A prospective study of mortality associated with anaesthesia and surgery: risk indicators of mortality in hospital
| Autor: | E. Henriksen, K. Eliasen, T. Pedersen |
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| Rok vydání: | 1990 |
| Předmět: |
Adult
Male medicine.medical_specialty Time Factors Comorbidity Postoperative Complications Sex Factors Risk Factors Cause of Death Epidemiology medicine Humans Anesthesia Prospective Studies Myocardial infarction Risk factor Intraoperative Complications Prospective cohort study Aged Cause of death Aged 80 and over business.industry Incidence Mortality rate Incidence (epidemiology) Age Factors General Medicine Middle Aged medicine.disease Surgery Hospitalization Anesthesiology and Pain Medicine Surgical Procedures Operative Female business |
| Zdroj: | Acta Anaesthesiologica Scandinavica. 34:176-182 |
| ISSN: | 1399-6576 0001-5172 |
| Popis: | The aims of this study were to: 1) determine the incidences and causes of mortality associated with anaesthesia and surgery, 2) identify important factors associated with mortality in hospital, and 3) estimate the mortality risk associated with anaesthesia and surgery when a combination of risk factors are present. A total of 7306 anaesthetized patients undergoing abdominal, urological, gynaecological, or orthopaedic surgery were included in the study. Of these, 0.05% (1:1800) died during anaesthesia, 0.1% (1:730) during the recovery period, and the overall mortality rate in hospital was 1.2% (1:81). Most deaths occurred in the elderly (greater than or equal to 70 years of age) and were unavoidable due to progression of the presenting condition, such as advanced cancer, or co-existing diseases such as cardiopulmonary or renal failure. Of the patients who developed myocardial infarction (MI) following anaesthesia, 67% (8/12) died in the postoperative period. Half of the MI patients who died received regional anaesthesia, and in addition suffered from periods of cardiovascular dysfunction intraoperatively. By utilizing logistic regression analysis, a model for prediction of mortality risk was developed. The model included five significant preoperative predictive variables: age; patients with history of chronic heart disease, and renal disease; emergency surgery; and the type of operation. With this model it is possible to distinguish between patients with very different mortality risks. |
| Databáze: | OpenAIRE |
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