University of Groningen
Early detection of patient deterioration in patients with infection or sepsis
Quinten, Vincent
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Quinten, V. (2019). Early detection of patient deterioration in patients with infection or sepsis. Rijksuniversiteit Groningen.
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Early detection of patient deterioration
in patients with infection or sepsis
© V.M. Quinten, 2018
All rights are reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form or by any other means without the written permission of the author. Financial support for printing this thesis was kindly provided by
Early detection of patient
deterioration in patients
with infection or sepsis
Proefschrift
ter verkrijging van de graad van doctor aan de Rijksuniversiteit Groningen
op gezag van de
rector magnificus prof. dr. E. Sterken en volgens besluit van het College voor Promoties.
De openbare verdediging zal plaatsvinden op woensdag 6 maart 2019 om 16.15 uur
door
Vincent Martijn Quinten
geboren op 5 februari 1985 te Hengelo
Promotor
Prof. dr. J.C. ter Maaten
Copromotores Dr. J.J.M. Ligtenberg Dr. M. van Meurs Beoordelingscommissie Prof. dr. T.W.L. Scheeren Prof. dr. H.R. Haak Prof. dr. J.E. Tulleken
Paranimfen
Michelle Ruël Ard Nijhuis
TABLE OF CONTENT
Chapter 1 Introduction and aims of the thesis 1
part I: preDICtING OUtCOMeS OF patIeNtS WIth
INFeCtION Or SepSIS IN the eMerGeNCY DepartMeNt 10 Chapter 2 Sepsis patients in the emergency department: stratification using
the Clinical Impression Score, Predisposition, Infection, Response and Organ dysfunction score or quick Sequential Organ Failure
Assessment score? 11
Chapter 3 Biomarkers or clinical observations to identify (outcome of)
emergency department patients with infection? 25
part II: treNDS aND VarIaBILItY IN VItaL SIGNS aS
preDICtOrS OF patIeNt DeterIOratION 30
Chapter 4 Sepsis: beyond mortality. 31
Chapter 5 Trends in vital signs and routine biomarkers in patients with sepsis during resuscitation in the emergency department: a prospective
observational pilot study. 35
Chapter 6 Repeated vital sign measurements in the emergency department predict patient deterioration within 72 hours: a prospective
observational study. 49
Chapter 7 Heart rate variability as early warning for patient deterioration in emergency department patients with sepsis: the study protocol of the
SepsiVit study. 67
Chapter 8 48-hour continuous heart rate variability as early warning for patient deterioration in emergency department patients with sepsis:
preliminary results of the SepsiVit study. 79
TABLE OF CONTENT
appeNDIx a Technical terms of heart rate variability analysis 125
appeNDIx B Technical details of the data preprocessing algorithm 127
Acknowledgments (in Dutch) 129
Curriculum Vitae 135
Chapter 1
Chapter 1
INtrODUCtION
Sepsis
Sepsis is a syndrome encompassing a multifaceted aberrant or dysregulated host response to an infecting pathogen. Sepsis can be identified by a constellation of clinical signs and symptoms in patients with suspected infection1. There is no gold standard diagnostic test for sepsis or
infection1-3. Sepsis was originally defined as an suspected infection in the presence of at least
two systemic inflammatory response syndrome (SIRS) criteria: (1) a body temperature >38°C or <36°C; (2) a heart rate >90 beats per minute; (3) tachypnea, manifested by a respiratory rate >20 breaths per minute, or hyperventilation indicated by a PaC02 of <4.3 kPa (<32 mm Hg); (4) white blood cell count >12·109/ L, < 4·109/ L, or >10% immature neutrophils (‘bands’)4.
The illness severity can be further classified into three categories: sepsis, severe sepsis and septic shock. Severe sepsis is sepsis associated with organ dysfunction, hypoperfusion or hypo-tension. Septic shock is defined as sepsis-induced hypo-tension persisting despite adequate fluid resuscitation4. These original criteria and categories are now known as the Sepsis-2 criteria.
More recent, the Sepsis-3 criteria have redefined sepsis as: a life-threatening organ dysfunction caused by a dysregulated host response to infection1. The Sepsis-3 criteria redefined the Sepsis-2
severity categories as follows: sepsis became infection and severe sepsis became sepsis. It should be noted that patients meeting the Sepsis-3 criteria have signs of organ failure by definition. In the remainder of this thesis, we will use the Sepsis-2 criteria. We chose to use the Sepsis-2 criteria, since the designs of the studies described in this thesis originate from before the introduction of the Sepsis-3 criteria, and furthermore, we are especially interested in patients that progress from infection into (multiple) organ failure.
Patient deterioration in sepsis
Sepsis is responsible for 2% of hospitalizations and 17% of in-hospital deaths5-8. Conservative
estimates indicate that sepsis is the leading cause of death and critical illness worldwide, with around 1400 sepsis-related deaths every day. The incidence of sepsis increases annually, likely reflecting aging populations with more comorbidities, greater recognition and (sometimes) reimbursement-favorable coding1,5,9,10. Sepsis-related mortality is still around 20%, although
prognosis is better than a decade ago. Survivors have a persistent decrement in their quality of life, sustain some degree of neuromuscular, functional, and/or neuropsychologic morbidity and have an increased mortality risk for more than a year after the sepsis episode11. Up to half
of all patients with sepsis are admitted through the emergency department (ED)6. The patient
population is very heterogeneous, since patients with sepsis present to the ED at various stages of the disease and sepsis often is a complication of life-limiting comorbidities7,8.
In 2002, the Surviving Sepsis Campaign (SSC) launched guidelines for the treatment of sepsis to reduce sepsis-related mortality worldwide12. Recent studies have shown that early and
aggressive resuscitation is more important than the specific kind of treatment provided13-16.
However, one in five patients presenting to the ED with infection or sepsis, deteriorate within 48 hours after hospital admission, despite treatment7,17. Deterioration can be defined as a move
Chapter 1
Clinical scoring systems and biomarkers for sepsis
Multiple attempts have been made to effectively stratify patients with sepsis, by using sepsis severity categories, clinical judgment, clinical scoring systems, and biomarkers4,20-23.
Stratification based on sepsis severity is not as accurate as clinical judgment or an adequate scoring system24. There are numerous scoring systems available; most predict sepsis-related
mortality and/or sepsis severity. These include the Predisposition, Infection, Response and Organ dysfunction (PIRO) score25, the Mortality in Emergency Department Sepsis (MEDS)
score26, the Sequential Organ Failure Assessment (SOFA) score27 and the recent quick SOFA
(qSOFA) score introduced with the Sepsis-3 definition1. However, not all scoring systems are
specifically designed for the ED and they may not be the most practical bedside tool as they may require information that is not readily available on ED admission, such as biomarker levels, patient history and living situation. There are also numerous sepsis-related biomarkers, however, almost all available biomarkers lack the required sensitivity and specificity to be of real clinical value19,22,23.
