Predictability of Adult Patient Medical Emergency Condition from Triage Vital Signs and Comorbidities: A Single-Center, Observational Study

doi:10.21203/rs.3.rs-4913657/v1

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Predictability of Adult Patient Medical Emergency Condition from Triage Vital Signs and Comorbidities: A Single-Center, Observational Study

https://doi.org/10.21203/rs.3.rs-4913657/v1

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Journal Publication

published 10 Oct, 2024

Read the published version in BMC Emergency Medicine →

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Background

Vital signs and comorbid diseases are the first information evaluated in patients admitted to the emergency department (ED). This study aims to assess the relationship between initial vital signs, comorbid diseases, and medical emergency conditions (MEC) in patients admitted to the ED.

Methods

This prospective study was designed as a single-center observational study, including patients admitted to a tertiary ED between 16.06.2022 and 09.09.2022. Patients younger than 18, readmitted to the ED within 24 hours, or absence of vital signs due to cardiac arrest were excluded from the study. Vital signs and comorbid diseases of all patients were recorded. The mortality within 24 hours, the need for intensive care unit admission, emergency surgery, and life-saving procedures were considered “medical emergency conditions”. The role of vital signs and comorbid diseases in predicting emergencies was analyzed by binary logistic regression.

Results

A total of 10022 patients were included in the study; 5056 (50.4%) were female, and 4966 (49.6%) were male. The median age of patients was 46 (min-max: 18–104). Six hundred four patients presented with a MEC. 3480 (34.7%) patients had at least one comorbidity, while 5031 (50.2%) patients had at least one abnormal vital sign. Hypoxia (Odd’s Ratio [OR]: 1.73), diastolic hypotension (OR: 3.71), tachypnea (OR: 8.09), and tachycardia (OR: 1.61) were associated with MECs. Hemiplegia (OR: 5.7), leukemia (OR: 4.23), and moderate-severe liver disease (OR: 2.99) were the most associated comorbidities with MECs. In our study, a MEC was detected in 3.6% (186 patients) of the patients with no abnormal vital signs and without any comorbidities.

Conclusion

Among the vital signs, hypoxia, diastolic hypotension, tachypnea, and tachycardia should be considered indicators of a MEC. Hemiplegia, leukemia, and moderate-severe liver disease are the most relevant comorbidities that may accompany the MECs.

Vital Signs

Comorbidity

Mortality

Medical Emergency Condition

Life-Saving Procedure

Over the years, overcrowding in emergency departments (ED) and high patient density have increased the importance of triage in the ED (1). Triage is the primary tool to assess patients’ severity of illness or injury upon arrival to the ED (2). The purpose of triage is to determine the patient’s emergency status and prioritize emergent patients (3). The critical step of triage is a dynamic process related to various components.

An initial clinical assessment is essential to distinguish the patients and recognize those needing immediate care. According to established international triage scores used worldwide, the parameters of these scores may vary (4). Common characteristics components are initial vital signs, chief complaint and discriminators, and prediction of resource requirements. However, the joint entity of these scoring systems is vital signs.

Vital signs, with their dynamic and instantaneous variability, are among the simplest and most important information obtained about admitted patients. Vital signs are measurements of the body's most basic functions; they help detect or monitor medical problems or patients’ progress. The four classic vital signs are body temperature, heart rate (HR), and blood pressure (5), respiratory rate (RR). These vital signs may significantly impact patient triage scores and clinical outcomes. For example, a patient admitted with a headache may have a different trajectory if their blood pressure is elevated. Similarly, the number of critical vital signs is associated with mortality; as the number of abnormal vital signs increases, mortality rates increase (6).

Besides vital signs, another entity that may be relevant to illness or injury severity and clinical outcome is the comorbid illness of a patient. Likewise, a patient admitted with a headache should be categorized differently if they have a history of a previous brain aneurysm.

Although initially developed for breast cancer patients, the Charlson comorbidity index (CCI) is a widely used index accepted as valid for predicting disease burden and mortality (7).

This study aims to determine the effect of vital signs and comorbidities on predicting medical emergency conditions (MEC) within 24 hours

Study Type and Design

This was a prospective study conducted in an academic ED environment. The study was approved by our institution's Health Research Ethics Board (number: İ04-211-22).

