Smart hospital: achieving interoperability and raw data collection from medical devices in clinical routine.

Introduction: Today, modern technology is used to diagnose and treat cardiovascular disease. These medical devices provide exact measures and raw data such as imaging data or biosignals. So far, the Broad Integration of These Health Data into Hospital Information Technology Structures-Especially in Germany-is Lacking, and if data integration takes place, only non-Evaluable Findings are Usually Integrated into the Hospital Information Technology Structures. A Comprehensive Integration of raw Data and Structured Medical Information has not yet Been Established. The aim of this project was to design and implement an interoperable database (cardio-vascular-information-system, CVIS) for the automated integration of al medical device data (parameters and raw data) in cardio-vascular medicine. Methods: The CVIS serves as a data integration and preparation system at the interface between the various devices and the hospital IT infrastructure. In our project, we were able to establish a database with integration of proprietary device interfaces, which could be integrated into the electronic health record (EHR) with various HL7 and web interfaces. Results: In the period between 1.7.2020 and 30.6.2022, the data integrated into this database were evaluated. During this time, 114,858 patients were automatically included in the database and medical data of 50,295 of them were entered. For technical examinations, more than 4.5 million readings (an average of 28.5 per examination) and 684,696 image data and raw signals (28,935 ECG files, 655,761 structured reports, 91,113 x-ray objects, 559,648 ultrasound objects in 54 different examination types, 5,000 endoscopy objects) were integrated into the database. Over 10.2 million bidirectional HL7 messages (approximately 14,000/day) were successfully processed. 98,458 documents were transferred to the central document management system, 55,154 materials (average 7.77 per order) were recorded and stored in the database, 21,196 diagnoses and 50,353 services/OPS were recorded and transferred. On average, 3.3 examinations per patient were recorded; in addition, there are an average of 13 laboratory examinations. Discussion: Fully automated data integration from medical devices including the raw data is feasible and already creates a comprehensive database for multimodal modern analysis approaches in a short time. This is the basis for national and international projects by extracting research data using FHIR.

Implantable cardiac monitors: artificial intelligence and signal processing reduce remote ECG review workload and preserve arrhythmia detection sensitivity.

Introduction: Implantable cardiac monitors (ICMs) provide long-term arrhythmia monitoring, but high rates of false detections increase the review burden. The new "SmartECG" algorithm filters false detections. Using large real-world data sets, we aimed to quantify the reduction in workload and any loss in sensitivity from this new algorithm. Methods: Patients with a BioMonitor IIIm and any device indication were included from three clinical projects. All subcutaneous ECGs (sECGs) transmitted via remote monitoring were classified by the algorithm as "true" or "false." We quantified the relative reduction in workload assuming "false" sECGs were ignored. The remote monitoring workload from five hospitals with established remote monitoring routines was evaluated. Loss in sensitivity was estimated by testing a sample of 2000 sECGs against a clinical board of three physicians. Results: Of our population of 368 patients, 42% had an indication for syncope or pre-syncope and 31% for cryptogenic stroke. Within 418.5 patient-years of follow-up, 143,096 remote monitoring transmissions contained 61,517 sECGs. SmartECG filtered 42.8% of all sECGs as "false," reducing the number per patient-year from 147 to 84. In five hospitals, nine trained reviewers inspected on average 105 sECGs per working hour. This results in an annual working time per patient of 83 min without SmartECG, and 48 min with SmartECG. The loss of sensitivity is estimated as 2.6%. In the majority of cases where true arrhythmias were rejected, SmartECG classified the same type of arrhythmia as "true" before or within 3 days of the falsely rejected sECG. Conclusion: SmartECG increases efficiency in long-term arrhythmia monitoring using ICMs. The reduction of workload by SmartECG is meaningful and the risk of missing a relevant arrhythmia due to incorrect filtering by the algorithm is limited.

QRS fragmentation does not predict mortality in survivors of acute myocardial infarction.