Vital signs in sepsis
A thorough re-evaluation of available physiological variables, including routine vital signs, is suggested by the latest SSC guidelines as they may describe the patient’s clinical state and response to treatment12. Sepsis is traditionally diagnosed and monitored based on infrequently
measured discrete absolute values of vital signs using thresholds derived from epidemiological research28. However, thresholds for the ‘average’ patient may not apply or be beneficial for
individual patients because of the heterogeneous nature of the patient population and
unpredictable individual’s response to treatment28. In the ED or intensive care unit (ICU), vital
signs are mostly measured continuously, however, most data is discarded by using only discrete values at specific points in time28,29. Surprising little is known about the relation between
vital signs and clinical outcomes, especially in the ED setting and despite the relative ease of measurement30-33. In addition, how to monitor and identify deteriorating patients in the ED
is also largely unknown34. Patient deterioration was preceded by changes in vital signs, often
hours before it was clinically noticed, in 80% of cases as shown by some small studies mainly in the ICU and on the nursing wards18,35-42. Additional information about response to treatment
of (early) signs of patient deterioration may be provided by monitoring changes in vital signs over time, this process is called variability analysis29.
INtrODUCtION
continuous variability analysis over time the state of the system can be tracked over time. Applied to patients continuous variability analysis has the potential to determine whether an individual patient is progressing towards a state of health or towards deterioration29. Many
types of signals and vital signs can be analyzed using variability analysis, however, heart rate variability (HRV) is the most studied29,43.
Heart rate variability
HRV analysis examines the beat-to-beat variation in heart rate. HRV can be measured readily, easily and non-invasively using equipment available in every ED43. Reduced or decreasing
HRV is associated with the diagnosis of sepsis, reflects greater severity of illness and predicts subsequent deterioration, impending shock and mortality in ICU patients28,36,37. Although a
couple of studies have been performed on HRV in adults with sepsis, HRV is most studied and applied in neonates to predict an increased likelihood of deterioration in the subsequent 24 hours28,45. Patients presenting to the ED with infection or sepsis are generally less severely
ill than ICU patients, therefore the question remains whether reduced HRV can be used as an early warning signal for impending patient deterioration in the ED population.
Modeling
One of the main challenges for the physician in the ED remains to determine the risk of deterioration for the individual patient28. A model could help the physician with the clinical
decision making. Traditional models should be easy to use, and therefore have only a few variables that do not require complex calculations46,47. However, because of the complex
non-linear behavior of the host response to infection (described above), it is unlikely that this can be captured in a simple model with only a few variables. Therefore, more complex analysis techniques are required, which can perform non-linear analyses and deal with missing data. These models may also reveal surprising relationships that challenge conventional knowledge46,48. For example, variability patterns are hidden in the data generally produced by
monitoring vital signs, by applying more advanced techniques these non-linear hidden patterns could be revealed. These patterns may provide valuable information on the host response to infection and for the early detection of patient deterioration. Early detection of deterioration could help to recognize patients at risk and potentially provide an opportunity to anticipate on or even prevent deterioration. This would potentially reduce mortality, morbidity and increase the quality of life.
Chapter 1
General aims and outline of this thesis
The general aim of this thesis was to gain insight into the different factors involved with deterioration of patients with infection or sepsis, in order to create a model for early detection of patient deterioration.
PART I: PREDICTION OF SEPSIS OUTCOMES OF SEPSIS IN THE EMERGENCY DEPARTMENT
Chapter 2 focuses on clinical scoring systems to predict in-hospital mortality and ICU admission. The predictive value of the clinical impression of the nurse and attending physician are compared with the PIRO and qSOFA scores for these outcomes.
In Chapter 3, relatively new biomarkers for sepsis and multiple organ failure are
investigated. The biomarkers tissue inhibitor of metalloproteinase-2 (TIMP-2), angiopoietin-2 (Ang-2), neutrophil gelatinase-associated lipocalin (NGAL), kidney injury molecule-1 (KIM-1) and insulin-like growth factor-binding protein-7 (IGFBP-7) were investigated together with routine biomarkers. The aim was to determine whether these new biomarkers help to identify severity of infection, need for ICU admission and organ failure.
PART II: TRENDS AND VARIABILITY IN VITAL SIGNS AS PREDICTORS OF DETERIORATION IN SEPSIS
Chapter 4 describes why it is time for sepsis research to move its focus from mortality to the occurrence and prevention of organ failure in sepsis.
Chapter 5 describes a pilot study aimed at detecting trends in vital signs (heart rate, blood pressure, respiratory rate, temperature and oxygen saturation) and routine biomarker levels during resuscitation of patients with sepsis in the ED. In this study, vital sign measurements and the routine blood draw were repeated after 3 hours in the ED.
Chapter 6 focuses on the additional value of repeated vital signs (heart rate, blood pressure, respiratory rate, temperature) in 30-minute intervals during the patient’s stay in the ED. The aim of this study was to determine whether there is a relation between trends in vital signs and patient deterioration (mortality, ICU admission or development of organ failure).
Chapter 7 describes the protocol of the SepsiVit study. The aim of this study is to determine whether continuous HRV measurement in patients presenting to the ED with suspected infection or sepsis during their first 48 hours of hospitalization can provide an early warning signal for patient deterioration within 72 hours from admission. The preliminary
INtrODUCtION
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Chapter 1
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PREDICTING OUTCOMES
OF PATIENTS WITH
INFECTION OR SEPSIS IN THE
EMERGENCY DEPARTMENT
PART I
Chapter 2 Sepsis patients in the emergency department: stratification using the Clinical Impression Score, Predisposition, Infection, Response and Organ dysfunction score or quick Sequential Organ Failure
Assessment score? 11
Chapter 3 Biomarkers or clinical observations to identify (outcome of)
Chapter 2
PUBLISHED AS
Chapter 2
Quinten VM, Van Meurs M, Wolffensperger AE, Ter Maaten JC, Ligtenberg JJM. Sepsis patients in the emergency department: Stratification using the Clinical Impression Score, Predisposition, Infection, Response and Organ dysfunction score
Sepsis patients in the emergency
department: stratification
using the Clinical Impression
Score, Predisposition, Infection,
Response and Organ dysfunction
score or quick Sequential Organ
Failure Assessment score?
part I
Abstract
OBJECTIVE
The aim of this study was to compare the stratification of sepsis patients in the emergency department (ED) for ICU admission and mortality using the Predisposition, Infection, Response and Organ dysfunction (PIRO) and quick Sequential Organ Failure Assessment (qSOFA) scores with clinical judgment assessed by the ED staff.