Study Setting and Population

The prospective observational study was conducted in a large tertiary care hospital with an approximate annual of 50,000 ED admissions. All adult patients admitted to the ED with any complaint between 16.06.2022 and 09.09.2022 were eligible for inclusion. Patients younger than 18 years, re-admitted to the ED within 24 hours, and presented with no vital signs due to cardiac arrest were excluded from the study. Informed consent was obtained from patients or legal guardians.

The vital signs recorded from patients were body temperature, heart rate (HR), systolic blood pressure (SBP), diastolic blood pressure (DBP), respiratory rate (RR), and oxygen saturation (SaO₂). Mindray Beneheart D6 was used for RR, HR, SaO_2, and blood pressure, and Unaan YNA-800 was used for body temperature. These data were recorded in the study form. According to the modified Charlson comorbid index, comorbidities were recorded in the study form as yes/no (7). Information regarding medical history was obtained from patients’ first-degree relatives or informal caregivers when patients were incompetent to give it themselves. A medical emergency condition was defined as mortality within 24 hours, need for intensive care unit admission, need for emergency surgery, and life-saving procedures. The MEC, as mentioned earlier, was reviewed through the “Hospital Information Management System” and if one of these four criteria was positive, the patient's status was recorded as in a "medical emergency condition" (3, 8). Assisted ventilation, intubation, surgical airway, emergent non-invasive positive pressure ventilation, defibrillation, emergent cardioversion, external pacing, chest needle decompression, pericardiocentesis, open thoracotomy, bronchoscopy, intraosseous access, significant intravenous fluid resuscitation, blood administration, control of major bleeding, hemodialysis, and use of medications like naloxone-dextrose-dopamine-dobutamine-noradrenaline-adrenalin-atropine-adenosine were considered as life-saving procedures. Patients who will benefit from the treatments to be applied in the intensive care unit, who cannot be followed and treated outside the intensive care unit, who need mechanical ventilation, who need non-invasive mechanical ventilation, who need continuous invasive hemodynamic monitoring, and who require vasoactive drug therapy were considered as patients who need for intensive care unit admission.

Abnormal vital signs were defined according to the following cutoff values: body temperature > 37.8 C° - body temperature < 35 C°, HR < 60 beats/minute–HR > 100 beats/minute, SBP < 90 mmHg – SBP > 140 mmHg, DBP < 60 mmHg – DBP > 90 mmHg, RR > 24 breaths/minute, and SaO₂ < 94%, RR < 12/minute – RR > 24/minute (9–13).

Statistical Analysis

All statistical analyses were performed using SPSS 26.0 (IBM SPSS Statistics for Windows, Version 26.0. Armonk, NY: IBM Corp. 2019) package program.

The mean and standard deviation with frequency and percentage were used as descriptive statistics for normally distributed data. The median and minimum-maximum values were used for non-normally distributed data. A comparison of categorical variables between groups was carried out with a Chi-square test or Fisher's exact test. The relationship between initial vital signs, comorbidities, and MECs was determined using binary logistic regression analysis, and the odds ratio was calculated to determine the factors affecting MEC. A p-value less than 0.05 was considered significant.

The study evaluated 10577 patients admitted to the ED between 16.06.2022 and 09.09.2022 (Figure.1). Five hundred fifty-five patients were excluded because of re-admission, age under 18, and cardiac arrest. Of 10022 patients participating in the study, 5056 (50.4%) were female, and 4966 (49.6%) were male. The median age of the patients was 46 (min-max: 18–104). Hypoxia was detected in 992 (9.9%) patients. 236 (2.4%) patients had diastolic hypotension, while 1691 (16.9%) had diastolic hypertension. Systolic hypotension was observed in 50 (0.5%) patients. 1986 (19.8%) patients had systolic hypertension. Tachypnea and high body temperature were detected in 170 (1.7%) and 593 (5.9%) patients. Pulse counts were outside the normal range in 2077 (20.7%) patients.

In 6360 patients without any comorbidity or MEC, mean DBP and SBP were 80 ± 11.7 mmHg and 127 ± 18.9 mmHg. Median RR, HR, and SaO₂ were 18/min (min-max: 10–29/min), 88/min (min-max: 49–170/min), and 97% (min-max: 75–100%) relatively. The mean body temperature was 36.4 ± 0.6°C.

