T wave alternans analysis using a modified moving average method: a comparison of various time series alignment and similarity detection techniques

T wave alternans (TWA) is a beat-to-beat change in the amplitude or shape of T wave. TWA is one of potential biomarkers for ventricular arrhythmias and can be a sign of serious heart disease. Because there is no gold standard in TWA measuring, modifications of existing methods and new solutions are possible. Modified moving average method, proposed by Nearing and Verrier, is one of mostly used in medical practise, but can give misleading results then T waves is not properly aligned or T wave length and morphology changes because of heart rate variability. It is known, that some ventricular arrhythmias can cause heart rate variability, so this type of error is unwanted, because online TWA measuring can become one of sudden ventricular arrhythmias predictors in the near future. In this work, variuos time series alignment and similarity detection techniques were used to improve TWA measuring and this measure capabilities in heart disease diagnostic were analized. TWA analysis with simulated and real data from ECG databases was performed and potentional biomarker was found by using biomarkers combining method, proposed by Liu, Liu and Halabi. 5

Patient-reported measures integration into a hospital information system: bibliometric analysis and case study

Patient-reported measures are useful in the public interest to improve the quality of care and to assess patients’ needs and priorities by helping to identify existing barriers. A bibliometric analysis was carried out to investigate the use and relevance of patient-reported measures in other countries, which showed the growth of the topic in the scientific literature and allowed the identification of the most important integration processes. Patient-reported measures have been implemented in the information system of Vilnius University Hospital Santaros Clinics and a pilot study with real patients is planned for the future to evaluate the results and propose how this system could be integrated into the Lithuanian eHealth system. Article in Lithuanian. Pacientų įtraukties įrankių integravimas į ligoninės informacinę sistemą: bibliometrinė analizė ir atvejo tyrimas Santrauka Pacientų įtraukties įrankiai yra naudingi viešajam interesui, siekiant gerinti sveikatos priežiūros kokybę ir įvertinti pacientų poreikius bei prioritetus, nes padeda nustatyti esamas kliūtis. Siekiant išsiaiškinti pacientų įtraukties įrankių naudojimą ir aktualumą kitose valstybėse, buvo atlikta bibliometrinė analizė, kuri parodė temos plėtojimąsi mokslinėje literatūroje ir leido identifikuoti svarbiausius integravimo procesus. Vilniaus universiteto ligoninės Santaros klinikų informacinėje sistemoje buvo įdiegti pacientų įtraukties įrankiai ir ateityje planuojama atlikti bandomąjį tyrimą su realiais pacientais, įvertinti rezultatus ir pasiūlyti, kaip ši sistema galėtų būti integruota į Lietuvos e. sveikatos sistemą. Reikšminiai žodžiai: elektroniniai sveikatos įrašai, kokybė, pacientų įtraukties įrankiai, e. sveikata, bibliometrinė analizė

Validation of the LITHUANIAN version of the 19-item audit of diabetes dependent quality of life (ADDQOL – LT) questionnaire in patients with diabetes

Abstract Background Currently there is no diabetes-specific quality of life (QOL) instrument available in Lithuanian language. We aimed to develop a Lithuanian version of a widely-used individualised instrument - the Audit of Diabetes Dependent Quality of Life questionnaire (ADDQOL-19) and assess the validity and reliability in patients with type 1 and type 2 diabetes mellitus (DM). Methods This study was conducted at the Primary Care and Endocrinology Outpatient Clinics in Vilnius. The ADDQOL was translated from the original English (UK) into Lithuanian using a standardized methodology of forward and back translation. After cognitive “debriefing” the validity and reliability of LT-ADDQOL questionnaire were assessed in a sample of 138 diabetes patients. Cronbach’s alpha coefficient, factor analysis, independent t tests and ANOVA were used. Results There were 106 participants with type 2 and 32 with type 1 DM included in the study with a mean age of 55.5 years (± 14.5) and 56.2% women. The Cronbach’s alpha coefficient was 0.908 and most of items loading values onto one single factor were larger than 0.40 (varied from 0.41 to 0.77), indicating good internal consistency and reliability of instrument. Conclusions We developed the Lithuanian version of ADDQOL-19 which is a valid and reliable instrument to measure impact of diabetes on QOL. It could be further used by clinicians and researchers for comprehensive assessment of QOL in adults with diabetes