PATIENTS AND METHODS
This was a prospective observational study in the ED of a tertiary care teaching hospital. Adult non-trauma patients with suspected infection and at least two Systemic Inflammatory Response Syndrome criteria were included. The primary outcome was direct ED to ICU admission. The secondary outcomes were in-hospital, 28-day and 6-month mortality, indirect ICU admission and length of stay. Clinical judgment was recorded using the Clinical Impression Scores (CIS), appraised by a nurse and the attending physician. The PIRO and qSOFA scores were calculated from medical records.
RESULTS
We included 193 patients: 103 presented with sepsis, 81 with severe sepsis and nine with septic shock. Fifteen patients required direct ICU admission. The CIS scores of nurse [area under the curve (AUC)=0.896] and the attending physician (AUC=0.861), in conjunction with PIRO (AUC=0.876) and qSOFA scores (AUC=0.849), predicted direct ICU admission. The CIS scores did not predict any of the mortality endpoints. The PIRO score predicted in-hospital (AUC=0.764), 28-day (AUC=0.784) and 6-month mortality (AUC=0.695). The qSOFA score also predicted in-hospital (AUC=0.823), 28-day (AUC=0.848) and 6-month mortality (AUC=0.620).
CONCLUSION
Clinical judgment is a fast and reliable method to stratify between ICU and general ward admission in ED patients with sepsis. The PIRO and qSOFA scores do not add value to this stratification, but perform better on the prediction of mortality. In sepsis patients, therefore, the principle of ‘treat first what kills first’ can be supplemented with ‘judge first and calculate
Chapter 2
Introduction
Time is of the essence in the treatment of sepsis; early and aggressive treatment is important to reduce mortality as indicated in recent studies1,2. In 30–50% of patients, sepsis treatment
is initiated in the emergency department (ED)3,4. Considering that ICU capacity is limited
and that not all sepsis patients will benefit from ICU admission, the main challenge that ED physicians face is to effectively stratify patients between patients requiring ICU treatment and patients who can be treated on the general ward. Incorrect stratification may result in increased morbidity and mortality, and increased length of stay5,6.
There are multiple ways to stratify patients with sepsis, such as stratification by using scoring systems, stratification on the basis of the clinical judgment of the nurse and attending physician, or stratification on the basis of the sepsis categories defined by the Surviving Sepsis Campaign2. However, stratification on the basis of sepsis categories is not as accurate
as clinical judgment or an adequate scoring system7. Numerous scoring systems for patients
with sepsis exist, which predict sepsis-related mortality as well as sepsis severity. These include the Predisposition, Infection, Response and Organ dysfunction (PIRO) score8, the
Mortality in Emergency Department Sepsis (MEDS) score9, the Mortality In Severe Sepsis
in the Emergency Department (MISSED) score10, the Sequential Organ Failure Assessment
(SOFA) score11 and the recent quick SOFA (qSOFA) score introduced with the new Sepsis-3
definitions6. Of these scoring systems, the PIRO score is one of the most comprehensive
scoring systems, while at the same time requiring data routinely available in the ED. Moreover, it was developed as both a staging system and to predict mortality, and is well known to stratify patients on the basis of the severity of disease and risk of mortality before ICU admission8,12.
However, it may not be the most practical bedside scoring system for the ED as it requires information that is not readily available on admission, such as biomarker levels, patient history and living situation. Thus, effective stratification can be delayed by having to wait for these details. This is a cause of concern as early ICU transfer may lead to improved patient outcomes13. The recent qSOFA score is a simple score that could be calculated at the bedside.
However, this score has not yet been validated for patients with sepsis in the ED6. The clinical
judgment of nurses and attending physicians are available at the bedside during ED admission and do not lead to the aforementioned delays. With this in mind, our aim was to compare the stratification for ICU admission and mortality using the PIRO and qSOFA scoring systems with clinical judgment assessed by the ED staff. We hypothesized that clinical judgment assessed by the ED staff would be as accurate for predicting ICU admission and mortality as the PIRO and qSOFA scoring systems for patients with sepsis in the ED.
part I
Patients and methods
STUDY DESIGN AND SETTING
A prospective observational study was carried out in the ED of the University Medical Center Groningen, a tertiary care teaching hospital with over 34 000 ED visits annually. The study was approved by the Medical Ethical Committee of the University Medical Center Groningen, the Netherlands (METc 2013/297; METc 2012.177). Written informed consent was obtained from all patients included in the study.
STUDY POPULATION AND PROTOCOL
Adult non-trauma patients visiting the ED between 8 a.m. and 6 p.m. with suspected infection or sepsis were screened for inclusion. Inclusion criteria included patients of 18 years and older age, suspected or confirmed infection and two or more Systemic Inflammatory Response Syndrome criteria as defined by the International Sepsis Definitions Conference14. Patients
were included from August 2012 until April 2014. Because of changes in research staffing, no patients were included between June 2013 and October 2013.
Vital parameters of patients were measured by a nurse upon arrival to the ED. All vital parameter measurements were performed using a bedside patient monitor (IntelliVue MP30 System with Multi-Measurement Module; Philips, Eindhoven, the Netherlands). Temperature was measured using an electronic tympanic ear thermometer (Genius 2; Mountainside Medical Equipment, Marcy, New York, USA). After briefly assessing the patient and immediately after the vital signs were available, the nurse and attending physician were asked for their clinical impression of the patient. The nurse and physician were asked for their impression separately to ensure adequate blinding. Their clinical impression was recorded using the Clinical Impression Score (CIS). The CIS score, a singular integer, ranges from 1, indicating not ill, to 10,
indicating extreme illness15.
For each patient, the PIRO score was calculated. The PIRO score takes several factors into account: the (P)redisposition, for example, age and patient history, the type of (I)nfection, the (R)esponse to treatment and factors that indicate (O)rgan failure, for example, lactate and systolic blood pressure8. The PIRO score was calculated using the results from routine blood
analysis, sociodemographic information gathered during admission and the patient’s electronic medical record. These medical records were subsequently monitored to allow for follow-up and to collect demographic data and patient history.
In light of the new Sepsis-3 consensus definitions, a post-hoc analysis on our data was carried out to calculate the qSOFA score. The qSOFA score is based on three items: altered mental status, respiratory frequency and systolic blood pressure. For each item, one point is scored. Patients with a qSOFA score of at least 2 are considered to have an increased mortality risk6.
The qSOFA score was calculated using the initial vital parameters measured during admission to the ED.
Chapter 2
ENDPOINTS AND DEFINITIONS
The primary endpoint for this study was direct admission to the ICU. The secondary endpoints were in-hospital, 28-day and 6-month mortality, indirect admission to the ICU and length of stay. For transfer to the ICU, we distinguished between direct and indirect admission. Direct admission was immediate transfer from ED to ICU. Indirect admission was transfer of a patient from ED to first a general ward and thereafter during the patient’s stay in the hospital to the ICU for any reason. In-hospital, 28-day and 6-month mortalities were defined as all-cause mortality during the patient’s stay in the hospital and within the respective times from the day of admittance. Length of stay was defined as the number of days in the hospital; any amount of time spent in-hospital during a 24-h period was considered a full day. Low oxygen saturation was defined as a peripheral SaO2 of less than 90% on room air or less than 95% with at least 2 l of oxygen supplementation per minute. Patients were categorized into sepsis severity groups using the definitions of the Surviving Sepsis Campaign2.
