Amutha Arockia Mary*
Department of Nursing, MGM Institute of Health Sciences, Kamothe, Navi Mumbai, India
Received Date: March 02, 2021; Accepted Date: March 18, 2021; Published Date: March 26, 2021
Citation: Mary AA (2021) Comparative Study between SOFA and qSOFA of Early Detection of Sepsis in Patients Admitted in Critical Care Unit. J Intensive & Crit Care Vol.7 No.2:38.
Introduction: The goal of Surviving sepsis campaign is to improve the patients’ outcome who suffers from sepsis that makes it vital to have defined policies and protocols to detect sepsis at the earliest and treat. The global burden of sepsis in relationship to mortality and morbidity ratio is increasing. But there is very minimal data about its occurrence in India.
It is been estimated that more than 30 million people are affected by sepsis globally among which 6 million death happens every year. This triggers the need for early detection. There are various predictive tools used to detect sepsis and mortality. SOFA score one among them which is in use since 1994. qSOFA is also a predictive tool which was recommended by the Sepsis-3 consensus to be used as a predictor outside the ICU. Sepsis related mortality is more in India as compared with its western counterparts. The aim of the research is to compare and determine the predicting ability of the tools qSOFA and SOFA when used upon patients with suspected infection at Emergency department and critical care units in the setting of tertiary care teaching hospitals at Navi Mumbai.
Methodology: The researcher conducted prospective observational non-experimental quantitative study on 100 patient samples. This study compared two tools to detect the effectiveness in predicting sepsis at the earliest. This study is conducted at Emergency department using qSOFA score and is conducted at critical care unit using SOFA criteria, at selected tertiary care teaching hospitals at Navi Mumbai. These institutions were selected for the study on the basis of ease in availability of the sample, researcher’s accessibility and familiarity with the institutions. The sensitivity and specificity of qSOFA and SOFA were assessed by area under the receiver operating curve (AUROC). The calculated sensitivity of qSOFA was 100%, with AUROC 0.70 (81.47% to 100% CI) and the specificity of qSOFA was 37.50%. The recorded sensitivity of SOFA was 95.45% with AUROC of 0.68 (77.16% to 99.88% CI).
Results: In patients with suspected infection the AUROC of qSOFA in predicting sepsis was 0.70 (81.47% to 100% CI) with 100% sensitivity and 37.50% specificity in comparison to the AUROC of SOFA score which was 0.68 (81.47% to 100% CI) with 95.45% sensitivity and 39.29% specificity. The outcome was measured on the basis of patient shifted to ward, shifted to critical care unit and in hospital death.
Conclusion: According to the observation made our study concludes that qSOFA has 100% sensitivity to detect sepsis at the earliest when applied on patients with suspected infection at emergency department in comparison to SOFA score when applied on patients with suspected infection at critical care units of tertiary care teaching hospital emergency department and critical care unit at Navi Mumbai. The researcher also found that the hurdle to the early detection is the signs and symptoms that are noticed during the normal course of infection leads to the increase of false positive. In spite of that the researcher found it is recommended to detect sepsis at the earliest with pre planned protocols utilizing effective tools and local healthcare policies as it is a global burden with a complex nature. Further research in this arena is highly recommended to generalize the findings.
Keywords: Sepsis; qSOFA; SOFA; Predictive tools.
Sepsis is one of the major causes of morbidity and mortality around the world. Epidemiological burden across countries is difficult to determine. It was noted that more than 30 million people gets affected by sepsis every year globally. The predominant epidemiologic data of sepsis are from western countries rather than India, sparse information is available regarding the epidemiology of sepsis in India. But severe sepsis is prevalent in Indian critical care setups as well and sepsisrelated mortality is high [1-5].
Patients who are critically ill are especially vulnerable to develop sepsis if the infection they suffer or acquired trigger malfunctioned cascade of inflammatory process . The third international consensus defined sepsis as "life-threatening organ dysfunction caused by a dysregulated host response to infection" . The sepsis-3 definitions recommends the importance of understanding the complex nature of the mistuned host response to infection and the body’s response to such insults . Critical dysfunction caused by sepsis with its fast-deteriorating nature warns for early detection and management to save the patient and to improve the quality of life for the survivors .
World health assembly (WHA) and World health organization (WHO) announced sepsis as a global health priority, in 2017 MAY, and urged UN member of the states to work on the aspects like diagnosis, prevention and management of sepsis . Sepsis can develop in any individual but high-risk populations are more vulnerable, like aged, neonates, pregnant women, patients with renal, autoimmune diseases, and immune- compromised patients in healthcare facilities, who underwent splenectomy etc., are at greater risk of developing sepsis. Sepsis which is itself a medical emergency due to its evolving nature, signals for early identification and rapid initiation of treatment both symptomatic as well as locating root cause and managing effectively to avoid further damage . The qSOFA score which is also known as quick sequential organ failure assessment is a bedside assessment tool to identify patients with suspected infection who are at the greatest risk of developing sepsis, that leads to poor outcome, outside critical care units . The third international consensus definition for sepsis recommends qSOFA to be used as a simple bedside prompt to identify infected patients who are likely to be septic . bThe third international sepsis consensus defines sepsis as “life-threatening organ dysfunction due to a dysregulated host response to infection”, recommending two elements criteria for clinicians, infection and acute life-threatening organ dysfunction . SOFA-the sequential organ failure assessment tool is recommended by sepsis-3 to quantify the severity of organ dysfunction, morbidity and to estimate the mortality risk. Higher the SOFA score, the greater the risk .
As there is no specific diagnostic test to confirm sepsis diagnosis it, needs prompt on- time clinical monitoring and vigilance to the deviated presentation of the otherwise normal course of infection to pick up with the evidence of organ malfunctioning. In 1991 the consensus conference held by ESICM and SCCM intended to clinically define sepsis by formulating systemic inflammatory response syndrome criteria to infection which was later referred to as sepsis-1, further this sepsis-1 criteria was refined in 2001 and denoted as sepsis-2 criteria. By the intense worship of patho-biologists, clinical trial and epidemiological evaluations the task force during their 2016 consensus coined sepsis-3 definition and circulated it to the professional societies globally. They stressed the importance of using clinical assessment scores like SOFA and qSOFA scores .
As per the recommendations given by sepsis 3 suggested the use of organ dysfunction assessment tools to identify patients with sepsis. The most commonly used tools like SOFA score and few others proved to be effective in identifying sepsis and to grade the level of organ dysfunction and the morbidity and mortality risk prediction based on the findings .
The increase in SOFA score more than 2 proved to predict that the patient is at increased risk of developing organ dysfunction that can lead to an increase in morbidity and mortality . The third international consensus suggested and recommended the use of qSOFA as a prompt to identify the patient at risk of developing sepsis and as a tool to predict morbidity/mortality .
The qSOFA is not a diagnostic tool but it is said to be the warning signal to the clinicians that possibly could direct the need for further assessment, and to be vigilant to identify organ dysfunction at the earliest to escalate the appropriate care for the patient without even a previously recognized infection or to identify the patients with the possibility of developing sepsis .
Most of the Health care set up especially with the emergency and critical care units has made it mandatory to use scoring systems to identify sepsis at the earliest. This is backed with the vigilant monitoring of vital clinical parameters to detect organ dysfunction at the earliest during triage in the emergency department .
These prediction tools can be measured on all the patients who get admitted to the emergency department and in the intensive care unit for early detection and prediction of morbidity and mortality risks .