Determinants of patient-perceived primary healthcare quality in Lithuania

Patient-centered care is considered to be one of the essential pillars of a modern healthcare system. Thus, quality assessment based on patients’ perceptions, views and experiences in their journey through the healthcare system is recognized as one of the key principles for quality improvement initiatives. Measuring patient satisfaction can be confounded by expectations and prior experiences, which can be at least partly overcome by evaluating patient-perceived healthcare quality (PPHQ). Understanding the principal constituents of PPHQ may aid healthcare professionals and decision makers in the healthcare management process and help in creating instruments to meaningfully measure patient feedback. Herein, we aimed to analyze the primary determinants of PPHQ and their interactions, with a focus on patient experiences and healthcare accessibility, using the example of Lithuanian primary healthcare. For this purpose, we conducted a cross-sectional representative telephone survey that included a total of 1033 respondents (48% male) who had encountered primary healthcare during last 3 years. Survey questions consisted of sociodemographic characteristics, patient perceptions of healthcare service provision, patient experiences, self-reported health status and overall PPHQ ranked with a 5-point Likert scale as the primary outcome. The classification-regression tree (CRT) technique was used to analyze the relationship between different explanatory variables and PPHQ, as well as their relative importance and interactions. The majority of respondents (89%) evaluated PPHQ as acceptable or good. CRT analysis identified staff behavior, organizational accessibility and financial accessibility as the most important factors affecting PPHQ. Importantly, the latter factors surpassed the effect of other known PPHQ determinants, such as sociodemographic characteristics or health status. Further analysis has revealed that the relative importance of staff behavior, including understanding, attention and empathy, increased when more problems with organizational accessibility were encountered. In conclusion, our study suggests that PPHQ in primary healthcare may primarily be determined by organizational and financial accessibility and staff behavior, which may also act as an important mediating factor. Keywords: healthcare accessibility; healthcare quality; patient experiences; patient-perceived healthcare quality; primary healthcare

Clinical features and three-year outcomes of Takotsubo (stress) cardiomyopathy: observational data from one centre.

Objective: The natural history, management, and outcome of Takotsubo (stress) cardiomyopathy (TTC) is not clear. The aim of this study was to investigate clinical features, define prognostic predictors, and assess the clinical course and outcomes of patients with TTC. Methods: We analyzed 64 patients (52 women) meeting the proposed Mayo Clinic diagnostic criteria for TTC. All patients were treated at Vilnius University Hospital Santariskiu Klinikos from 2001-01-01 to 2014-11-27. Data were collected on the basis of medical records and follow-up data was collected by phone. Results: The mean age of analyzed patients was 63.4 14.6 years; the mean follow-up was 2.9 years. More than half of the patients (52%) did not have any clear stressful triggers. During admission, symptoms such as chest pain (64%) and general weakness (45%) were reported more often than other symptoms. Almost all patients (94%) had the classical TTC form; the remaining 6% of patients had “inverted” TTC. The mean left ventricular ejection fraction (LVEF) on admission was 37.7% ( 8.2%). A pseudonormal or restrictive pattern of LV filling, moderate to severe mitral regurgitation (MR), and right ventricular involvement were uncommon in the patients. The in-hospital course showed cardiogenic shock in 23% of the cases, resulting in the death of 5 (8%) patients. We discovered that only peak concentration of troponin I was a significant predictor of in-hospital mortality (HR 1.067, 95%CI 1.022e1.113, pZ0.003). At the end of the follow-up period, 45 (87%) women and 8 (67%) men were alive. This makes the overall observed mortality at 3 years approximately 17.2%. Using multivariate analysis, elevation of BNP (HR for increase by 10 ng/l 1.002, 95%CI 1e1.003, pZ0.022) and cardiogenic shock on admission (HR 8.696, 95%CI 1.198e63.124, pZ0.032) were significant predictors of overall mortality. Other prognostic factors assessed on admission were nonsignificant predictors of overall mortality. Conclusions: Our analysis shows that in-hospital mortality is influenced by the peak concentration of troponin I, and overall mortality is affected by cardiogenic shock and the elevation of BNP during admission. The assessment of troponin I and BNP can help with the prognostication of TTC patients in our daily clinical practice

