Sofa And Sirs Score.docx

RESEARCH REPORT

KULLIYYAH OF MEDICINE INTERNATIONAL ISLAMIC UNIVERSITY MALAYSIA COMPARISON OF THE SIRS AND SOFA SCORES TO PREDICT OUTCOMES AMONG INFECTED CRITICALLY ILL PATIENTS

ABDULLAH BIN FAUZI MUHAMMAD ANUAR FAHMI ABD FATAH

SUPERVISOR ASSOC. PROF. DR. AZRINA MD RALIB DEPARTMENT OF ANAESTHESIOLOGY

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ABSTRACT Background: Sepsis is now perceived as one of the main health concern worldwide. The new definition of sepsis no longer includes SIRS as the tool to diagnosed sepsis. Nowadays, SOFA score is used to define sepsis. This research was done to know the best way to predict the prognosis of a patient in an ICU based on the diagnosis by SIRS which is the old definition as compare to diagnosing sepsis by using SOFA, which is the new method. Objective: We aimed to determine the best way to predict mortality in ICU patients with sepsis. Methodology: This was a retrospective observational cohort study conducted among 174 patients aged more than 18 years of age who are admitted to the ICU with suspected or proven infection. Independent variables were socio-demographic, sepsis SIRS and sepsis SOFA, diabetes mellitus and hypertension. The dependent variable is mortality and culture postive. We used data sets from the GlyICU study done previously. Statistical analysis used wee descriptive analysis, univariate analysis, multivariate analysis and area under the curve. Result: Among 174 patients with presumed infection, only 64 were confirmed to have bacteremia. Most of the patients (33.3%) admitted to the ICU has SIRS score of 2. The area under the curve for sepsis SOFA and sepsis SIRS against mortality are 0.489 and 0.477 respectively. There is also a significant association between sepsis SIRS and sepsis SOFA with culture positive (p<0.05). Conclusion The result shows that SOFA score was a better predictive tool for mortality as compared to SIRS score even though the p value was not significant for both. On the other hand, SIRS score was a better predictive tool for positive culture as compared to SOFA score. SOFA score is needed in diagnosing sepsis as SIRS evaluation had been found to missed diagnosed 39 patients with sepsis. Keyword SOFA, SIRS, mortality, positive culture

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TABLE OF CONTENTS ABSTRACT ...........................................................................................................................................2 DECLARATION....................................................................................................................................4 ACKNOWLEDGEMENT.....................................................................................................................5 LIST OF TABLES ................................................................................................................................6 LIST OF FIGURES……………………………………………………………………………….......7 LIST OF ABBREVIATIONS ..............................................................................................................8 1 INTRODUCTION.............................................................................................................................10 2 LITERATURE REVIEW ...............................................................................................................12 2.1 Sepsis…………..........................................................................................................................12 2.1.1 Sepsis 1 (1991) ………………………………………………………………………...12 2.1.2 Sepsis 2 (2001) ………………………………………………………………………...13 2.1.3 Sepsis 3 (2016)………………………………………………………………………....17 2.2 SOFA and SIRS Score in Predicting Adverse Outcome of Sepsis Patients………………..18 2.3 The Effect of Diabetes Mellitus on Mortality in Critically Ill Patients…………………….19 2.4 The Effect of Hypertension in Mortality in Critically Ill Patients………………………....19 2.5 Association of Diabetes Mellitus and Positive Blood Cultures in Critically Ill Patients….20 2.6 Association of Hypertension and Positive Blood Cultures in Critically Ill Patients………20 3 OBJECTIVES ..................................................................................................................................21 4.1 General objective .....................................................................................................................21 4.2 Specific objectives ....................................................................................................................21 4 METHODOLOGY ..........................................................................................................................22 4.1 Study Design………..................................................................................................................22 4.2 Study Duration…......................................................................................................................22 4.3 Study Criteria……………........................................................................................................22 4.4 Sampling Frame…………........................................................................................................22 4.5 Sampling Unit……….. .............................................................................................................22 4.6 Sample Size Calculation……………………………………………………...………………23 4.7 Sampling Method …………………………………………………………….…....................23 4.8 Statistical Analysis………………………………………………………………………...….23 4.9 Data Collection Strategy…………………………………………………………………..…24 4.10 Research Tools……………………………………………………………………………....24 4.11 Variables……………………………………………………………………………………..24 4.12 Ethical Considerations………………………………………………………………………24 5 RESULTS .........................................................................................................................................25 5.1 Socio – Demographic Characteristics.....................................................................................25 5.2 SIRS Total…………………......................................................................................................26 5.3 Total SOFA……………………………………………………………………………………27 5.4 Area under the Curve against Mortality………………………………………………...….28 5.5 Area under the Curve against Positive Culture…………………………………….………29 5.6 Sepsis SOFA and Sepsis SIRS Crosstabulation…………………………………….………31 5.7 Univariate Analysis against Culture Positive……………………………………………….32 5.8 Univariate Analysis against Mortality………………………………………………………33 3

5.9 Univariate Analysis against Culture Positive……………………………………………….34 6 DISCUSSION ...................................................................................................................................36 6.1 Socio – Demographic…............................................................................................................36 6.2 SIRS Total Score…...................................................................................................................37 6.3 SOFA Total Score……………………………………………………………………….........37 6.4 ROC Curve against Mortality……………………………………………………………….37 6.5 ROC Curve against Culture Positive…………………………………………………….….38 6.6 SIRS and SOFA Score against Mortality and Culture Positive……………………..…….38 6.7 Diabetes Mellitus with Culture Positive…………………………………………………..…38 6.8 Hypertension with Culture Positive………………………………………………………....39 6.9 Diabetes Mellitus and Mortality……………………………………………………………..39 6.10 Hypertension and Mortality…………………………………………………………….…..39 6.11 Compare Multivariate……………………………………………………………………....40 6.12 McNemar Test…………………………………………………………………………….…40 7 CONCLUSION AND RECOMMENDATION .............................................................................41 8 REFERENCES .................................................................................................................................42 9 APPENDIX 1: DATA DICTIONARY ..............................................................................................

