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The availability of simple, accurate, and affordable cuffless blood pressure (BP) devices has the potential to greatly increase the compliance with measurement recommendations and the utilization of BP measurements for BP telemonitoring. The aim of this study is to evaluate the correlation between findings from routine BP measurements using a conventional sphygmomanometer with the results from a portable ECG monitor combined with photoplethysmography (PPG) for pulse wave registration in patients with arterial hypertension. METHODS: The study included 500 patients aged 32-88 years (mean 64 ± 7.9 years). Mean values from three routine BP measurements by a sphygmomanometer with cuff were selected for comparison; within one minute after the last measurement, an electrocardiogram (ECG) was recorded for 3 min in the standard lead I using a smartphone-case based single-channel ECG monitor (CardioQVARK®-limited responsibility company "L-CARD", Moscow, Russia) simultaneously with a PPG pulse wave recording. Using a combination of the heart signal with the PPG, levels of systolic and diastolic BP were determined based on machine learning using a previously developed and validated algorithm and were compared with sphygmomanometer results. RESULTS: According to the Bland-Altman analysis, SD for systolic BP was 3.63, and bias was 0.32 for systolic BP. SD was 2.95 and bias was 0.61 for diastolic BP. The correlation between the results from the sphygmomanometer and the cuffless method was 0.89 (p = 0.001) for systolic and 0.87 (p = 0.002) for diastolic BP. CONCLUSION: Blood pressure measurements on a smartphone-case without a cuff are encouraging. However, further research is needed to improve the accuracy and reliability of clinical use in the majority of patients.
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Hipertensão , Fotopletismografia , Pressão Sanguínea , Determinação da Pressão Arterial , Eletrocardiografia , Humanos , Hipertensão/diagnóstico , Análise de Onda de Pulso , Reprodutibilidade dos Testes , SmartphoneRESUMO
Recent endeavors have led to the exploration of Machine Learning (ML) to enhance the detection and accurate diagnosis of heart pathologies. This is due to the growing need to improve efficiency in diagnostics and hasten the process of delivering treatment. Several institutions have actively assessed the possibility of creating algorithms for advancing our understanding of atrial fibrillation (AF), a common form of sustained arrhythmia. This means that artificial intelligence is now being used to analyze electrocardiogram (ECG) data. The data is typically extracted from large patient databases and then subsequently used to train and test the algorithm with the help of neural networks. Machine learning has been used to effectively detect atrial fibrillation with more accuracy than clinical experts, and if applied to clinical practice, it will aid in early diagnosis and management of the condition and thus reduce thromboembolic complications of the disease. In this text, a review of the application of machine learning in the analysis and detection of atrial fibrillation, a comparison of the outcomes (sensitivity, specificity, and accuracy), and the framework and methods of the studies conducted have been presented.
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State-of-the-art therapy improves the five-year survival rate of patients under the age of 20 with cranial and craniospinal tumors by up to 74%. The urgency of dealing effectively with late treatment-associated cardiovascular complications is rising. Objective: We aimed to assess echocardiographic parameters and exercise performance in subjects with a history of complex treatment for cranial and craniospinal tumors in childhood. Methods: the study of 48 subjects who underwent cranial and craniospinal irradiation for CNS tumors in childhood and 20 healthy age- and sex-matched volunteers was conducted. The examination included hormone studies, cardiopulmonary exercise testing, and, in the main group, echocardiography (ECHO). Results: In five (10.4%) patients, ECHO changes were detected after complex anti-cancer treatment: thickening and calcification of the aortic valve leaflets (2%), and reduction in the systolic LV and RV function (8% and 6%, respectively). Irradiation of various areas was a significant predictor for reduced exercise tolerance, hyperventilation at rest and upon exertion, and an increased ventilatory equivalent for carbon dioxide. Low exercise tolerance was associated with a younger age at the time of treatment initiation. Significant differences were noted between the control group and the childhood cancer survivors with endocrine disorders. Conclusions: The obtained data confirm the importance of regular cardiovascular and endocrine monitoring of this group of cancer survivors.
