Abstract
OBJECTIVE
Dyspnea is a frequent yet potentially life-threatening complaint in emergency departments. This study aimed to compare the predictive accuracy of the National Early Warning Score and the Manchester Triage System for key clinical outcomes among dyspneic ED patients.
METHODS
We retrospectively analyzed 726 adult dyspneic patients presenting to a tertiary ED. Demographics, initial vital signs, MTS triage category, and calculated NEWS values were recorded at admission. Outcomes included hospital ward admission, intensive care unit admission, in-hospital mortality, 48-hour reattendance, and length of stay. Statistical analyses comprised chi-square, Kruskal–Wallis, and logistic regression models.
RESULTS
The mean age was 61.1 years, and 52.9% were female. Of the patients, 13.8% were admitted to wards, 3.2% to ICUs, and 2.3% died; 4.1% reattended within 48 hours. NEWS risk stratification strongly aligned with MTS categories (p<0.001). Higher NEWS scores were associated with older age, higher respiratory and pulse rates, lower blood pressure, and reduced oxygen saturation. NEWS independently predicted hospital admission (OR=4.47, p<0.001) and ICU admission (OR=1.94, p=0.001), whereas MTS predicted ICU admission (inverse association, OR=0.34, p<0.001) and mortality (OR=0.30, p<0.001).
CONCLUSION
NEWS more accurately predicted hospital and ICU admission, while MTS was more strongly associated with mortality in dyspneic ED patients. These complementary roles suggest that combining both tools—or developing a dyspnea-specific hybrid model—may enhance risk stratification and improve outcomes.
Keywords: Dyspnea, early warning score, emergency service, hospital, mortality, triage
Highlight key points
NEWS strongly predicted both hospital and ICU admissions in dyspneic patients, whereas MTS demonstrated superior performance in forecasting mortality.
Both scoring systems significantly predicted ICU admission but provided complementary strengths across different clinical outcomes.
A combined or dyspnea-specific hybrid approach integrating NEWS and MTS may enhance triage accuracy and improve clinical decision-making.
Dyspnea is a frequent complaint causing visits to the emergency department (ED) and may be linked to an array of illnesses that range from benign to life-threatening [1]. Accurate and timely risk stratification in this patient group is therefore of critical importance for guiding early management and disposition decisions.
Various triage and early warning systems have been developed to support clinical decision-making in ED. Among these, MTS and the National Early Warning Score (NEWS) are widely utilized. The Manchester Triage System (MTS) is primarily designed to categorize urgency of care, whereas NEWS is intended to project clinical severity [2]. This difference might suggest that the two systems may not yield equivalent predictive performance in patients with certain presentations, including dyspnea [3].
In the hospital setting, triage judgments for patients are influenced not solely by established urgency categories but also by a comprehensive evaluation of physiological and clinical indicators, supplemented by the triage nurse’s clinical expertise and direct observation, without identifying the underlying etiology [4]. Unlike NEWS, MTS does not rely on a structured set of objective parameters; rather, it emphasizes urgency and clinical judgment in determining patient priority.
Both systems aim to provide an “all-in-one” evaluation framework by integrating different physiological and clinical variables into a single scoring tool. However, such a generalized approach might introduce bias when applied to specific patient groups, such as those presenting with dyspnea. For instance, fever is not a typical finding in most dyspneic patients unless associated with infectious etiologies such as pneumonia or sepsis, and its clinical weight may be limited in non-infectious conditions or old patients [5]. Similarly, blood pressure changes may only be of critical relevance in selected scenarios, such as acute pulmonary edema or shock states, yet remain a vital component of NEWS assessment. Besides, over-triage or under-triage in dyspneic patients in EDs is encountered in EDs, and tools to enhance triage accuracy are under discussion in the literature [6, 7]. Most existing studies have evaluated these tools in broad ED populations [8, 9], and comparative analyses focusing specifically on dyspnea are scarce. Given these potential limitations, there is a need to investigate the comparative performance of NEWS and MTS specifically in patients presenting with dyspnea. The aim of this study was to evaluate the relationship of NEWS and MTS scores with clinical outcomes, including hospital admission, ICU admission, mortality, and reattendance, to determine which of these scoring systems may be more appropriate for use in this patient population.