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DECLARATION We, hereby declare that the dissertation is the result of own investigations, except where otherwise stated. We also declare that it has not been previously or concurrently submitted as whole for any other degrees at IIUM or other institutions. ABDULLAH BIN FAUZI

1313825

………………..

MUHAMMAD ANUAR FAHMI BIN ABD FATAH

1312869

………………..

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ACKNOWLEDGEMENTS In the name of Allah, The Most Gracious and The Most Merciful. All praises are due to Allah who has poured His blessings and given us opportunities to conduct and complete this research successfully. First of all, we would like to extend our sincere gratitude and thankfulness to our supervisor Assoc Prof. Dr Azrina Md Ralib for her full commitments, support, guidance and sacrifice in helping us conducting our research. We would also like to extend our appreciation to Hospital Tengku Ampuan Afzan (HTAA) Intensive Care Unit Staffs in Kuantan Pahang for their warm welcome, support, cooperation and giving us approval to do our data collection there. Our deepest gratitude also to National Medical Research Register (NMRR) for endorsing our research registration and IIUM Research Committees (IREC) in helping us to safeguard patients’ care, rights and wellbeing thus promoting high ethical standards during our research. Not to forget to all our lecturers and friends, who had given us moral support and endless assistance throughout the study direct or indirectly. We believe that without their presence, we will not be able to appreciate and apprehend this study.

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LIST OF TABLES TABLE 1: The Acute Physiology and Chronic Health Evaluation II (APACHE II) score.....................................................................................................................................14 TABLE 2: The Simplified Acute Physiology Score II (SAPS II)…………...................15 TABLE 3: The Sequential Organ Failure Assessment (SOFA) score……...................25 TABLE 4: Sepsis-3 key features and definitions……………………………………….26 TABLE 5: Socio-demographic characteristics………………………………………….27 TABLE 6: Crosstabulation of Sepsis SOFA and Sepsis SIRS………………………...28 TABLE 7: Univariate Analysis against Culture Positive……………………………...32 TABLE 8: Univariate Analysis against Mortality…………………………………...…33 TABLE 9: Multivariate Analysis against Culture Positive…………………………....34 TABLE 10: Multivariate Analysis against Culture Positive……………………..……34

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LIST OF FIGURES FIGURE 1: Percentage of SIRS Totals………………………………………………..26 FIGURE 2: Percentage of Total SOFA ……………………………………………….26 FIGURE 3: Area under the Curve against …………………………………………...28 FIGURE 4: Area under the Curve against Culture Positive………….……………..30

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LIST OF ABBREVIATIONS

SIRS – Systemic Inflammatory Respond Syndrome SOFA – Sequential Organ Failure Assessment

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1. INTRODUCTION

Sepsis is defined as life –threatening organ dysfunction caused by a dysregulated human response to infection (Singer et al., 2016). The word of systemic inflammatory response syndrome (SIRS) is no longer included in definition, and currently sepsis is represented by 2 points or more of SOFA score with suspected infection (Singer et al., 2016). Growing aging populations with multiple comorbidities and cases identification also have thought to be contributing factors of its reported increasing incidence. In USA, sepsis incidence is known to have a significant longitudinal changes evidenced by a study done that shows an increment of sepsis incidence by 8.7% per year (Martin, 2013). Sepsis is also now considered as the main concern of health in worldwide (Schmidt et al., 2016). Based on conservative estimates, sepsis also will be the leading cause of death and also affecting worldwide (Singer et al., 2016). It has also been estimated from a recent meta-analysis that about 5.3 million are died due to sepsis (Balley et al., 2017). It is stated that more than $20 billion (5.2%) from total hospital cost in United States have been spent (Singer et al., 2016) to manage sepsis patients. On top of that, majority of critically ill patients in non-coronary intensive care unit (ICU) in United States also have died mainly due to sepsis (Mayr et al., 2013). One research in California shows that, about half of the documented mortality cases were diagnosed with sepsis (Liu, 2017). Sepsis treatment also is no more cost effective as it has caused burden to healthcare provider in 2013 which was around 23 billion dollars of expenditure (Gale, 2017). Prevention of sepsis nowadays has become an utmost public health priority according to CDC (Gale, 2017). Furthermore, a total 7.2 billion dollars had been spent by Medicare for sepsis hospitalization in 2013 (Gale, 2017). Apart from that, sepsis also constitutes major of ICU readmissions and death among lung transplant patients (Pietrantoni, 2003). According to (Seymour CW et al., 2016), predictive validity of SIRS based on latest definition of sepsis has the lowest value (Area Under Receiver Operating Curves (AUROC) = 10

0.64, 95% CI, 0.62-0.66). In contrary, qSOFA has higher predictive validity compared to SIRS with (AUROC = 0.66; 95% CI, 0.64-0.68) but turned out to be lower than SOFA which has the highest predictive value (AUROC = 0.74; 95% CI, 0.73-0.76). All of them have a significant value with p value <0.001. However, the large data sets used to support the new criteria of sepsis only include adult patients from high-income countries. The performance of the new definition of sepsis in lowincome and middle-income areas including Malaysia is unknown. A local study on the clinical utility of new definition of sepsis to predict outcomes is therefore warranted.