BACKGROUND: Despite advances in coronary revascularization and in heart failure management, myocardial infarction survivors remain at substantially increased mortality risk. Precise risk assessment and risk-adapted follow-up care are crucial to improve their outcomes. Recently, the fragmented QRS complex, i.e. the presence of additional spikes within the QRS complexes on a 12-lead electrocardiogram, has been discussed as a potential non-invasive risk predictor in cardiac patients. HYPOTHESIS: The aim of this study was to evaluate the prognostic meaning of the fragmented QRS complex in myocardial infarction survivors. METHODS: 609 patients with narrow QRS complexes <120 ms were included in a prospective cohort study while hospitalized for myocardial infarction and followed for 5 years. RESULTS: The prevalence of the fragmented QRS complex in these patients amounted to 46.8% (285 patients). These patients had no increased hazard of all-cause death (HR 0.84, 95%-CI 0.45-1.57, p = 0.582) with a mortality rate of 6.0% compared to 7.1% in patients without QRS fragmentations. Furthermore, the risks of cardiac death (HR 1.28, 95%-CI 0.49-3.31, p = 0.613) and of non-cardiac death (HR 0.6, 95%-CI 0.26-1.43, p = 0.25) were not significantly different in patients with QRS fragmentations. However, patients with QRS fragmentations had increased serum creatine kinase concentrations (1438U/l vs. 1160U/l, p = 0.039) and reduced left ventricular ejection fractions (52% vs. 54%, p = 0.011). CONCLUSIONS: The hypothesis that QRS fragmentation might be a prognostic parameter in survivors of myocardial infarction was not confirmed. But those with QRS fragmentation had larger myocardial infarctions, as measured by creatine kinase and left ventricular ejection fraction.

DWT-CNNTRN: a Convolutional Transformer for ECG Classification with Discrete Wavelet Transform.

Cardiovascular diseases are the leading cause of death worldwide. The diagnoses of cardiovascular diseases are usually carried out by cardiologists utilizing Electrocardiograms (ECGs). To assist these physicians in making an accurate diagnosis, there is a growing need for reliable and automatic ECG classifiers.In this study, a new method is proposed to classify 12-lead ECG recordings. The proposed model is composed of four components: the CNN(Convolutional Neural Network) module, the transformer module, the global hybrid pooling layer, and a classification layer. To improve the classification performance, the model takes the discrete wavelet transform of ECG signals as the model inputs and utilizes a hybrid pooling layer to condense the most important features over each period.The proposed model is evaluated using the test set of the China Physiological Signal Challenge 2018 dataset with 12-lead ECGs. It performs with an average accuracy of 0.86 and an average F1-scores of 0.83. The scores are particularly good for the block conditions (LBBB, RBBB, I-AVB). The main advantage of the proposed model is that, it obtains good results with a significantly smaller number of parameters compared to other individual and ensemble models.Clinical relevance- This work establishes a new ECG classifier model with high performance and low model size. It can make automatic ECG analysis more accessible, efficient, and accurate, especially in remote or underserved areas.

[Venous access routes for cardiac implantable electronic devices]. / Venöse Zugangswege in der kardialen Devicetherapie.

Various venous access routes in the region of the clavicle are available for cardiac device treatment. After many years of choosing access via the subclavian vein, current data explicitly show that lateral approaches such as preparation of the cephalic vein or puncture of the axillary vein are clearly superior in terms of probe durability and risk of complications. This article describes the preparation and performance of the various access techniques and is intended to provide a practical guide for the work in cardiac pacemaker operations. This work continues a series of articles designed for advanced training in specialized rhythmology.

Insertable cardiac monitor with a long sensing vector: Impact of obesity on sensing quality and safety.

