Evaluation of the discrepancy between clinical diagnostic hypotheses and anatomopathological diagnoses resulting from autopsies

Clinics (Sao Paulo). 2019:74:e1197. doi: 10.6061/clinics/2019/e1197. Epub 2019 Sep 16.

Abstract

Objectives: An objective of clinical autopsies is to determine the final cause of death and the pathological changes that may have triggered it. Despite advances in Medicine, the level of discrepancy between clinical and autopsy diagnoses remains significant. The aim of this study was to compare the data obtained from autopsies carried out at the São Bernardo do Campo/SP Death Verification Section with clinical diagnostic hypotheses proposed during medical care.

Method: This was a retrospective study involving the comparison of necroscopic reports issued by the São Bernardo do Campo/São Paulo Death Verification Section in 2014 and 2015 and the Cadaver Referral Guides completed by attending physicians prior to the necroscopic examination.

Results: A total of 465 cases were analyzed. In general, discrepancies between the clinical diagnostic hypothesis and the autopsy diagnosis occurred in 28% of the cases. A logistic regression model, with diagnostic discrepancy as a response variable and sex, age, duration of care, type of institution providing medical care and organ system as explanatory variables, was fit to the data; the results indicated that all explanatory variables with the exception of organ system are not significant (p>0.132).

Conclusions: Discrepancies between clinical diagnostic hypotheses and autopsy diagnoses continue to occur, despite new developments in complementary examinations and therapies. The odds of a discrepancy when patients present with diseases of the cardiac system are greater than those when there are problems in the vascular, endocrine and neurological systems.

MeSH terms

  • Adolescent
  • Adult
  • Age Factors
  • Aged
  • Autopsy / statistics & numerical data*
  • Cause of Death
  • Child
  • Child, Preschool
  • Diagnostic Errors / statistics & numerical data*
  • Duration of Therapy
  • Female
  • Humans
  • Infant
  • Logistic Models
  • Male
  • Middle Aged
  • Reference Values
  • Retrospective Studies
  • Time Factors
  • Young Adult