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2. LITERATURE REVIEW 2.1 Sepsis Sepsis definition has evolved and undergone series of changes from time to time. It is about 2000 years past, when the word sepsis has been used by ancient Greek literature describing organic material decay (Banerjee & M.Levy, 2017). The term of sepsis syndrome is also introduced in 1989, which is led to the definition of systemic inflammatory response syndrome (SIRS) criteria (Banerjee & M.Levy, 2017). Previously, there are many terms have been used in order to describe sepsis like bacteremia, septicemia, sepsis syndrome and also septic shock which eventually cause misunderstanding of the sepsis itself and also its related diseases (Zimbler & Campbell, 2004). 2.1.1 Sepsis 1 (1991) Definition of sepsis 1 was initiated during a consensus conference of American College of Chest Physicians (ACCP) and the Society of Critical Care Medicine (SCCM) to Sepsis and Noninfectious Systemic Inflammation held in 1991 (Vincent, 2009). The outcome was the establishment of non-infectious SIRS and sepsis definition which benefit to patients of sepsis and its sequalae (Vincent, 2009). The conference had achieved its goal in providing a framework to define systemic inflammatory response which then enabled our healthcare worker to diagnose and treat sepsis early (Vincent, 2009). Without a single definition of sepsis, it was hard to identify patients especially doing clinical trials (Vincent, 2009). Hence, by having this universally accepted single definition, further research in this field would be much easier (Vincent, 2009). The conference also decided to have a new terminology for those patients who have the same systemic response with severe infection cases, but they were only having inflammatory process without a proven infection such as pancreatitis, burns, ischemia or multiple trauma (Vincent, 2009). Hence a new term called systemic inflammatory response syndrome SIRS was introduced which can be defined as any presence of one or more of 4 criteria which are heart rate more than 90 beats/min, temperature higher than 38 ◦ C or less than 36 ◦ C, respiratory rate more than 20 breaths/min or PaCO2 below than 32mmHg, and the last one is white blood cell count more than 12000/mm3 with 10% immature neutrophils (Vincent, 2009). Sepsis was then referred as a combined SIRS and proven infection (Vincent, 2009). There were two other terminology being introduced which are severe sepsis and septic shock (Vincent, 2009). Severe sepsis was defined as organ dysfunction, 12

hypoperfusion abnormality, or sepsis-induced hypotension (Vincent, 2009). Meanwhile, septic shock was defined as severe sepsis with sepsis-induced hypotension persisting despite adequate fluid resuscitation (Vincent, 2009). 2.1.2 Sepsis 2 (2001) Later, another subsequent sepsis definition was established in 2001 during a consensus task force sponsored by the Society of Critical Care Medicine, European Society of Intensive Care Medicine, and American College of Clinical Pharmacy, American Thoracic Society, and the Surgical Infection Society (Gary et al., 2016). This conference was held with the aim of reviewing on sepsis management based on sepsis 1 definition (Gary et al., 2016). Hence, they decided for: 1- Sepsis 1 definition was retained but agreed on its some limitations 2- Sepsis diagnostic criteria need to be expanded 3- Acknowledging PIRO acronym which has separated characteristics and stages of sepsis : predisposition, infection, response to the infectious challenge, and organ dysfunction. Whether it was inflammation or organ dysfunction, both were indicated based on 21 bedside or laboratory tests which were actually known as expanded list of sepsis diagnostic criteria (Gary et al., 2016). Organ failure or mortality scoring system better known as early warning scores system (EWS) was later developed after sepsis 2 definition was introduced (Gary et al., 2016). This system was being used in ICU setting to triage critically ill patients based on their severity (Gary et al., 2016). This bedside evaluation was able to predict mortality rate within 28-30 days (Gary et al., 2016). Some of them are:

a.

APACHE II (the Acute Physiology and Chronic Health Evaluation II) Score, introduced in 1985,

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b.

MEWS (the Modified Early Warning Score), developed in 1999 as a modification of the Morgan’s Early Warning Score

c.

MEDS (see Table 3 & 4), and

d.

SOFA (the Sepsis-related Organ Failure Assessment).

Table 1 The Acute Physiology and Chronic Health Evaluation II (APACHE II) score.

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Table 2 The Simplified Acute Physiology Score II (SAPS II).

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Table 3 The Sequential Organ Failure Assessment (SOFA) score.

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2.1.3 Sepsis 3 (2016)

A task force of 19 critical care, infectious disease, surgical, and pulmonary specialist was conducted in 2014 by the European Society of Intensive Care Medicine (ESICM) and the Society of Critical Care Medicine (SCCM) in order to scrutinize the septic patient clinical criteria and definitions (Gary et al., 2016). This sepsis 3 task force defined sepsis as a “life threatening organ dysfunction due to a dysregulated host response to infection” which was thought to be more complex and not just infection or inflammation itself (Gary et al., 2016). The outcome of organ failure due to host response of infection had become the main idea of this definition while sepsis 1 and sepsis 2 had been eliminated (Gary et al., 2016). The result was taken from a publication in February 2016 issue of JAMA, the Journal of the American Medical Association which only the last 2 clinical stages was taken (Gary et al., 2016). Sepsis is now has the same definition with old description of severe sepsis (Gary et al., 2016). Below are the key features of sepsis based on its new definition. Table 4 Sepsis-3 key features and definitions.

Key Feature

Sepsis

Definition

Sepsis is a life-threatening organ dysfunction caused by a dysregulated host response to infection.

Septic shock

Septic shock is a subset of sepsis in which particularly profound circulatory, cellular, and metabolic abnormalities are associated with a greater risk of mortality than with sepsis alone.