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Background: Anti-cancer treatment can be fraught with cardiovascular complications, which is the most common cause of death among oncological survivors. Without appropriate cardiomonitoring during anti-cancer treatment, it becomes challenging to detect early signs of cardiovascular complications. In order to achieve higher survival rates, it is necessary to monitor oncological patients outpatiently after anti-cancer treatment administration. In this regard, we aim to evaluate the efficacy of single-lead ECG remote monitoring to detect cardiotoxicity in cancer patients with minimal cardiovascular diseases after the first cycle of polychemotherapy. Materials and methods: The study included patients 162 patients over 18 years old with first diagnosed different types of solid tumors, planed for adjuvant (within 8 weeks after surgery) or neoadjuvant polychemotherapy. All patients were monitored, outpatiently, during 14-21 days (depending on the regimen of polychemotherapy) after polychemotherapy administration using single-lead ECG. Results: QTc > 500 mc prolongation was detected in 8 patients (6.6 %), first-diagnosed arial fibrillation was detected in 11 patients (9 %) in period after chemotherapy administration. Moreover, left ventricular diastolic dysfunction using single-lead ECG after polychemotherapy was detected in 49 (40.1 %) patients with sensitivity 80 %, specificity 95 %, AUC 0.88 (95 % CI, 0.82-0.93). Conclusions: The side effects of cancer treatment may cause life-threatening risks. Early identification of cardiotoxicity plays a vital role in the solution of this problem. Using portable devices to detect early cardiotoxicity is a simple, convenient and affordable screening method, that can be used for promptly observation of patients.
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BACKGROUND: Diabetic retinopathy is the most common complication of diabetes mellitus and is one of the leading causes of vision impairment globally, which is also relevant for the Russian Federation. OBJECTIVE: To evaluate the diagnostic efficiency of a convolutional neural network trained for the detection of diabetic retinopathy and estimation of its severity in fundus images of the Russian population. METHODS: In this cross-sectional multicenter study, the training data set was obtained from an open source and relabeled by a group of independent retina specialists; the sample size was 60,000 eyes. The test sample was recruited prospectively, 1186 fundus photographs of 593 patients were collected. The reference standard was the result of independent grading of the diabetic retinopathy stage by ophthalmologists. RESULTS: Sensitivity and specificity were 95.0% (95% CI; 90.8-96.4) and 96.8% (95% CI; 95.5- 99.0), respectively; positive predictive value - 98.8% (95% CI; 97.6-99.2); negative predictive value - 87.1% (95% CI, 83.4-96.5); accuracy - 95.9% (95% CI; 93.3-97.1); Kappa score - 0.887 (95% CI; 0.839-0.946); F1score - 0.909 (95% CI; 0.870-0.957); area under the ROC-curve - 95.9% (95% CI; 93.3-97.1). There was no statistically significant difference in diagnostic accuracy between the group with isolated diabetic retinopathy and those with hypertensive retinopathy as a concomitant diagnosis. CONCLUSION: The method for diagnosing DR presented in this article has shown its high accuracy, which is consistent with the existing world analogues, however, this method should prove its clinical efficiency in large multicenter multinational controlled randomized studies, in which the reference diagnostic method would be unified and less subjective than an ophthalmologist.