MATERIALS AND METHODS
Study Design and Data Collection
This study was designed as a retrospective cross-sectional observational analysis and was conducted at the ED of a single tertiary training and research hospital. The study protocol was prepared in accordance with the principles of the Declaration of Helsinki and was approved by the institutional ethics committee (date: 09.10.2025, number: 2025/0203).
The study included all adult patients (≥18 years) who presented to the ED with an initial complaint of dyspnea between 2 January 2025 and 8 February 2025. The researchers obtained data from the institutional electronic health record system, known as Nucleus. Patients were eligible if they presented with dyspnea, had their initial triage performed using the MTS, and had complete and valid records of vital signs and clinical data. Patients were excluded if they were pregnant, in cardiac arrest, or directly admitted to the ICU from the ED of another hospital. Patients who were transferred from other hospitals were completely excluded from the analysis, whereas those transferred from our ED to an ICU in another facility (n=81, 11.2%) were considered as ICU admissions but were excluded from the mortality analysis because follow-up data on survival could not be obtained.
The following data were recorded: demographic characteristics (age and sex), initial vital signs at presentation (respiratory rate, pulse rate, body temperature, oxygen saturation, systolic and diastolic blood pressure), triage category according to MTS, and NEWS values. The MTS category was obtained, as recorded by the triage nurse at the initial ED presentation. The system stratifies patients into five urgency levels (red=immediate, orange=very urgent, yellow=urgent, green=standard, blue=non-urgent) based on presenting complaints, vital signs, and structured flowcharts. In our study, MTS assessments were performed by experienced triage nurses with at least five years of practice in triage, all of whom had received formal MTS training prior to the study period. The NEWS was calculated retrospectively based on the first set of vital signs recorded at admission. NEWS included seven parameters (RR, SpO2, supplemental oxygen, body temperature, SBP, HR, and AVPU), each scored from 0 to 3 according to deviation from normal ranges. The total NEWS score ranged from 0 to 20 and was categorized as low (0–4), medium (5–6), or high (≥7) risk. The NEWS physiological parameters were measured and monitored using a bedside integrated patient monitor (GE Healthcare, model B125) with dedicated sensors for heart rate, SpO2, non-invasive blood pressure, respiratory rate, and temperature. Clinical outcomes, including hospital ward admission, intensive care unit (ICU) admission, inter-hospital transfer, in-hospital mortality, reattendance within 48 hours, and length of hospital stay, were retrieved from the institutional electronic medical record system. In addition, diagnostic categories were determined from final discharge or referral diagnoses and grouped as cardiology-related, chest-related, infection-related, internal medicine–related, trauma-related, low-acuity diagnoses, diagnoses requiring ICU-level care, and other/undefined diagnoses.
Patients who were transferred to other hospitals or referral centers were included in all outcome analyses except for mortality, as complete follow-up data could not be obtained for this subgroup.
Statistical Analysis
The normality of data distribution was assessed using the Kolmogorov-Smirnov test when group size exceeded 50 (n>50) and the Shapiro-Wilk test when group size was less than 50 (n<50). For comparisons of non-normally distributed variables across groups, the Kruskal-Wallis H test was employed, and pairwise differences were further examined using the Dunn test with Bonferroni correction. For categorical variables, the chi-square test was applied when all expected cell counts were greater than 5, whereas the Fisher’s exact test was used when any expected cell count was less than 5. Pairwise comparisons of proportions were performed using the Z test with Bonferroni correction. Results of pairwise comparisons were presented with letter annotations.
Factors influencing the NEWS score were analyzed using multinomial logistic regression. which was used to model NEWS categories to allow category-specific effects and avoid the restrictive proportional odds assumption.