Besides, Sepsis 3 definition also suggested for Sequential [Sepsis-related] Organ Failure Assessment (SOFA) score as compared to SIRS criteria method to clinically diagnose patients who have organ dysfunction evidenced by increase of 2 points or more (Takala J, et al., 1996). However, knowing that so many laboratory test results were needed for SOFA score on patients 17

in ICU, 'quick SOFA' (qSOFA) was suggested by the Third International Consensus Group to be used as a tool for sepsis risk of deterioration (Takala J, et al., 1996). It was considered positive when there were presence of any 2 of the following: 

Altered mental state



Systolic blood pressure ≤100 mmHg



Respiratory rate≥ 22 breaths/minute.

Meanwhile, based on 2016 international consensus definition, septic shock was defined as sepsis if both of following are present: 

Persistent hypotension requiring vasopressors to maintain mean MAP ≥65 mmHg,



Serum lactate> 2 mmol/L (>18 mg/dL).

2.2 SOFA and SIRS Score in Predicting Adverse Outcomes of Sepsis Patients There are many ways or methods that have been used in predicting outcome of critically ill patients in ICU such as Acute Physiology and Chronic Health Evaluation (APACHE) , simplified acute physiology score (SAPS) , and mortality probability models (MPM) systems in 24 hour period of ICU stay (Bross et.al, 2001). Other study also has used SOFA score as a method for identifying those who have organ dysfunction by using its selected parameters where the highest degree of organ dysfunction is indicated by highest SOFA score (Bross et.al, 2001). Another scoring system which is called systemic inflammatory response syndrome score (SIRS) is also being used to predict mortality in sepsis patients (E. marik & M. Taeb, 2017). This score is compared with SOFA score in terms of their predictive validity and showed that SOFA score is better than SIRS criteria with area under the receiver operating characteristic curve 0.74 versus 0.64 (E. marik & M. Taeb, 2017). Many studies also stated that SIRS criteria is not ideal in diagnosing sepsis (E. marik & M. Taeb, 2017). SIRS criteria also proven to be not specific as it includes patients with no infection and adverse outcome (E. marik & M. Taeb, 2017). Besides, the association of SIRS criteria against mortality not only include increased risk of organ

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dysfunction but also has association with patients without organ dysfunction (E. marik & M. Taeb, 2017).

2.3 The Effect of Diabetes Mellitus on Mortality in Critically Ill patients It was said in one study that death or mortality effect was still unproven among critically ill patients with diabetes except developing complications (Hickmann, et al., 2011). It was found that there was no association between diabetic patient and risk of mortality except in cardiac surgery patients (Hickmann, et al., 2011). In spite of large scale of severity among those diabetic patients upon their admission to the ICU, it was reported by previous issue of Critical Care, Vincent and colleagues that patients with insulin-treated diabetes and patients without diabetes had no differences in mortality effect (Hickmann, et al., 2011). Although the mechanism was not yet understood, but study had contributed to growing evidence that mortality was not associated with diabetes in ICU setting (Hickmann, et al., 2011). In a study, even though patients with insulin-treated diabetes were tend to be more severe at baseline based on Simplified Acute Physiology Score (SAPS II) and Sequential Organ Failure Assessment (SOFA) score, there was still no significant differences in ICU among other groups against mortality (Hickmann, et al., 2011). It was also found that patients with insulin-treated diabetes only had more tendency to develop renal failure, but proven that diabetes was not an independent predictor of ICU or 28-day mortality (hazard ratio 0.78, confidence interval 0.58 to 1.07, P = 0.12) according to a Cox proportional hazards analysis correcting for differences in patient characteristics (Hickmann, et al., 2011).

2.4 The Effect of Hypertension on Mortality in Critically Ill Patients There was no previous study done regarding hypertension and its association with mortality among critically ill patients. However, there were some studies that closely related to this issue such as one study that mention those patients with hypertensive crisis in ICU had higher mortality rate with p<0.05 (Chelazzi C, et al., 2011). Another related study regarding hypertension and 19

mortality is that the outcome of death or complications such as obstructive shock, cardiogenic shock, right ventricular dysfunction and failure, severe hypoxemia were associated with prolonged elevation of pulmonary arterial pressure (V Tsapenko, et al., 2008).

2.5 Association of Diabetes Mellitus and Positive Blood Cultures in Critically Ill Patients The study regarding association of diabetes mellitus and positive blood culture among critically ill patients was still not adequate (Paridou P, et al., 2008). However, a result from a study shown that diabetes and also immunodeficiency has no association with culture positive which is in consistent with study done by Grace et al (Dolina, et al., 2012). A study by Paridou P, et al. also shown the same result where there was no association between diabetes mellitus and bloodstream infection among critically ill patients in a general ICU (Paridou P, et al., 2008). Meanwhile, there were many studies that also mentioned that diabetes was associated with culture positive. Trampuz A et al stated that diabetic patients had more tendency to develop bloodstream infection compared to non-diabetic patients (25.8/1000 admissions vs. 5.8/1000 admissions, p <0.0001). in a Cox proportional hazards regression model adjusting for age, gender, admission category and APACHE II score at admission in the ICU and comorbidities, it was found that there was a higher probability among diabetic patients of developing at least one blood stream infection episode as compared with nondiabetic patients (hazard ratio = 1.66, 95% confidence interval 1.04–2.64, P = 0.034).

2.6 Association of Hypertension and Positive Blood Cultures in Critically Ill Patients There was no previous study done regarding hypertension and its association with positive bacteremia among critically ill patients.

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3. OBJECTIVES

3.1 General Objectives To study the comparison between SIRS and SOFA scores to predict outcomes among infected critically ill patients.

3.2 Specific Objectives 1. To study socio-demographic 2. To find association between Sepsis SIRS n SOFA, positive culture, diabetes mellitus and hypertension against mortality. 3. To find association between Sepsis SIRS n SOFA, positive culture, diabetes mellitus and hypertension against positive culture. 4. To know the best tool to predict mortality and positive culture.