STATISTICAL METHODS
For normally distributed data, the mean and SD were calculated. The Shapiro–Wilk test for normality was used to test for normality. For binomial variables, frequency and percentage of cases were calculated. For non-normally distributed data, the median and interquartile ranges (IQR) were calculated. To compare the variance between sepsis severity groups, the nonparametric Jonckheere trend test was performed. Receiver operator characteristic (ROC) curves and the area under the ROC curve [area under the curve (AUC)] were calculated to determine the relationship between clinical score and endpoint. All AUCs were tested against the null hypothesis (AUC= 0.5) using the Wilcoxon signed rank test with continuity correction. For each combination of clinical score and outcome parameter with a significant AUC, we calculated cut-off point, sensitivity, specificity and positive/negative likelihood ratios. Cut-off points were chosen for maximum sensitivity and specificity, that is, closest to the upper-left corner of the ROC. Missing data were excluded from the analysis. All statistical analyses were carried out using IBM SPSS Statistics for Windows, version 20.0 (IBM Corp., Armonk, New York, USA), except for a comparison of AUCs, which was performed using MedCalc, version 14.12.0 (MedCalc, MedCalc Software bvba, Ostend, Belgium). A P-value of 0.05 or less was considered significant; all tests were two tailed.
part I
Results
PATIENT CHARACTERISTICS
Of the 193 patients enrolled in this study, 103 patients presented with sepsis, 81 presented with severe sepsis and nine patients presented with septic shock (Table 1). The most frequently suspected foci of sepsis were respiratory and urogenital. The CIS, PIRO and qSOFA scores increased, respectively, with sepsis severity (P= 0.001, < 0.001, and 0.002). However, although the PIRO score differentiated between sepsis categories, we did not observe a significant difference in CIS or qSOFA scores with respect to these categories. In the septic shock group, four (44%) patients had low oxygen saturation on admission. Although the respiratory rates of all patients were available to the attending physician and nurse, they were not recorded in ten cases. In one case, the peripheral oxygen saturation and the rate of oxygen supplementation were not recorded.
The length of stay increased significantly with sepsis severity (P= 0.002). The median length of stay of patients presenting with septic shock (13 days, IQR=6–19) was more than twice as long as that of patients presenting with sepsis (6 days, IQR=4–10).
ICU ADMISSION
Twenty-one of the 193 (10.9%) patients were admitted to the ICU, of whom 15 (7.8%) were admitted directly from the ED, whereas the remaining six (3.1%) were admitted to the ICU indirectly from a nursing ward (Table 2). One of the 21 patients presented with sepsis, but developed respiratory insufficiency in the ED and needed transfer to the ICU. Six of the 21
N Overall Sepsis Severe sepsis Septic Shock
Number of patients [n (%)] 193 193 (100%) 103 (53.4%) 81 (42.0%) 9 (4.7%)
Demographics
Age [median (IQR)] 193 60 (48-71) 60 (51-68) 60 (47.5-76) 64 (49-70.5)
Sex [n (%)]
Male 193 108 (56.0%) 49 (52.4%) 53 (65.4%) 6 (66.7%)
Female 193 85 (44.0%) 54 (47.6%) 28 (34.6%) 3 (33.3%)
Vital signs at admission in the emergency department
Heart rate (bpm) [median (IQR)] 193 110 (100-120) 110 (100-120) 110 (100-123) 115 (105-135) Syst. blood pressure (mm Hg) [mean ±SD] 193 124.5 ± 23.45 129.8 ± 19.46 122.9 ± 23.46 79.2 ± 13.63 Diast. blood pressure (mm Hg) [mean ±SD] 193 71.7 ± 15.38 74.2 ± 13.79 71.0 ± 15.66 48.7 ± 10.95 MAP (mm Hg) [mean ±SD] 193 89.4 ± 16.37 92.7 ± 13.47 88.5 ± 16.77 59.0 ± 10.89 Respiration rate (rpm) [median (IQR)] 183 22 (18-27) 21.5 (18-25.8) 22 (18-27) 30 (24-32.5) Oxygen saturation (%) [median (IQR)] 192 95 (92-98) 95 (94-98) 95 (91-98) 90 (84.3-97)
Supplemental oxygen [n (%)] 192 54 (28.5%) 29 (28.2%) 20 (24.7%) 5 (55.6%)
Temperature (°C) [median (IQR)] 193 38.5 (37.9-38.9) 38.5 (37.9-38.9) 38.5 (38.0-39.0) 37.6 (36.1-38.9) Suspected focus [n (%)] Respiratory 193 83 (57.0%) 46 (44.7%) 31 (38.3%) 6 (66.7%) Urogenital 193 64 (33.2%) 36 (35.0%) 25 (30.9%) 3 (33.3%) Skin/soft-tissue/wound 193 8 (4.1%) 4 (3.9%) 4 (4.9%) 0 (0.0%) Intra-abdominal 193 32 (16.6%) 18 (17.5%) 11 (13.6%) 3 (33.3%) Catheter/tube/implant 193 4 (2.1%) 3 (2.9%) 1 (1.2%) 0 (0.0%) Meningitis 193 2 (1.0%) 2 (1.9%) 0 (0.0%) 0 (0.0%)
Other or unknown focus 193 27 (14.0%) 13 (12.6%) 13 (16.0%) 1 (11.1%)
Chapter 2
patients presented with severe sepsis and were directly admitted to the ICU. Three of these patients had respiratory insufficiency and required mechanical ventilation, and three were transferred to the ICU as a result of persistent hemodynamic instability, despite treatment in the ED. Of the nine (4.7%) patients presenting with septic shock, eight required direct ICU admission, seven because of persistent hemodynamic instability, requiring inotropic support and one because of respiratory insufficiency. One of the nine septic shock patients was sufficiently stabilized in the ED so that general ward admission was possible. The chances in direct ICU admission increased with greater sepsis severity (P< 0.001).
