title: [Acute abdominal pain in the emergency department - a clinical algorithm for adult patients].
abstract: Acute abdominal pain represents the cardinal symptom behind a vast number of possible under-lying causes including several ones that re-quire surgical treatment. It is the most common sur-gical emergency, the most common cause for a surgical consultation in the emergency department and the most common cause for non-trauma related hospital admissions. The golden mis-sion statement is to rapidly identify whether the underlying cause requires an urgent or even immediate surgical intervention. However, behind the same cardinal symptom one may encounter harmless or non-urgent problems. By employing diagnostic means cost effectively and with the aim to avoid unnecessary exposure of the patient to X-rays in mind, the challenge remains to identify patients with an indication for emergency surgery from those who suffer from a less serious condition and thus can be treated conservatively and without any pressure of time. Dealing with such a highly complex decision-making process calls for a clinical algorithm. Many publications are available that have scrutinised the different aspects of the initial assessment and the emergency management of acute abdominal pain. How-ever, the large body of evidence seems to miss articles that describe a formally correct priority- and problem-based approach. Clinical algorithms apply to complex disease states such as acute abdominal pain and translate them into one clearly laid out, logically coordinated and systematic overall process. Our intention is to devel-op such an algorithm to approach acute abdominal pain from the surgeon's point of view. Based on daily practice and with reference to available literature, it is the aim of this study to define a work flow that simply summarises all steps in-volved and defines the required decision process in order to form the intellectual basis for an evidence-based clinical algorithm. The result is illustrated as a first draft of such an evidence-based algorithm to allow emergency evaluation of adult patients with acute abdominal pain.
authors.affiliation: Klinikum der Universität München Campus Grosshadern, Chirurgische Klinik und Poliklinik, München, Deutschland. heiko.trentzsch@med.uni-muenchen.de
authors.forename: H
authors.initials: H
authors.lastname: Trentzsch
authors.forename: J
authors.initials: J
authors.lastname: Werner
authors.forename: K-W
authors.initials: KW
authors.lastname: Jauch
mesh_terms: D000006:Abdomen, Acute / Q000191:economics / Q000209:etiology* / Q000601:surgery; D000328:Adult; D000368:Aged; D000465:Algorithms; D000700:Analgesics / Q000627:therapeutic use; D000701:Analgesics, Opioid / Q000627:therapeutic use; D003362:Cost-Benefit Analysis; D003661:Decision Support Techniques; D003937:Diagnosis, Differential; D003951:Diagnostic Errors; D004282:Documentation / Q000191:economics; D042241:Early Diagnosis; D004636:Emergency Service, Hospital / Q000191:economics; D019317:Evidence-Based Medicine / Q000191:economics; D005858:Germany; D006801:Humans; D008875:Middle Aged; D009313:National Health Programs / Q000191:economics; D010147:Pain Measurement / Q000187:drug effects; D010808:Physical Examination / Q000191:economics; D014057:Tomography, X-Ray Computed / Q000191:economics; D019564:Unnecessary Procedures / Q000191:economics; D057188:Workflow
chemical_list: D000700:Analgesics; D000701:Analgesics, Opioid