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5. METHODOLOGY

4.1 Study design The study design chosen for this research was a retrospective observational cohort study.

4.2 Study duration The research was carried out from 17th July 2017 – 26th August 2017

4.3 Study Criteria All patients in HTAA admitted from 2016 to 2017, age > 18 years consecutively admitted to the ICU with suspected or proven infection between the study period will be included. The exclusion criteria will be admission of < 24 hours and death or loss data.

4.4 Sampling frame Data sets from the GlyICU study that investigated the glucose control in the ICU setting of HTAA.

4.5 Sampling unit Patients from the GlyICU study that investigated the glucose control in the ICU setting of HTAA. 22

4.6 Sample Size Calculation The following sample size is calculated using the MedCalc Version 16.8.4 software for comparison of two ROC curves: •

SIRS versus SOFA: From previous studies the rank correlation between these two

scores is 0.43. We are interested to show that the discriminating power of SIRS and SOFA scores in infected critically ill patients, with an area under the ROC curve of 0.64 and 0.74, respectively, is significantly different. Using α-level of 0.05 and β-level of 0.20 (power is 80%), the required sample size is 292 patients.

4.7 Sampling Method We will be studying data sets from the GlyICU study that investigated the glucose control in the ICU setting of HTAA. The study has been registered with the National Medical Research Register (NMRR) and has been approved by the MREC. Waiver of consent has been seek due to the retrospective nature of this study. Baseline demographic and clinical-laboratory characteristics of the patients will be documented. The maximum SIRS criteria, SOFA score, and qSOFA score during the 24 hours of admission to the ICU will be calculated. Patients will be followed up until discharge of death in the ICU. Our primary outcome is all-cause ICU-mortality.

4.8 Statistical Analysis Statistical analysis will be performed using SPSS. Descriptive statistic will be performed for frequency estimates, measures of central tendency and dispersion. Receiver operating curve (ROC) will be used to evaluate the power of SIRS and SOFA score to predict outcomes.

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4.9 Data Collection Strategy A total of 252 of Gly ICU patients data was taken from the ICU unit of HTAA Kuantan Pahang database plus with 47 patients from acute kidney injury patients registry also from ICU HTAA unit. Then a total of 299 patients was obtained to be analyzed. However, during data collection, 26 patients had some missing information and need to be excluded. Hence only 273 of ICU patients data were taken in the study.

4.10 Research Tools No study instrument used

4.11 Variables 4.12.1 Independent variables: 1- Socio-demographic 2- Sepsis SIRS and Sepsis SOFA 3- Diabetes 4- Hypertension 4.12.2 Dependent variables: Mortality and Culture positive

4.12 Ethical Considerations This study is a retrospective cohort study to determine the validity of the new sepsis criteria among the infected critically ill patients in Malaysian ICU. All data that will be analysed were collected as part of routine audit/evaluation by the MRIC. We do not believe that analysis of this data will expose the patients to any harm. 24

5. RESULTS

5.1 Socio – Demographic Characteristics

Table 5 Socio-demographic characteristics Variables

Percentage (%)

Frequency

Total encounters with suspected

174

63.7

174

63.7

64

23.4

Age, mean (SD), years

174

54.55 (14.5) *

Male, No. (percentage)

151

55.3

229

83.9

Chinese

22

8.1

Indian

12

4.4

Other

10

3.7

infection, No. Infection type Presumed Confirmed bacteremia

Race, No. (percentage) Malay

Maximum SIRS within 24 h of

2.25 (1.0) *

ICU admission Maximum SOFA within 24 h of

8.02 (3.7) *

ICU admission No of SIRS with Sepsis

131

48

No of SOFA with Sepsis

169

61.9

Length of ICU stay (days)

11(11) ** 104

All-cause ICU-mortality *Mean (SD) **Median (IQR)

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38.1

Table 5 shows socio-demographic characteristics of 273 ICU patients from HTAA. There are 174 patients with suspected infection. 23.4% of them are confirmed to have bacteremia. Besides, mean age of patients is 54.6. Majority of them are Malay which constitutes 83.9% (229) of total patients. The remaining patients are equally distributed among Chinese, Indian and others. The mean score of SIRS and SOFA within 24 hours of ICU admission are 2.25 and 8.02 respectively. 48% (131) of patients are diagnosed with sepsis based on SIRS criteria while majority of them are diagnosed with SOFA criteria which constitutes 61.9% (169) of total patients. The mean length of ICU stay is 16.8 and the total no of mortality among patients is 104 (38.1%). 5.2 SIRS Total

Figure 1 Percentage of SIRS totals

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Figure 1 shows percentage of each SIRS score among ICU patients in HTAA. Patient with score 2 has the highest percentage with 33.3% of patients followed by score 3 with 29.3% of patients. 5.3 Total SOFA

Figure 2 Percentage of total SOFA

Figure 2 shows percentage of each SOFA score among ICU patients in HTAA. Patient with score 6 has the highest percentage with 12.8% of total patients. Patient with score 20 has the least percentage which constitutes 4% of total patients.

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5.4 Area under the Curve against Mortality

Area under the Curve against Mortality

Variable

Area

p value

Asymptotic 95% CI Lower Bound

Upper Bound

Sepsis SIRS

0.477

0.531

0.407

0.548

Sepsis SOFA

0.489

0.766

0.419

0.56

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Figure 3 Area under the curve against mortality Figure 3 shows receiver curve for the patients diagnosed with sepsis using SOFA and SIRS score with mortality. Area under the ROC curve (ROC) for sepsis SOFA is higher than sepsis SIRS which are 0.489 and 0.477 respectively. The p value for both sepsis SOFA and SIRS are not significant with confidence interval 95%. 5.5 Area under the Curve against Culture Positive

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Area under the Curve against Culture Positive

Variable

Area

p value

Asymptotic 95% CI Lower Bound

Upper Bound

Sepsis SIRS

0.625

0.002

0.548

0.703

Sepsis SOFA

0.616

0.005

0.541

0.691

Figure 4 Area under the curve against culture positive

Figure 4 shows receiver curve for the patients diagnosed with sepsis using SOFA and SIRS score with positive culture. Area under the ROC curve (ROC) for sepsis SOFA is lower than sepsis SIRS which are 0.616 and 0.625 respectively. The p value for both sepsis SOFA and SIRS are significant with p value <0.05 and confidence interval is 95%.