We assessed the accuracy of the CIS, PIRO and qSOFA scores in predicting overall and direct ICU admission. All three scores predicted overall and direct ICU admission (Table 3 and Table 4). For direct ICU admission, there was no significant difference between AUCs for the CIS scores of the nurse (AUC= 0.896) and the attending physician (AUC= 0.861). Furthermore, there was no significant difference between AUCs of the CIS scores and the PIRO (AUC= 0.876) and the qSOFA scores (AUC= 0.849). When assessing for sensitivity and the positive likelihood ratio of direct ICU admission, the CIS score scored higher than the PIRO score (Table 4). The CIS score of the attending physician for direct ICU admission also showed a good negative likelihood ratio (0.1). However, the qSOFA score showed the highest specificity for direct ICU admission at the cost of a low sensitivity (66.7%). The optimal cut-off point for direct ICU admission of the CIS scores of both the nurse and the attending physician was 8. Fifty-three of the 193 patients had a CIS score of the nurse above the cut-off point, of whom 22.6% were directly admitted to the ICU. Fifty-nine patients had a CIS score of the attending physician above the cut-off point, of whom 23.7% were directly admitted to the ICU. The optimal cut-off point of the PIRO score was 13. Forty-two patients had a PIRO score above this cut-off point, of whom 28.6% were directly admitted to the ICU, and 32 patients had a qSOFA score above the predefined cut-off point of two; 29.4% of these patients were directly admitted to the ICU.
Six of the 193 (3.1%) patients required an indirect transfer to the ICU (Table 2), five patients as a result of respiratory insufficiency and one because of hemodynamic instability. Notably,
N Overall Sepsis Severe sepsis Septic Shock J-t p
Number of patients [n (%)] 193 193 (100%) 103 (53.4%) 81 (42.0%) 9 (4.7%) Clinical outcome [n (%)] Admission to ICU 193 21 (10.9%) 4 (3.9%) 9 (11.1%) 8 (88.9%) <0.001* Direct 193 15 (7.8%) 1 (1.0%) 6 (7.4%) 8 (88.9%) <0.001* Indirect 193 6 (3.1%) 3 (2.9%) 3 (3.7%) 0 (0.0%) 0.468 In-hospital mortality 193 8 (4.1%) 3 (2.9%) 4 (4.9%) 1 (11.1%) 0.100
taBLe 2. results on the primary and secondary endpoints and clinical scores, including their distribution over the sepsis severity categories
part I CIS nurse CIS physician pI r O scor e qSOF a scor e aUC (95% CI) p aUC (95% CI) p aUC (95% CI) p aUC (95% CI) p 0.866 (0.793;0.938) <0.001* 0.793 (0.700;0.886) <0.001* 0.752 (0.628;0.876) <0.001* 0.811 (0.718;0.903) <0.001* 0.896 (0.817;0.976) <0.001* 0.861 (0.794;0.927) <0.001* 0.876 (0.791;0.961) <0.001* 0.849 (0.766;0.932) <0.001* 0.741 (0.616;0.867) 0.045* 0.553 (0.340;0.766) 0.686 0.415 (0.196;0.634) 0.481 0.670 (0.453;0.886) 0.157 tality 0.643 (0.456;0.830) 0.172 0.652 (0.476;0.828) 0.146 0.764 (0.648;0.880) 0.011* 0.823 (0.707;0.939) 0.002* 0.706 (0.538;0.874) 0.065 0.667 (0.471;0.863) 0.134 0.784 (0.657;0.912) 0.011* 0.848 (0.733;0.963) 0.002* 0.530 (0.411;0.649) 0.623 0.528 (0.419;0.637) 0.644 0.695 (0.592;0.798) 0.001* 0.620 (0.500; 0.740) 0.046* eceiv
er operator characteristics cur
ve; CI, confidence inter
val; CIS, Clinical I
mpr ession Scor e; P IR O, P redisposition, I nfection, R esponse, O rgan failur e; qSOF A, quick S equential
rea under cur
ve for the primar
y and secondar
Chapter 2
only the CIS score obtained from the nurse at the ED significantly predicted indirect ICU admission (AUC: 0.741; Table 3 and Table 4).
MORTALITY
We assessed the CIS, PIRO and qSOFA scores for in-hospital, 28-day and 6-month mortality (Table 2, Table 3 and Table 4). Eight of the 193 patients died during their stay in the hospital (Table 2). One of these eight patients died after more than 28 days in the hospital. The CIS scores did not significantly predict any of the assessed mortality end-points (Table 3 ). Conversely, the PIRO and qSOFA scores were predictors for mortality. For all three mortality endpoints, the PIRO score showed the highest sensitivity and the qSOFA score showed the highest specificity (Table 4).
Cut-off pointa Sensitivity Specificity Lr+
Lr-Admission to ICU
CIS nurse 8 80.0% 77.8% 3.6 0.3
CIS physician 8 80.0% 75.0% 3.2 0.3
PIRO score 14 57.1% 89.0% 5.2 0.5
qSOFA score 2 57.1% 87.2% 4.5 0.5
Direct admission to ICU
CIS nurse 8 85.7% 76.3% 3.6 0.3
CIS physician 8 93.3% 74.6% 3.7 0.1
PIRO score 13 80.0% 83.1% 3.0 0.2
qSOFA score 2 66.7% 86.5% 4.9 0.4
Indirect admission to ICU
CIS nurse 7 100.0% 40.3% 1.7 0.0 In-hospital mortality PIRO score 12 75.0% 76.8% 3.2 0.3 qSOFA score 2 62.5% 84.3% 4.0 0.4 28-day mortality PIRO score 12 85.7% 76.9% 3.7 0.3 qSOFA score 2 71.4% 84.4% 4.6 0.3 6-month mortality PIRO score 10 70.4% 67.5% 2.2 0.4 qSOFA score 2 33.3% 84.9% 2.2 0.8
CIS, Clinical Impression Score; LR− , negative likelihood ratio; LR+ , positive likelihood ratio; PIRO, Predisposition, Infection, Response and Organ dysfunction; qSOFA, quick Sequential Organ Failure Assessment.
aPoint in the receiver operator characteristics curve with the maximum specificity and sensitivity for the outcome variable.
taBLe 4. Cut-off points, sensitivity, specificity and likelihood ratios for the Clinical Impression, pIrO and qSOFa scores
part I
Discussion
Time is of the essence in the treatment of sepsis; early and aggressive treatment is imported to reduce mortality1,2. The main challenge that ED physicians face is effectively stratifying
patients on the basis of the need for ICU treatment. Especially, considering that ICU capacity is limited, not all patients may benefit from ICU admission and incorrect stratification may result in increased morbidity, mortality and length of stay5,6. In this study, we compared
stratification for ICU admission and mortality using the PIRO and qSOFA scoring systems with clinical judgment assessed by the ED nurse and attending physician. We hypothesized that clinical judgment would be as accurate to predict ICU admission and mortality as these scoring systems. The clinical judgment of the ED staff was recorded using the CIS. We found that clinical judgment and the PIRO and qSOFA scoring systems performed equally well as predictors of direct ICU admission. Furthermore, we found that the PIRO and qSOFA scores predicted for the mortality endpoints, whereas clinical judgment did not.
