Seltene Erkrankungen auf der Intensivstation

Seltene Erkrankungen bleiben oft lange unerkannt und manifestieren sich nicht selten mit intensivmedizinischem Handlungsbedarf. Trotz ihrer geringen Prävalenz verursachen seltene Erkrankungen eine erhebliche medizinische, wirtschaftliche und psychologische Belastung für Patient*innen, Angehörige und das Gesundheitssystem. Herausforderungen bei der Diagnostik und therapeutische Empfehlungen werden in diesem Beitrag zusammengefasst dargestellt.

Kernaussagen

• Es gibt weltweit keine einheitliche Definition für seltene Erkrankungen.

• Seltene Erkrankungen bleiben oft lange unerkannt und manifestieren sich nicht selten mit intensivmedizinischem Handlungsbedarf.

• Die Diagnostik wird durch Biases wie Anchoring Bias, Availability Bias und Premature Closure erschwert. Hier kann der Einsatz von diagnostischen Checklisten, KI-gestützten Entscheidungshilfen und multidisziplinären Diskussionen hilfreich sein.

• Aufgrund der geringen Patientenzahl sind klinische Studien erschwert, sodass es häufig nur wenig Evidenz gibt und oft nur wenige Medikamente zur Behandlung zugelassen sind.

• Trotz ihrer geringen Prävalenz verursachen seltene Erkrankungen eine erhebliche medizinische, wirtschaftliche und psychologische Belastung für Patient*innen, Angehörige und das Gesundheitssystem.

Schlüsselwörter

maschinelles Lernen - Bias - Orphan Drugs - Seltene Erkrankungen - Künstliche Intelligenz

Keywords

orphan diseases - compassionate use

Publication History

Article published online:
10 October 2025

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