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5.6 Sepsis SOFA and Sepsis SIRS crosstabulation Table 6 Crosstabulation of Sepsis SOFA and Sepsis SIRS Sepsis SOFA * Sepsis SIRS Crosstabulation Sepsis SIRS No Count No

% within Sepsis SIRS

Total

Yes

103

1

104

72.5%

0.8%

38.1%

39

130

169

27.5%

99.2%

61.9%

142

131

273

100.0%

100.0%

100.0%

Sepsis Count

SOFA Yes

% within Sepsis SIRS Count

Total

% within Sepsis SIRS

Table 6 shows the relationship between patient with sepsis SOFA and sepsis SIRS. It shows that, 130 patients (99.2%) are diagnosed with sepsis according to both SIRS and SOFA score. However, there are 39 patients (27.5%) diagnosed with sepsis based on SOFA only but not SIRS.

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5.7 Univariate Analysis against Culture Positive

Table 7 Univariate Analysis against Culture Positive

Variable

Odds Ratio

p value

Asymptotic 95% CI Lower Bound

Upper Bound

Sepsis SIRS

2.815

0.001

1.561

5.077

Sepsis SOFA

3.025

0.001

1.552

5.898

Hypertension

0.987

0.962

0.562

1.732

Diabetes

1.502

0.177

0.832

2.708

A univariate logistic regression was done to determine the relationship between the variables (sepsis SIRS, sepsis SOFA, hypertension, diabetes) against culture positive. The results are presented in Table 7. There is a significant association between sepsis SIRS and sepsis SOFA with culture positive. (both p<0.05). However, there is no significant relationship between hypertension and diabetes with culture positive. (both p>0.05). Sepsis SOFA is 3 times more likely to have culture positive compared to sepsis SIRS, hypertension and diabetes with odd ratio of 2.815, 0.987 and 1.502 respectively.

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5.8 Univariate Analysis against Mortality

Table 8 Univariate Analysis against Mortality

Variable

Odds Ratio

p value

Asymptotic 95% CI Lower Bound

Upper Bound

Sepsis SIRS

0.834

0.469

0.511

1.362

Sepsis SOFA

0.913

0.723

0.553

1.509

Hypertension

1.197

0.474

0.731

1.959

Diabetes

0.979

0.934

0.595

1.613

Table 8 show a relationship between the variables (sepsis SIRS, sepsis SOFA, hypertension, diabetes) and mortality. All of the variables show no significant association with mortality. (all p>0.05). However, patient with hypertension is 1 time for likely to result in mortality.

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5.9 Multivariate Analysis against Culture Positive

Table 9 Multivariate Analysis against Culture Positive

Variable

Odds Ratio

p value

Asymptotic 95% CI Lower Bound

Upper Bound

Sepsis SIRS

2.79

0.001

1.544

5.044

Diabetes

1.41

0.265

0.771

2.577

Table 9 shows a multivariate analysis to show relationship between diabetes and sepsis SIRS against culture positive. There is significant association between sepsis SIRS against culture positive after adjusted with diabetes with a p < 0.05.

5.10 Multivariate Analysis against Culture Positive

Table 10 Multivariate Analysis against Culture Positive

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Variable

Odds Ratio

p value

Asymptotic 95% CI Lower Bound

Upper Bound

Sepsis SOFA

2.93

0.002

1.492

5.752

Diabetes

1.281

0.424

0.698

2.352

Table 10 shows a multivariate analysis to predict culture positive based on sepsis SOFA and diabetes. The patients predicted culture positive result is -2.073 + 1.075 (sepsis SOFA) + 0.248 (diabetes). Both of the variables were not a significant predictor of culture positive. (p>0.05). Result show that sepsis SIRS and sepsis SOFA independently diagnosed with culture positive. However, sepsis SOFA shows a higher odd ratio (2.930) compared to sepsis SIRS with an odd ratio of 2.790.

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6. DISCUSSION

6.1 Socio - Demographic

Result shows that the majority of the patients admitted to ICU are Malay which consisted 83.9%. This might be due to the highest number of populations in Malaysia is Malay as compared to other races specifically in Kuantan city.

Besides, the maximum SIRS score within 24 hours of admission is 2.25 which is in consistent with a study, where it was stated that the mean maximal SIRS score for ICU patients in general surgical ICU of an urban university tertiary care medical center was 1.9

Commented [AF1]: http://jamanetwork.com/journals/jamasur gery/fullarticle/390191

± 0.1. which is quite near to our result (Talmor et al., 1999). Hence, we can say that majority of patients who are admitted to ICU have SIRS positive criteria by the definition of the SIRS positive itself. Meanwhile, the maximum SOFA score within 24 hours of admission is 8.02 which is nearly the same with a study which shows mean SOFA score of the patients is 7.13 ± 2.36 with minimum 2 and maximum 16 (Safari et al., 2016). Hence, we can also conclude that majority of patients have a positive SOFA score during admission which shows high risk of getting poor prognosis or outcome. 36

Commented [AF2]: https://www.ncbi.nlm.nih.gov/pmc/articl es/PMC5154578/

The median length of ICU stay among crtitically patients of HTAA is 11 which is contradicted with a study done by Marik and Hedman (2000) which shows median of ICU stay of 1.4. This might be due to the advanced healthcare services and facilities provided by the country which is also a modern country, USA.

