Evidence map›Paper›PMID 18925315›Full record

ArticleClinics (Sao Paulo, Brazil)2008

Clinico-pathological discrepancies in a general university hospital in São Paulo, Brazil.

Fabiana Kotovicz, Thais Mauad, Paulo H N Saldiva

Abstract readComparative Study
In one paragraph

Article in Clinics (Sao Paulo, Brazil), 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

14 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  10. NHETS - Necropsy Heart Transplantation Study.Arquivos brasileiros de cardiologia · 2014
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors.

Fabiana KotoviczLaboratory of Air Pollution, Department of Pathology, Faculdade de Medicina, Universidade de São Paulo, São Paulo, SP, Brazil.
Thais Mauad
Paulo H N Saldiva

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionThe autopsy rate has continuously diminished over the past few decades, reducing the quality of medical care and the accuracy of statistical health data.

objectiveTo assess the accuracy of clinical diagnoses by comparing pre- and postmortem findings, and to identify potential risk factors for misdiagnoses.

methodsRetrospective evaluations performed between June 2001 and June 2003 in a 2,500-bed tertiary university hospital in São Paulo, Brazil, including 288 patients who died at that institution and had a postmortem examination.

resultsClinical and autopsy records were reviewed and compared for categorization using the adapted Goldman criteria. The overall major and minor discrepancy rates were 16.3% and 28.1%, respectively. The most common missed diagnoses were pulmonary embolism, pneumonia, and myocardial infarction, and the most prevalent underlying diseases were infectious diseases, cerebro-cardiovascular conditions, and malignancies. Patients age 60 or older had an increased risk of diagnostic disagreement, as did female patients. The period of hospitalization, last admission unit at the hospital and underlying disease were not significantly related to the pre-mortem diagnostic accuracy. DISCUSSION: The discrepancy rate found in this study is similar to those reported globally. The factors influencing diagnostic accuracy as well as the most commonly missed diagnoses are also consistent with the literature.

conclusionAutopsy remains a crucial tool for improving medical care, and effort must be focused on increasing its practice worldwide.

Indexed as

Cause of DeathAdolescentAdultAgedAged, 80 and overAutopsyBrazilCerebrovascular DisordersChildChild, PreschoolCommunicable DiseasesCross-Sectional StudiesDiagnostic ErrorsFemaleHospitals, UniversityHumans

Identifiers

PMID18925315
PMCPMC2664713

What OpenQuestion holds

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.