Descriptive results were presented as mean±standard deviation (SD), median (minimum–maximum) for continuous variables, and frequency (n) and percentage for categorical variables. A significance level of p<0.05 was considered statistically significant. All statistical analyses were performed using IBM SPSS Statistics for Windows, Version 26.0 (IBM Corp., Armonk, NY, USA, 2019).
RESULTS
A total of n=726 patients were included in the study. Patients who were transferred to other centers (n=81, 11.2%) were included in all analyses except for mortality assessment. The mean age of the study population was 61.05±22.44 years (median: 67, range: 18–99). Of the patients, n=384 (52.9%) were female and n=342 (47.1%) were male. Regarding clinical outcomes, n=100 (13.8%) patients required hospital ward admission, and n=23 (3.2%) required intensive care unit admission. The mean length of stay was 38.93±107.19 hours (median: 4, range: 0–1210). Mortality occurred in n=17 (2.3%) patients. Reattendance within 48 hours after discharge was observed in n=30 (4.1%) patients. In terms of diagnostic distribution, n=122 (16.8%) patients had cardiology-related diagnoses, n=142 (19.6%) had chest-related diagnoses, n=128 (17.6%) had infection-related diagnoses, n=75 (10.3%) had internal medicine–related diagnoses, n=8 (1.1%) presented with trauma, and n=295 (40.6%) were diagnosed with low-acuity diagnoses. Additionally, n=19 (2.6%) had other/undefined diagnoses, while n=109 (15.0%) presented with conditions requiring ICU-level care.
Table 1 provides an overview of the demographic and clinical characteristics across the different Manchester Triage System (MTS) categories. According to the Manchester Triage System, the largest proportion of patients was classified as normal (n=277, 38.2%), followed by urgent (n=178, 24.5%), non-urgent (n=152, 20.9%), very urgent (n=83, 11.4%), and critical (n=36, 5.0%). The mean NEWS score was 3.78±3.47 (median: 3, range: 0–14). Based on NEWS risk stratification, n=387 (53.3%) patients were classified as low risk, n=141 (19.4%) as medium risk, and n=198 (27.3%) as high risk. NEWS risk stratification was strongly aligned with Manchester Triage categories, with high NEWS risk scores corresponding to higher urgency categories (p<0.001). Cardiology (36.1%, 33.7%) and chest-related diagnoses (36.1%, 25.3%, 32.6%) were more common in the Critical, Very Urgent, and Urgent groups compared with lower acuity categories (p<0.001). Infection (28.9%) and internal medicine diagnoses (21.7%, 14.6%) were also more frequent in the Very Urgent and Urgent groups (p=0.005, p<0.001). Low acuity diagnosis predominated in the non-urgent (69.1%) and normal (54.9%) groups (p<0.001). Diagnoses requiring intensive care were highest in the Critical (44.4%) and Very Urgent (57.8%) categories (p<0.001).
Table 1.
Comparison of demographic and clinical characteristics according to the manchester triage system
| Critical (n=36) | Very urgent (n=83) | Emergency (n=178) | Normal (n=277) | Non-urgent (n=152) | Test stat. | p | |
|---|---|---|---|---|---|---|---|
| Age | 79 (34–95)a | 76 (19–95)a | 75 (18–99)a | 63 (19–99)b | 42.5 (18–93)c | 134.98 | <0.001h |
| Gender (%) | 0.412 | 0.982x | |||||
| Female | 55.6 | 55.4 | 52.8 | 52 | 52.6 | ||
| Male | 44.4 | 44.6 | 47.2 | 48 | 47.4 | ||
| Ward admission (%) | 134.468 | <0.001f | |||||