The information derived has got multifaceted benefits like to provide the family with the anticipatory prognosis, to improve the quality of care provided, and to avoid life- threatening consequences of organ dysfunction and failures. And also, to improve the quality of life of the survivors which gets complicated due to debilitating effects of organ dysfunction and failures .
The Centre for disease control in its campaign stressed upon "get ahead of sepsis" realizing the fact of detecting sepsis at the earliest is the only way to reduce the high mortality rate associated with sepsis because of its nature of rapid deterioration and in the case of survivors to reduce the rate of patients being discharged to hospice care after organ failure sets in. Hence it urges for early recognition and initiation of prompt management of sepsis .
The CDC director Brenda Fitzgerald, said that detecting sepsis early and starting immediate treatment is often the difference between life and death. The mentoring work starts with preventing infection that causes sepsis. ‘Get Ahead of Sepsis’ stress on suspecting and identifying the sepsis at the earliest by the health care professional is very essential and vital initial step to stay ahead of sepsis .
The health care facilities should have a well-established pathway for the management of sepsis which includes tools or prompts that can be used on patients fulfilling inclusion criteria for early detection. Based on which policies can be made to manage the patient effectively. That includes the checklist to manage the factors that contribute to the development of the sepsis with prime focus on host factors. Vigilantly framed policies to tackle healthcare-related sepsis inducing factors by having antibiotic policies, asepsis policies, pathology vigilance to track the culture-positive with pre-set reporting protocols etc .
Since there is no well-proven prompt or tool to identify sepsis at the earliest, it became prime importance to identify the effective tool, even though qSOFA and SOFA has been tested before for the same purpose, it has to be tested in multiple centers to rule out its applicability. SOFA is recommended by Sepsis-3 as a tool to identify acute organ failure and qSOFA by third international consensus as a bedside prompt which doesn't need any supportive investigation. Since sparse information is available in the Indian scenario regarding the utility of these tools, testing it on Indian set up to identify the sepsis at the earliest becomes essential.
The surviving sepsis campaign along with the Institute for Healthcare Improvement insisted upon the importance of creating bundles and guidelines to help the clinicians to deliver effective management based on the direction lead by them . Among all the guidelines and bundles made by world-renowned team and societies stress is made on early detection which is felt as a paramount for both sepsis caused by host- related insult and that develop later by healthcare-related factors .
Creating a check for sepsis at healthcare setups and communitylevel needs well- formulated team based algorithms, with periodic reassessments and vigilance that starts with ethically approved early detection protocols, utilizing standardized tools.
"Comparative study between qSOFA and SOFA of early detection of sepsis in patients admitted in critical care unit".
Objectives of the Study
To assess sepsis in critically ill patients using SOFA.
To assess sepsis by using qSOFA scorings system.
To compare the SOFA score and qSOFA score in early detection of sepsis.
Sepsis: According to the Third International Consensus Definitions for Sepsis is “Sepsis is defined as life-threatening organ dysfunction caused by a dysregulated host response to infection” . In this study “Sepsis” refers to the detection of organ dysfunction evident by predictor scores.
Detection: According to oxford dictionaries detection is “the process or action of detecting the presence of something concealed” . In this study “detection” stands for detecting sepsis in critically ill patients at the earliest.
Intensive care unit: According to Merriam-webster dictionary Intensive care unit is “a section of a hospital where special medical equipment and services are provided for patients who are seriously injured or ill” . In this study “Intensive care unit” refers to the unit at the hospital where critically ill patients are the group of people who needs constant monitoring and interventions are treated.
qSOFA-quick sepsis-related organ failure assessment: According to the Third International Consensus Definitions for Sepsis The qSOFA is “a bedside prompt that may identify patients with suspected infection that are at high risk for a poor outcome outside the intensive care unit” . In this study “qSOFA” is a tool to detect sepsis that helps in planning treatment and predicting mortality
SOFA-Sequential Organ Failure Assessment: According to the European Society of Intensive Care and Emergency Medicine SOFA is “a Score that Predicts ICU mortality based on lab results and clinical data” . In this study, “Sequential Organ Failure Assessment (SOFA) Score” is a tool used to Predicts ICU mortality based on lab results and clinical data
Assumptions of the study are:
• Identifying sepsis at the earliest may help in the early initiation of measures to prevent further deterioration.
• qSOFA may be an effective tool to identify sepsis at the earliest, as it does not need biochemical values.
• SOFA score may help to identify sepsis in patient admitted at critical care units.
The study is delimited to:
• Study is limited to 100 subjects, 50 each for qSOFA and SOFA Scoring.
• One tertiary care hospital in Navi Mumbai.
• Patients in Critical Care Units for SOFA scoring.
• Patients at Emergency room for qSOFA scoring.
In general, the Conceptual frameworks are the synthesis of researchers intended research activities that are systematically framed and placed in order, to carry out the process effectively .
The core objective of this study is to identify sepsis at the earliest Using qSOFA and sofa The conceptual framework used in this study is Ida Jean Orlando's 'Theory of Deliberative Nursing Process' .
The theorist presented three essential elements:
• The behaviour of the patient.
• The reaction of the nurse.
• Action is taken to the benefit of the patient.
• The behaviour of the patient.
The first element based on the theory is to identify the patient's response to infection
Identifying the signs of dysregulated host response to infection paves the need for early detection of deviations. As explained by the theorist the assessment of the patient on an individual basis can be accomplished by using tools like qSOFA and SOFA.
The tools which have been carefully framed based on evidence with the specific purpose to assess the system-wise deviations that sepsis can cause help the practitioner to identify the patients who are at risk of developing sepsis.
The reaction of the nurse
The second element based on the theory is the reaction based on the findings of the assessment. After the assessment the reaction of the healthcare team can be tuned towards approximating the deviations in the critical period to prevent Dysregulations to cause irreversible damage. The nurse practitioner has to react by conveying the finding to the team and act hand in hand by up-regulating supports provided or initiate one which fits within the professional profile limitations based on the demand of the situation. The second step about sepsis can be co-related to damage control measures that have to be done to stabilize the patient and to keep a check on the Dysfunction cause by the Dysregulations.
Action is taken to the benefit of the patient
The third step of the theory can be met by initiating the specific measures guided by the patient presentation and the assessment findings, accordingly to eliminate the underlying cause that initiated the Dysregulations.
This chapter gave an intense understanding of the current situation both globally as well as nationally. By understanding the incidence and the burden of sepsis and the manageable nature of it, if it is identified at the earliest, boost the researcher to work further to find an effective tool to identify it as early as possible.
This chapter deals with the introduction, needs of the study, problem statement, objectives of the study, operational definitions, and conceptual framework used in the study, and the next chapter will deal with the review of the literature.
A Review of literature is a systematic search of specific topic from scholarly sources. Literature review will throw light on current phenomenon, theories and recommendations relevant to the study topic. The general approach to review of literature includes identifying, analyzing and evaluating various research articles, books and journals. It can also help us to understand the impact geographical differences and other demographic data can cause .
The review of literature for this study is done using studies published on journals like NCBI, MEDSCAPE, NP Journals, JAMA Network Journals, Research gate Journals, Indian Journal of Critical Care Medicine, the LANCET Journals, Lung India-Official publication of Indian Chest Society.
The review of literature for the current study is segregated and presented under the following sections
Concept and definition of sepsis…
• Literatures related to Incidence of sepsis and sepsis burden at the national and global level
• Predictors of sepsis which are prevalently used its need and impact on positive patient outcome and mortality prediction.
