Predicting in-hospital mortality and unanticipated admissions to the intensive care unit using routinely collected blood tests and vital signs: development and validation of a multivariable model
<strong>Aim</strong> The National Early Warning System (NEWS) is based on vital signs; the Laboratory Decision Tree Early Warning Score (LDT-EWS) on laboratory test results. We aimed to develop and validate a new EWS (the LDTEWS:NEWS risk index) by combining the two and evaluating the d...
| Main Authors: | , , , , , , , |
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| Format: | Journal article |
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Elsevier
2018
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| _version_ | 1826285734569443328 |
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| author | Redfern, O Pimentel, M Prytherch, D Meredith, P Clifton, D Tarassenko, L Smith, G Watkinson, P |
| author_facet | Redfern, O Pimentel, M Prytherch, D Meredith, P Clifton, D Tarassenko, L Smith, G Watkinson, P |
| author_sort | Redfern, O |
| collection | OXFORD |
| description | <strong>Aim</strong> The National Early Warning System (NEWS) is based on vital signs; the Laboratory Decision Tree Early Warning Score (LDT-EWS) on laboratory test results. We aimed to develop and validate a new EWS (the LDTEWS:NEWS risk index) by combining the two and evaluating the discrimination of the primary outcome of unanticipated intensive care unit (ICU) admission or in-hospital mortality, within 24 hours. <p><strong>Methods</strong> We studied emergency medical admissions, aged 16 years or over, admitted to Oxford University Hospitals (OUH) and Portsmouth Hospitals (PH). Each admission had vital signs and laboratory tests measured within their hospital stay. We combined LDT-EWS and NEWS values using a linear time-decay weighting function imposed on the most recent blood tests. The LDTEWS:NEWS risk index was developed using data from 5 years of admissions to PH, and validated on a year of data from both PH and OUH. We tested the risk index’s ability to discriminate the primary outcome using the c-statistic.</p> <p><strong>Results</strong> The development cohort contained 97,933 admissions (median age = 73 years) of which 4,723 (4.8%) resulted in in-hospital death and 1,078 (1.1%) in unanticipated ICU admission. We validated the risk index using data from PH (n = 21,028) and OUH (n = 16,383). The risk index showed a higher discrimination in the validation sets (c-statistic value (95% CI)) (PH, 0.901 (0.898-0.905); OUH, 0.916 (0.911–0.921)), than NEWS alone (PH, 0.877 (0.873–0.882); OUH, 0.898 (0.893–0.904)).</p> <p><strong>Conclusions</strong> The LDTEWS:NEWS risk index increases the ability to identify patients at risk of deterioration, compared to NEWS alone.</p> |
| first_indexed | 2024-03-07T01:33:16Z |
| format | Journal article |
| id | oxford-uuid:944bc411-416b-4801-95ff-45d834cecf03 |
| institution | University of Oxford |
| last_indexed | 2024-03-07T01:33:16Z |
| publishDate | 2018 |
| publisher | Elsevier |
| record_format | dspace |
| spelling | oxford-uuid:944bc411-416b-4801-95ff-45d834cecf032022-03-26T23:38:25ZPredicting in-hospital mortality and unanticipated admissions to the intensive care unit using routinely collected blood tests and vital signs: development and validation of a multivariable modelJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:944bc411-416b-4801-95ff-45d834cecf03Symplectic Elements at OxfordElsevier2018Redfern, OPimentel, MPrytherch, DMeredith, PClifton, DTarassenko, LSmith, GWatkinson, P<strong>Aim</strong> The National Early Warning System (NEWS) is based on vital signs; the Laboratory Decision Tree Early Warning Score (LDT-EWS) on laboratory test results. We aimed to develop and validate a new EWS (the LDTEWS:NEWS risk index) by combining the two and evaluating the discrimination of the primary outcome of unanticipated intensive care unit (ICU) admission or in-hospital mortality, within 24 hours. <p><strong>Methods</strong> We studied emergency medical admissions, aged 16 years or over, admitted to Oxford University Hospitals (OUH) and Portsmouth Hospitals (PH). Each admission had vital signs and laboratory tests measured within their hospital stay. We combined LDT-EWS and NEWS values using a linear time-decay weighting function imposed on the most recent blood tests. The LDTEWS:NEWS risk index was developed using data from 5 years of admissions to PH, and validated on a year of data from both PH and OUH. We tested the risk index’s ability to discriminate the primary outcome using the c-statistic.</p> <p><strong>Results</strong> The development cohort contained 97,933 admissions (median age = 73 years) of which 4,723 (4.8%) resulted in in-hospital death and 1,078 (1.1%) in unanticipated ICU admission. We validated the risk index using data from PH (n = 21,028) and OUH (n = 16,383). The risk index showed a higher discrimination in the validation sets (c-statistic value (95% CI)) (PH, 0.901 (0.898-0.905); OUH, 0.916 (0.911–0.921)), than NEWS alone (PH, 0.877 (0.873–0.882); OUH, 0.898 (0.893–0.904)).</p> <p><strong>Conclusions</strong> The LDTEWS:NEWS risk index increases the ability to identify patients at risk of deterioration, compared to NEWS alone.</p> |
| spellingShingle | Redfern, O Pimentel, M Prytherch, D Meredith, P Clifton, D Tarassenko, L Smith, G Watkinson, P Predicting in-hospital mortality and unanticipated admissions to the intensive care unit using routinely collected blood tests and vital signs: development and validation of a multivariable model |
| title | Predicting in-hospital mortality and unanticipated admissions to the intensive care unit using routinely collected blood tests and vital signs: development and validation of a multivariable model |
| title_full | Predicting in-hospital mortality and unanticipated admissions to the intensive care unit using routinely collected blood tests and vital signs: development and validation of a multivariable model |
| title_fullStr | Predicting in-hospital mortality and unanticipated admissions to the intensive care unit using routinely collected blood tests and vital signs: development and validation of a multivariable model |
| title_full_unstemmed | Predicting in-hospital mortality and unanticipated admissions to the intensive care unit using routinely collected blood tests and vital signs: development and validation of a multivariable model |
| title_short | Predicting in-hospital mortality and unanticipated admissions to the intensive care unit using routinely collected blood tests and vital signs: development and validation of a multivariable model |
| title_sort | predicting in hospital mortality and unanticipated admissions to the intensive care unit using routinely collected blood tests and vital signs development and validation of a multivariable model |
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