All three scores performed equally well as predictors of ICU admission. However, it must be noted that the qSOFA score had a low sensitivity (66.7%), suggesting that about a third of patients requiring ICU treatment will be missed by this score. De Groot et al also found that the PIRO and clinical judgment scores performed equally on the stratification between ICU and general ward admission for an ED population with only severe sepsis and septic shock17.
In our study, more than half of the population included patients with (uncomplicated) sepsis. Comparing our results with the results of De Groot, our results suggest that using clinical judgment and the PIRO score to stratify patients in a population including sepsis does not affect the accuracy of the scores. The qSOFA score was not reported in the study by De Groot and can therefore not be compared. Tsai et al found that the PIRO score predicted ICU admission with an AUC of 0.889, in patients unexpectedly transferred from the ED to the ICU18. This AUC is comparable with the AUC for direct ICU admission in our results (AUC=
0.876). Our results show that the PIRO and qSOFA scores compared with clinical judgment (measured using the CIS score) are equally good predictors of ICU admission. Considering that clinical judgment can be easily determined bedside within the first 15 min after the patient’s arrival at the ED, this suggests that clinical judgment is an important asset early in the ED stratification process.
It should be noted that the relationship between clinical judgment and ICU admission is not independent; in everyday practice, a patient judged by the treating physician as critically ill or requiring a critical intervention (e.g. ventilation, inotropes) may be more readily admitted to the ICU. This dependency might have introduced a bias that causes an overestimation of the performance of the CIS scores. This bias is potentially limited by the fact that our hospital’s ICU functions as a closed-format ICU. This entails that an ED physician first needs to consult the ICU physician for admission to the ICU. Furthermore, neither CIS, PIRO nor qSOFA scores were communicated to the ICU physician when requesting a transfer; the scores, therefore, did not influence the decision to admit a patient to the ICU.
Perhaps even more interesting than the prediction of direct ICU admission is the prediction of indirect ICU admission as it may provide an opportunity to preventively admit a patient to the
Chapter 2
193 patients were indirectly admitted to the ICU. This makes our study underpowered to be conclusive on the prediction of indirect ICU admission. A larger study designed to compare clinical judgment with the PIRO and qSOFA scores is required to be conclusive on predicting indirect ICU admission. However, we speculate that changes over time in scores or vital signs might be more accurate at predicting indirect ICU admission (or patient deterioration) than scores or measurements on a single point in time16. Therefore, we plan further studies to assess
changes in scores and vital signs over time.
The new Sepsis-3 definitions place more emphasis on organ dysfunction6. Our results suggest
that being alert for organ dysfunction (included as elements in the PIRO and qSOFA scores) may aid in predicting mortality. However, to stratify between ICU and general ward admission, the use of a scoring system that includes indicators of organ failure does not add value. Furthermore, the Sepsis-3 definitions no longer include the group of patients with (uncomplicated) sepsis. According to the Sepsis-3 definitions, the patients in our study population with sepsis would have been designated as patients with infection (but not sepsis) without organ failure6. However, our study results show that ICU admission was 4% and
mortality was 3% in the sepsis group. Therefore, further studies should focus on the best way to treat patients in this group (i.e. with infection without organ failure) and on how to best detect early signs of organ failure.
We compared clinical judgment with the PIRO and qSOFA scores for the mortality endpoints. Clinical judgment did not significantly predict any of the mortality endpoints, whereas the PIRO and qSOFA scores did predict mortality. The PIRO score had the best sensitivity and the qSOFA score had the best specificity for the in-hospital and 28-day mortality endpoints. Mortality in our study was lower than expected on the basis of the existing literature3,7,19,20.
Especially, the in-hospital mortality rate of 4.9% in the severe sepsis category and the 28-day and 6-month mortality rates were lower than those in previous studies. These low mortality rates may be partially explained by the fact that we introduced a novel sepsis bundle in our ED in 2008. The aims of this bundle include earlier recognition of septic patients, immediate nurse/physician contact at admission, administration of antibiotics within 60 min and routine fluid resuscitation during the first 2 h (for as long as required)16. Furthermore, it should be
noted that the recent literature reports considerably lower mortality rates compared with earlier publications. This suggests an increased global awareness of sepsis in addition to an early and initially more aggressive treatment1,21,22.
Although low mortality is a positive outcome for our patients, the small number of events limits the power of our results. However, the AUCs for in-hospital and 28-day mortality of PIRO and CIS scores in our study agree with the results of previous studies7,18. The AUC
for the qSOFA score for non-ICU patients as set out by the Third International Consensus Definitions for Sepsis and Septic Shock is not (yet) known, and can therefore not be compared
part I
correction may further improve the predictive accuracy of the CIS score. Fourth, this study was not designed to measure or correct for nurse or physician fatigue. We do not expect that this considerably affected our results as all staff work maximum 9-h shifts, with a maximum of 48 h/week. In other hospitals, shifts may be longer and the effects of fatigue larger. Fifth, daytime-only inclusion of patients introduced a selection bias. Our visit logs show that 65% of admissible patients visited our ED within this time-frame. However, previous clinical evaluations in our department (unpublished data) showed that patients visiting our ED outside this time-frame did not have more severe sepsis. Hence, whether daytime-only inclusion introduced a significant bias in our results is questionable. Finally, treatment limitations dictated by individual patient wishes or by severe comorbidity (Table 1) introduced a bias that led us to underestimate the performance of CIS, PIRO and qSOFA scores as patients who might have required ICU treatment were not transferred to the ICU.
As with any scoring system or biomarker used in medicine, they can only be used as a tool to guide the treating physician. The stratification of patients into different (risk-)groups is a sensible and effective way to triage and to communicate with other physicians in a standardized way. However, scoring systems on their own merits are not a substitute for individual decision-making. Therefore, scoring systems should always be evaluated within the context of the individual patient and the patient’s wishes, and not as a hard criterion for ICU admission.
Conclusion
This study shows that clinical judgment is both fast and reliable in stratifying sepsis patients between the ICU and the general ward. Furthermore, our results show that the PIRO and qSOFA scores do not add value to this stratification process. Therefore, compared with clinical judgment, the PIRO and qSOFA scores perform better as predictors of mortality. In patients with sepsis, we therefore conclude that the principle ‘treat first what kills first’ can be supplemented with ‘judge first and calculate later’.
Chapter 2
REFERENCES
1 The Process Investigators. A Randomized Trial of Protocol-Based Care for Early Septic Shock. N Engl J Med 2014; 370: 1683–93.
2 Dellinger RP, Levy MM, Rhodes A, et al. Surviving sepsis campaign: International guidelines for management of severe sepsis and septic shock: 2012. Crit Care Med 2013; 41: 580–637.
3 Shapiro N, Howell MD, Bates DW, Angus DC, Ngo L, Talmor D. The association of sepsis syndrome and organ dysfunction with mortality in emergency department patients with suspected infection. Ann Emerg Med 2006; 48: 583–90.