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It would be useful to develop a reliable method for the cuffless measurement of blood pressure (BP), as such a method could be made available anytime and anywhere for the effective screening and monitoring of arterial hypertension. The purpose of this study is to evaluate blood pressure measurements through a CardioQVARK device in clinical practice in different patient groups. METHODS: This study involved 167 patients aged 31 to 88 years (mean 64.2 ± 7.8 years) with normal blood pressure, high blood pressure, and compensated high blood pressure. During each session, three routine blood pressure measurements with intervals of 30 s were taken using a sphygmomanometer with an appropriate cuff size, and the mean value was selected for comparison. The measurements were carried out by two observers trained at the same time with a reference sphygmomanometer using a Y-shaped connector. In the minute following the last cuff-based measurements, an electrocardiogram (ECG) with an I-lead and a photoplethysmocardiogram were recorded simultaneously for 3 min with the CardioQVARK device. We compared the systolic and diastolic BP obtained from a cuff-based mercury sphygmomanometer and smartphone-case-based BP device: the CardioQVARK monitor. A statistical analysis plan was developed using the IEEE Standard for Wearable Cuffless Blood Pressure Devices. Bland-Altman plots were used to estimate the precision of cuffless measurements. RESULTS: The mean difference between the values defined by CardioQVARK and the cuff-based sphygmomanometer for systolic blood pressure (SBP) was 0.31 ± 3.61, while that for diastolic blood pressure (DBP) was 0.44 ± 3.76. The mean absolute difference (MAD) for SBP was 3.44 ± 2.5 mm Hg, and that for DBP was 3.21 ± 2.82 mm Hg. In the subgroups, the smallest error (less than 3 mm Hg) was observed in the prehypertension group, with a slightly larger error (up to 4 mm Hg) found among patients with a normal blood pressure and stage 1 hypertension. The largest error was found in the stage 2 hypertension group (4-5.5 mm Hg). The largest error was 4.2 mm Hg in the high blood pressure group. We, therefore, did not record an error in excess of 7 mmHg, the upper boundary considered acceptable in the IEEE recommendations. We also did not reach a mean error of 5 mmHg, the upper boundary considered acceptable according to the very recent ESH recommendations. At the same time, in all groups of patients, the systolic blood pressure was determined with an error of less than 5 mm Hg in more than 80% of patients. While this study shows that the CardioQVARK device meets the standards of IEEE, the Bland-Altman analysis indicates that the cuffless measurement of diastolic blood pressure has significant bias. The difference was very small and unlikely to be of clinical relevance for the individual patient, but it may well have epidemiological relevance on a population level. Therefore, the CardioQVARK device, while being worthwhile for monitoring patients over time, may not be suitable for screening purposes. Cuffless blood pressure measurement devices are emerging as a convenient and tolerable alternative to cuff-based devices. However, there are several limitations to cuffless blood pressure measurement devices that should be considered. For instance, this study showed a high proportion of measurements with a measurement error of <5 mmHg, while detecting a small, although statistically significant, bias in the measurement of diastolic blood pressure. This suggests that this device may not be suitable for screening purposes. However, its value for monitoring BP over time is confirmed. Furthermore, and most importantly, the easy measurement method and the device portability (integrated in a smartphone) may increase the self-awareness of hypertensive patients and, potentially, lead to an improved adherence to their treatment. CONCLUSION: The cuffless blood pressure technology developed in this study was tested in accordance with the IEEE protocol and showed great precision in patient groups with different blood pressure ranges. This approach, therefore, has the potential to be applied in clinical practice.
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BACKGROUND: Cardiopulmonary exercise testing (CPET) has shown to be useful for preoperative risk stratification in various types of intra-abdominal and thoracic surgery. However, data about the predictive value of CPET for cardiovascular outcome after gastric or oesophageal cancer surgery are inconclusive. The aim of this study was to evaluate the prognostic value of CPET parameters for the prediction of cardiovascular complications in patients with this type of surgery. METHODS: This is a prospective single-centre interventional cohort study including 200 consecutive patients who underwent elective surgery for oesophageal and/or gastric cancer. Symptom-limited CPET was performed preoperatively to evaluate the potential of various test-derived parameters including anaerobic threshold (AT) to predict cardiovascular complications within 30 days after surgery. RESULTS: 200 patients (mean age 68±14.2 years) met inclusion and exclusion criteria: oesophageal surgery 54 pts, gastric surgery 132 pts and combined oesophageal/gastric surgery 14 pts. 41/200 pts (20.5%) experienced cardiovascular complications during and within 30 days after surgery including 4 non-fatal myocardial infarctions (2%), 1 stroke (0.5%); 6 dead from cardiovascular causes (3%) and less serious complications in 30 patients (15%) including angina attacks and antiarrhythmic therapy for ventricular arrhythmias or for atrial fibrillation/flutter. Results from preoperative CPET indicate that an AT level below 11 mL/kg/min was highly predictive for any cardiovascular complication (p=0.02, OR 6.33, 95% CI 1.78 to 22.47). An AT level <9.5 had the best predictive accuracy for major perioperative cardiac complications (sensitivity 93%, specificity 68%, positive predicative value 75%, negative predicative value 98.8%). CONCLUSION: CPET is a useful perioperative risk assessment tool for patients undergoing surgery for oesophageal and gastric cancer, which carries a particularly high risk for cardiovascular complications. An AT <9.5 mL/kg/min turned out to be the most reliable predictor for major cardiovascular complications.