Screening for coronavirus disease 2019 (COVID-19) at the Pediatric Emergency Department during different pandemic phases

The wide spectrum of COVID-19 symptoms complicates the selection of target groups for screening. We aimed to compare data of children screened for COVID-19 at the pediatric emergency department in Vilnius between different phases throughout 1 year (Phase I: March–May, 2020; Phase II: June–September, 2020; and Phase III: October, 2020–February, 2021) and to evaluate the possible predictors of the disease. SARS-CoV-2 PCR tests were positive for 2.7% of tested children (248/9,238), significantly higher during the Phase III (5.5%) compared with the Phase I (0.6%, p = 0.000) and Phase II (0.3%, p = 0.000). Infants and teenagers (12–17 years) accounted for a larger proportion of COVID-19 patients (24.6 and 26.2%, respectively) compared to other age groups: 1–2 years (18.9%), 3–6 years (14.9%), and 7–11 years (15.3%). There were more COVID-19 cases among children with a known SARS-CoV-2 exposure compared to those who did not declare any contact (18.2 vs. 1.1%, p = 0000). When symptoms were adjusted for age, gender and known exposure to SARS-CoV-2, we found that fever (OR 2.66; 95% CI 1.89–3.81), pharyngitis (OR 1.35; 95% CI 1.01–1.80), headache (OR 1.81; 95% CI 1.09–2.90), and anosmia/ageusia (OR 6.47; 95% CI 1.61–22.47) were the most significant predictors. Conclusion: Although high numbers of testing were maintained throughout the year, the positive test results were significantly higher during the Phase III. Age (<1 year, 12–17 years), a history of exposure to SARS-CoV-2 and some symptoms, such as fever, pharyngitis, headache and anosmia/ageusia could aid in targeting groups for screening for COVID-19 in children

Association of cardio-ankle vascular index with cardiovascular risk factors and cardiovascular events in metabolic syndrome patients

Objectives: We aimed to investigate the association between arterial stiffness assessed as cardio-ankle vascular index (CAVI) and cardiovascular (CV) risk factors and CV events in the middle-aged metabolic syndrome (MS) patients. Materials and methods: A follow-up study was carried out in 2106 middle-aged (53.83+-6.17 years old, 62% women) MS subjects without overt atherosclerotic disease. Patients were initially recruited in 2009–2011 as participants of the Lithuanian High Cardiovascular Risk (LitHiR) primary prevention program and followed up for 3.8+-1.7 years for CV events. Thorough cardiometabolic risk assessment was carried out at inclusion. Results: Subjects with higher CAVI had worse lipid and glucose metabolism profile: elevated total cholesterol (TC) and low-density lipoprotein cholesterol (LDL-C), decreased highdensity lipoprotein cholesterol (HDL-C), higher fasting and oral glucose tolerance test (OGTT) glucose levels (all P < 0.001), and lower fasting insulin (P = 0.021). Greater age (P < 0.001), heart rate (P = 0.016), and mean arterial pressure (P < 0.001) were also associated with higher CAVI. Over the follow-up period, 93 (4.4%) patients developed a cardiovascular event: 55(2.6%) patients had myocardial infarction and 38 (1.8%) suffered a cerebrovascular event. Fatal CV events comprised 6.5% (n = 6) of all CV events. CAVI was statistically significantly associated with occurrence of myocardial infarction (P = 0.027) and total cardiovascular events (P = 0.045), but not cerebrovascular events (P = 0.65). However, this association was dependent on age and gender

Which Clusters of Metabolic Syndrome Are the Most Associated with Serum Uric Acid?

