Das Elektrokardiogramm des Sporttreibenden und der Sport-assoziierte plötzliche Herztod.

Regelmässiges körperliches Training induziert strukturelle, elektrische und funktionelle Anpassungen des Herzens. Die grösste Herausforderung für den Arzt liegt darin, Veränderungen hinweisend für eine strukturelle Herzerkrankung von physiologischen, trainingsassoziierten Anpassungen im Sinne eines 'Athlete's heart' zu unterscheiden. Bei zugrundliegender Kardiopathie ist sportliche Aktivität nicht die Ursache, sondern kann ein Trigger für belastungsabhängige Tachyarrhythmien bzw. für den belastungsabhängigen plötzlichen Herztod (SCD) sein. Um Athleten mit einer kardialen Grunderkrankung und erhöhtem Risiko für einen SCD frühzeitig zu identifizieren wird in Europa ein Preparticipation Screening empfohlen, welches von der Schweizerischen Gesellschaft für Sportmedizin (SGSM) übernommen wurde. Dieses Screening umfasst neben der spezifischen Anamnese und der Herzauskultation auch ein Ruhe-Elektrokardiogramm (Ruhe-EKG). Aufgrund der hohen Anzahl falsch-positiver EKG-Befunde wurden in den letzten Jahren die Beurteilungskriterien des Athleten-EKGs wiederholt angepasst, die Sensitivität und insbesondere auch die Spezifität konnte mit den „verfeinerten Seattle Kriterien“ 2014 deutlich verbessert werden. Der frühen Repolarisation galt in den letzten Jahren ein Hauptaugenmerk: neben dem (Ausdauer-) Training besteht eine klare Assoziation zum männlichen Geschlecht, zur Ethnie, zu den Veränderungen des vegetativen Nervensystems und zu erhöhten QRS-Voltage-Kriterien.

How to prevent overdiagnosis.

Overdiagnosis is the diagnosis of an abnormality that is not associated with a substantial health hazard and that patients have no benefit to be aware of. It is neither a misdiagnosis (diagnostic error), nor a false positive result (positive test in the absence of a real abnormality). It mainly results from screening, use of increasingly sensitive diagnostic tests, incidental findings on routine examinations, and widening diagnostic criteria to define a condition requiring an intervention. The blurring boundaries between risk and disease, physicians' fear of missing a diagnosis and patients' need for reassurance are further causes of overdiagnosis. Overdiagnosis often implies procedures to confirm or exclude the presence of the condition and is by definition associated with useless treatments and interventions, generating harm and costs without any benefit. Overdiagnosis also diverts healthcare professionals from caring about other health issues. Preventing overdiagnosis requires increasing awareness of healthcare professionals and patients about its occurrence, the avoidance of unnecessary and untargeted diagnostic tests, and the avoidance of screening without demonstrated benefits. Furthermore, accounting systematically for the harms and benefits of screening and diagnostic tests and determining risk factor thresholds based on the expected absolute risk reduction would also help prevent overdiagnosis.

Biomarker-guided personalised emergency medicine for all - hope for another hype?