• SOFA score related studies
• qSOFA score related studies
Third international consensus definition of sepsis
Information was taken from the article published on JAMA network journal on February 23rd 2016. This article is about the third international consensus organized by fine experts to redefine sepsis, during this consensus the definition of sepsis was refined and the approach to sepsis was also regenerated .
The new definition was framed as “life threatening organ dysfunction caused by a dysregulated host response to infection”. They further added that organ dysfunction can be detected by using Sequential organ failure assessment which when scored more than 2 points warrants hospital mortality greater than 10%. They also recommended qSOFA the new prompt which can be used at bedside to score the patients at risk of developing sepsis and to predict mortality associated with it. qSOFA was formulated to score the patients outside ICU like Emergency department or ward .
They insisted that the new definition and updates of clinical criteria should be used in the place of the old definitions and clinical criteria that will in turn assist in early detection and timely initiation of preventive or corrective management upon patient who falls at the risk criteria of developing sepsis .
Studies related to the incidence of sepsis and sepsis burden at the national and global level. A study which was published in the journal of Indian society of critical care medicine, September 21st, 2017 provided some essential data about Indian perspectives. This study described about the epidemiology of sepsis in the critical care unit of a tertiary care hospital in India. This was conducted from June 2006 to May 201. The study mentioned that during the five years period there were total of 4711 admissions out of which 286 admissions were with sepsis. During the period of the study, the patients admitted with sepsis was 56%, mortality at ICU was 63.6%, in hospital mortality and mortality within 28 days period 62.8%. The median length of ICU stay was found to be 8 days and the percentage of mortality which was caused due to sepsis was 85% .
Another study published on LANCET on global incidence and burden of sepsis presented that the incidence of developing sepsis varied among global locations. They found that 85% of incidence of sepsis occurred in low and low middle or middle SDI (Socio demographic index) country. The definition of sepsis is operationalized in various healthcare organizations by using standardized scoring tools like qSOFA and SOFA . A retrospective cohort study conducted between 2009 till 2014 at 409 academic community hospitals in UDA to evaluate the incidence and mortality trends caused by sepsis, using electronic health record data collection based on sepsis-3 criteria. Found increase in incidence by 10.3% and decline in hospital mortality by 3.3%. But there was no change noted in death or transferring, discharging .
A retrospective cohort study analyzed medical record of randomly selected 568 adults admitted at 6 academic hospitals at USA from January 2014 till December 2015, to assess the prevalence of sepsis. 300 subjects were included out of which 198 patients died because of sepsis 34.9% with the class interval of 95%, the researcher discussed that most patient had co morbidities, and among the patients who developed sepsis better hospital care could have prevented sepsis related mortality hence further innovative preventive care pathway following sepsis diagnosis has been recommended .
Studies related to the predictors of sepsis
A retrospective cohort study of patients presented at ED of urban academic hospital conducted from November 2008 to October 2010 for early recognition of sepsis at the emergency department among patients who can progress to severe sepsis or shock during their stay at the hospital can be treated on time so as to enhance patient outcome This cohort consisted of 582 patients who got admitted to emergency department with nonsevere sepsis and monitored their progress with the predefined formulated predictors. Hence 108 patients (18.6%) were found to progress to sepsis. From the predictors used in this study mentioned that Sr. Albumin<3.5 g/dl and diastolic blood pressure<52 mmHg were the independent predictor of early sepsis related signs and symptoms among patients suspected to have sepsis. This study recommended the need for predictors will enhance the early detection of sepsis .
A study which was conducted at medical ICUs of tertiary care hospital situated at south India, from January 2013 to December 2014, indicated that APACHE score>25, SOFA score of 8.5 respectively during the time of admission and the need for the use of invasive ventilation were identified as the independent predictor of ICU mortality among adults due to sepsis. Hence this study recommended the need for the use of predictors in early detection of sepsis and initiating measures following the interventions presented by surviving sepsis campaign will improve the outcome of the patient .
A retrospective study conducted between 2009 June and 2014 February at a 54 bedded medical surgical intensive care unit, using the predictor scoring system like Apache II and APACHE III identified total of 2,054 patients who has developed sepsis. The score of APACHE 11 ranged between 19 ± 7, and APACHE III ranging between 68 ± 28. The estimated hospital mortality rate was 18.3% and ICU mortality was found to be 11.8%. But they mentioned that APACHE II to be better than APACHE III as it found to be more complex and needs more variables and data which were time consuming .
A study conducted at emergency department (ED) or hospital wards from November 2008 until January 2016 to test the effectiveness of qSOFA opposed with other predictive tools. Found that sensitivity of qSOFA as 54% and specificity was 67%, concluded that performance of other predictors used to score early warning signs are accurate than that of qsofa . A secondary data analysis study conducted to compare the performance of qSOFA which is recommended by sepsis-3 with SIRS sepsis-1 recommendation among 1,689 patients presented at emergency department with suspected infection at a tertiary care hospital in the year 2017. The researcher found that performance of qSOFA was superior to SIRS in predicting in hospital mortality related to sepsis .
A prospective cohort study conducted at Tertiary care teaching hospital in south India on patients admitted at ICU for 6 months, projected that SOFA out performed MEDS and PIRO but underperformed APACHE II and recommended the use of APACHE II to predict sepsis .
A study conducted using computer based automated algorithm to obtain information from open source opposed to PhysioNet 2019. The researcher gathered 853 ICU patients from 104 teaching hospitals to identify sepsis at the earliest. Total of 60,000 patients admitted to ICU were analyzed opposed to 40 clinical presentations on hourly basis, applying sepsis-3 criteria.
Researcher found that the computer based approach detected sepsis hours prior to clinical detection, researcher recommended further studies need to be conducted to generalize the findings .
Literature related to the use of Sofa score
A prospective observational study to evaluate the predictive efficiency of SOFA scoring tool on patients enrolled at emergency department at Carolinas medical centre an 800 bedded teaching hospital, from 2005 November to 2007 October. Scoring was done at time zero (T0) and at 72 h post ICU admission (T72). Out of the 248 patients included in the study 51 died (51/248) of sepsis related complications. The rate of mortality was found to be 21%. The study found that accuracy of the scoring done with SOFA to predict in hospital mortality was fair to good .
A Prospective observational cohort study conducted from April 1 to July 31, 1999 at 31 bedded medico surgical ICU at a university hospital in Belgium to determining the effectiveness of SOFA Score. Total of 352 patients were assessed using SOFA score. They found that scoring the patient during the first few days of ICU admission found to be a good indicator of the patient outcome. Irrespective of the initial score and increase in the following subsequent reading during the first 48 h of ICU stay indicated mortality rate of 50% [35,36].
A single center prospective observational study using SOFA score was conducted for 12 months period from May 2013 to April 2014, at a medical and neurological ICU, of a large tertiary care academic hospital. They intended to evaluate correlation existing between SOFA score with the patient outcome. They recorded the score at the time of admission to ICU and later after 48 h [37,38]. Total of 84 elderly patients were scored during the period of study and the data was analyzed. This study found that SOFA scoring done after 48 h are effective in monitoring and predicting the patient outcome unlike done just once during admission to ICU. The SOFA score which was getting low from the better with good specificity and lower sensitivity. The author recommended the use of qSOFA as a predictive tool .