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Commented [AF3]: https://www.ncbi.nlm.nih.gov/pubmed/1089 0670

6.2 SIRS Total Score

The result describes that majority of patients have a SIRS score of 2 which is contradicted with a study done by Jacom and Tatum (2017) which shows score 1 has the highest percentage among patients in trauma center. It is also can be said that more than half of the patients in ICU have positive SIRS criteria which is 2 or more criteria, which is also

Commented [AF4]: https://www.ncbi.nlm.nih.gov/pubmed/2 8547319

contradicted with the same study which has nearly half of patients with no SIRS criteria (Jacom & Tatum, 2017).

6.3 SOFA Total Score

Result from our study shows that majority of ICU patients have SOFA score of 2 or more which is in consistent with a study by which shows that 98% of descendants have score of

Commented [AF5]: Assessment of Clinical Criteria for Sepsis For the Third International Consensus Definitions

2 or more (W.Seymour et al., 2017).

for Sepsis and Septic Shock (Sepsis-3)

Hence, it means that the majority of the patients who are admitted to the ICU have an organ dysfunction which are preceded by infection upon admission.

6.4 ROC Curve against Mortality

The area under the ROC curve is higher in sepsis SOFA as compared to sepsis SIRS which is in consistent with a study by Marik & Taeb (2017) which shows that SOFA score has a greater predictive value as compared to SIRS (AUROC 0.75 vs 0.59, respectively; all comparisons p values <0.001). Hence, SOFA score is a better tool to measure the outcome of critically ill patients admitted to ICU. A better tool of measurement is really important so that we will not miss sepsis which is diagnosed by SOFA yet not diagnosed by SIRS criteria.

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6.5 ROC Curve against Culture Positive

The area under the ROC curve is a little bit higher in sepsis SIRS as compared to sepsis SOFA. This means that SIRS has a better predictivity score than SOFA for positive culture of infection. However, the difference is very small and it may be insignificant to the result. There is a study found that there is no significant correlation between number of bottles

Commented [AF6]: https://www.ncbi.nlm.nih.gov/pubmed/2 1627578

positive for culture and mortality against SOFA score (Savithri et al., 2011). It is also supported by a study stated that those patients in an ICU of a university hospital in Singapore with low SOFA score are more likely to be culture negative (Phua et al., 2013).

6.6 SIRS and SOFA score against Mortality and Culture Positive

Both SIRS and SOFA score have no significant difference against mortality with p value >0.001. This might be due to insufficient sample size that affected the result. However, SIRS and SOFA score show significant difference against culture positive with SOFA score has a higher odds ratio compared to SIRS score. Less studies are being conducted regarding the score itself in association with mortality, yet researchers tend to use ROC curve to compare the predictive value of SIRS and SOFA score with mortality.

6.7 Diabetes Mellitus with Culture Positive There is no significant difference between diabetes mellitus with culture positive. It is in consistent with the study done by Paridou P, et al. which also state that there is no correlation between diabetes mellitus and blood stream infection among critically ill patients in general ICU. Apart from that, there are also a few studies that mentioned otherwise. A study done by Trampuz A et al highlighted that there is a high tendency of having a bloodstream infection in diabetic patients as compared to non-diabetic patients. (25.8/1000 admissions vs. 5.8/1000 admissions, p <0.0001).

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Commented [AF7]:

6.8 Hypertension with Culture Positive

The result shows that there is no significant correlation between hypertension and culture positive, with a p>0.05. Actually, less studies also being conducted to associate hypertension itself with culture positive. However, some studies found that Hepatitis A virus and Helicobacter pylori are significantly associated with hypertension (Jeffrey,

Commented [AF8]: https://www.medscape.com/viewarticle/7 84813

2004). The association is still significant even though with the presence of other additional risk factors such as cholesterol level, gender, age and diabetes (Zhu, 2004). Their research also found that usually the risk would be higher if it is concomitant with the high CRP level (Jeffrey, 2004).

6.9 Diabetes Mellitus and Mortality Results shows that there is no significant correlation between DM and mortality in critically ill patients, with a p>0.05. The result was similar to the study by Hickmann et all in 2011 which stated that there is no significant association between diabetic patients and risk of mortality. The relation between diabetic patient and ICU mortality remains unclear. However, there is various mechanism proposed to explain the outcome of diabetic patients and non-diabetic in regard to ICU mortality. Insulin given to diabetic patients and a higher body mass index have a protective mechanism against ICU mortality among this group of patients (Siegelaar et al., 2020)

6.10 Hypertension and Mortality

There is no significant association between hypertension and mortality with p value >0.05. However, hypertensive patients have 1.2 times higher probability to result in mortality. There’s no previous study that mentioned association between hypertension and mortality among critically ill patients. However, there’s one research did a study entitled Incidence, Associated Clinical Factors and Outcome of Hypertensive Crises in Critically Ill Patients: A Prospective Survey. The result shows that mortality rate among patients in ICU/hospital 40

Commented [AF9]: https://www.ncbi.nlm.nih.gov/pmc/articles /PMC2887115/

were higher in hypertensive crisis patients with p<0.05 which is contradicted with our study (Chelazzi et al., 2011)

Commented [AF10]: https://www.omicsonline.org/incidence -associated-clinical-factors-and-outcome-of-hypertensive-crisesin-critically-ill-patients-a-prospective-survey-21556148.1000128.php?aid=123

6.11 Compare multivariate Result show that sepsis SIRS and sepsis SOFA independently diagnosed with diabetes against culture positive. However, sepsis SOFA shows a higher odd ratio (2.930) compared to sepsis SIRS with an odd ratio of 2.790. Thus, there is no significant association between sepsis SIRS and diabetes against culture positive. The same result was found between sepsis SOFA and diabetes. However, this is contradicted with a study stated that sepsis and infection are more likely to be diagnosed in diabetic patients (Koh

Commented [AF11]: https://www.ncbi.nlm.nih.gov/pmc/articl es/PMC3303037/

et al., 2012). There a lot of studies had been done in regarding to this. However, they found that the results are still conflicting. Some found it is affected by diabetes, some are not, and some studies found it has a protective effect (Schuetz et al., 2011).

