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1st February 2022
Relevant vital sign cut off values used for the risk stratification and hence prognosis for patients attending an emergency department do not exist for some signs which has important implications for their use and interpretation. This was the conclusion of a large study by a team from the Emergency Department, Maxima Medical Centre, Veldhoven, The Netherlands.
An emergency department encounters a large number of sick patients who require quick evaluation to detect those who have serious medical problems and which might require hospital admission. This has led to the introduction of various triage tools such as the modified early warning score (MEWS) which serves as a rapid, simple triage method to identify medical patients in need of hospital admission and those at increased risk of in-hospital death. Other tools commonly used such as the quick sequential organ failure assessment (qSOFA) rely on the use of vital sign measurements and specify a cut-off for each vital sign to discriminate between a better or worse prognosis. However, the use of disease severity assessment tools may not be appropriate, particularly for elderly patients as revealed in one study of sepsis, which concluded that ‘prognostic and discriminative performance of the five most commonly used disease severity scores was poor and less useful for risk stratification of older ED sepsis patients.’
For the present study, the Dutch team looked to assess the association between vital signs and relevant clinical outcomes such as mortality and admission to an intensive care unit. In addition, they wanted to determine whether a single cut-off or threshold existed for each vital sign and the extent to which these were influenced by advancing age. They undertook an observational study at three EDs in the Netherlands and examined consecutive adult patients (18 years and older) where one or more of the following vital signs were measured: respiratory rate (RR), peripheral oxygen saturation (SpO2), systolic (SBP) and diastolic (DBP) blood pressure, mean arterial blood pressure (MAP), heart rate (HR) and temperature. Patients were stratified by age into three categories; 18 – 65, 66 – 80 and > 80 years and the primary outcome was whether there was a vital sign category that could be used as a cut-off to predict the outcome of in-hospital mortality or ICU admission.
A total of 101,416 patients with a mean age of 59.6 years (49.6% female) were included in their analysis. In many cases the vital sign values were outside of the usual range. For example, 23.4%, 79.1% and 14.2% of the total cohort had a RR, SBP and SP02 respectively, outside of the normal range. This proportion was also higher in older patients as seen for example with SBP for which 83.3% of patients aged > 80 had a reading outside of the normal range compared to 76.3% of those aged 18 to 65 years.
Among the cohort, a total of 2374 (2.3%) patients died. The adjusted odds ratios (aOR) for predicted mortality increased gradually with worsening values of SBP and SpO2 although there was no clear cut-off point for SBP, DBP, Sp02 and HR and mortality. In addition, for all vital signs, older adults had a larger increase in absolute mortality. For ICU admission, SBP had a relevant cut-off at 70mmHg and for MAP there was a threshold of < 60 mmHg.
In summarising their findings, the authors noted how in-hospital mortality increased gradually with decreasing SBP and SpO2 and there was no evidence of a specific cut-off for either vital sign. For DPB, MAP and HR, there was a quasi-U-shaped association with in-hospital mortality and while there was a single cut-off for MAP, RR and temperature, the authors argued that using a single cut-off value would ignore further increase of risk with more extreme values for these vital signs.
They concluded that the use of a single cut-off for each vital sign in acute care deserves scrutiny and that age-adjusted numerical scores would improve risk stratification since older patients have a larger increase in mortality with changing vital signs even after adjustment for confounds.
Candel BGJ et al. The association between vital signs and clinical outcomes in emergency department patients of different age categories Emerg Med J 2022
1st June 2021
The routine measurement of parameters such as body temperature, heart and respiration rate, although non-specific, are of value in the overall assessment of a patient’s general wellbeing. In addition to the assessment of physical signs, further information can be gathered from laboratory analysis of blood or urine. However, all of these evaluations require that the person attends a clinic appointment. In recent years, the development of wearable technology has enabled the measurement of some vital signs such as heart rate and temperature but there has been limited research into the value of this longitudinally collected data. Nevertheless, it is possible that wearable technology has the potential to provide useful data for managing health conditions. But in order to fully utilise the data captured by wearable devices, it is necessary to determine whether these data are able to accurately mirror the results obtained in a clinic. This was the idea behind a study by a team from the Department of Genetics, Stanford University, US, which set out to determine if the vital signs collected from a wearable device (wVS) could be used as a non-invasive proxy measurement of clinical laboratory data using models of the relationship between wVS and clinical labs.
A total of 54 participants with a mean age of 56 years (44% male) were monitored for an average of 3.3 years. The wearable device measured heart rate, skin temperature, accelerometery and electrodermal activity (EDA). This latter measurement of the electrical properties of the skin, can assess skin hydration. Using heart rate, the researchers found that the wVS recordings was identical to the clinic-based measurements (both 71 beats per minute). Using machine learning models, the researchers extended their work and observed a high correlation between changes in wVS data and haematocrit, red blood cell count, haemoglobin and platelet count. For example, a higher body temperature and lower levels of movement (as assessed by accelerometery) tended to indicate illness, which matched up with a higher white blood cell count.
Commenting on their findings, the authors suggested that the continuous data collected by a wVS could be used to detect deviations from normal and thus serve as a means of identifying the need for further clinical laboratory evaluation. Although more work needs to be done, these initial results suggest that wearable devices have the potential to assess clinical parameters that, at present, can only be measured in laboratories.
Dunn J et al. Wearable sensors enable personalised predictions of clinical laboratory measurements. Nat Med 2021