A systematic review of 45 retrospective and prospective observational studies done by following PRISMA-P methodology, including studies that were published until 2018, April. The sample size was 413,634 patients; the study setting was emergency department, ICU and general ward, pre hospital emergency care provider at North America, Asia and Australasia. The AUROC of qSOFA ranged from 0.58–0.81, sensitivity ranged from 0.1-0.74 and 0.42–0.97. The researcher concluded that the AUROC of qSOFA in predicting in hospital mortality was poor and it is not good to use in routine clinical practices .
Another study was conducted at south-western part of Pennsylvania in the year 2012, with the objective of determining the predictive validity of qSOFA, collected samples from nine hospitals at Pennsylvania using the electronic health records criteria method to collect samples of adults who were suspected to have infection. The AUROC of initial qSOFA was 0.83 (95% CI, 0.82-0.84), at 24 h AUROC=0.86, and mean at 48 h was AUROC=0.86. Hence they concluded that serial qSOFA scoring over time is efficient in identifying patients who are at high risk for developing sepsis .
A study to check the predictive performance of qSOFA in developing countries, randomly sampled 752 patients admitted to a large tertiary care hospital at Jamaica between the years 2015 to 2016. The objective of the study was to determine how qSOFA predicts the need for intensive care and death among those patients who were suspected with infection. The study found that those patients who turned positive to qSOFA on admission were three times more likely to need prolonged ICU stay or die. Specificity of qSOFA was found to be high (84%) but sensitivity was low (39%). Hence the author suggested to combine the qSOFA with SIRS criteria. The study concluded that qSOFA score is a useful predicting tool in predicting the need for ICU stays and death .
A systematic review and Meta–analysis on articles published till March 2018 on use of qSOFA on patients with community acquired pneumonia. 17,868 samples with pneumonia were studied, found that the patients with qSOFA more than or equal to 2 with pneumonia had increased risk of death. The risk ratio was 3.35 with poor sensitivity. The researcher concluded that the association of qSOFA in predicting mortality among patients with community acquired pneumonia is high .
Comparative studies of qSOFA, SOFA and other standardized predictors
Another retrospective secondary study analysed 1 randomised clinical trial and 8 cohort studies between 2003 to 2017 of 6569 adults’ patients who were hospitalized with suspected infection. Concluded that qSOFA AUROC to be 0.70 was better than other predictive tools. Since this study was conducted at different geographical area the author recommended further research to confirm. Recommended the use of qSOFA outside ICU as its predictive quality to identify sepsis among the study population from LMICs was good .
A retrospective study conducted by 2012 to 2014, on patients with the diagnosis of pneumonia. Using mortality predictive tools like qSOFA, CRB and CRB-65. The investigator interpreted that AUC of qSOFA was similar in all three tools. But mortality prediction of qSOFA score more than 2 was better than other tools . The correlation of qSOFA score from 0-3 in relation to ICU admission was 3-9% to 45.3%. Concluded that those patient with high qSOFA score demonstrated high ratio of hospital mortality and ICU admission as compared with CRB .
Another prospect observational study comparing qSOFA and SOFA in predicting the mortality associated with septic shock among patients in emergency department in low middle-income country. Total sample size for final analysis was 760 patients, using qSOFA and SOFA criteria, on arrival, followed by continuous monitoring of the progress, recovery or deterioration thereafter.
For patients with severe sepsis, The AUROC of qSOFA was 0.92 (95% CI: 0.89–0.94), sensitivity was 96% and Specificity was 87%. And the AUROC of SOFA was 0.63 (95% CI: 0.55–0.70) with sensitivity of 71% and specificity of 57% concluded that qSOFA score to be an effective tool in predicting the mortality upon SOFA score when applied on severe sepsis and patient who are in septic shock. They recommend having further evidence to use it outside ICU at low income countries .
An observational study which was conducted at a single centre academic urban tertiary care 500 bedded hospital at USA by Churpek and Colleagues, from 2008, November till 2016 January, compared qSOFA with NEWS, SIRS, and MEWS. The total study population was 30,677 patients who were suspected to have infection.
They addressed qSOFA as risk predictor among suspected patient population and a prompt for the provider to diagnose sepsis. NEWS was better than all other predictors, with qSOFA preceded to be best to SIRS. When comparing NEWS with qSOFA, the specificity of qSOFA was high in specificity than NEWS, suggested that qSOFA can be used but should not replace other established early warning scoring system in order to detect suspected sepsis .
This chapter deals with the literature review from various reliable sources with the intension to get a guidance of how to carry on with the research in Indian setup, to understand the recommendation made regarding the sepsis prediction. The purpose to review the literature since first definition of sepsis was made by 1996 till today. And to evaluate standardized tools like qSOFA and SOFA can be effectively utilized in mortality prediction and identification of sepsis at the earliest to improve the patient outcome and to reduce the burden caused by sepsis both nationally and internationally.
A research is a systematic way of analyzing a topic under study which could be a novel or something based on previous work done .
Research methodology is the compilation of the most vital parts of research which is arranged in a systematic manner and with prescribed description .
The properly drawn research methodology will guide the researcher right from the beginning like identifying the area of the research, the process to adapt and design of research, data collection principles, analysis strategies, ethical inputs, the obstacles that can be anticipated or the recommendations that has to be focused on .
This chapter deals with the methodology that is been chosen for the present study, that includes the research approach, research design, variables under study, population, sample, sampling technique, graphic representation of the design, setting of the study, tool, its content validity, reliability, pilot study, plan for data collection, data gathering process, and the process of data analysis.
The present study aimed at comparing qSOFA and SOFA in detecting sepsis at the earliest among patients at emergency department and critical care units respectively in hospitals at Navi Mumbai.
Planned research procedures that follow distinct approach will yield what it is intended to. The research approaches in other words are the actual plan of action.
The approach that a research investigator use, contains the vital frameworks based on which the whole study evolve and revolve.
It is determined based on the problem under study. In general the research approaches are divided into two essential categories.
• The approach that is used for data collection.
• The approach that is used for data analysis and reasoning.
• The approach used for this research is prospective observational quantitative method.
The research design is the blueprint of the plan of action which evolves after the determination of the approach of the study.
The research design equips the researcher with the flow of the study methodologist. The problem under study will determine what type of research design has to be adapted. A suitable research deign will enable researcher to obtain the evidence effectively that can address research problem under study .
The research design used for the current study is nonexperimental quantitative research design among patients at emergency department and critical care units of selected hospitals at Navi Mumbai.
Schematic representation of research study and design Tool 1 – qSOFA
Setting of the study
Setting refers to the surroundings, situation, location and time frame at which something forms or occurs .
In this study setting refers to Tertiary care teaching hospital at Navi Mumbai.
In research population refers to large group of subjects sharing well defined and distinguishable characteristic in relation to the interest of the research .
In this study population comprises of all the patients presenting at Emergency department and critical care units at tertiary care hospitals in Navi Mumbai.
The target population are the entire set of the person or the objects that the researcher study upon to evaluate the problem statement under study .
In this study target population is all critically ill patients with suspected infection presenting at emergency department, admitted at critical care unit in selected tertiary care hospitals at Navi Mumbai.
It refers to the concentration of the samples that adapt to designated criteria and accessible to the researcher as a group of subject for the study. It is actually a subset of the population which was targeted. The accessible population is otherwise called as study population .
In this study accessible population refers to patients presented at emergency department with suspected infection and critically ill patients admitted to MICU, SICU and EMSICU of a tertiary Navi Mumbai.
Sample is defined as the unit of the population elements that represent the target population .
