48
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Comparing In-Hospital Mortality Prediction by Senior Emergency Resident's Judgment and Prognostic Models in the Emergency Department

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Background

          A comparison of emergency residents' judgments and two derivatives of the Sequential Organ Failure Assessment (SOFA), namely, the mSOFA and the qSOFA, was conducted to determine the accuracy of predicting in-hospital mortality among critically ill patients in the emergency department (ED).

          Methods

          A prospective cohort research was performed on patients over 18 years of age presented to the ED. We used logistic regression to develop a model for predicting in-hospital mortality by using qSOFA, mSOFA, and residents' judgment scores. We compared the accuracy of prognostic models and residents' judgment in terms of the overall accuracy of the predicted probabilities (Brier score), discrimination (area under the ROC curve), and calibration (calibration graph). Analyses were carried out using R software version R-4.2.0.

          Results

          In the study, 2,205 patients with median age of 64 (IQR: 50-77) years were included. There were no significant differences between the qSOFA (AUC 0.70; 95% CI: 0.67-0.73) and physician's judgment (AUC 0.68; 0.65-0.71). Despite this, the discrimination of mSOFA (AUC 0.74; 0.71-0.77) was significantly higher than that of the qSOFA and residents' judgments. Additionally, the AUC-PR of mSOFA, qSOFA, and emergency resident's judgments was 0.45 (0.43-0.47), 0.38 (0.36-0.40), and 0.35 (0.33-0.37), respectively. The mSOFA appears stronger in terms of overall performance: 0.13 vs. 0.14 and 0.15. All three models showed good calibration.

          Conclusion

          The performance of emergency residents' judgment and the qSOFA was the same in predicting in-hospital mortality. However, the mSOFA predicted better-calibrated mortality risk. Large-scale studies should be conducted to determine the utility of these models.

          Related collections

          Most cited references46

          • Record: found
          • Abstract: not found
          • Article: not found

          Comparing the Areas under Two or More Correlated Receiver Operating Characteristic Curves: A Nonparametric Approach

            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Assessing the performance of prediction models: a framework for traditional and novel measures.

            The performance of prediction models can be assessed using a variety of methods and metrics. Traditional measures for binary and survival outcomes include the Brier score to indicate overall model performance, the concordance (or c) statistic for discriminative ability (or area under the receiver operating characteristic [ROC] curve), and goodness-of-fit statistics for calibration.Several new measures have recently been proposed that can be seen as refinements of discrimination measures, including variants of the c statistic for survival, reclassification tables, net reclassification improvement (NRI), and integrated discrimination improvement (IDI). Moreover, decision-analytic measures have been proposed, including decision curves to plot the net benefit achieved by making decisions based on model predictions.We aimed to define the role of these relatively novel approaches in the evaluation of the performance of prediction models. For illustration, we present a case study of predicting the presence of residual tumor versus benign tissue in patients with testicular cancer (n = 544 for model development, n = 273 for external validation).We suggest that reporting discrimination and calibration will always be important for a prediction model. Decision-analytic measures should be reported if the predictive model is to be used for clinical decisions. Other measures of performance may be warranted in specific applications, such as reclassification metrics to gain insight into the value of adding a novel predictor to an established model.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Prognostic Accuracy of the SOFA Score, SIRS Criteria, and qSOFA Score for In-Hospital Mortality Among Adults With Suspected Infection Admitted to the Intensive Care Unit.

              The Sepsis-3 Criteria emphasized the value of a change of 2 or more points in the Sequential [Sepsis-related] Organ Failure Assessment (SOFA) score, introduced quick SOFA (qSOFA), and removed the systemic inflammatory response syndrome (SIRS) criteria from the sepsis definition.
                Bookmark

                Author and article information

                Contributors
                Journal
                Biomed Res Int
                Biomed Res Int
                BMRI
                BioMed Research International
                Hindawi
                2314-6133
                2314-6141
                2023
                15 May 2023
                : 2023
                : 6042762
                Affiliations
                1Department of Medical Informatics, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
                2Department of Emergency Medicine, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
                3Pharmaceutical Research Center, Mashhad University of Medical Sciences, Mashhad, Iran
                4Department of Health Information Technology, Faculty of Paramedical Sciences, Mashhad University of Medical Sciences, Mashhad, Iran
                5Department of Medical Informatics, Amsterdam UMC Location University of Amsterdam, Netherlands
                Author notes

                Academic Editor: Patrizia Vizza

                Author information
                https://orcid.org/0000-0003-1168-7234
                https://orcid.org/0000-0003-4814-6327
                https://orcid.org/0000-0002-0355-6181
                https://orcid.org/0000-0002-6565-9493
                https://orcid.org/0000-0003-3755-1212
                https://orcid.org/0000-0003-4324-7954
                https://orcid.org/0000-0003-0617-9374
                Article
                10.1155/2023/6042762
                10202605
                37223337
                5fd5d6db-71ab-4125-ab0f-5e23e1e65320
                Copyright © 2023 Zahra Rahmatinejad et al.

                This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 22 February 2022
                : 26 September 2022
                : 20 October 2022
                Funding
                Funded by: Mashhad University of Medical Sciences
                Award ID: 941594
                Categories
                Research Article

                Comments

                Comment on this article

                scite_
                0
                0
                0
                0
                Smart Citations
                0
                0
                0
                0
                Citing PublicationsSupportingMentioningContrasting
                View Citations

                See how this article has been cited at scite.ai

                scite shows how a scientific paper has been cited by providing the context of the citation, a classification describing whether it supports, mentions, or contrasts the cited claim, and a label indicating in which section the citation was made.

                Similar content63

                Cited by7

                Most referenced authors681