| No | 91.7 | 72.3 | 64.6 | 96 | 100 | ||
| Yes | 8.3ab | 27.7bc | 35.4c | 4ads | 0d | ||
| Mortality (%) | 37.288 | <0.001f | |||||
| No | 88.4 | 82.6 | 97.3 | 100 | 100 | ||
| Yes | 11.6ab | 17.4b | 2.7ac | 0c | 0c | ||
| Intensive care admission (%) | 209.362 | <0.001f | |||||
| No | 55.6ab | 45.8b | 77a | 99.3c | 100c | ||
| Yes | 11.1ab | 14.5b | 3.9ac | 0d | 0cd | ||
| Referral | 33.3ab | 39.8b | 19.1a | 0.7c | 0c | ||
| Discharge time | 9.5 (1–734)a | 19 (1–1210)a | 14 (1–665)a | 2 (0–615)b | 1 (1–141)c | 287.354 | <0.001h |
| Reattendance (%) | 16.993 | 0.001f | |||||
| No | 97.2 | 96.4 | 97.2 | 92.4 | 100 | ||
| Yes | 2.8ab | 3.6ab | 2.8ab | 7.6b | 0a | ||
| NEWS score | 8 (5–9)a | 9 (5–14)a | 5 (0–11)b | 1 (0–12)c | 0 (0–9)d | 336.491 | <0.001h |
| NEWS categorization (%) | 406.042 | <0.001f | |||||
| Low risk | 0a | 0a | 27b | 73.6c | 88.8d | ||
| Moderate risk | 22.2abc | 15.7cd | 39.9b | 14.8ac | 5.3d | ||
| High risk | 77.8a | 84.3a | 33.1b | 11.6c | 5.9c |
NEWS: National Early Warning score; h: Kruskal-Wallis H test, median (min–max); x: Pearson chi-square test; f: Fisher’s exact test, n (%); a–d: Triaged groups sharing the same letter do not differ significantly (Bonferroni-corrected Dunn test, Bonferroni-corrected Z test).
Table 2 provides an overview of the demographic and clinical characteristics across the different NEWS risk groups. Analysis showed that mortality, ICU admission, hospital transfer, and hospital ward admissions were significantly higher in the medium- and high-risk NEWS groups compared with the low-risk group (all p<0.001). Discharge times were longer in medium- and high-risk categories (p<0.001), while gender distribution and reattendance rates did not differ significantly between groups (p=0.539 and p=0.506, respectively). Cardiology (23.4% and 28.3%), chest (27.7% and 34.3%), infection (29.3%), and internal medicine–related diagnoses (17.7%) were significantly more frequent in the medium- and high-risk groups compared with the low-risk group (p<0.001). Conversely, low-acuity diagnosis predominated in the low-risk group (63.3%) and declined sharply with increasing risk (p<0.001).
Table 2.
Comparison of demographic and clinical characteristics according to NEWS risk groups
| Low risk (n=387) | Moderate risk (n=141) | High risk (n=198) | Test stat. | p | |
|---|---|---|---|---|---|
| Age | 46 (18–97)a | 76 (25–99)b | 77 (19–97)b | 189.205 | <0.001h |
| Gender (%) | 1.237 | 0.539x | |||
| Female | 52.2 | 50.4 | 56.1 | ||
| Male | 47.8 | 49.6 | 43.9 | ||
| Ward admission (%) | 168.043 | <0.001x | |||
| No | 100 | 74.5 | 67.7 | ||
| Yes | 0a | 25.5b | 32.3b | ||
| Mortality (%) | 18.404 | <0.001f | |||
| No | 99.8 | 95.7 | 94.0 | ||
| Yes | 0.2a | 4.3b | 6.0b | ||
| Intensive care admission (%) | 141.277 | <0.001f | |||
| No | 99a | 75.2b | 67.2b | ||
| Yes | 0a | 5.7b | 7.6b | ||
| Referral | 1a | 19.1b | 25.3b | ||
| Discharge time | 87 (56–127)a | 79 (36–169)b | 75 (34–178)b | 361.018 | <0.001h |
| Reattendance (%) | 1.464 | 0.506f | |||
| No | 96.6 | 95 | 94.9 | ||
| Yes | 3.4 | 5 | 5.1 |
NEWS: National Early Warning score; h: Kruskal–Wallis H test, median (min–max); x: Pearson chi-square test; f: Fisher’s exact test, n (%); a–c: Groups sharing the same letter do not differ significantly (Bonferroni-corrected Dunn test, Bonferroni-corrected Z test).
