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Clinical decision making and laparoscopy versus computer prediction in the management of the acute abdomen

Clinical decision making and laparoscopy versus computer prediction in the management of the acute abdomen

British Journal of Surgery 76(10): 1011-1013

A prospective study has been undertaken of 321 patients with acute abdominal pain admitted to hospital under one surgical firm over a period of 21 months. During the first 10 months patients were classified on admission according to the perceived need for operation, with laparoscopy being performed on all those in whom the need for operation was uncertain. In addition, all women with suspected appendicitis underwent laparoscopy because previous studies by us and others have demonstrated a high error rate in this group. During the second 11 months of the study a similar system of classification and procedure was used but the patient's initial assessment was entered on a structured data sheet. After the patient had been discharged home this information was entered into a computer-aided diagnosis program. Hypothetical retrospective computer-aided decisions were then made about patient management. The final management error rate (correct decision to operate or not) was compared with the actual error rate using the clinical system. The final overall error rate in the first 10 months was 11 out of 163 patients and this was improved to 3 out of 158 in the second 11 months of the study by the addition of the structured data sheet to selective laparoscopy. A management policy based entirely on diagnostic probabilities taken from the computer-aided diagnosis program would have produced an error rate of 26 out of 158. We conclude that in the management of the acute abdomen a policy based on clinical decision combined with selective laparoscopy may be superior to one based on diagnostic probabilities alone. Further improvement in results follows the introduction of a structured data sheet for initial data collection.

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Accession: 039569711

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PMID: 2532048

DOI: 10.1002/bjs.1800761007

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