
The autopsy has long been regarded as an important tool for clinical confrontation, education and quality assurance. The aims of this study were to examine the correlation between the clinical diagnosis and autopsy findings in adult patients who died in an intensive care unit (ICU) and to identify the types of errors in diagnosis to improve quality of care. Autopsies from 289 patients who died in the ICU during a 2-year period were studied. Post-mortem examination revealed unexpected findings in 61 patients (21%) including malignancy, pulmonary embolism, aspergillosis, myocardial or mesenteric infarction and unsuspected bacterial, viral or fungal infection. These unexpected findings were classified as Goldman class I errors in 17 (6%), class II in 38 (13%) and class III in six (2%) cases. Although the incidence of unexpected findings with clinical significance was low, post-mortem examination remains a valuable source of pertinent information that may improve the management of ICU patients.
Adult, Aged, 80 and over, Male, Diagnostic Errors -- statistics & numerical data, Diagnostic discrepancy, Reproducibility of Results, Sciences bio-médicales et agricoles, Post-mortem examination, Middle Aged, Intensive Care Units, Intensive Care Units -- statistics & numerical data, Intensive care, Cause of Death, 80 and over, Humans, Female, Autopsy, Diagnostic Errors, Aged
Adult, Aged, 80 and over, Male, Diagnostic Errors -- statistics & numerical data, Diagnostic discrepancy, Reproducibility of Results, Sciences bio-médicales et agricoles, Post-mortem examination, Middle Aged, Intensive Care Units, Intensive Care Units -- statistics & numerical data, Intensive care, Cause of Death, 80 and over, Humans, Female, Autopsy, Diagnostic Errors, Aged
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| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