In this study, the sample comprises of the entire patient presented at Emergency department with suspected infection and all those patients admitted in the critical care unit with suspected infection, during the period of data collection
Sampling Size and Technique
Sample size: It is the number of people who are included in the study . Sample size of 100 were selected for the study, 50 sample for SOFA and 50 sample for qSOFA
Sampling technique: It is the process of selecting a part of the population to represent the total population .
In this study non-probability convenient sampling technique was used to select the sample based on inclusion and exclusion criteria. The process is continued until 100 representative samples were collected.
Inclusion criteria: It is the eligibility criteria which specify the exact population characteristics by which it can be decided whether they could or would not be classified as a representative of the population .
Exclusion Criteria: The specific criteria of the study population if present could lead to difficulty in analysis or false reading .
In this study the inclusion and exclusion criteria are the following.
The Inclusion criteria:
• Patients who are ≥ 18 years of age.
• Patients who fulfill qSOFA and SOFA criteria.
• Are suspected to have infection.
• The Exclusion criteria are
• Patients who are less than 18 years of age
• Patient who are brought dead
• Patient who have DNR request.
Data collection technique
Data collection technique: It is a technique adopted by the researcher to collect data in a systematic manner .
In this study the data pertaining to qSOFA and SOFA criteria was collected prospectively by obtaining data from patient, records and monitor. At emergency department and critical care units.
Data collection instrument/tool: The research tool also called as the research instruments is a device used to collect the data. This instrument helps the measurement and observation of variables of interest. The type of data collection instrument used in the study is determined by the data collection technique selected .
This is a prospective observational quantitative study comparing qSOFA and SOFA score in detecting sepsis at the earliest
Description of the instrument: Based on the objectives of the study, the investigator used qSOFA and SOFA score for data collection. The researcher approached the official authority for the grant of permission to use the tool. After obtaining permission from the issuing authority and hospital ethical committee the tool was used for data collection
Tools used in this study are qSOFA and SOFA score
qSOFA- The quick sepsis related organ dysfunction assessment score.
It is prompt which can be used out of the ICU in identifying patients who are at high risk of developing sepsis.
It is calculate in reference to the mortality ratio. The qSOFA score ≥ 2 are considered as positive for qSOFA and the patients are categorised as having increase risk of developing sepsis. The qSOFA is recommended by Sepsis-3 as a bed side prompt that can be used outside the ICU for early detection with minimal vital parameters.
It is encompassed of three criteria with one point designated for each, they are, 7 Systolic blood pressure which is less than or equal to 100 mmHg.
• Respiratory rate above or equal to 22 breaths per minute.
• Altered mentation-GCS less than .
• SOFA–Sequential organ failure assessment score. SOFA score is designed in such a way to provide insights into the acute onset of organ dysfunction in patients admitted at critical care units. The score more than 2 indicated organ dysfunction .
It is calculated by scoring 6 different systems and awarded 1 point for each variation. SOFA score more than 2 is criteria for diagnosing organ dysfunction. The increase in score reflects the worsening of the organ dysfunction.
The systems assessed are respiratory in relation to pao2/Fio2 ratio, cardiovascular in relation to MAP and use of vasopressors, liver in relation to bilirubin level, coagulation derangement in relation to platelets, kidney in relationship with increase in creatinine level and decrease in urinary output, central nervous system by assessing GCS .
The initial SOFA score was calculated during the first 24 h of ICU admission. And those patients who turned positive were score for two more days.
Scoring and interpretation of the instrument
|Systolic blood pressure ≤ 100||1|
|Respiration ≥ 22||1|
Table 1: The qSOFA criteria.
• 1 point for low blood pressure SBP ≤ 100 mmHg,
• 1 point for high respiratory rate of ≥ 22 breaths per min, 1 point for altered mentation -Glasgow coma Scale<15.
• qSOFA score 2 or more Positive qSOFA score less than 2- Negative
• The score ranges from 0 to3 points. The presence of 2 or more qSOFA points near the onset of infection was associated with a greater risk of death or prolonged intensive care unit stay.
|S.no||SOFA criterion variables|
|2||Glasgow coma scale|
|3||Mean arterial pressure or administration of vasopressors required|
|4||Bilirubin (mg/dl) (μmol/L)|
Table 2: SOFA criteria.
|Pao2/Fio2 ration/FiO2 (mmHg)||SOFA score|
|<200 and mechanically||3|
|<100 and mechanically ventilated||4|
|MAP or the use of vasopressors||SOFA score|
|MAP ≥ 70 mmHg||0|
|Dobutamine (any dose)||2|
|or the use of dopamine ≤ 5 µg/kg/min|
|Use of any of these drugs Dopamine>5 µg/kg/min Epinephrine ≤ 0.1 µg/kg/min||3|
|Non-epinephrine ≤ 0.1 µg/kg/min|
|Use of any of these drugs Dopamine>15 µg/kg/min Epinephrine ≤ 0.1 µg/kg/min||4|
|Non-epinephrine ≤ 0.1 µg/kg/min|
Table 3: SOFA score more than 2 indicated organ dysfunction
|Glasgow coma scale||SOFA score|
|Bilirubin (mg/dl)||SOFA score|
|Creatinine (mg/dl)||SOFA score|
|3.5–4.9 (300-440) (or<500 ml/d)||3|
|Less than 5 ml/h||4|
|or less than 200 ml/d|
Table 4: SOFA score more than 2 indicated organ dysfunction.
Content validity of the tool
Validity: It is defined as the degree to which an instrument measures what it is supposed to measure or the degree to which it is used to provide data, which is compatible with other relevant evidence .
Content validity: It refers to the method of measurement that actually measures the expected content. It involves a methodical examination of the tool to determine whether it covers all the aspect of the study . qSOFA and SOFA are standardised tools, official permission was taken from the authorities.
Issuing authority provided the researcher with freehold to use the tools without creating any modifications. Additionally 12 experts’ opinion was taken and incorporated their suggestions and recommendation in the demographic part of data collection.
Ethical approval was obtained from the Institutional Ethical Review Committee of MGM Institute of Health Science, Kamothe, consisting of 12-15 members. Ethical approval was obtained from institutional ethical review committee of MGM Institute of Health Sciences Kamothe. Permission from higher authority of the hospital were obtained to conduct the study Explanation of the process to the subject and relatives. The matter was read before the patient or relative and their signature was taken on the consent form.
Pilot study is a small scale or a trial version of a study done as a preparatory measure before conducting a major study, which helps in assessing the feasibility and the refinement needed if any . Pilot study was conducted during December 1st to December 31st of 2019 at MGM medical hospital Kamothe Navi Mumbai on 20 patients, 10 each for qSOFA and SOFA scoring. The pilot study indicated that both qSOFA and SOFA is an effective tool, but it has to be ascertained with larger sample. The pilot study gave the researcher the insight into the actual process of data collection and analysis. The design and tool were found to be feasible.