Background: Fat layers in obese patients can impair R-wave detection and diagnostic performance of a subcutaneous insertable cardiac monitor (ICM). We compared safety and ICM sensing quality between obese patients [body mass index (BMI) ≥ 30 kg/m2] and normal-weight controls (BMI <30 kg/m2) in terms of R-wave amplitude and time in noise mode (noise burden) detected by a long-sensing-vector ICM. Materials and methods: Patients from two multicentre, non-randomized clinical registries are included in the present analysis on January 31, 2022 (data freeze), if the follow-up period was at least 90 days after ICM insertion, including daily remote monitoring. The R-wave amplitudes and daily noise burden averaged intraindividually for days 61-90 and days 1-90, respectively, were compared between obese patients (n = 104) and unmatched (n = 268) and a nearest-neighbour propensity score (PS) matched (n = 69) normal-weight controls. Results: The average R-wave amplitude was significantly lower in obese (median 0.46 mV) than in normal-weight unmatched (0.70 mV, P < 0.0001) or PS-matched (0.60 mV, P = 0.003) patients. The median noise burden was 1.0% in obese patients, which was not significantly higher than in unmatched (0.7%; P = 0.056) or PS-matched (0.8%; P = 0.133) controls. The rate of adverse device effects during the first 90 days did not differ significantly between groups. Conclusion: Although increased BMI was associated with reduced signal amplitude, also in obese patients the median R-wave amplitude was >0.3 mV, a value which is generally accepted as the minimum level for adequate R-wave detection. The noise burden and adverse event rates did not differ significantly between obese and normal-weight patients.Registration: URL: https://www.clinicaltrials.gov; Unique identifier: NCT04075084 and NCT04198220.

Diagnostic yield of an insertable cardiac monitor in a large patient population.

Background: Insertable cardiac monitors (ICMs) are increasingly used for cardiac rhythm diagnosis with expanding indications. Little has been reported about their use and efficacy. Objective: The study sought to evaluate the clinical utility of a novel ICM (Biotronik BIOMONITOR III) including the time to diagnosis in unselected patients with different ICM indications. Methods: Patients from 2 prospective clinical studies were included to determine the diagnostic yield of the ICM. The primary endpoint was time to clinical diagnosis per implant indication or to the first change in atrial fibrillation (AF) therapy. Results: A total of 632 patients were included with a mean follow-up of 233 ± 168 days. Of 384 patients with (pre)syncope, 34.2% had a diagnosis at 1 year. The most frequent therapy was permanent pacemaker implantation. Of 133 patients with cryptogenic stroke, 16.6% had an AF diagnosis at 1 year, resulting in oral anticoagulation. Of 49 patients with an indication for AF monitoring, 41.0% had a relevant change in AF therapy based on ICM data at 1 year. Of 66 patients with other indications, 35.4% received a rhythm diagnosis at 1 year. Moreover, 6.5% of the cohort had additional diagnoses: 26 of 384 patients with syncope, 8 of 133 patients with cryptogenic stroke, and 7 of 49 patients with AF monitoring. Conclusion: In a large unselected patient population with heterogeneous ICM indications, the primary endpoint of rhythm diagnosis was achieved in ∼1 in 4, and additional clinically relevant findings was achieved in 6.5% of patients at short-term follow-up.

The Role of RYR2 in Atrial Fibrillation.

Background. Atrial fibrillation (AF) is a common arrhythmia in elderly patients and is associated with increased risk of mortality. The pathogenesis of AF is complex and based on multiple genetic and environmental factors. Genome-wide association studies identified several loci in AF patients, indicating the complex genetic architecture of this disease. In rare cases, familial forms of AF have been described. Today, pathogenic variants in at least 11 different genes are associated with monogenic AF. Case presentation. The 37-year-old male patient presented to our emergency department with AF. At the age of 35, he had already been diagnosed with paroxysmal AF. Additionally, his 34-year-old brother had also been diagnosed with AF as well as nonobstructive hypertrophic cardiomyopathy. Moreover, the patient's father was diagnosed with AF in his twenties. Transthoracic echocardiography and cardiac MRI revealed a reduced systolic left ventricular ejection without any signs of hypertrophic cardiomyopathy. Genetic testing identified the heterozygous missense variants c.3371C > T, p.(Pro1124Leu) in RYR2 (NM_001035.3) and c.2524C > A, p.(Pro842Thr) in HCN4 (NM_005477.3) in the patient's and his brother's DNA. Discussion. This case of familial AF helps to strengthen the role of RYR2 as a disease gene in the context of AF. Although the variant in RYR2 needs to be classified formally as variant of unknown significance, we regard it as probably disease-causing due to the previously published data. As RYR2 has already been identified as a possible target for prevention and therapy of AF, the knowledge of variants in RYR2 might become even more crucial for individual molecular therapies in the future.