Polymorbid patients, diverse diagnostic and therapeutic options, more complex hospital structures, financial incentives, benchmarking, as well as perceptional and societal changes put pressure on medical doctors, specifically if medical errors surface. This is particularly true for the emergency department setting, where patients face delayed or erroneous initial diagnostic or therapeutic measures and costly hospital stays due to sub-optimal triage. A "biomarker" is any laboratory tool with the potential better to detect and characterise diseases, to simplify complex clinical algorithms and to improve clinical problem solving in routine care. They must be embedded in clinical algorithms to complement and not replace basic medical skills. Unselected ordering of laboratory tests and shortcomings in test performance and interpretation contribute to diagnostic errors. Test results may be ambiguous with false positive or false negative results and generate unnecessary harm and costs. Laboratory tests should only be ordered, if results have clinical consequences. In studies, we must move beyond the observational reporting and meta-analysing of diagnostic accuracies for biomarkers. Instead, specific cut-off ranges should be proposed and intervention studies conducted to prove outcome relevant impacts on patient care. The focus of this review is to exemplify the appropriate use of selected laboratory tests in the emergency setting for which randomised-controlled intervention studies have proven clinical benefit. Herein, we focus on initial patient triage and allocation of treatment opportunities in patients with cardiorespiratory diseases in the emergency department. The following five biomarkers will be discussed: proadrenomedullin for prognostic triage assessment and site-of-care decisions, cardiac troponin for acute myocardial infarction, natriuretic peptides for acute heart failure, D-dimers for venous thromboembolism, C-reactive protein as a marker of inflammation, and procalcitonin for antibiotic stewardship in infections of the respiratory tract and sepsis. For these markers we provide an overview on physiopathology, historical evolution of evidence, strengths and limitations for a rational implementation into clinical algorithms. We critically discuss results from key intervention trials that led to their use in clinical routine and potential future indications. The rational for the use of all these biomarkers, first, tackle diagnostic ambiguity and consecutive defensive medicine, second, delayed and sub-optimal therapeutic decisions, and third, prognostic uncertainty with misguided triage and site-of-care decisions all contributing to the waste of our limited health care resources. A multifaceted approach for a more targeted management of medical patients from emergency admission to discharge including biomarkers, will translate into better resource use, shorter length of hospital stay, reduced overall costs, improved patients satisfaction and outcomes in terms of mortality and re-hospitalisation. Hopefully, the concepts outlined in this review will help the reader to improve their diagnostic skills and become more parsimonious laboratory test requesters.

The use of plant-based bioassays in homeopathic basic research.

OBJECTIVES The objective was to evaluate homeopathic basic research studies that use plant-based bioassays. With this in view, a compilation was made of the findings of three systematic literature reviews covering plant-based bioassays in the three fields of healthy, abiotically, or biotically stressed plants. This compilation focused on investigations using advanced experimental methods and detailed descriptions, also with the aim of supporting the design of future experiments. METHODS Publications included had to report on studies into the effects of homeopathic preparations on whole plants, seeds, plant parts and cells. Outcomes had to be measured by established procedures and statistically evaluated. A Manuscript Information Score (MIS) was applied using predefined criteria to identify publications with sufficient information for adequate interpretation (MIS ≥ 5). Additional evaluation focused on the use of adequate controls to investigate specific effects of homeopathic preparations, and on the use of systematic negative control (SNC) experiments to ensure the stability of the bioassay. Only a fraction of the studies reported here were performed with 'ultra high' dilutions, whereas other studies were performed with moderate or high dilutions. RESULTS A total of 157 publications were identified, describing a total of 167 experimental studies. 84 studies included statistics and 48 had a MIS ≥ 5, thus allowing adequate interpretation. 29 studies had adequate controls to identify specific effects of homeopathic preparations, and reported significant effects of decimal and centesimal homeopathic potencies, including dilution levels beyond Avogadro's number. 10 studies reported use of SNC experiments, yielding evidence for the stability of the experimental set-up. CONCLUSION Plant models appear to be a useful approach for investigating basic research questions relating to homeopathic preparations, but more independent replication trials are needed in order to verify the results found in single experiments. Adequate controls and SNC experiments should be implemented on a routine basis to exclude false-positive results.

