SynthesisBMC infectious diseases2022
Clinical prediction models for diagnosis of COVID-19 among adult patients: a validation and agreement study.
Synthesis in BMC infectious diseases, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05582382 (Validation of Prognostic Clinical Risk Scores in Predicting Outcomes for Patients Diagnosed With COVID-19 During Initial Triage Assessment), which is not on this map. Cited by 3 papers.
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.
Validation of Prognostic Clinical Risk Scores in Predicting Outcomes for Patients Diagnosed With COVID-19 During Initial Triage Assessment
Who cites it
3 citing papers in PubMed.
- Conventional and Novel Diagnostic Tools for the Diagnosis of Emerging SARS-CoV-2 Variants.Vaccines · 2023Review
- Development of Clinical Risk Scores for Detection of COVID-19 in Suspected Patients During a Local Outbreak in China: A Retrospective Cohort Study.International journal of public health · 2022Article
- Guidelines for Triage of COVID-19 Patients Presenting With Multisystemic Symptoms.Quality management in health careReview
Corrections and comments
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Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundSince the beginning of the pandemic, hospitals have been constantly overcrowded, with several observed waves of infected cases and hospitalisations. To avoid as much as possible this situation, efficient tools to facilitate the diagnosis of COVID-19 are needed.
objectiveTo evaluate and compare prediction models to diagnose COVID-19 identified in a systematic review published recently using performance indicators such as discrimination and calibration measures.
methodsA total of 1618 adult patients present at two Emergency Department triage centers and for whom qRT-PCR tests had been performed were included in this study. Six previously published models were reconstructed and assessed using diagnostic tests as sensitivity (Se) and negative predictive value (NPV), discrimination (Area Under the Roc Curve (AUROC)) and calibration measures. Agreement was also measured between them using Kappa's coefficient and IntraClass Correlation Coefficient (ICC). A sensitivity analysis has been conducted by waves of patients.
resultsAmong the 6 selected models, those based only on symptoms and/or risk exposure were found to be less efficient than those based on biological parameters and/or radiological examination with smallest AUROC values (< 0.80). However, all models showed good calibration and values above > 0.75 for Se and NPV but poor agreement (Kappa and ICC < 0.5) between them. The results of the first wave were similar to those of the second wave.
conclusionAlthough quite acceptable and similar results were found between all models, the importance of radiological examination was also emphasized, making it difficult to find an appropriate triage system to classify patients at risk for COVID-19.
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