Electrocardiogram Quality Classification based on Robust Best Subsets Linear Prediction Error

Abstract A computationally efficient electrocardiogram (EC

Prediction model for an early revision for dislocation after primary total hip arthroplasty

Dislocation is one of the most common complications after primary total hip arthroplasty (THA). Several patient-related risk factors for dislocation have been reported in the previous literature, but only few prediction models for dislocation have been made. Our aim was to build a prediction model for an early (within the first 2 years) revision for dislocation after primary THA using two different statistical methods. The study data constituted of 37 pre- or perioperative variables and postoperative follow-up data of 16 454 primary THAs performed at our institution in 2008–2021. Model I was a traditional logistic regression model and Model II was based on the elastic net method that utilizes machine learning. The models’ overall performance was measured using the pseudo R2 values. The discrimination of the models was measured using C-index in Model I and Area Under the Curve (AUC) in Model II. Calibration curves were made for both models. At 2 years postoperatively, 95 hips (0.6% prevalence) had been revised for dislocation. The pseudo R2 values were 0.04 in Model I and 0.02 in Model II indicating low predictive capability in both models. The C-index in Model I was 0.67 and the AUC in Model II was 0.73 indicating modest discrimination. The prediction of an early revision for dislocation after primary THA is difficult even in a large cohort of patients with detailed data available because of the reasonably low prevalence and multifactorial nature of dislocation. Therefore, the risk of dislocation should be kept in mind in every primary THA, whether the patient has predisposing factors for dislocation or not. Further, when conducting a prediction model, sophisticated methods that utilize machine learning may not necessarily offer significant advantage over traditional statistical methods in clinical setup.publishedVersionPeer reviewe

Thicker polyethylene inserts (≥ 13 mm) increase the risk for early failure after primary cruciate-retaining total knee arthroplasty (TKA) : a single-centre study of 7643 TKAs

PURPOSE: This study investigates whether thicker (PE) inserts lead to a greater risk for revision after TKA. The differences between the TKA designs of three manufacturers (NexGen, PFC Sigma, Triathlon) are also compared. METHODS: A total of 7643 primary TKA surgeries were included. PE inserts were divided into two groups-"thick PE inserts" with a thickness of 13 mm (mm) or more and "standard PE inserts" with a thickness of less than 13 mm. Three cruciate-retaining (CR) TKA designs (NexGen, PFC Sigma, Triathlon) were included in the study. The differences in failure rates between groups were investigated using Kaplan-Meier survival curves and Cox regression model with hazard ratios (HR). Failure rates were investigated short-term ( 2 years; HR 1.6, CI 1.1 to 2.3) follow-up. The highest revision rate was observed in patients who received the Triathlon TKA with a thicker PE insert (HR 2.6, CI 1.2 to 5.7). CONCLUSION: The results indicate that thicker PE inserts are associated with increased risk for revision in primary TKA. Further research is required to ascertain whether more conformed PE inserts or constrained knee designs instead of thick CR inserts will ultimately lead to better clinical outcomes. LEVEL OF EVIDENCE: III.publishedVersionPeer reviewe

EpiMetal:an open-source graphical web browser tool for easy statistical analyses in epidemiology and metabolomics

MOTIVATION: An intuitive graphical interface that allows statistical analyses and visualizations of extensive data without any knowledge of dedicated statistical software or programming. IMPLEMENTATION: EpiMetal is a single-page web application written in JavaScript, to be used via a modern desktop web browser. GENERAL FEATURES: Standard epidemiological analyses and self-organizing maps for data-driven metabolic profiling are included. Multiple extensive datasets with an arbitrary number of continuous and category variables can be integrated with the software. Any snapshot of the analyses can be saved and shared with others via a www-link. We demonstrate the usage of EpiMetal using pilot data with over 500 quantitative molecular measures for each sample as well as in two large-scale epidemiological cohorts (N >10 000). AVAILABILITY: The software usage exemplar and the pilot data are open access online at [http://EpiMetal.computationalmedicine.fi]. MIT licensed source code is available at the Github repository at [https://github.com/amergin/epimetal]