In patients with cardiology-related diagnoses, ICU admission was significantly higher (p<0.001). Among those with chest-related diagnoses, rates of hospital admission (p<0.001), ICU admission (p=0.001), and reattendance (p=0.002) were elevated. In the infection-related group, hospital admission was also significantly more frequent (p=0.003). For internal medicine–related diagnoses, both hospital admission (p<0.001) and mortality (p<0.001) were higher, whereas ICU admission and reattendance did not differ significantly.
Table 3 presents the multinomial logistic regression analysis evaluating factors associated with NEWS risk group membership, with the low-risk group used as the reference category. The overall model was statistically significant (χ2=986.948, p<0.001) and demonstrated strong explanatory power (Nagelkerke R2=0.857). In this model, age was independently associated with higher NEWS risk categorization, particularly for the moderate-risk group compared with the low-risk group (OR=1.045, 95% CI 1.018–1.073, p=0.001),
Table 3.
Determination of factors influencing NEWS score categories
| OR | Wald | SE | 95% CI | p | |
|---|---|---|---|---|---|
| Low risk | Reference category | ||||
| Moderate risk | |||||
| Age | 1.045 | 10.806 | 0.013 | (1.018–1.073) | 0.001 |
| Internal medicine admission | 0.073 | 6.599 | 1.018 | (0.010–0.538) | 0.010 |
| ICU admission | 0.144 | 5.010 | 0.866 | (0.026–0.786) | 0.025 |
| High risk | |||||
| Age | 1.028 | 3.356 | 0.015 | (0.998–1.059) | 0.067 |
| Internal medicine admission | 0.049 | 8.754 | 1.020 | (0.007–0.361) | 0.003 |
| ICU admission | 0.449 | 0.795 | 0.899 | (0.077–2.614) | 0.373 |
NEWS: National Early Warning score; OR: Odds ratio; SE: Standard error; CI: Confidence interval; Nagelkerke R2=0.857; χ2=986.948; p<0.001; ICU: Intensive care unit.
DISCUSSION
Our study population mainly consisted of older adults, evenly distributed between women and men, reflecting the typical demographic profile of dyspneic patients in the emergency department [10]. Dyspnea constitutes a small proportion of overall emergency department presentations. However, in contrast to other common complaints such as abdominal pain or minor injuries, dyspneic presentations are disproportionately associated with higher morbidity and mortality [11]. This imbalance highlights dyspnea as a high-risk sentinel symptom in the acute setting. Consequently, rather than extrapolating from general ED populations, it becomes clinically more relevant to specifically examine how risk stratification tools such as the NEWS and the MTS perform in this subgroup of patients.
This study provides a targeted comparison of the two methods concerning dyspnea. In our study, MTS and NEWS predicted mortality similarly. Patients triaged to the critical and very urgent categories had the highest mortality rates, reflecting the system’s ability to capture overall severity at presentation, even without detailed physiological scoring. This is consistent with Brazilian data showing that patients classified as “red” (critical) by MTS had significantly higher in-hospital mortality [12]. NEWS has also been validated as a mortality predictor in ED cohorts [13–15]. Souza et al. [16] evaluated the reliability of the MTS and emphasized that priority assignment in triage involves not only rational, flowchart-based decisions but also intuition and clinical experience. Overall, prior prospective, large retrospective, and meta-analytic studies [13, 17, 18] support that NEWS aligns well with triage acuity and reliably predicts mortality which appears to be consistent with our findings. However, because transferred patients were excluded from the mortality analysis which are likely more severely ill, our mortality estimates may be conservative, limiting the depth of mortality-related comparisons. Also in a large single-center study conducted in Portugal, the MTS was found to be strongly associated with hospital admission, with admission rates increasing in parallel with higher MTS categories [19]. In another study, the MTS was compared with the Emergency Severity Index (ESI), and both indices were reported to be predictive of hospital admission [20]. In our study, both systems predicted ICU admission. Evidence from a multicenter European evaluation confirms that NEWS ≥7 is associated with markedly increased ICU risk [14]. However, in a recent large retrospective study including over 27,000 ED patients, the MTS outperformed NEWS in predicting ICU admission and hospitalization, whereas NEWS was slightly superior for mortality [21].