Absence of Hepatitis Delta Infection in a Large Rural HIV Cohort in Tanzania

OBJECTIVES The epidemiological and clinical determinants of hepatitis delta virus (HDV) infection in sub-Saharan Africa are ill-defined. We determined the prevalence of HDV infection in HIV/hepatitis B virus (HBV)-co-infected individuals in rural Tanzania. DESIGN AND METHODS We screened all hepatitis B virus (HBV)-infected adults under active follow-up in the Kilombero and Ulanga Antiretroviral Cohort (KIULARCO) for anti-HDV antibodies. In positive samples, we performed a second serological test and nucleic acid amplification. Demographic and clinical characteristics at initiation of antiretroviral therapy (ART) were compared between anti-HDV-negative and positive patients. RESULTS Among 222 HIV/HBV-coinfected patients on ART, 219 (98.6%) had a stored serum sample available and were included. Median age was 37 years, 55% were female, 46% had WHO stage III/IV HIV disease and median CD4 count was 179 cells/μL. The prevalence of anti-HDV positivity was 5.0% (95% confidence interval 2.8%-8.9%). There was no significant predictor of anti-HDV positivity. HDV could not be amplified in any of the anti-HDV-positive patients and the second serological test was negative in all of them. CONCLUSIONS We found no confirmed case of HDV infection among over 200 HIV/HBV-co-infected patients in Tanzania. As false-positive serology results are common, screening results should be confirmed with a second test.

Investigating the potential of reported cattle mortality data in Switzerland for syndromic surveillance

Systems for the identification and registration of cattle have gradually been receiving attention for use in syndromic surveillance, a relatively recent approach for the early detection of infectious disease outbreaks. Real or near real-time monitoring of deaths or stillbirths reported to these systems offer an opportunity to detect temporal or spatial clusters of increased mortality that could be caused by an infectious disease epidemic. In Switzerland, such data are recorded in the "Tierverkehrsdatenbank" (TVD). To investigate the potential of the Swiss TVD for syndromic surveillance, 3 years of data (2009-2011) were assessed in terms of data quality, including timeliness of reporting and completeness of geographic data. Two time-series consisting of reported on-farm deaths and stillbirths were retrospectively analysed to define and quantify the temporal patterns that result from non-health related factors. Geographic data were almost always present in the TVD data; often at different spatial scales. On-farm deaths were reported to the database by farmers in a timely fashion; stillbirths were less timely. Timeliness and geographic coverage are two important features of disease surveillance systems, highlighting the suitability of the TVD for use in a syndromic surveillance system. Both time series exhibited different temporal patterns that were associated with non-health related factors. To avoid false positive signals, these patterns need to be removed from the data or accounted for in some way before applying aberration detection algorithms in real-time. Evaluating mortality data reported to systems for the identification and registration of cattle is of value for comparing national data systems and as a first step towards a European-wide early detection system for emerging and re-emerging cattle diseases.

A simulation study on the statistical monitoring of condemnation rates from slaughterhouses for syndromic surveillance: an evaluation based on Swiss data

Syndromic surveillance (SyS) systems currently exploit various sources of health-related data, most of which are collected for purposes other than surveillance (e.g. economic). Several European SyS systems use data collected during meat inspection for syndromic surveillance of animal health, as some diseases may be more easily detected post-mortem than at their point of origin or during the ante-mortem inspection upon arrival at the slaughterhouse. In this paper we use simulation to evaluate the performance of a quasi-Poisson regression (also known as an improved Farrington) algorithm for the detection of disease outbreaks during post-mortem inspection of slaughtered animals. When parameterizing the algorithm based on the retrospective analyses of 6 years of historic data, the probability of detection was satisfactory for large (range 83-445 cases) outbreaks but poor for small (range 20-177 cases) outbreaks. Varying the amount of historical data used to fit the algorithm can help increasing the probability of detection for small outbreaks. However, while the use of a 0·975 quantile generated a low false-positive rate, in most cases, more than 50% of outbreak cases had already occurred at the time of detection. High variance observed in the whole carcass condemnations time-series, and lack of flexibility in terms of the temporal distribution of simulated outbreaks resulting from low reporting frequency (monthly), constitute major challenges for early detection of outbreaks in the livestock population based on meat inspection data. Reporting frequency should be increased in the future to improve timeliness of the SyS system while increased sensitivity may be achieved by integrating meat inspection data into a multivariate system simultaneously evaluating multiple sources of data on livestock health.