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      Development and validation of a novel computer-aided score to predict the risk of in-hospital mortality for acutely ill medical admissions in two acute hospitals using their first electronically recorded blood test results and vital signs: a cross-sectional study

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          Abstract

          Objectives

          There are no established mortality risk equations specifically for emergency medical patients who are admitted to a general hospital ward. Such risk equations may be useful in supporting the clinical decision-making process. We aim to develop and externally validate a computer-aided risk of mortality (CARM) score by combining the first electronically recorded vital signs and blood test results for emergency medical admissions.

          Design

          Logistic regression model development and external validation study.

          Setting

          Two acute hospitals (Northern Lincolnshire and Goole NHS Foundation Trust Hospital (NH)—model development data; York Hospital (YH)—external validation data).

          Participants

          Adult (aged ≥16 years) medical admissions discharged over a 24-month period with electronic National Early Warning Score(s) and blood test results recorded on admission.

          Results

          The risk of in-hospital mortality following emergency medical admission was 5.7% (NH: 1766/30 996) and 6.5% (YH: 1703/26 247). The C-statistic for the CARM score in NH was 0.87 (95% CI 0.86 to 0.88) and was similar in an external hospital setting YH (0.86, 95% CI 0.85 to 0.87) and the calibration slope included 1 (0.97, 95% CI 0.94 to 1.00).

          Conclusions

          We have developed a novel, externally validated CARM score with good performance characteristics for estimating the risk of in-hospital mortality following an emergency medical admission using the patient’s first, electronically recorded, vital signs and blood test results. Since the CARM score places no additional data collection burden on clinicians and is readily automated, it may now be carefully introduced and evaluated in hospitals with sufficient informatics infrastructure.

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          Most cited references25

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          The meaning and use of the area under a receiver operating characteristic (ROC) curve.

          A representation and interpretation of the area under a receiver operating characteristic (ROC) curve obtained by the "rating" method, or by mathematical predictions based on patient characteristics, is presented. It is shown that in such a setting the area represents the probability that a randomly chosen diseased subject is (correctly) rated or ranked with greater suspicion than a randomly chosen non-diseased subject. Moreover, this probability of a correct ranking is the same quantity that is estimated by the already well-studied nonparametric Wilcoxon statistic. These two relationships are exploited to (a) provide rapid closed-form expressions for the approximate magnitude of the sampling variability, i.e., standard error that one uses to accompany the area under a smoothed ROC curve, (b) guide in determining the size of the sample required to provide a sufficiently reliable estimate of this area, and (c) determine how large sample sizes should be to ensure that one can statistically detect differences in the accuracy of diagnostic techniques.
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            Two further applications of a model for binary regression

            D R Cox (1958)
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              • Abstract: found
              • Article: not found

              Validation of the National Early Warning Score in the prehospital setting.

              Early intervention and response to deranged physiological parameters in the critically ill patient improves outcomes. A National Early Warning Score (NEWS) based on physiological observations has been developed for use throughout the National Health Service (NHS) in the UK. Although a good predictor of mortality and deterioration in inpatients, its performance in the prehospital setting is largely untested. This study aimed to assess the validity of the NEWS in unselected prehospital patients.
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                Author and article information

                Journal
                BMJ Open
                BMJ Open
                bmjopen
                bmjopen
                BMJ Open
                BMJ Publishing Group (BMA House, Tavistock Square, London, WC1H 9JR )
                2044-6055
                2018
                6 December 2018
                : 8
                : 12
                : e022939
                Affiliations
                [1 ] departmentFaculty of Health Studies , University of Bradford , Bradford, UK
                [2 ] Bradford Institute for Health Research , Bradford, UK
                [3 ] departmentSchool of Clinical Therapies , University College Cork , Cork, Ireland
                [4 ] departmentDepartment of Renal Medicine , York Teaching Hospital NHS Foundation Trust Hospital , York, UK
                [5 ] York Teaching Hospital NHS Foundation Trust Hospital , York, UK
                [6 ] departmentDepartment of Strategy and Planning , Northern Lincolnshire and Goole NHS Foundation Trust , Scunthorpe, UK
                [7 ] Northern Lincolnshire and Goole NHS Foundation Trust , Scunthorpe, UK
                [8 ] departmentSchool of Health and Social Work , University Of Hull , Hull, UK
                Author notes
                [Correspondence to ] Dr Mohammed A Mohammed; m.a.mohammed5@ 123456bradford.ac.uk
                Article
                bmjopen-2018-022939
                10.1136/bmjopen-2018-022939
                6286481
                30530474
                e6fe0b42-3572-4827-b4bf-bd8c96654fd9
                © Author(s) (or their employer(s)) 2018. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.

                This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.

                History
                : 15 March 2018
                : 24 September 2018
                : 16 October 2018
                Categories
                Health Services Research
                Research
                1506
                1704
                Custom metadata
                unlocked

                Medicine
                computer aided risk score,hospital mortality,vital signs and blood test,national early warning score,emergency admission

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