Telemedical monitoring in patients with inborn cardiac disease - experience of a tertiary care centre.

BACKGROUND: The number of cardiologically relevant genetic findings will continue to increase. This is due to the use of high-throughput sequencing techniques and the critical role of incidental findings in cardiac disease genes. Telemedicine can be a useful diagnostic tool to monitor the heart rhythm of patients with inborn cardiac diseases. METHODS: Patients were screened once they had been referred to our outpatient department for rare cardiac diseases between January 2020 and May 2022. Those patients who underwent genetic testing and were consequently diagnosed with a genetic disorder were included in this study. Their medical records were evaluated regarding implanted cardiac electronic devices and findings in the telemedical monitoring. RESULTS: 304 patients were seen in our outpatient department for rare cardiac diseases in the mentioned period. In 100 cases, genetic testing was performed. 10 patients (10%) with an identified inborn cardiac disease were monitored via telemedicine until the end of May 2022. 4 patients were monitored by implantable loop recorders (ILR), 4 patients were monitored by Implantable Cardioverter Defibrillators (ICD), and 2 patients received both devices. Clinical relevant arrhythmias making medical intervention necessary were identified in 4 cases. In two cases, data interpretation was hampered by sinus tachycardia caused by physical exercise. DISCUSSION: Telemonitoring of the heart rhythm by medical devices is beneficial for patients with monogenic heart diseases. Especially, when the indication for an ICD is not clear, implantation of a telemonitored ILR can be a suitable choice. However, rhythm analysis can be challenging in young patients who are physically active.

Heartbeat Classification by Random Forest With a Novel Context Feature: A Segment Label.

OBJECTIVE: Physicians use electrocardiograms (ECG) to diagnose cardiac abnormalities. Sometimes they need to take a deeper look at abnormal heartbeats to diagnose the patients more precisely. The objective of this research is to design a more accurate heartbeat classification algorithm to assist physicians in identifying specific types of the heartbeat. METHODS AND PROCEDURES: In this paper, we propose a novel feature called a segment label, to improve the performance of a heartbeat classifier. This feature, provided by a Convolutional Neural Network, encodes the information surrounding the particular heartbeat. The random forest classifier is trained based on this new feature and other traditional features to classify the heartbeats. RESULTS: We validate our method on the MIT-BIH Arrhythmia dataset following the inter-patient evaluation paradigm. The proposed method is competitive with other similar works. It achieves an accuracy of 0.96, and F1-scores for normal beats, ventricular ectopic beats, and Supra-Ventricular Ectopic Beats (SVEB) of 0.98, 0.93, and 0.74, respectively. The precision and sensitivity for SVEB are 0.76 and 0.78, which outperforms the state-of-the-art methods. CONCLUSION: This study demonstrates that the segment label can contribute to precisely classifying heartbeats, especially those that require rhythm information as context information (e.g. SVEB). Clinical impact: Using a medical devices embedding our algorithm could ease the physicians' processes of diagnosing cardiovascular diseases, especially for SVEB, in clinical implementation.

New-generation miniaturized insertable cardiac monitor with a long sensing vector: Insertion procedure, sensing performance, and home monitoring transmission success in a real-world population.