6.12 McNemar Test

The result from McNemar test which is presented in a cross tab between definitions of sepsis from SIRS and SOFA has a p<0.0001. Meaning that, those 39 patients who are diagnosed with SOFA but not with SIRS are not due to chance. These 39 patients also have higher percentage of culture positive 23% vs 12%, p=0.09 (although, not statistically significant) and also have higher death or dialysis 72% vs 53%, p=0.046. Meaning that even this group is not classified by SIRS, they are clinically an important group of patients diagnosed as sepsis by SOFA but not SIRS. If we used SIRS definition, we may have missed this important group of patients

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Commented [AF12]: https://www.ncbi.nlm.nih.gov/pmc/articl es/PMC3041224/

7. CONCLUSION AND RECOMMENDATIONS Majority of patients who were admitted to ICU in HTAA during this study was Malay followed by other races which were Chinese, Indian and others. 61.9% of the patients were positively diagnosed with sepsis thru SOFA which was more sensitive as compared to sepsis diagnosed with SIRS which were only 48%. The result from the area under the curve shows that SOFA score was a better predictive tool for mortality as compared to SIRS score even though the p value was not significant for both. In contrast, SIRS score was a better predictive tool for positive culture as compared to SOFA score with a slight difference of value which might be affected by inadequate sample size. It was also found that 39 patients were missed to be diagnosed by SIRS score but positive thru SOFA score. Hence, it was important to use SOFA score as compared to SIRS score in diagnosing sepsis because it is more sensitive. Patients with positive SOFA and SIRS criteria were also highly associated with positive culture, but with SOFA has a higher odd ratio. However, SOFA and SIRS score had no significant association with mortality. Multivariate analysis also showed that SIRS and SOFA score can independently diagnose sepsis regardless the patients were diabetic or not. We would like to recommend that further studies with a larger sample size should be conducted in future so that a more accurate result could be attained. Relationships between SIRS and SOFA score with other comorbidities should also be studied further so that we can prevent or reduce the incidence of sepsis by reducing the other risk factors. What is more important is that SOFA score was highly recommended tools to be used in diagnosing sepsis as compared to SIRS and also to predict mortality in future. Other parameters such as usage of mechanical ventilation, dialysis, source of infection, organisms infected should be included in future studies so that we can reduce the incidence of sepsis.

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9. APPENDIX Data Dictionary 1- ICU - The Intensive Care Unit (ICU) is a unit in the hospital where seriously ill patients are cared for by specially trained staff. The ICU staff includes doctors, nurses, respiratory therapists, clinical nurse specialists, pharmacists, physical therapists, nurse practitioners, physician assistants, dietitians, social workers, and chaplains. Seriously ill patients require close observation and monitoring. Specially trained nurses care for one or two patients at a time, each shift. ICU doctors are specially trained critical care doctors. http://www.cpmc.org/learning/documents/icu-ws.html 2- GlyICU – Patients admitted to ICU whom are under glucose monitoring 3- Suspected infection - A condition where a person is presumed to be inflicted by bacteria/virus/fungi through a provisional diagnosis. 4- Confirmed bacteremia - A condition where a person is proven to be infected by bacteria mainly through a culture test. 5- Manual ventilation - Manual ventilation is a basic skill that involves airway assessment, maneuvers to open the airway, and application of simple and complex airway support devices and effective positive-pressure ventilation using a bag and mask https://pdfs.semanticscholar.org/be2b/63fb0c1c54f2606209c7b771066ed2de451e.pdf 6- Length of stay The length of an inpatient episode of care, calculated from the day ofadmission to day of discharge, and based on the number of nights spent in hospital. Patients admitted and disc harged on thesame day have a length of stay of less than one day. http://medical-dictionary.thefreedictionary.com/length+of+stay

7- Sepsis - a life-threatening organ dysfunction caused by a dysregulated host response to infection. http://jamanetwork.com/journals/jama/fullarticle/2492881

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8- SIRS - is identified by two or more symptoms including fever or hypothermia, tachycardia, tachypnea and change in blood leucocyte count. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2806258/

9- SOFA - simple and objective score that allows for calculation of both the number and the severity of organ dysfunction in six organ systems (respiratory, coagulatory, liver, cardiovascular, renal, and neurologic. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2703722/ 10- Mortality rate - An estimate of the portion of a population that dies during a specified period. Dictionary of epidemiology 11- Positive culture - Blood cultures that are positive for the bacteria or fungi means that the person tested likely has a blood infection with that microorganism. https://labtestsonline.org/understanding/analytes/blood-culture/tab/test/

12- Sepsis SOFA - Patient with life-threatening organ dysfunction caused by a dysregulated host response to infection based on SOFA score. 13- Sepsis SIRS - Patients with life-threatening organ dysfunction caused by a dysregulated host response to infection based on SIRS 14- Incidence rate - The rate at which new events occur in a population. A dictionary of epidemiology by Miquel Porta 15- Infection - A pathologic process caused by the invasion of normally sterile tissue or fluid by pathogenic or potentially pathogenic microorganisms. http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.555.3049&rep=rep1&type=pdf

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