Data collection process
Written permission was taken from the Medical Superintendent of MGM hospital Kamothe Navi Mumbai. Data collection was done from 1st January to 29th February 2020 using non probability convenient sampling. Patients who meet inclusion criteria were selected. Informed consent was obtained. The data collection of qSOFA was done at Emergency department and for SOFA was done at critical care units. qSOFA sample was collected on patients with suspected infection presented at Emergency department, and follow up was done based on the fulfillment of the criteria. Those patient became positive to qSOFA with ≥ 2 points were further observed for signs of sepsis for 3 to 7 days until signs of sepsis appear, diagnosed with sepsis, shifted toward or dead. And the negative patient was observed following 24 h. For those patients who fulfilled inclusion criteria for SOFA were scored using SOFA tool. The patients enrolled for SOFA were scored for 3 days and positive patients were followed up for minimum 3 to maximum 7 days or until death or shift to ward. And the negative patient was observed once after 24 h. The obtained values and demographic data were assessed using frequency tables, sensitivity and specificity analysis. To determine the percentage of true positive and true negative prediction capabilities of the tools. And the final values were compared using comparative table.
Process of data analysis
Data analysis is a process used to convert raw data into operational data, the prime indication of using data analysis is to answer the research question, test hypothesis or for both . The plan for data analysis included both descriptive and inferential statistics. The collected data was organized, tabulated, and analyzed based on the objectives of the study by using descriptive statistics, frequency and percentage, inferential statistics and AUROC. Analysis of the study is organized and presented in the following sections:
Section 1: Distribution of patient data collected for using SOFA score based on demographic data.
Section 1.2: Distribution of Clinical parameters and signs of data collected for using SOFA score.
Section 1.3: Distribution of clinical parameters among patient who developed sepsis.
Section 1.4: Analysis of clinical variables collected using the SOFA score.
Section 1.5: Distribution of ABG analysis of patients who developed sepsis.
Section 1.6: Analysis of clinical parameters collected using the SOFA score.
Section 1.7: Analysis of Clinical parameters of patients monitored using SOFA score with Mann-Whitney U test, Wilcoxon W test and Z test
Section 1.8: Co-relation of clinical parameters detected with Mann-Whitney U test, Wilcoxon W test and Z test
Section 1.9: Analysis of patients SOFA Score for Sensitivity and specificity interpretation.
Section 1.10: Analysis of AUROC curve of SOFA score variable.
Section 2: Distribution of patient demographic data collected for using qSOFA score.
Section 2.1: Distribution of patient variables based on elements of qSOFA.
Section 2.2: Distribution of clinical parameters of patients who were included in qSOFA score analysis and developed sepsis.
Section 2.4: Analysis of clinical parameters of qSOFA using Mann-Whitney U
Section 2.5: Analysis of Sensitivity and specificity of qSOFA score interpretation.
Section 2.6: Distribution of AUROC of qSOFA score.
Section 2.7: Comparison between qSOFA and SOFA based on the outcome.
This chapter deals with the Research Approach and Design , variable under study, setting of the study, population, sample and sampling technique, data collection technique, data collection instrument/tool, intervention programme, ethical consideration, pilot study, data collection process, plan for data analysis and the next chapter would deal with the data analysis and its interpretation.
Statistical analysis is an organized way of arranging, analysing the collected data and exploring it to discover the outcomes, presenting it in patterns and visually depicting figures that describes the findings and hence will help to co-relate it with the objectives . This chap t er pr esen ts the analy sis and interpretation of data collected from 100 critically ill patients with suspected infection. Out of which 50 patients samples collected using qSOFA scoring tool and 50 patients samples collected using SOFA scoring tool . Analysis of objectives was done with the help of descriptive and inferential statistics. The data collected was first organized and coded and entered into the computer. The data processing was done using R statistic package. Data is described in terms of frequency, percentage, data comparison was done using mean and standard deviation, test of normality Mann-Whitney U test, Wilcoxon W and Z test to compare the significance of difference between the outcomes. Calculated the Sensitivity and specificity and AUROC of the data collected using qSOFA and SOFA scores [62,63].
• To assess sepsis in critically ill patients using SOFA.
• To assess sepsis in critically ill patients using qSOFA .
To compare of SOFA score and qSOFA score in early detection of sepsis Analysis of the study is organized and presented in the following sections:
Section 3: Distribution of patient data collected for using SOFA score based on demographic data.
|Age group (years)||f||%|
|18 - 29||6||12%|
|30 - 39||3||6%|
|40 - 49||11||22%|
|50 - 59||7||14%|
|60 - 69||12||24%|
Table 5: Age and gender characteristics of patient data collected for using SOFA score Socio demographic characteristics, n = 50.
Table 5 shows 64% of patient population who became positive to SOFA score were male and the people at early and late adulthood. And the true positive percentage of SOFA score was 73% .
Section 3.1: Distribution of clinical parameters assessed for SOFA sampling.
|CLINICAL PARAMETERS AND SIGNS||DEVELOPED SEPSIS||NO SEPSIS||Total|
|Altered mental status||6.41||2.54||13.86||1.33||10.58||4.2|
Table 6: Clinical parameters and signs, n=50.
Table 6 shows the mean and standard deviation of the clinical parameters used in the demographic data of patient who were included in the study for SOFA analysis and found to have developed sepsis. The patient who developed sepsis showed significantly low GCS, SPO2 and diastolic blood pressure .
Section 3.2 Distribution of clinical parameters based on data of SOFA among patient who developed sepsis. n=50
Figure 4 Depicts the co-relation of clinical parameters distribution in patients developed sepsis. The mean GCS-6.41, SPO2–86.77, RR -33.18, HR-117.09, and hypothermia-101.58 was found to be significant with the development of sepsis [67,68].
Significantly low GCS, increased RR and hyperthermia were noticed among patients who developed sepsis .
Section 3.3: Distribution according to variables of ABG among SOFA scored patients who developed sepsis
Table 7: Distribution of ABG variables, n=50
Table 7 shows the significance of ABG values in the SOFA sampled patients who developed sepsis. There is significant corelation between sepsis and increased lactate levels, increased PCO2 and HCO3 .
Section 3.4.: Pictorial distribution ABG variables among SOFA scored patients who developed sepsis
Figure 5 Show the significance of alteration in ABG among SOFA samples who developed sepsis were distributed as lactate-4.89, HCO3-31.16, Pco2-46.18, Po2-114.05 and PH-35 as the mean values. Significant co-relation between sepsis and increased lactate levels, increased PCO2 and HCO3 noticed among patient who developed sepsis .
Section 3.5: Analysis of clinical variable among the SOFA sampled patients who developed sepsis
|PaO2/FiO2 ratio, O 1||304.41||58.77||300|
|PaO2/FiO2 ratio, O 2||340.86||106.8||316|
|PaO2/FiO2 ratio, O 3||320.14||87.64||306|
|GCS, O 1||6.27||2.35||8|
|GCS, O 2||6.14||2.53||8|
|GCS, O 3||5.86||2.62||8|
|MAP or MAP with Vasopressor, O1||79.09||18.94||73|
|MAP or MAP with Vasopressor, O2||77.14||14.87||71|
|MAP or MAP with Vasopressor, O3||76.05||14.52||73|
|Creatinine or Urine output, O1||3.95||2.15||4|
|Creatinine or Urine output, O2||4.85||2.75||3.8|
|Creatinine or Urine output, O3||5.54||3.09||4.2|
Table 8: Distribution of clinical variable among the SOFA sampled patients who developed sepsis. n=50
Table 8 Shows the analysis of SOFA score among patients who developed sepsis, there is significant relationship between sepsis and the clinical parameters measured using SOFA score, with mean values of GCS-3.41, Sr. Bilirubin of 3.68, Platelets of 59136, and creatinine of 5.54.