Background: Insertable cardiac monitors (ICMs) require an invasive procedure and are used for purely diagnostic purposes. Therefore, simplicity of the insertion procedure, low complication rate, long-term patient acceptance, sensing quality, and reliable remote monitoring are of great importance. Objective: To evaluate a novel ICM (BIOMONITOR III) regarding all these aspects. Methods: BIOMONITOR III has a miniaturized profile, long sensing vector (≈70 mm), a fast insertion tool for pocket formation and ICM placement in 1 step, and daily automatic Home Monitoring (HM) function. We evaluated the insertion procedure, complication rate, patient acceptance, sensing quality, and HM performance in 653 patients with BIOMONITOR III inserted for any ICM indication within 2 ongoing studies involving 51 sites in 11 countries. Results: The median time from skin incision to wound closure was 4.0 minutes (interquartile range, 2.3-6.2 minutes). Median follow-up period was 274 days (interquartile range, 175-342 days). Serious adverse device-related events occurred in 6 patients (0.9%). No deep infections were reported in 334 patients without antibiotic prophylaxis. The wearing comfort was good or excellent in ≈95%. The mean R-wave amplitude (0.73 mV) and HM transmission rate (≈94% of days) were stable over 1.5 years. R-wave amplitudes were larger (mean 0.80 vs 0.62 mV, P < .001) and noise burden was lower (median 3.7 vs 14.5 minutes/day, P < .001) for ICM insertions parallel to the heart's long axis (54.2%) vs parasternal (41.3%). A gross visibility of P waves was 95.1%. Conclusion: The study demonstrated fast insertion times, low complication rate, high patient acceptance, and favorable long-term sensing and HM performance of the ICM.

The Polyscore of autonomic parameters predicts mortality and identifies low-risk individuals among diabetic survivors of acute myocardial infarction.

Survivors of an acute myocardial infarction with diabetes mellitus retain an increased mortality risk. Reliable assessment of individual risk is required for effective and cost-efficient medical care in these patients. The Polyscore is a previously established risk predictor consisting of seven autonomic tests derived from electrocardiogram, blood pressure, and respiration. The Polyscore allows classification of survivors of myocardial infarction in groups at low, intermediate and high mortality risk. The aim of this study was to investigate the prognostic value of the Polyscore in diabetic survivors of acute myocardial infarction, which may be impaired by the presence of diabetic autonomic neuropathy. Survivors of an acute myocardial infarction were included in a prospective cohort study during hospitalisation due to the index event at two university hospitals in Munich, Germany. The Polyscore was determined from simultaneous non-invasive 30-min recordings of electrocardiogram, continuous arterial blood pressure, and respiration which were performed in all participants. Patients were followed for 5 years. The primary and secondary outcomes were all-cause mortality and cardiac mortality. 184 of 941 enrolled patients (19.6%) suffered from diabetes mellitus. 5-year-mortality was higher in diabetic patients (15.2%) compared to non-diabetic patients (5.8%). A multivariable Cox regression model confirmed the Polyscore as a strong predictor of mortality in diabetic post-MI patients (intermediate risk: HR 6.56, 95% CI 1.61-26.78, p = 0.004, mortality 22.8%; high risk: HR 18.76, 95% CI 4.35-80.98, p < 0.001, mortality 68.8%). There was no interaction between diabetes mellitus and the Polyscore regarding mortality prediction (p = 0.775). Interestingly, in contrast to the groups at intermediate and high risk (73 patients, 39.7%), the Polyscore identified a majority of diabetic patients (111, 60.3%) with a low mortality risk, comparable to that of low-risk non-diabetic patients (3.6% and 2.1%, respectively, p = 0.339). Consistent results were observed for cardiac mortality. This analysis shows that the Polyscore predicts all-cause and cardiac mortality in diabetic survivors of acute myocardial infarction. Within these patients it identifies a large population not affected by the excess mortality associated with diabetes in this setting. Thus, the Polyscore may facilitate risk-adapted follow-up strategies in diabetic survivors of myocardial infarction.

Myocarditis or inherited disease? - The multifaceted presentation of arrhythmogenic cardiomyopathy.