4 Hall MJ, Williams SN, DeFrances CJ, Golosinskiy A. Inpatient care for septicemia or sepsis: a challenge for patients and hospitals. NCHS Data Brief 2011; 62: 1–8.
5 Kennedy M, Joyce N, Howell MD, Lawrence Mottley J, Shapiro NI. Identifying infected emergency department patients admitted to the hospital ward at risk of clinical deterioration and intensive care unit transfer. Acad Emerg Med 2010; 17: 1080–5.
6 Singer M, Deutschman CS, Seymour CW, et al. The Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3). JAMA 2016; 315: 801.
7 de Groot B, Lameijer J, de Deckere ER, Vis A. The prognostic performance of the predisposition, infection, response and organ failure (PIRO) classification in high-risk and low-risk emergency department sepsis populations: comparison with clinical judgement and sepsis category. Emerg Med J 2014; 31: 292–300. 8 Rubulotta F, Marshall JC, Ramsay G, Nelson D, Levy M, Williams M. Predisposition, insult/infection,
response, and organ dysfunction: A new model for staging severe sepsis. 2009; 37: 1329–35.
9 Shapiro NI, Wolfe RE, Moore RB, Smith E, Burdick E, Bates DW. Mortality in Emergency Department Sepsis (MEDS) score: a prospectively derived and validated clinical prediction rule. Crit Care Med 2003; 31: 670–5.
10 Sivayoham N, Rhodes A, Cecconi M. The MISSED score, a new scoring system to predict Mortality In Severe Sepsis in the Emergency Department: a derivation and validation study. Eur J Emerg Med 2014; 21: 30–6.
11 Vincent J-L, Moreno R, Takala J, et al. The SOFA (Sepsis-related Organ Failure Assessment) score to describe organ dysfunction/failure. 1996; 22: 707–10.
12 Howell MD, Talmor D, Schuetz P, Hunziker S, Jones AE, Shapiro NI. Proof of principle: the predisposition, infection, response, organ failure sepsis staging system. Crit Care Med 2011; 39: 322–7. 13 Ligtenberg JJM, Bens BW, ter Maaten JC. One more idea on preventable ICU deaths... Crit Care 2012; 16:
1.
14 Levy MM, Fink MP, Marshall JC, et al. 2001 sccm/esicm/accp/ats/sis international sepsis definitions conference. Intensive Care Med 2003; 29: 530–8.
15 van der Vegt AE, Holman M, ter Maaten JC. The value of the clinical impression in recognizing and treating sepsis patients in the emergency department. Eur J Emerg Med 2012; 19: 373–8.
16 Quinten VM, van Meurs M, Ter Maaten JC, Ligtenberg JJ. Trends in vital signs and routine biomarkers in patients with sepsis during resuscitation in the emergency department: a prospective observational pilot study. BMJ Open 2016; 6: 9718.
17 de Groot B, de Deckere ER, Flameling R, Sandel MH, Vis A. Performance of illness severity scores to guide disposition of emergency department patients with severe sepsis or septic shock. Eur J Emerg Med 2012; 19: 316–22.
part I
22 Stevenson EK, Rubenstein AR, Radin GT, Wiener RS, Walkey AJ. Two decades of mortality trends among patients with severe sepsis: a comparative meta-analysis. Crit Care Med 2014; 42: 625–31.
Chapter 3
Chapter 3
PUBLISHED AS Quinten VM, Van Meurs M, Ter Maaten JC, Ligtenberg JJM. Biomarkers or Clinical Observations to Identify (Outcome of) Emergency Department Patients
with Infection? Shock 2016; 46: 108.
Biomarkers or clinical observations
to identify (outcome of) emergency
department patients with infection?
part I
To the Editor: In their recent article in Shock, Day et al assess the value of the addition of a set
of inflammatory and endothelial biomarkers to clinical data when predicting the infectious etiologies of abnormal vital signs in Emergency Department (ED) patients1. The authors found
that the combination of interleukin-6 and soluble E-selectin, the initial temperature, and a history of fever improved identifying infection. We agree with their conclusion that in future studies clinical data should be integrated into prediction models of infection. Recently, we reviewed the literature on biomarkers in sepsis and wondered whether adding the relatively new biomarkers for sepsis and multi-organ failure (MOF), tissue inhibitor of metalloproteinase-2, angiopoietin-2 (Ang-2), neutrophil gelatinase-associated lipocalin (NGAL), kidney injury molecule-1 (KIM-1), and insulin-like growth factor-binding protein-7 (IGFBP-7) to routine laboratory determinations could help to identify severity of infection, complications, need for ICU admission, and outcome. In patients admitted to our university medical center-based ED with a clinical suspection of infection, venous blood samples for biomarkers were collected at admittance to the ED, in combination with blood for routine laboratory analysis. A total of 94 patients were included: 40 patients with sepsis, 51 with severe sepsis, and 3 patients with septic shock.
Lactate and blood urea nitrogen (BUN) were the routine markers that distinguished best between sepsis and severe sepsis (P<0.001 and P=0002): lactate accounted for a large (r=-0.51) effect size and BUN for a medium (r=-0.32) effect size. Creatinine was a predictor for MOF. C-reactive protein was a predictor for both respiratory failure and admittance to the ICU. The biomarkers KIM-1 and IGFBP-7 significantly distinguished between sepsis and severe sepsis (P=0.001 and P=0.015): KIM-1 showed a medium (r=-0.35) effect size and IGFBP-7 a small-to-medium (r=-0.25) effect size. IGFBP-7 was the only biomarker that predicted for the primary endpoint, 6-month mortality. Plasma NGAL was the best biomarker to predict MOF. The only biomarker to predict acute kidney injury was IGFBP-7. Ang-2 was both a predictor for respiratory failure and admittance to the ICU. The review article by Pierrakos and Vincent lists 178 biomarkers, proposed for (diagnosis of) sepsis: almost none of them showed a sensitivity and specificity over 90%2. In conclusion, combinations of biomarkers
might contribute and —in the future— may be part of (machine learning) models helping us in taking the right patient treatment and placement decisions in patients with infections in the ED. It is paramount that these biomarkers will be available fast during patients’ stay in the ED. Until that time clinical judgment and vital signs are most important in diagnosing (severity of) infection3. In the last 10 years, the early recognition of the septic patient, reevaluating,
and adjusting treatment in a timely manner using treatment bundles has improved outcome substantially4; now it is time for fine-tuning our diagnostic modalities during acute ED
Chapter 3
REFERENCES
1 Day DE, Oedorf K, Kogan S, et al. The Utility of Inflammatory and Endothelial Markers to Identify Infection in Emergency Department Patients. Shock 2015; 44: 215–20.