Background and Objectives: Metabolic syndrome is defined as three or more of five components; therefore, there are 16 possible different clusters of metabolic risk factors that are under one diagnosis of metabolic syndrome. In this study, we evaluated the different clusters of metabolic syndrome (MetS) across serum uric acid (SUA) quartiles and analyzed the association of these clusters with SUA levels, respectively, in both men and women. Materials and Methods: A total of 606 subjects were recruited to a cross-sectional study from the ongoing Lithuanian High Cardiovascular Risk primary prevention program (LitHiR). All of the study subjects were diagnosed with MetS (according to the 2005 National Cholesterol Education Program Adult Treatment Panel III MetS definition). Results: In the middle-aged population of patients with MetS living in Lithuania, a high proportion of hyperuricaemia was detected&mdash;35.5% (95% Cl 31.7% to 39.4%). For women possessing all five MetS components, the chances of having hyperuricaemia are 2.807 higher than for women with three risk factors (p &lt; 0.001). However, men do not have a statistically significantly higher chance of having hyperuricaemia, depending on the number of MetS components in our population. Using multivariable models, the statistically significant chance of having hyperuricaemia was observed only in women possessing all five MetS components (OR = 2.386, p &lt; 0.0001), compared to any other of 15 MetS clusters. After adjustment for age and sex, the chance of having hyperuricaemia for individuals with the cluster of all five MetS components, compared to any other of 15 MetS clusters, remained (OR = 1.982, p = 0.001). Also, a lower probability (OR = 0.653, p = 0.039) of having hyperuricaemia was observed for individuals having the combination of abnormal plasma glucose, blood pressure, and waist circumference. Conclusions: Patients with the clustering of all five metabolic syndrome components are at higher risk for having hyperuricaemia than patients with any other combination of MetS clusters. This risk is even higher for women. It could be beneficial for patients presented with all five MetS components to be screened for SUA concentration in the primary CVD prevention program

Prevalence of Cardiovascular Risk Factors in Middle-Aged Lithuanian Men Based on Body Mass Index and Waist Circumference Group Results from the 2006&ndash;2016 Lithuanian High Cardiovascular Risk Prevention Program

Background and aims: This study aimed to estimate the prevalence of cardiovascular risk factors in middle-aged Lithuanian men categorized according to body mass index and waist circumference results. Methods and results: The data were from the Lithuanian High Cardiovascular Risk primary prevention program between 2009 and 2016. This community-based cross-sectional study comprised 38,412 men aged 40 to 54 years old. We compared the prevalence of arterial hypertension, dyslipidaemia, diabetes mellitus, smoking, and metabolic syndrome in body mass index (BMI) and waist circumference (WC) groups. Regarding the allometric anthropometrics for WC, A Body Shape Indices (ABSIs) were analyzed with respect to mortality risk and smoking status. The most prevalent risk factor in men was dyslipidaemia, followed by arterial hypertension and smoking (86.96%, 47.94%, and 40.52%, respectively). All risk factors except for smoking were more prevalent in men with overweight or obesity as measured by BMI compared to men with normal weight. Similarly, smoking was the only cardiovascular risk factor that was more prevalent among subjects with normal WC compared to those with increased WC or abdominal obesity. Elevated ABSI, which is associated with higher mortality risk, was more prevalent in smokers. Conclusion: The most prevalent cardiovascular risk factor among middle-aged Lithuanian men was dyslipidaemia, with a surprisingly high prevalence in all BMI and WC groups. Smoking was the only risk factor most prevalent in subjects with low or normal weight according to BMI. It was also more prevalent in the normal WC group compared to the increased WC or abdominal obesity groups, but ABSI values associated with higher mortality were more prevalent among smokers than non-smokers

Development and Integration of Patient-Reported Measures into E-Health System: Pilot Feasibility Study

Patient-centered care is recognized as a key element in recent healthcare management strategies. However, the integrated collection of patient feedback capturing the entire journey of patients with complex medical conditions remains understudied. Herein, we aimed to describe the development of an instrument prototype for the collection of PROMs and PREMs that would encompass a whole patient journey at a single time point. We further describe the process of its integration into a hospital’s information system (HIS) and the results of a pilot feasibility study in adult patients with kidney and hematological diseases. We developed an instrument consisting of original PREM and generic EQ-5D-5L questionnaires. E-questionnaires were handled with REDCap software (version 12.5.14) and integrated into the HIS. Patients refusing to use e-questionnaires (48%) were offered paper administration and were older (64 vs. 50 years). The overall response rate for e-questionnaires was 57.1% with a median completion time of 2.0 and 3.7 min for PROM and PREM, respectively. Psychological and social services and primary care setting (diagnosis establishment and involvement in continuous care) were identified as most problematic. The majority of PREM dimensions encompassing different levels of care significantly correlated with PROM responses. Our data indicate the feasibility and potential relevance of the proposed approach, although wider-scale studies in diverse settings are needed