SynthesisIntensive care medicine2024
Clinical vs. autopsy diagnostic discrepancies in the intensive care unit: a systematic review and meta-analysis of autopsy series.
Synthesis in Intensive care medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.
What it found
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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.
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.
Who cites it
7 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Pooled it
- Computed Tomography Yield and Predictors of Pulmonary Embolism in Mechanically Ventilated Patients-A Retrospective Study.Acta anaesthesiologica Scandinavica · 2026Article
- Major discrepancy between clinical and autopsy diagnosis: a descriptive single-center analysis and its implications for the South African public health system.Frontiers in medicine · 2026Article
- Exploring the dark side of the moon: diagnostic errors in critically ill patients.Intensive care medicine · 2025Article
- Clinical Significance ofJournal of intensive care medicine · 2025Article
- Modernizing autopsy practices in the ICU to advance critical care diagnostics-authors' response.Intensive care medicine · 2025Article
- Modernizing autopsy practices in the ICU to advance critical care diagnostics.Intensive care medicine · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeThe aim of this study was to assess whether there is a discrepancy between clinical and autopsy-based diagnoses in adult intensive care unit (ICU) patients.
methodsWe conducted a systematic review of cohort studies reporting on conventional autopsy-confirmed missed diagnoses. The discrepancy rate was per study calculated by dividing the number of patients with a missed diagnosis by the number of autopsies. Missed diagnoses were classified according to the Goldman classification as 'major' and 'minor' with major missed diagnoses further differentiated into Class I missed diagnoses (i.e., diagnoses that may have altered therapy or survival) and Class II missed diagnoses (i.e., diagnoses that would not have altered therapy or survival). Class I missed diagnoses constitute the primary outcome of interest. Pooled estimates for discrepancy rates (95% confidence intervals) were calculated using a mixed-effects logistic regression model with 'study' as random effect. Meta-regression was used to assess relationships between major discrepancy rates and autopsy rates, start year of study, and ICU type.
resultsForty-two studies were identified totaling 6305 analyzed autopsies and 1759 patients with missed diagnoses. The pooled discrepancy rates for Class I and major missed diagnoses were 6.5% (5-8.5) and 19.3% (15.3-24), respectively. Meta-regression analysis revealed that autopsy rate was inversely associated with discrepancy rate. Class I discrepancy rates did not change over time. Burn and trauma ICUs had lower discrepancy rates as compared to medical ICUs, possibly because of higher autopsy rates.
conclusionsMissed diagnoses remain common in ICUs. A higher autopsy rate does not reveal more major diagnostic errors. These data support a clinically driven autopsy policy rather than a systematic autopsy policy.
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Identifiers
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Registered trials
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.