categories, and an evaluation study on the classification power of the KLT- and LPT-based feature vectors to classify between ischaemic and non-ischaemic ST segment episodes of the LTST DB. Classification accuracy using the KLT and LPT feature vectors was 90% and 82%, respectively, when using the k-Nearest Neighbors (k = 3) classifier and 10-fold cross-validation. New sets of feature-vector time series for both transformations were derived for the records of the LTST DB which is freely available on the PhysioNet website and were contributed to the LTST DB. The KLT and LPT present new possibilities for human-expert diagnostics, and for automated ischaemia detection.

SUBMITTER: Amon M

PROVIDER: S-EPMC4749300 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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Publications

Electrocardiogram ST-Segment Morphology Delineation Method Using Orthogonal Transformations.

Amon Miha M Jager Franc F

PloS one 20160210 2

Differentiation between ischaemic and non-ischaemic transient ST segment events of long term ambulatory electrocardiograms is a persisting weakness in present ischaemia detection systems. Traditional ST segment level measuring is not a sufficiently precise technique due to the single point of measurement and severe noise which is often present. We developed a robust noise resistant orthogonal-transformation based delineation method, which allows tracing the shape of transient ST segment morpholo ...[more]

PMID: 26863140

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Project description:ObjectiveWe evaluated ST-segment monitoring to detect clinical decompensation in infants with single ventricle anatomy. We proposed a signal processing algorithm for ST-segment instability and hypothesized that instability is associated with cardiopulmonary arrests.DesignRetrospective, observational study.SettingTertiary children's hospital 21-bed cardiovascular ICU and 36-bed step-down unit.PatientsTwenty single ventricle infants who received stage 1 palliation surgery between January 2013 and January 2014. Twenty rapid response events resulting in cardiopulmonary arrests (arrest group) were recorded in 13 subjects, and nine subjects had no interstage cardiopulmonary arrest (control group).InterventionsNone.Measurements and main resultsArrest data were collected over the 4-hour time window prior to cardiopulmonary arrest. Control data were collected from subjects with no interstage arrest using the 4-hour time window prior to cardiovascular ICU discharge. A paired subgroup analysis was performed comparing subject 4-hour windows prior to arrest (prearrest group) with 4-hour windows prior to discharge (postarrest group). Raw values of ST segments were compared between groups. A 3D ST-segment vector was created using three quasi-orthogonal leads (II, aVL, and V5). Magnitude and instability of this continuous vector were compared between groups. There was no significant difference in mean unprocessed ST-segment values in the arrest and control groups. Utilizing signal processing, there was an increase in the ST-vector magnitude (p = 0.02) and instability (p = 0.008) in the arrest group. In the paired subgroup analysis, there was an increase in the ST-vector magnitude (p = 0.05) and instability (p = 0.05) in the prearrest state compared with the postarrest state prior to discharge.ConclusionsIn single ventricle patients, increased ST instability and magnitude were associated with rapid response events that required intervention for cardiopulmonary arrest, whereas conventional ST-segment monitoring did not differentiate an arrest from control state.

Project description:BACKGROUND:Plaque rupture (PR) and plaque erosion (PE) are main causes of acute myocardial infarction with different demographic and histology characteristics and need different treatment strategy. PR and PE can be identified with optical coherence tomography (OCT) accurately, but convenient and effective noninvasive markers for them are rarely found. History of diabetes mellitus (DM) was reported to be a potential predictor of PR in ST-segment elevated myocardial infarction (STEMI) patients, but the predictive value of other glucose-related variables for it is still uncertain. Present study aimed to clear the relationship between some glucose-related variables and plaque morphology in patients with STEMI. METHODS:We consecutively enrolled 872 STEMI patients and divided them into PR group (n = 616) and PE group (n = 256) based on OCT diagnostic criteria. The relationship of glucose-related variables, including random plasma glucose on admission (ARPG), glycosylated hemoglobin (HbA1c), post-PCI fasting plasma glucose (PFPG), DM history, glucose variable tendency (GVT) and the acute-to-chronic glycemic ratio (A/C), to the PR risk of STEMI patients was analyzed. The correlation between the glucose-related variables and plaque morphology was analyzed meanwhile. RESULTS:Among the glucose-related variables, ARPG and GVT were confirmed to be independent predictors for PR after adjusting for other traditional risk factors in nondiabetic patients. The higher the ARPG level, the more PR risk the STEMI patients had. And high HbA1c and APPG were demonstrated to have a weak and positive correlation with lipid constituents and stenosis degree of culprit vessel. CONCLUSIONS:Compared to HbA1c, DM history, and some other glucose-related variables, ARPG and GVT were risk factors for PR in STEMI patients, especially those without DM. And high HbA1c and ARPG were positively correlated with the development of vulnerable plaque in culprit vessels. Trial registration Present study is a retrospective one and the population came from the EROSION study of our center previously. It was approved by the Ethics Committee of the Second Affiliated Hospital of Harbin Medical University (Approval reference number, KY2017-249), and all patients provided written informed consent prior to the inclusion in the study and the investigation conformed to the principles outlined in the Declaration of Helsinki.

Dataset Information

Electrocardiogram ST-Segment Morphology Delineation Method Using Orthogonal Transformations.

Publications

Electrocardiogram ST-Segment Morphology Delineation Method Using Orthogonal Transformations.

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