At least one MEC was detected in 604 (6%) of all patients (Table.1). At least one of the life-saving procedures was applied to 320 (3.2%) patients. Non-invasive mechanical ventilation, endotracheal intubation, and surgical airway were applied in 44, 58, and 2 patients. Defibrillation, medical/electrical cardioversion, and external pacing were required in 2, 22, and 4 patients, respectively. Fluid resuscitation was performed in 60 patients, blood replacement was performed in 92 patients, vasopressor agents were performed in 66 patients, and hemodialysis was performed in 38 patients. Adrenaline was administered in 64 patients for anaphylaxis. Six patients needed needle/tube thoracostomy, 48 needed bleeding control surgery, and ten needed bronchoscopy.

Of the 604 patients with one of the MEC, 206 (34.1%) had hypoxia, and 97 (16.1%) had diastolic hypotension. Elevated DBP was recorded in 112 (18.5%) patients. Tachypnea, bradycardia, and tachycardia were detected in 101 (59.4%), 91 (14.3%), and 188 (31.1%) patients, respectively. Female gender and increasing age were associated with MECs. Fever and SBP were not statistically significant in predicting the MEC. Table 2 shows the frequencies and the odds ratios of vital signs and comorbidities regarding MEC. Hemiplegia, leukemia, moderate-severe liver disease, and any tumor presence had the most significant relationship with MECs. Other comorbidities in the modified Charlson comorbidity index did not significantly predict the MEC at admission.

Table 1

Frequency of Medical Emergency Conditions
Medical Emergency Conditions	n *	Percentage	Percentage in all patients (n = 10022)
Mortality within 24 hours	40	6.6	0.4
ICU requirement	410	67.9	4.1
Emergency Surgery requirement	86	14.2	0.9
Life-Saving procedures	320	52.9	3.2
*: Some of the patients have a coexistence of medical emergency conditions. ICU: intensive care unit

Table 2

Risk Factors in Patients with the MEC
Significant Risks	Non-MEC n (%)	Any MEC n (%)	OR	95% CI		p-value
Significant Risks	Non-MEC n (%)	Any MEC n (%)	OR	Lower	upper	p-value
CAD	775 (83.6%)	152 (16.4%)	1,566	1,231	1,993	0.000
PVD	234 (85.4%)	40 (14.6%)	1,530	1,023	2,288	0.038
CTD	288 (89.4%)	34 (10.6%)	1,619	1,066	2,459	0.024
Diabetes Mellitus	1146 (87.3%)	166 (12.7%)	1,318	1,052	1,651	0.016
Hemiplegia	20 (62.5%)	12 (37.5%)	5,378	2,248	12,870	0,000
Moderate-Severe Kidney Disease	276 (80.7%)	66 (19.3%)	1,583	1,139	2,201	0.006
Any Tumor Presence	361 (84.9%)	64 (15.1%)	2,268	1,666	3,088	0,000
Leukemia	46 (85.2%)	8 (14.8%)	4,239	1,935	9,284	0,000
Moderate-Severe Liver Disease	90 (75%)	30 (25%)	2,990	1,857	4,814	0,000
Metastatic Solid Tumor	228 (78.4%)	58 (21.6%)	2,360	1,647	3,382	0,000
Hypoxia	786 (79.2%)	206 (20.8%)	1,739	1,366	2,215	0,000
Diastolic Hypotension	236 (70.1%)	97 (29.1%)	3,718	2,711	5,100	0,000
Diastolic Hypertension	1691 (93.8%)	112 (6.2%)	0.945	0.748	1,195	0.638
Tachypnea	69 (40.6%)	101 (59.4%)	8,090	5,528	11,840	0,000
Bradycardia	78 (85.7%)	13 (14.3%)	1,291	0.662	2,519	0.453
Tachycardia	1798 (90.5%)	188 (9.5%)	1,611	1,309	1,983	0,000
MEC: Medical Emergency Condition, CAD: Coronary Artery Disease, PVD: Peripheral Vascular Disease, CTD: Connective Tissue Disease, OR: Odd's ratio, CI: Confidence interval, p-value < 0.05 was considered significant.

At least one MEC was detected in 3.6% (n = 186) of the patients with no abnormal vital signs or comorbidities. As the number of abnormal vital signs increased, the rate of MEC increased. The relationship between the number of abnormal vital signs, including the mean arterial pressure and the presence of MEC, is shown in Table 3.