Direct Estimation of HDL-Mediated Cholesterol Efflux Capacity from Serum

BACKGROUND: HDL-mediated cholesterol efflux capacity (HDL-CEC) is a functional attribute that may have a protective role in atherogenesis. However, the estimation of HDL-CEC is based on in vitro cell assays that are laborious and hamper large-scale phenotyping. METHODS: Here, we present a cost-effective high-throughput nuclear magnetic resonance (NMR) spectroscopy method to estimate HDL-CEC directly from serum. We applied the new method in a population-based study of 7603 individuals including 574 who developed incident coronary heart disease (CHD) during 15 years of follow-up, making this the largest quantitative study for HDL-CEC. RESULTS: As estimated by NMR-spectroscopy, a 1-SD higher HDL-CEC was associated with a lower risk of incident CHD (hazards ratio, 0.86; 95% CI, 0.79-0.93, adjusted for traditional risk factors and HDL-C). These findings are consistent with published associations based on in vitro cell assays. CONCLUSIONS: These corroborative large-scale findings provide further support for a potential protective role of HDL-CEC in CHD and substantiate this new method and its future applications. (C) 2019 American Association for Clinical ChemistryPeer reviewe

EpiMetal: an open-source graphical web browser tool for easy statistical analyses in epidemiology and metabolomics

Motivation: An intuitive graphical interface that allows statistical analyses and visualizations of extensive data without any knowledge of dedicated statistical software or programming.Implementation: EpiMetal is a single-page web application written in JavaScript, to be used via a modern desktop web browser.General features: Standard epidemiological analyses and self-organizing maps for datadriven metabolic profiling are included. Multiple extensive datasets with an arbitrary number of continuous and category variables can be integrated with the software. Any snapshot of the analyses can be saved and shared with others via a www-link. We demonstrate the usage of EpiMetal using pilot data with over 500 quantitative molecular measures for each sample as well as in two large-scale epidemiological cohorts (N>10 000).Availability: The software usage exemplar and the pilot data are open access online at [http://EpiMetal.computationalmedicine.fi ]. MIT licensed source code is available at the Github repository at [https://github.com/amergin/epimetal].</div