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Doenças Cardiovasculares , Neoplasias Esofágicas , Neoplasias Gástricas , Idoso , Idoso de 80 Anos ou mais , Doenças Cardiovasculares/complicações , Doenças Cardiovasculares/etiologia , Estudos de Coortes , Neoplasias Esofágicas/complicações , Teste de Esforço/métodos , Fatores de Risco de Doenças Cardíacas , Humanos , Pessoa de Meia-Idade , Complicações Pós-Operatórias/diagnóstico , Complicações Pós-Operatórias/etiologia , Estudos Prospectivos , Medição de Risco , Fatores de Risco , Neoplasias Gástricas/complicações , Neoplasias Gástricas/diagnóstico , Neoplasias Gástricas/cirurgiaRESUMO
Background: Screening for atrial fibrillation has the potential to significantly reduce cardiovascular morbidity and mortality. However, questions in regard to how to screen, on whom to screen, and the optimal setting of screening remain unanswered. Objective: To assess the applicability of a federal cardiac monitoring for atrial fibrillation (AF) screening and remote heart rhythm monitoring in patients at high cardiovascular risk in a mixed urban and rural population in Russia. Methods: This is a prospective multicenter cohort study including 3249 individuals with high cardiovascular risk (mean age 56 ± 12.8 years) from the larger Moscow region who were screened for AF using a smartphone-case based single-lead ECG monitor over a period of 18 month. The endpoints were considered as number of newly diagnosed AF; mean time to diagnosis; number of patients for the first time assigned to anticoagulation therapy; frequency of adverse events. Results: A trial fibrillation was diagnosed in 126 patients, 36 of them for the first time. The mean time to diagnosis was 3 ± 2 days. Of 36 patients, the CHA2DS2-VASc score was ≥1 in 34 cases, ≥2 in 29 cases. Anticoagulant therapy was first induced in 31 patients. One death in newly diagnosed group and two deaths in chronic group were registered. There were a total of eight hospitalizations: one in newly diagnosed and seven in chronic AF patients. Conclusion: Our results indicate that a Federal AF screening system in patients at high cardiovascular risk by using a smartphone-case based single lead ECG which is supported by centrally located ECG specialist and central data management is feasible and reliable when performed in a mixed urban and rural area. Further studies are needed to evaluate the full potential of this approach.
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Fibrilação Atrial , Acidente Vascular Cerebral , Adulto , Idoso , Fibrilação Atrial/diagnóstico , Fibrilação Atrial/epidemiologia , Estudos de Coortes , Eletrocardiografia , Humanos , Programas de Rastreamento/métodos , Pessoa de Meia-Idade , Atenção Primária à Saúde , Estudos Prospectivos , Fatores de Risco , Acidente Vascular Cerebral/prevenção & controleRESUMO
Aims: To investigate the potential of a signal processed by smartphone-case based on single lead electrocardiogram (ECG) for left ventricular diastolic dysfunction (LVDD) determination as a screening method. Methods and Results: We included 446 subjects for sample learning and 259 patients for sample test aged 39 to 74 years for testing with 2D-echocardiography, tissue Doppler imaging and ECG using a smartphone-case based single lead ECG monitor for the assessment of LVDD. Spectral analysis of ECG signals (spECG) has been used in combination with advanced signal processing and artificial intelligence methods. Wavelengths slope, time intervals between waves, amplitudes at different points of the ECG complexes, energy of the ECG signal and asymmetry indices were analyzed. The QTc interval indicated significant diastolic dysfunction with a sensitivity of 78% and a specificity of 65%, a Tpeak parameter >590 ms with 63% and 58%, a T value off >695 ms with 63% and 74%, and QRSfi > 674 ms with 74% and 57%, respectively. A combination of the threshold values from all 4 parameters increased sensitivity to 86% and specificity to 70%, respectively (OR 11.7 [2.7-50.9], P < .001). Algorithm approbation have shown: Sensitivity-95.6%, Specificity-97.7%, Diagnostic accuracy-96.5% and Repeatability-98.8%. Conclusion: Our results indicate a great potential of a smartphone-case based on single lead ECG as novel screening tool for LVDD if spECG is used in combination with advanced signal processing and machine learning technologies.