2 Pierrakos C, Vincent J-L. Sepsis biomarkers: a review. Crit Care 2010; 14: R15.
3 van der Vegt AE, Holman M, ter Maaten JC. The value of the clinical impression in recognizing and treating sepsis patients in the emergency department. Eur J Emerg Med 2012; 19: 373–8.
4 Ligtenberg JJ, ter Maaten JC, Zijlstra JG. Back to basics in sepsis treatment: Critically ill patients need intensive care. Crit. Care. 2014; 18: 405.
TRENDS AND VARIABILITY IN
VITAL SIGNS AS PREDICTORS
OF PATIENT DETERIORATION
PART II
Chapter 4 Sepsis: beyond mortality. 31
Chapter 5 Trends in vital signs and routine biomarkers in patients with sepsis during resuscitation in the emergency department: a prospective
observational pilot study. 35
Chapter 6 Repeated vital sign measurements in the emergency department predict patient deterioration within 72 hours: a prospective
observational study. 49
Chapter 7 Heart rate variability as early warning for patient deterioration in emergency department patients with sepsis: the study protocol of the
SepsiVit study. 67
Chapter 8 48-hour continuous heart rate variability as early warning for patient deterioration in emergency department patients with sepsis:
Chapter 4
PUBLISHED AS
Chapter 4
Quinten VM, van Meurs M, Ligtenberg JJ, ter Maaten JC. Prehospital antibiotics for sepsis: beyond mortality? Lancet Respir Med 2018; 6: 168–70.
Sepsis: beyond mortality.
Chapter 4
PUBLISHED AS
part II
In the Lancet Respiratory Medicine, Nadia Alam and colleagues assessed prehospital
administration of intravenous ceftriaxone 2000 mg in addition to usual care (fluid resuscitation and supplementary oxygen) in the ambulance for patients with suspected sepsis in the
randomized controlled PHANTASi trial1.Unfortunately, this early intervention did not lead to
improved sepsis survival compared with patients receiving usual care alone. Fewer patients died in the study (8% across both arms) than was predicted (40%) based on epidemiological studies at the time of the trial design. As is commonly known, mortality from sepsis has substantially decreased in recent decades, and in fact, the low mortality rate of PHANTASi exceeds that from our previous cohort study (4%) in our emergency department2.
In an accompanying comment, Jean-Louis Vincent argued that the low severity of illness of the patients included in PHANTASi made it difficult to show an effect of prehospital antibiotics on mortality3. Although we agree with this argument, the patients included in this well
designed trial matched the mix of sepsis severity and percentage of admissions to intensive care in our emergency department cohort. Therefore, we disagree with Vincent that only patients with signs of organ dysfunction–i.e., with sepsis according to the Sepsis-3 definitions –might benefit from early antibiotics4. Furthermore, we disagree that the PHANTASi trial reinforces
the fact that timing of antibiotics is not very important in patients with infection. In a separate study, investigators showed that 22% of patients presenting at an emergency department with suspected sepsis without signs of organ dysfunction developed organ dysfunction within 48 h of admission despite antibiotic and supportive treatment5. Previously, we noted that 4% of
patients with uncomplicated sepsis needed to be admitted to an intensive-care unit, and such patients would probably benefit from early administration of antibiotics2. Alam and colleagues
showed that the number of patients readmitted to hospital after 28 days was significantly lower in the intervention group with prehospital antibiotics, but could not explain the reason for this difference1. We speculate that early antibiotics might attenuate the development of organ
failure during a patient’s hospital stay, and suggest that the time has come to make a shift from mortality towards (early) signs of organ failure as a marker and endpoint for future emergency department-based sepsis research. There is more to life than death alone.
Chapter 4
REFERENCES
1 Alam N, Oskam E, Stassen PM, et al. Prehospital antibiotics in the ambulance for sepsis: a multicentre, open label, randomised trial. Lancet Respir Med 2018; 6: 40–50.
2 Quinten VM, Van Meurs M, Wolffensperger AE, Ter Maaten JC, Ligtenberg JJM. Sepsis patients in the emergency department: Stratification using the Clinical Impression Score, Predisposition, Infection, Response and Organ dysfunction score or quick Sequential Organ Failure Assessment score? Eur J Emerg Med 2018; 25: 328–34.
3 Vincent JL. Antibiotic administration in the ambulance? Lancet Respir Med 2018; 6: 5–6.
4 Singer M, Deutschman CS, Seymour C, et al. The third international consensus definitions for sepsis and septic shock (sepsis-3). JAMA - J Am Med Assoc 2016; 315: 801–10.
5 Glickman SW, Cairns CB, Otero RM, et al. Disease progression in hemodynamically stable patients presenting to the emergency department with sepsis. Acad Emerg Med 2010; 17: 383–90.
Chapter 5
PUBLISHED AS
Chapter 5
Trends in vital signs and routine
biomarkers in patients with
sepsis during resuscitation in the
emergency department: a prospective
observational pilot study.
Quinten VM, van Meurs M, Ter Maaten JC, Ligtenberg JJ. Trends in vital signs and routine biomarkers in patients with sepsis during resuscitation in the emergency department: a prospective observational pilot study. BMJ Open 2016; 6: 9718.
part II
ABSTRACT
OBJECTIVES
Sepsis lacks a reliable and readily available measure of disease activity. Thereby, it remains unclear how to monitor response to treatment. Research on numerous (new) biomarkers associated with sepsis provided disappointing results and little is known about changes in vital signs during sepsis resuscitation. We hypothesized that trends in vital signs together with routine biomarker levels during resuscitation might provide information about the response to treatment at a very early stage of sepsis in the emergency department (ED). We therefore explore trends in vital signs and routine biomarker levels during sepsis resuscitation in the ED. DESIGN
Prospective observational pilot study. SETTING
ED of a tertiary care teaching hospital. PARTICIPANTS
99 Adult non-trauma patients with suspected infection and 2 or more systemic inflammatory response syndrome criteria admitted to the ED.
PRIMARY AND SECONDARY OUTCOME MEASURES
Vital signs and biomarker levels at admittance (T0) and after 3 h in the ED (T1). RESULTS
In total, data of 99 patients were analyzed. Of these patients, 63 presented with sepsis, 30 with severe sepsis and 6 with septic shock. All vital signs decreased, except for peripheral oxygen saturation which increased. Almost all routine biomarker levels decreased during resuscitation, except for C reactive protein, bands, potassium, troponin T and direct bilirubin which remained stable. Sodium, chloride and N-terminal prohormone of brain natruretic peptide increased slightly.
CONCLUSIONS
Vital signs and biomarker levels showed descending trends during resuscitation, except for parameters directly affected by treatment modalities. Despite these trends, most patients improved clinically. Trends in vital signs and routine biomarkers might be helpful in predicting clinical course and response to treatment in patients with sepsis during early resuscitation.