Section 3.6: Analysis of Clinical parameters of patients monitored using SOFA score with Mann-Whitney U test, Wilcoxon W test and Z test .
|Mann- Whitney U||p-value||Interpretation|
Table 9: Analysis of ABG values using Mann-Whitney U test, Wilcoxon W test and Z test, n=50
Table 9 Show the significance of increased lactate levels, PCO2 and HCO3 among the samples that developed sepsis. But PH and PO2 were non-significant among the patients who developed sepsis.
Section 3.7: Distribution of clinical parameters monitored using SOFA score in detecting sepsis.
|Mann- Whitney U||Wilcoxon W||Z||p-value||Interpretation|
|PaO2/FiO2 ratio, O 1||71||324||-4.639||0||S|
|PaO2/FiO2 ratio, O 2||134||387||-3.405||0.001||S|
|PaO2/FiO2 ratio, O 3||73.5||326.5||-4.588||0||S|
|GCS, O 1||0||253||-6.152||0||S|
|GCS, O 2||7||260||-6.421||0||S|
|GCS, O 3||6.5||259.5||-6.429||0||S|
|MAP or MAP with||109.5||362.5||-3.886||0|
|MAP or MAP with||62.5||315.5||-4.809||0|
|MAP or MAP with||78||331||-4.513||0|
|Creatinine or Urine||13.5||419.5||-5.788||0|
|Creatinine or Urine||16||422||-5.747||0|
|Creatinine or Urine||24||430||-5.587||0|
Table 10: Analysis with SOFA Variables, n =50
Table 10 Table shows significance to the test of normality with the p value less than 0.05 among all the clinical parameters of SOFA in patients developed sepsis .
Section 3.8: Sensitivity and specificity of SOFA score interpretation.
|Sensitivity||95.45%||77.16% to 99.88%|
|Specificity||39.29%||21.50% to 59.42%|
|Positive Likelihood Ratio||1.57||1.15 to 2.15|
|Negative Likelihood Ratio||0.12||0.02 to 0.83|
|Disease prevalence (*)||44.00%||29.99% to 58.75%|
|Positive Predictive Value (*)||55.26%||47.49% to 62.78%|
|Negative Predictive Value (*)||91.67%||60.55% to 98.75%|
|Accuracy (*)||64.00%||49.19% to 77.08%|
Table 11: Sensitivity and Specificity of SOFA score
Table 11 Shows the interpretation based on sensitivity and specificity obtained from SOFA score. It depicts that sensitivity of SOFA score is 95.45% and Specificity is 39.29%, Which indicates that there is increased ratio of false positive among patients scored with SOFA criteria.
Section 3.9: Analysis of AUROC curve for SOFA score
Figure 6 Shows the AUROC of SOFA score which is 0.67 (77.16% to 99.88% CI), 95.45% sensitivity and 39.29% of specificity.
Section 4: Distribution of patient demographic data collected for qSOFA scoring.
|Age group (years)||f||%||Age group (years)||f||%|
|qSOFA Samples||qSOFA positive|
|18 - 29||11||22%||18 - 29||6||30%|
|30 - 39||7||14%||30 - 39||1||5%|
|40 - 49||6||12%||40 - 49||2||10%|
|50 - 59||7||14%||50 - 59||3||15%|
|60 - 69||10||20%||60 - 69||4||20%|
|Total Positive||37||75%||True Positive||20||74%|
|Total Negative||13||25%||True Negative||13||48%|
Table 12: Socio demographic characteristics of patient data collected for using qSOFA score, n = 50.
Table 12 Among the samples collected using qSOFA score 70% of patient developed sepsis were male population and 30% were at early adulthood and 40% were late adulthood and elderly. And out of 37 Positive cases 20 became true positive which is 74% .
Section 4.1: Distribution of patient’s clinical parameters based on elements of Qsofa
|SYSTOLIC BLOOD PRESSURE|
Table 13: Distribution of clinical parameters of qSOFA score, n=50
Table 13 Shows the distribution of patient variable of qSOFA, the mean of GCS–9, RR-34, Systolic blood pressure-86.50 among the patient who developed sepsis and found to be significant. There is significant relationship between sepsis and low GCS, increased RR and altered systolic blood pressure.
Section 4.2: Distribution of patients’ clinical parameters of qSOFA who developed sepsis
Figure 7 shows the qSOFA clinical parameters of patients developed sepsis. The Mean GCS-9.60, Mean RR-34.10 and the Mean of Systolic BP-86.50. There is significant relationship between sepsis and low GCS, increased RR and altered systolic blood pressure .
Section 4.3: Analysis of test of normality on qSOFA variable
|qSOFA criteria||Mann- Whitney U||Wilcoxon W||Z-Test||P- value||Interpretation|
Table 14: Analysis of test of normality on qSOFA variables, n = 50.
Table 14 Show that there is significant co -relation between sepsis and decreased systolic blood pressure and altered mentation, but the analysis of respiratory rate did not showed any significance with the sepsis.
Section 4.4: Analysis of data based on Sensitivity and specificity of qSOFA score interpretation.
|Sensitivity||#####||81.47% to 100.00%|
|Specificity||37.50%||21.10% to 56.31%|
|Positive Likelihood Ratio||1.6||1.22 to 2.09|
|Negative Likelihood Ratio||0||-|
|Disease prevalence||36.00%||22.92% to 50.81%|
|Positive Predictive Value||47.37%||40.76% to 54.07%|
|Negative Predictive Value||#####||-|
|Accuracy||60.00%||45.18% to 73.59%|
Table 15: Sensitivity and Specificity of qSOFA score
Table 15 Shows the sensitivity and specificity of qSOFA in detecting sepsis and predicting mortality. The Sensitivity of qSOFA was found to be 100% whereas specificity was 37.50%. This indicates the increased ratio of false positive values.
Section 4.5: Analysis based of patients clinical parameter Depiction of sensitivity and specificity of qSOFA in detecting sepsis.
Figure 8 Shows the sensitivity and specificity of qSOFA scoring which depicts that qSOFA has 100% sensitivity whereas specificity of 37.50%. This indicates the increased ratio of false positive values.
Section 4.6: Analysis of AUROC of qSOFA data
Figure 9 shows the AUROC of qSOFA which is 0.70% (81.47% to 100% CI) with sensitivity of 100% and specificity of 37.50%.
Section 4.7: Comparison between qSOFA and SOFA based on the outcome
Figure 10 Depicts that qSOFA has 100 % sensitivity with 81.47% to 100% CI and 37.50% specificity whereas SOFA has 95.45% sensitivity with 77.16% to 99.88% CI and 39.39% specificity .
Section 4.8: Comparative AUROC of qSOFA and SOFA based on the outcome
Figure 11 Shows the AUROC of qSOFA is 0.70% with 95% CI and Sensitivity of 100% The AUROC of SOFA is 0.67% with 95% CI and Sensitivity of 95.45%.
This chapter deals with the analysis and interpretation of data which is categorized into sections according to objective of the study. Analysis was done using descriptive and inferential statistics. Mann-Whitney U test is used because of nonparametric data. Comparison done with bar diagram and AUROC curve.
The current chapter deals with the discussion of the findings of the study, its implication, recommendation for future research in this field, nursing consideration, limitation and summary.
Findings related to the socio-demographic characteristic of patients
This study was conducted on 100 samples out of which 50 samples were collected using qSOFA score and 50 sample were collected for SOFA. The demographic data for both the category was also collected after getting approval from the various experts .