The two systems thus offer different perspectives on risk stratification and may be most effective when applied in combination. The MTS is a triage system, which is primarily designed to prioritize the urgency of presentation rather than predict the need for hospitalization. A previous study reported no clear association between case-mix severity and triage classification, suggesting that triage prioritization does not always align with actual admission needs [8], and in the case of dyspnea, there may be patients with significant symptoms who do not ultimately require hospitalization but are nonetheless prioritized by nurses. On the other hand, NEWS integrates physiological parameters such as respiratory rate, heart rate, blood pressure, and oxygen saturation, which capture acute deterioration and thereby guide inpatient admission decisions. Our findings are therefore in line with the broader literature, although it should be noted that our cohort consisted exclusively of patients presenting with dyspnea, whereas most previous studies evaluated heterogeneous ED populations.
In the multinomial model, age was independently associated with being classified as moderate risk compared with the low-risk reference group. This finding suggests that, beyond the physiology-driven structure of the NEWS, increasing age and possibly frailty [22] may contribute to risk differentiation, particularly around the transition from low to intermediate acuity. Analyses of NEWS categories should rely on baseline patient characteristics available at presentation and concurrent physiological indicators.
Only the MTS was associated with reattendance, whereas the NEWS showed no meaningful predictive value for this outcome. As revisits are largely influenced by extrinsic factors such as outpatient access, follow-up quality, and social determinants rather than acute physiological compromises [23]. The development of predictive models to identify patients at high risk of revisiting is needed for further conclusions.
Limitations
This study has several limitations that should be acknowledged. First, the retrospective and single-center design restricts causal inference and limits the generalizability of the findings to other settings with different patient populations, staffing patterns, and triage protocols. The study period covered only a short winter interval, which may have introduced seasonal bias, as respiratory infections and dyspneic presentations are more prevalent during this time of the year. Furthermore, the overall number of mortality events was relatively small, which reduces statistical power for detecting associations with death and may lead to unstable regression estimates. Also imbalances in MTS subgroup frequencies and small sample sizes in several categories could have compromised statistical reliability, model stability, and interpretability.
Second, although patients transferred from our emergency department to other hospitals were included in the ICU admission analysis, they were excluded from mortality evaluation because outcome data were unavailable. This approach may have underestimated true mortality rates and introduced selection bias. Similarly, 48-hour reattendance was captured only within the same institution; presentations to other hospitals could not be accounted for.
Third, both scoring systems have intrinsic limitations. The Manchester Triage System relies on nurse assessment and may be influenced by subjective judgment and inter-observer variability, which was not measured in this study. The NEWS was calculated retrospectively from the first set of vital signs at admission, without considering subsequent changes during the ED stay or the timing of interventions (such as oxygen therapy), which may have affected its predictive accuracy.
Finally, outcome measures such as hospital and ICU admission may be subject to institutional policies, bed availability, and physician discretion, and may not fully reflect the patient’s clinical need.
Conclusion
Together, these findings indicate that NEWS and MTS provide complementary prognostic information in dyspneic patients. Applying either system in isolation may be insufficient, and a dyspnea-specific adaptation that integrates features from both approaches could improve accuracy and reduce over- or under-triage.
Footnotes
Cite this article as: Aciksari K. Predictive values of news and Mts in patients presenting with dyspnea: A comparative cohort study. North Clin Istanb 2026;13(2):131–138.
Ethics Committee Approval
The Goztepe Prof. Dr. Suleyman Yalcin City Hospital Training and Research Hospital Non-interventional Clinical Trials Ethics Committee granted approval for this study (date: 09.10.2025, number: 2025/0203).
Informed Consent
Written informed consents were obtained from patients who participated in this study.
Conflict of Interest
The author declare that there is no conflict of interest.
Financial Disclosure
The author declared that this study has received no financial support.
Use of AI for Writing Assistance
Not declared.
Peer-review
Externally peer-reviewed.
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