INTRODUCTION: Arrhythmogenic right ventricular cardiomyopathy (ARVC) is now usually referred to as arrhythmogenic cardiomyopathy (ACM) because of the possible left and biventricular affection. In recent years, it has been shown that early-stage ACM, especially in women carrying a disease-causing variant in the DSP gene, may present with clinical signs of myocarditis. CASE PRESENTATION: The female patient was diagnosed with myocarditis based on arrhythmia and findings on magnetic resonance imaging at the age of 24 years. An additional performed myocardial biopsy confirmed a lymphocytic inflammatory reaction. Subsequently, the patient experienced cardiac arrest because of ventricular fibrillation and was resuscitated. As a result, she received an implantable cardioverter defibrillator, and repeated ablations of recurrent ventricular tachycardia were performed. After four years, molecular genetic testing identified the heterozygous, likely pathogenic nonsense variant c.4789G > T, p.(Glu1597*) in DSP (NM_004415.4). Based on this finding, ACM could be diagnosed, and a heart transplantation was performed only a few months later because of rapid disease progression. DISCUSSION: Truncating variants in DSP have been associated with fulminant progression of arrhythmia. However, the currently used ARVC task force criteria are inadequate to detect DSP-associated ACM with left dominant presentation. Moreover, the initial diagnosis of myocarditis may distract from a more extensive search for other causes. Consequently, in cases of recurrent or unusually prolonged myocarditis, especially if present without detected pathogens, molecular genetic testing should be considered.

Diagnostic Accuracy of High-Sensitive Troponin for the Identification of Myocardial Infarction in Patients Presenting with Acute Heart Failure.

BACKGROUND: The differentiation of myocardial infarction (MI) in the setting of acute heart failure (AHF) can be challenging because the majority of patients presenting with AHF show elevations of high-sensitive troponin (hs-Tn). Fast identification of MI is crucial to perform timely coronary angiography and to improve clinical outcome. OBJECTIVES: The aim of the present study was to assess the diagnostic accuracy of different levels of hs-Tn for the identification of type 1 MI in patients with AHF. METHODS: This was a retrospective single-center analysis of admitted AHF patients with documentation of high-sensitive troponin T (hs-TnT). RESULTS: A total of 649 patients were enrolled into the present study. Of them, 18% had type 1 MI, 7% had type 2 MI, 69% had myocardial injury, and 6% had no myocardial injury. The area under the curve of hs-TnT for the prediction of type 1 MI was 0.70. Sensitivity and specificity of the hs-TnT 99th percentile upper reference limit (URL) for type 1 MI was 100% and 8%, respectively. The Youden index derived cut-off of hs-TnT was 50 ng/L, showing a sensitivity and specificity for type 1 MI of 63% and 68%, respectively. No significant difference regarding 30-day mortality was found depending on the presence of type 1 MI (odds ratio 1.86; 95% confidence interval 0.91-3.81). CONCLUSIONS: Hs-TnT-based identification of type 1 MI in patients with AHF requires higher cut-offs compared with the 99th percentile URL used in overall acute coronary syndrome populations. However, the adjusted cut-off provided only moderate sensitivity and specificity.

Prognostic impact of high-sensitive troponin on 30-day mortality in patients with acute heart failure and different classes of left ventricular ejection fraction.

High-sensitive troponin T (hs-TnT) is increasingly used for prognostication in patients with acute heart failure (AHF). However, uncertainty exists whether hs-TnT shows comparable prognostic performance in patients with heart failure and different classes of left ventricular ejection fraction (LV-EF). The aim of the present study was to assess the prognostic value of hs-TnT for the prediction of 30-day mortality depending on the presence of HF with preserved ejection fraction (HFpEF), HF with mid-range LV-EF (HFmrEF) and HF with reduced LV-EF (HFrEF) in patients with acutely decompensated HF. Patients admitted to our institution due to AHF were retrospectively included. Clinical information was gathered from electronic and paper-based patient charts. Patients with myocardial infarction were excluded. A total of 847 patients were enrolled into the present study. A significant association was found between HF groups and hs-TnT (regression coefficient -0.018 for HFpEF vs. HFmrEF/HFrEF; p = 0.02). The area under the curve (AUC) of hs-TnT for the prediction of 30-mortality was significantly lower in patients with HFpEF (AUC 0.61) than those with HFmrEF (AUC 0.80; p = 0.01) and HFrEF (AUC 0.73; p = 0.04). Hs-TnT was not independently associated with 30-day outcome in the HFpEF group (OR 1.48 [95%-CI 0.89-2.46]; p = 0.13) in contrast to the HFmrEF group (OR 4.53 [95%-CI 1.85-11.1]; p < 0.001) and HFrEF group (OR 2.58 [95%-CI 1.57-4.23]; p < 0.001). Prognostic accuracy of hs-TnT in patients hospitalized for AHF regarding 30-day mortality is significantly lower in patients with HFpEF compared to those with HFmrEF and HFrEF.

