Vital signs are routinely measured from patients presenting to the emergency department (ED), but how they predict clinical outcomes like hospitalization is unclear.
To evaluate how pulse, respiratory rate, temperature, and mean arterial pressure (MAP) at ED presentation predicted probability of hospitalization, transfer to another center, or death in the ED (as a composite outcome) vs. other ED dispositions (discharged, eloped, and sent to observation or labor and delivery), and to assess the performance of different modeling strategies, specifically, models including flexible forms of vital signs (as restricted cubic splines) vs. linear forms (untransformed numeric variables) vs. binary transformations (vital signs values categorized simply as normal or abnormal).
We analyzed the data of 12,660 adults presenting for medical illnesses to the ED at the University of California, San Francisco Medical Center, San Francisco, California, throughout 2014. We used flexible forms of vital signs data at presentation (pulse, temperature, respiratory rate, and MAP) to predict ED disposition (admitted, transferred, or died, vs. other ED dispositions) and to guide binary transformation of vital signs. We compared performance of models including vital signs as flexible terms, binary transformations, or linear terms.
A model including flexible forms of vital signs and age to predict the outcome had good calibration and moderate discrimination (C-statistic = 71.2, 95% confidence interval [CI] 70.0–72.4). Binary transformation of vital signs had minimal impact on performance (C-statistic = 71.3, 95% CI 70.2–72.5). A model with linear forms was less calibrated and had slightly reduced discrimination (C-statistic = 70.3, 95% CI 69.1–71.5).
Findings suggest that flexible modeling of vital signs may better reflect their association with clinical outcomes. Future studies to evaluate how vital signs could assist clinical decision-making in acute care settings are suggested.
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- Effect of vital signs on advanced life support interventions for prehospital patients.Prehosp Emerg Care. 1997; 1: 145-148
- Vital signs in hospital patients: a systematic review.Int J Nurs Stud. 2001; 38: 643-650
- Description of vital signs data measurement frequency in a medical/surgical unit at a community hospital in United States.Data Brief. 2018; 16: 612-616
- Standards for frequency of measurement and documentation of vital signs and physical assessments.Crit Care Nurse. 2010; 30: 74-76
- Clinical relevance of routinely measured vital signs in hospitalized patients: a systematic review.J Nurs Scholarsh. 2014; 46: 39-49
- Abnormal vital signs are strong predictors for intensive care unit admission and in-hospital mortality in adults triaged in the emergency department - a prospective cohort study.Scand J Trauma Resusc Emerg Med. 2012; 20: 28
- Effect of vital signs on triage decisions.Ann Emerg Med. 2002; 39: 223-232
- Evaluation of the patient with acute chest pain.Radiol Clin North Am. 2010; 48: 745-755
- How vital are the vital signs? A multi-center observational study from emergency departments of Pakistan.BMC Emerg Med. 2015; 15: S10
- Predictive value of initial triage vital signs for critically ill older adults.West J Emerg Med. 2013; 14: 453-460
- Prognosis and risk factors for deterioration in patients admitted to a medical emergency department.PLoS One. 2014; 9: e94649
- Effect of advanced age and vital signs on admission from an ED observation unit.Am J Emerg Med. 2013; 31: 1-7
- The prevalence and significance of abnormal vital signs prior to in-hospital cardiac arrest.Resuscitation. 2016; 98: 112-117
- The association between vital signs and mortality in a retrospective cohort study of an unselected emergency department population.Scand J Trauma Resusc Emerg Med. 2016; 24: 21
- A simple prognostic index based on admission vital signs data among patients with sepsis in a resource-limited setting.Crit Care. 2015; 19: 86
- Rapid Emergency Medicine Score: a novel prognostic tool for predicting the outcomes of adult patients with hepatic portal venous gas in the emergency department.PLoS One. 2017; 12: e0184813
- Rapid Emergency Medicine score: a new prognostic tool for in-hospital mortality in nonsurgical emergency department patients.J Intern Med. 2004; 255: 579-587
- Clinical pathway improves pediatrics asthma management in the emergency department and reduces admissions.J Asthma. 2015; 52: 806-814
- Multivariable prognostic models: issues in developing models, evaluating assumptions and adequacy, and measuring and reducing errors.Stat Med. 1996; 15: 361-387
- Formula and nomogram for the sphygmomanometric calculation of the mean arterial pressure.Heart. 2000; 84: 64
- Using and interpreting restricted cubic splines.Institut für Soziologie, Eberhard Karls Universität Tübingen, Tübingen, Germany2009
- Predictive margins and marginal effects in Stata 11th German Stata Users group meeting.University of Potsdam, Potsdam, Germany2013
- Interpreting the concordance statistic of a logistic regression model: relation to the variance and odds ratio of a continuous explanatory variable.BMC Med Res Methodol. 2012; 12: 82
- Derivation and validation of a universal vital assessment (UVA) score: a tool for predicting mortality in adult hospitalised patients in sub-Saharan Africa.BMJ Glob Health. 2017; 2: e000344
- Association of body temperature and antipyretic treatments with mortality of critically ill patients with and without sepsis: multi-centered prospective observational study.Crit Care. 2012; 16: R33
- Task shifting: the use of laypersons for acquisition of vital signs data for clinical decision making in the emergency room following traumatic injury.World J Surg. 2017; 41: 3066-3073
- Emergency department visits for nonurgent conditions: systematic literature review.Am J Manag Care. 2013; 19: 47-59
- The APACHE III prognostic system. Risk prediction of hospital mortality for critically ill hospitalized adults.Chest. 1991; 100: 1619-1636
- Monitoring vital signs: development of a modified early warning scoring (MEWS) system for general wards in a developing country.PLoS One. 2014; 9: e87073
- Automated analysis of vital signs to identify patients with substantial bleeding before hospital arrival: a feasibility study.Shock. 2015; 43: 429-436
- The comparison of modified early warning score with rapid emergency medicine score: a prospective multicentre observational cohort study on medical and surgical patients presenting to emergency department.Emerg Med J. 2014; 31: 476-481
- The impact of emergency department observation units on United States emergency department admission rates.J Hosp Med. 2015; 10: 738-742
Published online: January 13, 2020
Accepted: November 10, 2019
Received in revised form: October 28, 2019
Received: April 27, 2019
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