Discussion

We found that the accuracy of NEWS in predicting death within 1 and 7 days decreased as patients’ age increased. We also found that the risk of death for patients over 65 years of age was statistically significantly higher when the value of NEWS exceeded seven for 1-day mortality and four for 7-day mortality compared with patients under 65 years of age. Adding age as a three-category parameter to NEWS improved its predictive performance for 1 and 7 day mortalities when assessed with cNRI. In the multivariate logistic regression model, single NEWS parameters had an uneven effect on the prediction of mortality.

Omission of age as a parameter from the original NEWS seems somewhat confusing. It is mentioned as a parameter considered to be included in both the first and second editions based on the knowledge that older age increases risk of death,1 12 but the only in-hospital study reference given as an explanation13 actually promotes age as a component of an EWS. To the best of our knowledge, there are no prehospital studies regarding the effect of age on NEWS and only one recent study evaluates the addition of age as a parameter to NEWS to improve its predictive performance.18 This study demonstrated an improved prediction of in-hospital mortality.

De Groot et al found out that a number of early warning scores (EWSs) including NEWS performed worse in patients aged 70 years or over than in younger patients in predicting in-hospital mortality of ED sepsis patients.19 Jarvis et al have also explored the comparability of mortality prediction in different EWSs.20 In this study, removing age as a parameter decreased the predictive performance of the EWSs incorporating age, although it made them more comparable to EWSs using solely vital sign data. Two studies21 22 have compared the predictive performance of NEWS when recorded in a prehospital environment and on arrival to ED. Of these, the study by Mitsunaga et al focused specifically on older adult patients. In their study, the endpoints were admission to hospital and in-hospital mortality. For both, the AUC was significantly lower than what we present here for 1 and 7 day mortalities. In addition to these, we were able to find only two studies23 24 evaluating the predictive performance of EWSs in older adult patients, neither of which are from prehospital cohorts.

Frailty is considered as a superior outcome predictor compared with chronological age in older adults, but as Aguayo et al point out, there is currently no golden standard for measuring frailty. The different frailty scales cannot be compared due to differing concepts and diagnostic accuracy.11 They suggest preferring a multimodal scale, which would be cumbersome to use in an EWS context, especially in emergency care. Thus, even though chronologic age does not strictly correlate with medical fitness of a specific patient, on a population level, older age still is strongly associated with increased disease burden, use of medications possibly altering physiological measurements (eg, beta blockers) and lower physiological reserves for recovering from critical illness. Decisions limiting the older patients outside the most invasive and intensive interventions might also partly explain the results of improved performance in predicting 1- and 7-day mortality.

Even though the cut-offs for age groups used in our study might not be optimal or fully generalisable to all populations, as their risk stratification weight could differ in different societies and clinical environments, our data suggest that age is a significant determinant of outcome and can be used to improve a physiological scoring system. As demonstrated in figure 2, the age groups based on previous studies seemed to fit well with the changes in risk of death observed for this prehospital cohort: the risk of death increases up to around 65 years, stays constant for up to around 80–85 years and then starts to increase rapidly.

Our data support de Groot et al, 19 who showed that predictive performance of NEWS is reduced in older in-hospital patients. Our results are also in agreement with recent study by Lee et al,18 which shows that age as an additional parameter in NEWS significantly improved the in-hospital mortality prediction based on NEWS calculated at admission. Even though in-hospital mortality is a suboptimal outcome measure for performance of NEWS, as it is best suited to detect short timescale mortality, the study still supports the rationale of using age as a parameter to improve the predictive ability of an EWS. Optimally, this would also improve the ability of NEWS to identify patients who are likely to benefit from treatment from those who are likely to die despite active efforts.

We used cNRI and LRT to analyse the improvement in diagnostic performance when adding age as an additional parameter to NEWS, as AUROC is suboptimal for detecting small improvements when modifying already well-performing models. Both cNRI and LRT also have their issues. cNRI improvement may not be easy to determine, while LRT p-values should be interpreted with regard to the large sample size. As shown in table 2, the overall performance of the model improved, and the new model had a better ability to predict death when the score value increased. According to the groupwise cNRI data, the new model decreased the ability to correctly detect true negatives and thus reduced specificity; this was overcome by an even stronger performance in correctly detecting mortalities thus increasing sensitivity. The reduced specificity is caused by surviving older patients receiving higher total scores but compensated in the overall model performance as older patients are also more likely to die. Increased maximum score due to an additional parameter should be taken into account and if the risk strata are to be used, they need to be modified accordingly.

The data regarding varying ORs for mortality for different parameters in the three age groups are intriguing. For example, for the youngest age group, a disturbance in level of consciousness seemed to be less hazardous. Reasons for lowered level of consciousness are likely to differ between the age groups, but this could also reflect the reduced capacity of older adults to overcome such significant medical issues that result in lowered consciousness. Interestingly, HR did not seem to predict 1-day or 7-day mortality to any degree in any of the age groups in our study population.

There were limitations in this study. This is a retrospective analysis of a prehospital patient cohort in just one developed country in one geographical area. Thus, it likely does not fully represent the global perspective in regard of, for example, the age limits used for risk stratification. There is also a high risk of selection bias as at the time of data collection there was no EMS protocol requiring input of all required data to the electronic patient record system and a significant proportion of the patients encountered were excluded from the study based on missing vital signs and due to this, a large majority of the patients encountered by EMS were excluded from the study. We were also unable to exclude patients with DNAR orders, which may have altered these patients’ treatment priorities and outcomes, as these data were not available in a structured form in the EMS patient records. Specifically, DNAR orders may have affected a larger proportion of the older age groups and thus increased mortality in these subgroups. The limitations and possible sources of bias are further discussed in our previous publication from the same patient cohort.4 As this was a post-hoc analysis of existing data, no power calculations were performed for this specific research question. Thus, despite the large study cohort, the study might not have been powered to achieve statistical significance in the performed analyses.

On the other hand, the strengths of the study include a large study cohort, data accuracy through electronic patient records and linking to mortality via patient specific national identity number. Performing the study in a prehospital environment also gives access to data from patients that have received no treatments altering their vital signs. These data were also collected from a single EMS system, which is likely to further improve data quality.

Future studies should include confirming these results in another cohort. Further work into determining the optimal age groups for risk stratification should also be conducted. Age should be reconsidered as an additional parameter for NEWS, as it improves the predictive performance without significantly increasing its complexity, as age of the patient can be easily automatically extracted from electronic patient record systems. It is still unsolved whether current NEWS parameter scoring thresholds are optimal and what are the optimal parameters. As shown in the current study, HR did not seem to contribute to mortality prediction.

In conclusion, these results demonstrate that NEWS does not work similarly in mortality prediction of the prehospital patients older than 65 years, as their risk of death is higher than the younger patients at similar NEWS values. We suggest confirming these results in other patient populations and to consider age as an additional parameter in possible future revisions of NEWS. Meanwhile, prehospital clinicians should take into account the increased risk of death at similar scores in the older patients when assessing NEWS values of these patients.