Common misunderstandings of evidence-based medicine.

Currently, most evidence assessments in guidelines or health technology assessments (HTAs) rely on the assumption that a randomized controlled trial (RCT) is always the best source of evidence. However, if the outcome in a control group is certain, e.g. death within a short time with an almost 100% chance, or if an event can only occur in the treatment group, there is no need for a randomized control group; the evidence cannot be improved by a control group, nor by an RCT design. If a cause-effect relationship is certain ("primary or direct evidence"), a therapeutic effect can be diluted in the population of an RCT by cross-over, etc. This can lead to serious misinterpretations of the effect. While experts such as the GRADE group or Cochrane institutes recommend using all available evidence, the leading approach in many guidelines and HTAs is assessing "the best available trials", i.e. RCTs. But since RCTs only deliver probabilities of cause-effect relationships, it is not appropriate to demand RCTs for certain effects. A control group can only diminish the net value of a treatment since the outcome in the control group is subtracted from the outcome in the treatment group. Therefore, under identical circumstances, an RCT will always show lower effect rates compared to a single arm study of the same quality, for desired as well as for adverse effects. Considering these inconsistencies in evidence-based medicine interpretation, the evidence pyramid with RCTs at the top is not always a reliable indicator for the best quality of evidence.

[Embolic stroke of undetermined source (ESUS) - Classification of a new stroke entity]. / Embolischer Schlaganfall mit ungeklärter Emboliequelle (ESUS) ­ Klassifikation einer neuen Schlaganfallentität.

Embolic stroke of undetermined source (ESUS) represents a subpopulation of cryptogenic strokes defined by its embolic stroke pattern on imaging and if after a carefully performed diagnostic evaluation, a specific, well recognized cause of stroke has not been identified. This review article analyses the basics of the ESUS concept and provides an overview of the evidence from recent cohort studies. The definition, aetiology and diagnosis of ESUS are reassessed. Targeted diagnostics in ESUS patients can reduce the number of cryptogenic strokes by making a specific diagnosis.

Detection of Atrial Fibrillation on Stroke Units: Comparison of Manual versus Automatic Analysis of Continuous Telemetry.

BACKGROUND: Detection of atrial fibrillation (AF) is one of the primary diagnostic goals for patients on a stroke unit. Physician-based manual analysis of continuous ECG monitoring is regarded as the gold standard for AF detection but requires considerable resources. Recently, automated computer-based analysis of RR intervals was established to simplify AF detection. The present prospective study analyzes both methods head to head regarding AF detection specificity, sensitivity, and overall effectiveness. METHODS: Consecutive stroke patients without history of AF or proof of AF in the admission ECG were enrolled over the period of 7 months. All patients received continuous ECG telemetry during the complete stay on the stroke unit. All ECGs underwent automated analysis by a commercially available program. Blinded to these results, all ECG tracings were also assessed manually. Sensitivity, specificity, time consumption, costs per day, and cost-effectiveness were compared. RESULTS: 216 consecutive patients were enrolled (70.7 ± 14.1 years, 56% male) and 555 analysis days compared. AF was detected by manual ECG analysis on 37 days (6.7%) and automatically on 57 days (10.3%). Specificity of the automated algorithm was 94.6% and sensitivity 78.4% (28 [5.0%] false positive and 8 [1.4%] false negative). Patients with AF were older and had more often arterial hypertension, higher NIHSS at admission, more often left atrial dilatation, and a higher CHA2DS2-VASc score. Automation significantly reduced human resources but was more expensive compared to manual analysis alone. CONCLUSION: Automatic AF detection is highly specific, but sensitivity is relatively low. Results of this study suggest that automated computer-based AF detection should be rather complementary to manual ECG analysis than replacing it.

[Bradyarrhythmias: diagnostics]. / Diagnose bradykarder Herzrhythmusstörungen.

Bradyarrhythmias cause symptoms such as syncope, dizziness, or exercise intolerance and lead to the implantation of > 100 000 pacemakers in Germany annually. They are caused either by sinus node dysfunction (sinus bradycardia, sinoatrial block, sinusarrest, preautomatic pauses in paroxysmal atrial fibrillation, chronotropic incompetence) or by atrioventricular (AV) conduction abnormalities (AV block, complex bundle branch block). Optimal therapy of bradycardia crucially depends on ECG documentation which frequently requires Holter monitoring in the case of intermittent bradycardia. The differential diagnosis of the ECG can sometimes be demanding, for instance in distinguishing sinus bradycardia or AV block from blocked supraventricular premature beats, in understanding chronotropic sinus node incompetence, 2:1 AV block, complete AV block in atrial fibrillation, bifascicular and imminent trifascicular bundle branch block or vagally induced bradycardia. This review presents the ECG in bradycardia and provides tips for a confident interpretation.