Table 3

Abnormal Vital Findings and Medical Emergency Conditions Frequencies
Total Abnormal Vital Findings	Medical Emergency Conditions		n = 10022
Total Abnormal Vital Findings	None	Any	n = 10022
0	4991 (96.4%)	186 (3.6%)	5177
1	661 (92.1%)	57 (7.9%)	718
2	1653 (93.9%)	108 (6.1%)	1761
3	373 (88%)	51 (12%)	424
4	398 (91.1%)	39 (8.9%)	437
5	73 (73%)	27 (27%)	100
6	767 (92.4%)	63 (7.6%)	830
7	122 (84.1%)	23 (15.9%)	145
8	298 (90%)	33 (10%)	331
9	77 (88.5%)	10 (11.5%)	87
10	5 (41.7%)	7 (58.3%)	12

The measurement, recording, and reporting of vital signs are integral to patient management. These findings vary in disease and provide immediate information for the experienced healthcare professional about the underlying pathology. In addition, comorbidities give information on the patient’s prognosis and lead to different ways of patient management. The study showed the importance of vital signs such as DBP and comorbidities in determining a patient’s emergency status, such as MECs.

The oxygen saturation expresses the percentage of hemoglobin molecules saturated with oxygen. This indicates the state of hypoxemia. As in our study, hypoxia carries a risk for mortality, and mortality rates increase as hypoxia deepens (6, 14). It is a marker for hospitalized patients' intensive care unit (ICU) admission (15). The low oxygen saturation value before discharge is even significant for re-admission to the ED (9, 12). Diastolic blood pressure is the resting pressure on the arteries between each cardiac contraction. Low DBP causes high pulse pressure, and increased pulse pressure may indicate arterial stiffness, often due to aging or cardiovascular disease. High diastolic blood pressure causes low pulse pressure, which may be a marker of poor heart function with decreased cardiac output. Although not mentioned in the literature, which is similar to our study (9, 12, 14), low DBP can predict mortality (6); it has even been shown that low DBP is a better predictor of cardiac arrest (16). Even though high DBP was not found significant in predicting the emergency status in the study, Bleyer et al. showed an increase in mortality at values of 120–130 mmHg and above for DBP, unlike our study (6). Systolic blood pressure is the maximum pressure on the arteries during left ventricular contraction. Low SBP causes low pulse pressure, a marker of poor heart function, and reduced cardiac output. On the other hand, high SBP may be due to renal, endocrine, intracranial, pregnancy-related, and cardiovascular causes, as well as essential. In the study, low and high SBP was not statistically significant in predicting the MEC. Contrary to the survey, low SBP was a risk factor for mortality, and mortality rates increase as the low SBP deepens (6, 14). The low SBP before discharge resulted in re-admission to the ED and mortality (9, 12). An increase in mortality was found at values of 200 mmHg and above for SBP (14).

Respiratory rates vary with age. The average resting RR for adults is 10–20 breaths per minute. An increased number of breaths carries a significant risk for mortality, and mortality rates increase as tachypnea worsens (6, 14). A high RR before discharge is a good indicator for re-admission to the ED. As the number of breaths increases, the transfer rates of hospitalized patients to the ICU and mortality increase (12, 16). Heart rate is an important variable that determines cardiovascular risk. Tachycardia is a resting HR above 100 beats/min in adults. Tachycardias may occur due to physiological processes such as effort, anemia, pain, and anxiety. It may also arise for compensation in pathological processes such as hypoxia, fever, acidosis, hyperthyroidism, shock, and coronary ischemia. A heart rate below 60 beats/minute is bradycardia in adults except for athletes (17). A high HR is significant for mortality; the mortality rates increase with an increase in heart rate (6, 14). Tachycardia is a good indicator of in-hospital cardiac arrest, and a high heart rate before discharge increases the re-admission to the ED (9, 12, 16). While low heart rate was not statistically significant in predicting emergencies in the study, an increase in mortality was found in low heart rates (14). Body temperature is a vital sign affected by many internal and external sources. A healthy person's body temperature ranges from 36.5 to 37.8° C. Like the study, Nguyen et al. did not find an increase in re-admission to the ED and 30-day mortality with high body temperature before discharge (12). However, there are also studies showing an increase in mortality as the body temperature increases, and there is an increase in re-admissions to the ED in patients with high body temperature before discharge (6, 9, 14). Current findings have not clarified the role of body temperature in predicting an emergency status. Bleyer et al. classified the comorbid diseases of the patients as chronic heart failure, chronic obstructive pulmonary disease, cancer, dementia, end-stage renal disease, and other end-stage diseases. Similar to our study, there was no mortality risk in the presence of chronic heart failure or dementia. Still, an increased mortality risk was observed in end-stage renal and other end-stage diseases (6). It has been shown that the vital signs and comorbidities affect mortality, transfer to the ICU, and the frequency of re-admissions to the ED (6, 9, 12, 14, 15). Charlson Comorbidity index skoru arttıkça mortalite ihtimalinin de arttığı görülmüştür (18, 19). It is also recommended that comorbidities be used to determine trauma patients' initial triage and prognosis. (20). It is seen that the importance of comorbidities in terms of triage is underestimated, especially in elderly trauma patients. (21). Likewise, it is reported that comorbidities should be considered to predict the prognosis after surgery (22, 23). Even an artificial intelligence-based triage system was created in which comorbidities were encountered. (24). Although there are similar studies, the difference in the outcome part and the calculation of the emergency risk based on comorbid diseases are the most valuable aspects of the study.