The distribution of demographic data of qSOFA consist of 76% of male population and 24% of female population and the demographic distribution of SOFA consists of 64% of male population and 36% of female population. The demographic distribution of population who are most vulnerable or the population among which sepsis was prevalent was found to be the young, early adulthood and in elderly population was notice with qSOFA samples as well as SOFA samples .
Findings related to SOFA score among patients admitted in the critical care unit
The first reading of the patient recorded using the tool SOFA was done within 24 hours of admission to the critical care unit, followed by two consecutive days of assessment and recording. Those patients who were found to be positive or had SOFA score of more than 2 were tracked for the progress there after until they were diagnosed with sepsis, transferred to ward or diseased. The patients who were shifted to other hospital were excluded from the study .
Findings related to qSOFA score among patients brought to Emergency department
The sample for qSOFA were collected and recorded at the time of presentation to emergency department even before any test reports are available. Those patients who fit the inclusion criteria were assessed and when found positive were recorded and followed for the progress. Follow up of qSOFA positive patient who were transferred to critical care units was done until disease progress to sepsis, or transferred to ward or diseased. Those patients who are transferred to other facility were excluded .
The main objective of this study is to detect sepsis at the earliest using the two standardized tools. The study was conducted after getting due approval from the hospital ethical committee and official permission was obtained from the authorities who framed the tools. 11 Experts from the hospital reviewed tool and presented their valuable opinions. There were many studies conducted using this tool in high income countries but there are limited research has been done by low and middle income countries. SOFA score was introduced in the year 1994 during a critical care consensus organized by the critical care society of Europe. qSOFA is a recently introduced tool which was first presented and proposed for use at 3rd international consensus in the year 2016 .
The demographic data used for qSOFA was concise and without additional tests. SOFA had additional clinical parameters and biochemical readings. The common distribution among the tools was signs of infection .
The sample for qSOFA was collected at the first encounter of the patient at the emergency department. Rapid evaluation of the patient did using demographic data to check for fitness into the inclusion criteria. And those patients became positive or those who score 2 and above of qSOFA were included in the study. The follow up of the patient who was sifted to criticalcare unit was done until the patient diagnosed with sepsis, diseased or shifted to ward. Most of the qSOFA positive patient was very young and elderly. 40% of the patient who developed sepsis after been positive for qSOFA was elderly adults and 35% were very young and adult patients. Assessing for patient at risk was done using 3 parameter assessment which includes “Altered mentation, Systolic blood pressure less than or equal to 100 mm of hg, and Respiratory rate more than or equal to 22 bpm . Most of the patient who was positive to qSOFA found to have alteration in mentation and respiration. But the patient who developed sepsis had GCS mean of 9 or less than 9 with mean systolic blood pressure of 90 mm of hg, the mean respiratory rate among patient who developed sepsis after becoming positive to qSOFA scoring was found to be 34 bpm. The p value was less than 0.05 which was assessed using Mann-Whitney U test and was found to be significant. QSOFA had 100% sensitivity but the Specificity was 37.50%, with accuracy of 60% .
SOFA was scored within 24 h of critical care admission after assessing the patient for inclusion criteria. The patients who are positive or with more than 2 SOFA score were included in the study. The patient was score for three consecutive days and recorded after which the patient was monitored until diagnosed with sepsis or diseased or shifted to ward .
The demographic data of SOFA includes more elements and included clinical parameters and blood values. The patient was scored using SOFA scoring tool. The SOFA score contains 6 elements which focus on different system. Hence SOFA score can also help in detecting system wise dysfunction. The patient enrolled for SOFA score had mean of 86.77% Spo2, the mean value of diastolic blood pressure was 67.14 mm of hg and GCS mean was 6.4 among patient who developed sepsis after becoming positive to SOFA score . There was rise in lactate level in both the group of sample. Since the tool had nonparametric variables test of normality was not able to be concluded with Kolmogorov-Smirnov test of normality hence Mann-Whitney U test was used and found the p-value less than 0.05 for all the clinical parameters included in the SOFA and found it to be significant. The sensitivity of SOFA score was 95.45% but the specificity was 39.39% with the 64% accuracy .
The objective of detecting sepsis was obtained by using both the tool with high level of sensitivity the specificity of both the tool was found to be low. But that cannot be concluded as ineffective since variation in clinical parameters are common and the definition of sepsis itself says that it’s a dysregulations with vague evidence of origin and it is depending upon the unique physiological factors like host response and the virulence of the organism involved .
The objectives of evaluating the effectiveness of qSOFA and SOFA in detecting sepsis at the earliest were found to be. 74% of patient becomes positive to qSOFA out of which 51% of patient developed sepsis. 70% of patient becomes positive to SOFA out of which 60% of patient developed sepsis [89-95].
According to the observation made the study concludes that qSOFA has 100% sensitivity to detect sepsis at the earliest when applied on patients with suspected infection at emergency department in comparison to SOFA score which had 95.45% of sensitivity when applied on patients with suspected infection at critical care units of tertiary care teaching hospital emergency department and critical care unit at Navi Mumbai, The researcher also found that the hurdle to the early detection is the signs and symptoms that are noticed during the normal course of infection leads to the increase of false positive. In spite of that the researcher found it is recommended to detect sepsis at the earliest with pre planned protocols utilizing effective tools and local healthcare policies as it is a global burden with a complex nature. Further research in this arena is highly recommended to generalize the findings.
Since the most of the clinical variables included in the tools are found during regular course of infection can increase the number of false positive. Needs vigilant monitoring and paper works and training, hence time consuming.
The findings of the study have number of implications for nursing practice, patient and institutional benefit.
The critical care nurses who are trained to identify the patient at risk of developing sepsis can enhance prioritization and organization of care provided. System wise assessment can be done and communicated to the specialist and plan the care pathway accordingly. Nurses will be equipped with the knowledge of identifying the deviations and dysregulations and be prepared to face the situation with pre-planned protocols will reduce anxiety and stress.
Positive patient outcome
Sepsis is a serious complication and a global burden, since it has rapid progress and leads to organ dysfunction and increased morbidity, but for those the patient who recovers from it faces lots of disabilities and morbidities. Hence identify sepsis at the earliest should be the goal of critical care personnel. If the patient is identified at the earliest organ failure or deterioration can be prevented which can enhance positive recovery with planned protocols framed as per the hospitals policy. Treating patient with sepsis is expensive the patient need high end monitors, supports and investigations and medications, which can be managed well with early detection and plan of actions.
Research is a process of finding answer or solution, which is very essential for nursing profession and it should be an ongoing process. By being prepared as Jean Ida a nursing theorist mentioned nurse has to be equipped to handle changes exhibited by patient with positive professional reaction that benefits the patient.
Based on the findings of the study the proposed recommendations for future research are follows: Scoring the patients using qSOFA tool at the emergency department may help to identify sepsis at the earliest in susceptible patients.
SOFA score may be used at the critical care units to monitor organ functions and to detect dysfunction at the earliest. Hospital protocol may include the use of qSOFA and SOFA and the pre and post procedure protocols.
Similar study was conducted to compare qSOFA and SOFA and found that qSOFA to be effective, but in this current study both have been sensitive in detecting sepsis, but with less specificity. Hence further research has to be carried out with more population and different geographical area.
qSOFA is a recently introduce tool and need further research support. Hospital may adapt a protocol to identify the patients at risk of developing sepsis and on-going education and nursing knowledge updates may be planned and followed to have positive
This chapter deals with the summary of the research study, bringing forth the major Findings of the study, discussion, conclusion, nursing implications, limitations and Recommendations are given at the end of the study.