New methods for vectorcardiographic signal processing

Abstract Vectorcardiography (VCG) determines the direction and magnitude of the heart’s electrical forces. Interpretation of the digital three-dimensional vectorcardiography in clinical applications requires robust methods and novel approaches for calculating the vectorcardiographic features. This dissertation aimed to develop new methods for vectorcardiographic signal processing. The robustness of selected pre-processing and feature extraction algorithms was improved, novel methods for detecting the injured myocardial tissue from electrocardiogram (ECG) were devised, and dynamical behavior of vectorcardiographic features was determined. The main results of the dissertation are: (1) Digitizing process and proper filtering did not produce significant distortions for dipolar Singular Value Decomposition -based ECG parameters from a diagnostic viewpoint, whereas non-dipolar parameters were very sensitive to the pre-processing operations. (2) A novel method for estimating the severity of the myocardial infarction (MI) was developed by combining the action potential based computer model and 12-lead ECG patient data. Using the method it is possible to calculate an approximate estimate of the maximum troponin value and therefore the severity of the MI. In addition, the size and location of the myocardial infarction was found to affect diagnostic significant Total-cosine-R-to-T parameter (TCRT) - changes, both in the simulations and in the patient study. (3) Furthermore, the results showed that carefully targeted improvements to the basic algorithm of the TCRT parameter can evidently decrease the number of algorithm-based failures and therefore improve the diagnostic value of TCRT in different patient data. (4) Finally, a method for calculating beat-to-beat vectorcardiographic features during exercise was developed. It was observed that the breathing affects the beat-to-beat variability of all the QRS/T angle measures and the trend of the TCRT parameter during exercise was found to be negative. Further, the results of the thesis clearly showed that the QRS/T angle measures exhibit a strong correlation with the heart rate in individual subjects. The results of the dissertation highlight the importance of robust algorithms in a VCG analysis. The results should be taken into account in further studies, so that the vectorcardiography can be utilized more effectively in clinical applications.Tiivistelmä Vektorikardiorgafia (VKG) kuvaa sydämen sähköisen toiminnan suuntaa ja suuruutta sydämen lyönnin eri vaiheissa. Vektorikardiogrammin onnistunut tulkinta kliinisissä sovelluksissa edellyttää luotettavia menetelmiä ja uusia lähestymistapoja vektorikardiografisten piirteiden laskennassa. Tämän väitöskirjan tavoitteena oli kehittää uusia vektorikardiografisia signaalinkäsittelymenetelmiä. Väitöstyössä parannettin tiettyjen elektrokardiorgafisen (EKG) -signaalin esikäsittelyvaiheiden ja piirteentunnistusalgoritmien luotettavuutta, kehitettiin uusia menetelmiä vaurioituneen sydänlihaskudoksen tunnistamiseen EKG-signaalista, sekä tutkittiin vektorikardiografisten piirteiden dynaamista käyttäytymistä. Väitöskirjan päätulokset voidaan tiivistää seuraavasti: (1) Paperitallenteisten EKG-tallenteiden digitointiprosessi ja EKG-signaalin asianmukainen suodatus ei aiheuta diagnostisesti merkittäviä vääristymiä ns. dipolaarisiin singulaariarvohajotelmaan (SVD) perustuviin EKG-parametreihin. Kuitenkin ns. ei-dipolaariset herkemmät parametrit ovat sensitiivisiä näille esikäsittelyvaiheille. (2) Väitöskirjatyössä kehitettiin uusi menetelmä sydäninfarktin vakavuuden arvioimiselle 12-kanavaisesta EKG-signaalista käyttäen aktiopotentiaaleihin perustuvaa tietokonemallia. Väitöstyössä todettiin, että menetelmää käyttäen on mahdollista laskea karkea estimaatti kliinisessä käytössä olevalle maksimaaliselle troponiiniarvolle, joka kertoo vaurion määrästä sydänlihaskudoksessa. Lisäksi sydäninfarktin koon ja sijainnin havaittiin vaikuttavan vektorikardiografiseen de- ja repolarisaation suhdetta kuvaavaan diagnostisesti merkittävään Total-cosine-R-to-T- (TCRT) muuttujaan. (3) Tulokset osoittivat myös, että tekemällä muutamia pieniä parannuksia alkuperäiseen TCRT-parametrin algoritmiin, voidaan merkittävästi vähentää parametrin laskennassa aiheutuvia vääristymiä ja täten parantaa TCRT-parametrin diagnostista arvoa erilaisissa potilasaineistoissa. (4) Neljänneksi, työssä kehitettiin menetelmä, jolla vektorikardiografisia piirteitä laskettiin dynaamisesti lyönti lyönniltä. Hengityksen havaittiin aiheuttavan rasitustestin aikana merkittävää lyöntikohtaista vaihtelua. Työssä havaittiin myös, että niin TCRT-parametrilla kuin myös muillakin de- ja repolarisaation välistä suhdetta kuvaavilla muuttujilla oli selvä korrelaatio sydämen sykkeen kanssa. Väitöskirjan tulokset korostavat luotettavien algoritmien tärkeyttä vektorikardiografisessa analyysissä. Tulosten huomioiminen jatkotutkimuksissa edesauttaa vektorikardiografian hyödyntämistä kliinisissä sovelluksissa

Whole blood chromium concentration is very rarely elevated independently of whole blood cobalt

Abstract Due to the risk of adverse reactions to metal debris resulting from increased wear of the arthroplasty more than one million metal-on-metal (MoM) hip replacements worldwide are in active follow-up. Follow-up usually includes measurement of both whole blood cobalt (Co) and chromium (Cr) concentrations. Our experience is that Cr is seldom independently elevated. We wanted to ascertain whether blood Cr measurements could be omitted from follow-up protocols without lowering the quality of follow-up. We identified 8438 whole blood Co and Cr measurements performed without or prior to revision surgery. When the cut-off levels 5 µg/L and 7 µg/L were used, Cr was independently elevated in only 0.5% (95% confidence interval, CI, 0.3 to 0.6) and 0.2% (CI 0.1 to 0.3) of the measurements. The models with continuous variables showed that the higher the blood metal concentrations are the lower the percentage of measurements with Cr higher than Co. Our results suggest that whole blood Cr is very rarely independently elevated and therefore the authorities should consider omitting Cr measurements from their screening guidelines of MoM hip replacements. We believe this change in practice would simplify follow-up and lead to cost savings without decreasing the quality of follow-up