Limitations

There are some limitations in the study. It was a single-center study with the patient population of a single region. Other limitations in the study are that other early warning systems, triage grading, and re-measurements of vital signs were not evaluated.

Hypoxia, low DBP, tachypnea, tachycardia, and some comorbidities are good predictors of a MEC. Adding DBP and comorbidities to the early warning scoring systems should be considered. Healthcare providers should consider that MECs may occur in patients without abnormal vital signs. While performing triage, the patient should be evaluated as a whole with vital signs, comorbidities, and general condition.

Emergency Department

MEC

Medical Emergency Condition

the Odd’s Ratio

Respiratory Rate

Heart Rate

CCI

Charlson Comorbidity Index

Ethics approval and consent to participate: Ethics Committee approval was obtained before the study to derivate the patient files from the Ethics Committee of Ankara University. (number: İ04-211-22). Informed consent was obtained from patients or legal guardians.

Consent for publication: Not Applicable

Availability of data and materials: The datasets generated and/or analyzed during the current study are not publicly available due the patients’ files were derived from archives of Hacettepe University but are available from the corresponding author on reasonable request.

Competing interests: The authors declare that they have no competing interests.

Funding: This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

Authors' contributions: MY and OP have set up the main idea and hypothesis of the study. MY, ASY, and SG developed the theory and organized the material and method section. MGE and ABO evaluated the data given in the conclusion. MY, ASY, and AK wrote the discussion part of the article, after OP reviewed it, made necessary regulations, and approved it. All authors discussed the entire study and approved the final version of the manuscript.

Acknowledgments: Not Applicable

Authors’ information:

Maral YAZICI MD: Pazarcık State Hospital, Emergency Service, Kahramanmaraş, Türkiye

Ahmet Sefa YETER MD: Dr. Abdurrahman Yurtaslan Ankara Oncology Training and Research Hospital, Emergency Service, Ankara, Türkiye

Sinan GENÇ; MD: Ankara University School of Medicine Department of Emergency Medicine, Ankara, Türkiye

Ayça KOCA; MD: Ankara University School of Medicine Department of Emergency Medicine, Ankara, Türkiye

Ahmet Burak OĞUZ; MD: Ankara University School of Medicine Department of Emergency Medicine, Ankara, Türkiye

Müge GÜNALP ENEYLİ; Prof: Ankara University School of Medicine Department of Emergency Medicine, Ankara, Türkiye

Onur POLAT; Prof: Ankara University School of Medicine Department of Emergency Medicine, Ankara, Türkiye

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No competing interests reported.

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You are reading this latest preprint version

Predictability of Adult Patient Medical Emergency Condition from Triage Vital Signs and Comorbidities: A Single-Center, Observational Study

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Journal Publication

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Abstract

Background

Methods

Results

Conclusion

Figures

BACKGROUND

METHODS

Study Type and Design

Study Setting and Population

Statistical Analysis

RESULTS

DISCUSSION

CONCLUSION

Abbreviations

Declarations

References

Additional Declarations

Status:

Journal Publication

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