Ugeskrift for laeger
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Ugeskrift for laeger · Sep 2009
Comparative Study[Drug-drug interactions in intensive care patients].
The purpose of this study was to investigate the frequency of potential drug-drug interactions (DDIs) within the first 24 hours of admission to an intensive care unit, and to determine which drugs were involved in potential DDIs along with the clinical relevance of the identified DDIs. ⋯ A total of 71% of the 98 enrolled patients were exposed to one or more potential DDIs. We found an average of 2.5 potential DDIs per patient. Antithrombotic drugs, opioids and loop diuretics were most frequently involved in potential DDIs. The clinical relevance varied because the majority of the identified potential DDIs were normal drug combinations.
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Ugeskrift for laeger · Sep 2009
Case Reports[Use of D-dimer to exclude upper extremity deep venous thrombosis].
D-dimer is often used to exclude deep venous thrombosis, primarily in the lower extremities. We describe a 38-year-old man who had deep venous thrombosis in the left vena subclavia in spite of a normal D-dimer. Only one inconclusive survey compares the value of D-dimer and upper extremity deep venous thrombosis. We conclude that where deep venous thrombosis of the upper extremities is suspected, you cannot rely on the D-dimer value, but should examine the patient using other modalities such as colour Doppler ultrasound.
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A case of Takotsubo cardiomyopathy is described in a postmenopausal woman admitted for suspected recent myocardial infarction, triggered by significant social stress during a family Christmas dinner. Coronary angiography showed no significant lesions. Acute echocardiography demonstrated apical ballooning and an ejection fraction of 30%. The clinical course was uneventful and after one month, echocardiography showed complete resolution of the apical ballooning and recovery of left ventricular systolic function.
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There is little agreement on the philosophy of measuring clinical quality in health care. How data should be analyzed and transformed to healthcare information is an ongoing discussion. To accept a difference in quality between health departments as a real difference, one should consider to which extent the selection of patients, random variation, confounding and inconsistency may have influenced results. The aim of this article is to summarize aspects of clinical healthcare data analyses provided from the national clinical quality databases and to show how data may be presented in a way which is understandable to readers without specialised knowledge of statistics.