Integration of mobile sensors in a telemedicine hospital system: remote-monitoring in COVID-19 patients.

Aim: The goal is to design and, in a next step, establish a scalable, multi-center telemonitoring platform based on existing systems for monitoring COVID-19 patients in home quarantine. In particular, the focus will be on raw data acquisition, integration of sensor data into the hospital system, structured data storage, and interoperability. Subject and methods: Data necessary for monitoring, otherwise provided in various portals, will be continuously queried and integrated into the hospital system via a new interface in this proof-of-concept work. Results: Based on extensive preliminary work at Klinikum rechts der Isar with a structured clinical database, we extend our system's integration of raw data and visualization in dashboards, as well as scientific provision of data from mobile sensors for monitoring patients in home quarantine. Conclusion: Based on existing integrated telemonitoring systems supporting semantic and syntactic interoperability, short-term provision of scientific databases is possible. The integration of different mobile sensors into a clinical system for remote monitoring of patients around the clock is still new and to our knowledge unique.

Accuracy of high-sensitive troponin depending on renal function for clinical outcome prediction in patients with acute heart failure.

High-sensitive troponin T (hs-TnT) is increasingly used for clinical outcome prediction in patients with acute heart failure (AHF). However, there is an ongoing debate regarding the potential impact of renal function on the prognostic accuracy of hs-TnT in this setting. The aim of the present study was to assess the prognostic value of hs-TnT within 6 h of admission for the prediction of 30-day mortality depending on renal function in patients with AHF. Patients admitted to our institution due to AHF were retrospectively included. Clinical information was gathered from electronic and paper-based patient charts. Patients with myocardial infarction were excluded. A total of 971 patients were enrolled in the present study. A negative correlation between estimated glomerular filtration rate (eGFR) and hsTnT was identified (Pearson r = - 0.16; p < 0.001) and eGFR was the only variable to be independently associated with hsTnT. The area under the curve (AUC) of hs-TnT for the prediction of 30-mortality was significantly higher in patients with an eGFR ≥ 45 ml/min (AUC 0.74) compared to those with an eGFR < 45 ml/min (AUC 0.63; p = 0.049). Sensitivity and specificity of the Youden Index derived optimal cut-off for hs-TnT was higher in patients with an eGFR ≥ 45 ml/min (40 ng/l: sensitivity 73%, specificity 71%) compared to patients with an eGFR < 45 ml/min (55 ng/l: sensitivity 63%, specificity 62%). Prognostic accuracy of hs-TnT in patients hospitalized for AHF regarding 30-day mortality is significantly lower in patients with reduced renal function.

A case report of RASA1-associated inherited lymphoedema with recurrent life-threatening lymphangitis.

