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Year : 2013  |  Volume : 3  |  Issue : 3  |  Page : 63-67

Major discrepancies between clinical and postmortem diagnoses in critically ill cancer patients: Is autopsy still useful?

Division of Pulmonary, Critical Care and Sleep Medicine, Wayne State University School of Medicine, Detroit, Michigan, USA

Correspondence Address:
Ayman O Soubani
Division of Pulmonary, Critical Care and Sleep Medicine, 3990 John R 3 Hudson, Detroit, MI 48201
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/2231-0770.118460

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Objective: Describe the major discrepancies between the clinical and postmortem findings in critically ill cancer patients admitted to the medical intensive care unit (MICU). Materials and Methods: Retrospectively review of the medical records of all cancer patients who were admitted to the MICU and underwent postmortem examination over 6 year period. The records were reviewed for demographics, Acute Physiology and Chronic Health Evaluation (APACHE) II score, clinical cause of death, and postmortem findings. Results: There were 70 patients who had complete medical records. Mean age was 54.7 years (standard deviation (SD) ±14.8 years). Twenty-six patients had hematopoeitic stem cell transplantation (group I), 21 patients had hematological malignancies (group II), and 23 patients had solid malignancies (group III). The APACHE II score on admission to the MICU was 24.2 ± 8.0. Sixty-seven patients were mechanically ventilated, and the MICU stay was (mean ± SD) 9.0 ± 11.6 days. Major discrepancies between the clinical and postmortem diagnoses (Goldman classes I and II) were detected in 15 patients (21%). The most common missed diagnoses were aspergillosis, pulmonary embolism, and cancer recurrence. There were no differences between groups regarding the rate of major discrepancies. Conclusion: Despite the advances in the diagnosis and treatment of critically ill cancer patients, autopsies continue to show major discrepancies between the clinical and postmortem diagnoses. Autopsy is still useful in this patient population.

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