Why the study?
Does a simple algorithm based on ECG, clinical findings, and case history improve diagnostic accuracy and reduce false positive CCU referrals in patients admitted with acute chest pain?
Does a simple algorithm based on ECG, clinical findings, and case history improve diagnostic accuracy and reduce false positive CCU referrals in patients admitted with acute chest pain?
A simple algorithm using ECG, clinical findings, and case history significantly improves diagnostic accuracy and reduces unnecessary CCU admissions for emergency room patients with acute chest pain.
May reduce unnecessary CCU admissions in acute chest pain; leaves open prospective validation before practice change.
A simple algorithm, which improves the diagnostic performance in patients arriving with acute chest pain in the emergency room, has been developed. The algorithm is solely based on information immediately available to the physician and includes elements from ECG, clinical findings and case history. As postulated, a stepwise use of all these variables improved the diagnostic accuracy and reduced the false positive cardiac-care unit (CCU) referral rate in a prospective study of 1450 patients admitted with acute chest pain. Compared to previous hospital practice during a preceding control period, sensitivity in diagnosing patients with unstable ischaemic heart diseases increased from 86% to 94% (P < 0.01), and specificity increased from 44% to 56% (P < 0.001). Accordingly, accuracy increased from 67% to 81% (P < 0.001), and false positive CCU-admission rate decreased from 35% to 19%. The greatest improvement in physician's diagnostic decisions was observed among patients without clear-cut signs of acute ischaemic heart disease on admission.
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Rollag et al. (1992) studied this question.
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