BACKGROUND: Most cases of lymphoedema are secondary to other causes, while cases of primary lymphoedema, in particular that of congenital origin, are uncommon. Limited genetic disorders are so far known to be associated with lymphatic malformation including mutations in RASA1. This clinical case highlights the possible complications of RASA1-associated lymphatic malformation in a female suffering from recurrent life-threatening septic lymphangitis. CASE SUMMARY: A 23-year-old female patient presented with congenital lymphoedema of the lower right extremity. At the age of eight, she first suffered from an episode of lymphangitis. Thereafter, she developed recurrent episodes of lymphangitis predominately occurring during menstruation and culminating into severe and life-threatening septicaemias. Due to the menstrual association, endometriosis was suspected but could not be confirmed. Furthermore, angiography could not detect any sign of arteriovenous fistula. Single-Photon-Emission-Computed-Tomography confirmed absent major lymphatics of the right leg with severely impaired and prolonged dermal lymphatic backflow. Genetic testing identified a disease-causing variant in the RASA1 gene. DISCUSSION: To our knowledge, this is the first case of recurrent septic lymphangitis with close relation to menstruation in a female with RASA1-associated lymphatic malformation. Due to the possible de novo or somatic origin of a pathogenic variant, a genetic disease should be considered in spite of an unremarkable family history or a localized lymphoedema. Although there is no curative therapy available yet, the knowledge of the underlying genetic defect is important for interdisciplinary patient care and might be crucial for individual molecular therapies in the future.

Longitudinal Assessment of Health and Quality of Life of COVID-19 Patients Requiring Intensive Care-An Observational Study.

Long-term health consequences in survivors of severe COVID-19 remain unclear. Eighteen COVID-19 patients admitted to the intensive care unit at the University Hospital Rechts der Isar, Munich, Germany, between 14 March and 23 June 2020, were prospectively followed-up at a median of 36, 75.5, 122 and 222 days after discharge. The health-related quality of life (HrQoL) (36-item Short Form Health Survey and St. George's Respiratory Questionnaire, SGRQ), cardiopulmonary function, laboratory parameters and chest imaging were assessed longitudinally. The HrQoL assessment revealed a reduced physical functioning, as well as increased SGRQ impact and symptoms scores that all improved over time but remained markedly impaired compared to the reference groups. The median radiological severity scores significantly declined; persistent abnormalities were found in 33.3% of the patients on follow-up. A reduced diffusion capacity was the most common abnormal pulmonary function parameter. The length of hospitalization correlated with role limitations due to physical problems, the SGRQ symptom and the impact score. In conclusion, in survivors of severe COVID-19, the pulmonary function and symptoms improve over time, but impairments in their physical function and diffusion capacity can persist over months. Longer follow-up studies with larger cohorts will be necessary to comprehensively characterize long-term sequelae upon severe COVID-19 and to identify patients at risk.

Remote monitoring of COVID-19 positive high-risk patients in domestic isolation: A feasibility study.

BACKGROUND: If a COVID-19 patient develops a so-called severe course, he or she must be taken to hospital as soon as possible. This proves difficult in domestic isolation, as patients are not continuously monitored. The aim of our study was to establish a telemonitoring system in this setting. METHODS: Oxygen saturation, respiratory rate, heart rate and temperature were measured every 15 minutes using an in-ear device. The data was transmitted to the Telecovid Centre via mobile network or internet and monitored 24/7 by a trained team. The data were supplemented by daily telephone calls. The patients´ individual risk was assessed using a modified National Early Warning Score. In case of a deterioration, a physician initiated the appropriate measures. Covid-19 Patients were included if they were older than 60 years or fulfilled at least one of the following conditions: pre-existing disease (cardiovascular, pulmonary, immunologic), obesity (BMI >35), diabetes mellitus, hypertension, active malignancy, or pregnancy. FINDINGS: 153 patients (median age 59 years, 77 female) were included. Patients were monitored for 9 days (median, IQR 6-13 days) with a daily monitoring time of 13.3 hours (median, IQR 9.4-17.0 hours). 20 patients were referred to the clinic by the Telecovid team. 3 of these required intensive care without invasive ventilation, 4 with invasive ventilation, 1 of the latter died. All patients agreed that the device was easy to use. About 90% of hospitalised patients indicated that they would have delayed hospitalisation further if they had not been part of the study. INTERPRETATION: Our study demonstrates the successful implementation of a remote monitoring system in a pandemic situation. All clinically necessary information was obtained and adequate measures were derived from it without delay.